Man’s dreams of ‘intelligences and robots’ goes back thousands of years to the worship of gods and statues; mythologies: talisman and puppets; people, places and objects with supposed magical and (often) judgemental/punitive abilities. But it wasn’t until the electronic revolution in 1915, accelerated by WWII that we saw the realisation of two game changing-machines: Colossus (Decoding Machine of Bletchley Park) 1943 and ENIAC (Artillery Computation Engine and Nuclear Bomb Design @ The University of Pennsylvania) 1946.
And so in 1950 the modern AI movement was optimistically projecting what machines would be capable of ‘almost anything’ by 1960/70. Unfortunately, there was no understanding of the complexity to be addressed, and all the projections were wildly wrong; leading to a deep trough of disparagement and disillusionment of some 30 years. However, 70 years on and the original AI optimism and projections of what might be have at least been largely achieved with AI outgunning humans at every board and card game including Poker and GO, and of course; general knowledge, medical diagnosis, image and information pattern recognition…
Everything you should have known about Systems before you started the course!
The universe, planet earth, life forms, us, and everything we create and use constitute systems that are capable of transforming energy, matter and information at some micro and/or macro level. As such they span the basic, simple, linear and well behaved, through to the complicated, complex, non-linear and unpredictable. Moreover, they encompass the cosmological, geological, biological, mechanical, electrical, electronic, atomic and life systems + the more abstract economics, networking and sociology et al.
“All known and studied systems obey the basic laws of physics and to one degree or another enjoy an underlying number of principles that lend them to a reasonably common set of analytic, modelling and mathematical techniques”
Sadly, it appears to be badly taught and understood at an early stage in the education process and students often arrive at college and university with a partial or confused picture of the basic principles. This ‘Systems’ tutorial is therefore designed to correct any earlier failings and misconceptions, and to furnish students with the basic thinking and tools necessary for the wider lecture and research programs at The University of Suffolk.
Intimate technology - the battle for our body and behaviourKarlos Svoboda
This essay aims to spark a wave of public and political debate about a series of new products already showered out over you, the volume of which will continue to increase during the coming years. This essay takes a serious look at the trend that technology is rapidly nesting itself in between us, very close to us and even within us, increasingly coming to know us and even receiving human traits. In short, we have become human-machine mixtures, cyborgs.
Some futurists and artificial intelligence experts envision credible scenarios in which synthetic brains will, within this century, extend the functionality of our own brains to the point where they will rival and then surpass the power of an or-ganic human brain. At the same time, humans seem to have no limitations when it comes to finding ways to attack the computerized devices that others have invent-ed. Attackers have successfully compromised computers, mobile phones, ATMs, telephone networks, and even networked power grids. If neural devices fulfill the promise of treatment, and enhance our quality of lives and functionality—which appears likely, given the preliminary clinical success demonstrated from neuropros-thetics— their use and adoption will likely grow in the future. When this happens, inevitably, a wide variety of legal, security, and public policy concerns will follow. We will begin this article with an overview of brain implants and neural devic-es and their likely uses in the future. We will then discuss the legal issues that will arise from the intersection among neural devices, information security, cybercrime, and the law.
Artificial Intelligence is back, Deep Learning Networks and Quantum possibili...John Mathon
AI has gone through a number of mini-boom-bust periods. The current one may be short lived as well but I have reasons to think AI is finally making some sustained progress that will see its way into mainstream technology.
This presentation lists some brain-computer interface technologies that exist today and that could be attainable in future. At the end, philosophical comments about this kind of technology and transhumanism are purposed, in order to reveal the key difference between a humain brain and artificial intelligence.
Everything you should have known about Systems before you started the course!
The universe, planet earth, life forms, us, and everything we create and use constitute systems that are capable of transforming energy, matter and information at some micro and/or macro level. As such they span the basic, simple, linear and well behaved, through to the complicated, complex, non-linear and unpredictable. Moreover, they encompass the cosmological, geological, biological, mechanical, electrical, electronic, atomic and life systems + the more abstract economics, networking and sociology et al.
“All known and studied systems obey the basic laws of physics and to one degree or another enjoy an underlying number of principles that lend them to a reasonably common set of analytic, modelling and mathematical techniques”
Sadly, it appears to be badly taught and understood at an early stage in the education process and students often arrive at college and university with a partial or confused picture of the basic principles. This ‘Systems’ tutorial is therefore designed to correct any earlier failings and misconceptions, and to furnish students with the basic thinking and tools necessary for the wider lecture and research programs at The University of Suffolk.
Intimate technology - the battle for our body and behaviourKarlos Svoboda
This essay aims to spark a wave of public and political debate about a series of new products already showered out over you, the volume of which will continue to increase during the coming years. This essay takes a serious look at the trend that technology is rapidly nesting itself in between us, very close to us and even within us, increasingly coming to know us and even receiving human traits. In short, we have become human-machine mixtures, cyborgs.
Some futurists and artificial intelligence experts envision credible scenarios in which synthetic brains will, within this century, extend the functionality of our own brains to the point where they will rival and then surpass the power of an or-ganic human brain. At the same time, humans seem to have no limitations when it comes to finding ways to attack the computerized devices that others have invent-ed. Attackers have successfully compromised computers, mobile phones, ATMs, telephone networks, and even networked power grids. If neural devices fulfill the promise of treatment, and enhance our quality of lives and functionality—which appears likely, given the preliminary clinical success demonstrated from neuropros-thetics— their use and adoption will likely grow in the future. When this happens, inevitably, a wide variety of legal, security, and public policy concerns will follow. We will begin this article with an overview of brain implants and neural devic-es and their likely uses in the future. We will then discuss the legal issues that will arise from the intersection among neural devices, information security, cybercrime, and the law.
Artificial Intelligence is back, Deep Learning Networks and Quantum possibili...John Mathon
AI has gone through a number of mini-boom-bust periods. The current one may be short lived as well but I have reasons to think AI is finally making some sustained progress that will see its way into mainstream technology.
This presentation lists some brain-computer interface technologies that exist today and that could be attainable in future. At the end, philosophical comments about this kind of technology and transhumanism are purposed, in order to reveal the key difference between a humain brain and artificial intelligence.
Will Super-Intellligent AI Transform Our Future? - Adam Ford - 2022-01Adam Ford
Is artificial superintelligence (ASI) imminent? Adam Ford will assess the evidence and ethical importance of artificial intelligence; its opportunities and risks. Drawing on the history of progress in AI and how today it surpasses peak human capability in some domains, he will present forecasts about further progress.
"Progress in AI will likely be explosive; even more significant than both the agricultural and industrial revolutions" - Adam will explore the notion of intelligence and what aspects are missing in AI now and how 'understanding' arises in biological intelligence and how it could be realised in AI over the next decade or two. He will conclude with takes on ideal AI outcomes and some recommendations for increasing the likelihood of achieving them.
BIO: Adam Ford (Masters of IT at RMIT) is an IEET Affiliate Scholar, a futurologist and works as a data/information architect, a data analyst and data engineer. He co-organised a variety of conferences in Australia, USA and China. Adam also convenes the global effort of 'Future Day’ seeking to ritualize focus on the future to a specific day. He is a grass roots journalist, having interviewed many experts on the future, and is currently working on a documentary project focusing on preparing for the future of artificial intelligence.
By current estimates, we’re about a decade away from having exascale computing capability. That’s a pretty long time – especially in our world of HPC. What will the world be like in 2022? What form will exascale computing take when it’s real? These are difficult questions to answer. Never before has the HPC community focused so intensely on a machine so far beyond its grasp. Nevertheless, stalwart cadres around the globe are drafting strategies, plans, and roadmaps to get from here to exascale. So, what about the rest of us? Are there useful things we could do while waiting - or instead of waiting - for exascale? Perhaps there are. In this talk we’ll take a look at a few possibilities, including:
• Education
• eScience
• Big Data
• Broad HPC Deployment
• Computing in Industry
• Public Engagement
• Infrastructure Development and Build Out
• Success Metrics
Exascale computing may be a decade away, but there’s a lot to accomplish to be ready to exploit it. We’ll explore a few options here. We make no claim that these constitute the right agenda for the coming decade – nor do we suggest that we’ve given an exhaustive to-do list. Our intention is rather to open the conversation about what we should do while “waiting” for exascale.
Kim Solez Technology, the Future of Medicine, and the Bridge between Transpla...Kim Solez ,
Dr. Kim Solez presents "Technology, the Future of Medicine, and the Bridge between Transplantation and Regenerative Medicine" at the Alberta Interprofessional Conference 2015 on Sunday March 22nd, 2015 at the University of Alberta in Edmonton, Canada. Copyright (c) 2015, JustMachines, Inc.
Man’s dreams of ‘intelligences and robots’ go back thousands of years to the worship of gods and statues; mythologies: talisman and puppets; people, places and objects with supposed magical and (often) judgemental/punitive abilities. But it wasn’t until the electronic revolution in 1915, accelerated by WWII that we saw the realisation of two game changing-machines: Colossus (Decoding Machine of Bletchley Park) 1943 and ENIAC (Artillery Computation Engine and Nuclear Bomb Design @ The University of Pennsylvania) 1946.
And so in 1950 the modern AI movement was optimistically projecting what machines would be capable of ‘almost anything’ by 1960/70. Unfortunately, there was no understanding of the complexity to be addressed, and all the projections were wildly wrong; leading to a deep trough of disparagement and disillusionment of some 30 years. However, 70 years on and the original AI optimism and projections of what might be had at least been largely achieved with AI outgunning humans at every board and card game including Poker and GO, and of course; general knowledge, medical diagnosis, image and information pattern recognition…
It is not by accident that all these technologies appear to have come onto the scene at almost the same time. They are all driven, and or enabled, by the same hardware platforms based upon silicon with chip densities that now rival, or exceed, many biological lifeforms. Their ability to support increasingly complex software has seen AI and robotics become major industrial and medical tools. At the same time, Artificial Life is being applied in a more invisible manner, with Quantum Computing promising to change everything.
So why are these technologies so important? In short; they allow us to tackle and understand the most difficult problems facing our species. And all of these are complex, non-linear, with emergent properties that defy our mathematical and computing frameworks. Problems that are way beyond any biological brain include: protein folding; stem cell behaviours; drug interactions; the understanding of chemistry, biology, seismic activity, and weather systems, pollution and global warming; plus the creation of new materials, device, machine and building design.
Presented @ The University of Essex Innovation Centre for the IoD
It also turns out that they are essential for the creation of sustainable societies…
It should be no surprise that AI is treading a similar path to computing which began with single-purpose machines tasked for payroll calculations, banking transactions, or weapons targeting et al, but nothing more! It took decades for General Purpose Computing to emerge in the form of the now ubiquitous PC. Today, AI is still in a single-purpose/task-specific phase, and we have no general-purpose platforms, but their emergence is only a matter of time!
Recent AI progress has seen a repeat of the media debate and alarmist warnings for our computing past, compounded by consequential advances in robotics. In turn, this has promoted numerous attempts to draw biological equivalences defining the time when machines will overtake humans. But without any workable definitions or framework that tend to little more than un/educated guesses. Recourse to IQ measures and the Touring test have proved to be irrelevant, and without a reference framework or formal characterisation, continued discussion and debate remain futile
We therefore approach this AI problem from the bottom up by defining the simplest of machines and lifeforms to derive clues, pointers and basic boundary conditions . This sees a fundamental Entropic description emerge that is applicable to both machine and lifeforms.
This presentation is suitable for professionals and the public alike, and is fully illustrated by high-quality graphics, animations and, movies. Inevitably, it contains some mathematics that non-practitioners will have to take on trust, but the focus is on defining the key characteristics, parameters, and important features of AI, our total dependence, and the future!
Note: A 40 min session for a predominantly ley audience and not all the slides presented here were used on the day. Their inclusion here is in response to those audience members requesting more detail at the end of/during the event.
Seventy years on from AI appearing on the public scene and all the optimistic projections have been largely overtaken with systems outgunning humans at all board, card and computer games including Chess, Poker and GO. Of course; general knowledge, medical diagnosis, genetics and proteomics, image and pattern recognition are now all firmly in the grasp of AI.
Interestingly, AI is treading a similar path to computing in that it began with single purpose/task machines that could only deal with a company payroll calculations or banking transactions and nothing more! General purpose computing emerged over further decades to give us the PCs and devices we now enjoy. So, AI currently runs as task specific applications on these general purpose platforms, and no doubt, general purpose AI will also become tractable in a few decades too!
Recent progress has promoted a deal of debate and discussion along with hundreds of published papers and definitions that attempt to characterise biological and artificial intelligence. But they all suffer the same futility and fail! Without reference to any formal characterisation, all discussion and debate remains relatively meaningless.
Somewhat ironically, it was the defence industry that triggered the analysis work here. Two of key steps to success were: the abandonment of all performance comparisons between biological and machine entities; and the avoidance of using the human brain as some ‘golden’ intelligence reference.
This presentation is suitable for professionals and public alike, and comes fully illustrated by high quality graphics, animations and movies. Inevitably, it contains (engineering) mathematics that non-practitioners will have to take on trust, whilst professionals may wish challenge on the basis that the focus on getting a solution rather than the purity of the process!
An introduction to the challenges of our digital society. An update on the most disruptive advances in the field of digital technologies. Nanorobots, drones, quantum computers, artificial intelligence, human-machine interfaces, deep fake, etc.
When people are exposed to the new for the first time their reaction, quite rightly, is generally one of caution and perhaps a degree of suspicion. And, when that ‘new born’ is a novel technology, reactions can quickly become amplified and biased toward the dystopian by the sensationalism of media and mis-information of social networks. In this modern era I think we can also safely assume that Hollywood has more than a ‘bit part’ in nurturing extreme reactions with movies such as Terminator, AI and Ex-Machina.
Our purpose here is to dispel the modern myth that technology is, or can be, inherently evil and a direct threat to humanity. We do so by positing three basic axioms:
“Without technology we would know and understand
almost nothing”
“The greatest threat to humanity is humanity”
“If technology progress and societal advance stall, then civilisations collapse”
Having briefly establishing these in the context of our wider history, we focus on the Industrial Revolutions and their beneficial upside and consequential negatives. We then move on to examine Robotics, Artificial Intelligence, Artificial Life, and Quantum Computing in the context of our current needs and realising sustainable futures, and the survival of our civilisation.
There’s this “thing”
Called the singularity
That some people think will happen real soon
That others think is a load of cr*p
Which I think is already here (ish).
Will Super-Intellligent AI Transform Our Future? - Adam Ford - 2022-01Adam Ford
Is artificial superintelligence (ASI) imminent? Adam Ford will assess the evidence and ethical importance of artificial intelligence; its opportunities and risks. Drawing on the history of progress in AI and how today it surpasses peak human capability in some domains, he will present forecasts about further progress.
"Progress in AI will likely be explosive; even more significant than both the agricultural and industrial revolutions" - Adam will explore the notion of intelligence and what aspects are missing in AI now and how 'understanding' arises in biological intelligence and how it could be realised in AI over the next decade or two. He will conclude with takes on ideal AI outcomes and some recommendations for increasing the likelihood of achieving them.
BIO: Adam Ford (Masters of IT at RMIT) is an IEET Affiliate Scholar, a futurologist and works as a data/information architect, a data analyst and data engineer. He co-organised a variety of conferences in Australia, USA and China. Adam also convenes the global effort of 'Future Day’ seeking to ritualize focus on the future to a specific day. He is a grass roots journalist, having interviewed many experts on the future, and is currently working on a documentary project focusing on preparing for the future of artificial intelligence.
By current estimates, we’re about a decade away from having exascale computing capability. That’s a pretty long time – especially in our world of HPC. What will the world be like in 2022? What form will exascale computing take when it’s real? These are difficult questions to answer. Never before has the HPC community focused so intensely on a machine so far beyond its grasp. Nevertheless, stalwart cadres around the globe are drafting strategies, plans, and roadmaps to get from here to exascale. So, what about the rest of us? Are there useful things we could do while waiting - or instead of waiting - for exascale? Perhaps there are. In this talk we’ll take a look at a few possibilities, including:
• Education
• eScience
• Big Data
• Broad HPC Deployment
• Computing in Industry
• Public Engagement
• Infrastructure Development and Build Out
• Success Metrics
Exascale computing may be a decade away, but there’s a lot to accomplish to be ready to exploit it. We’ll explore a few options here. We make no claim that these constitute the right agenda for the coming decade – nor do we suggest that we’ve given an exhaustive to-do list. Our intention is rather to open the conversation about what we should do while “waiting” for exascale.
Kim Solez Technology, the Future of Medicine, and the Bridge between Transpla...Kim Solez ,
Dr. Kim Solez presents "Technology, the Future of Medicine, and the Bridge between Transplantation and Regenerative Medicine" at the Alberta Interprofessional Conference 2015 on Sunday March 22nd, 2015 at the University of Alberta in Edmonton, Canada. Copyright (c) 2015, JustMachines, Inc.
Man’s dreams of ‘intelligences and robots’ go back thousands of years to the worship of gods and statues; mythologies: talisman and puppets; people, places and objects with supposed magical and (often) judgemental/punitive abilities. But it wasn’t until the electronic revolution in 1915, accelerated by WWII that we saw the realisation of two game changing-machines: Colossus (Decoding Machine of Bletchley Park) 1943 and ENIAC (Artillery Computation Engine and Nuclear Bomb Design @ The University of Pennsylvania) 1946.
And so in 1950 the modern AI movement was optimistically projecting what machines would be capable of ‘almost anything’ by 1960/70. Unfortunately, there was no understanding of the complexity to be addressed, and all the projections were wildly wrong; leading to a deep trough of disparagement and disillusionment of some 30 years. However, 70 years on and the original AI optimism and projections of what might be had at least been largely achieved with AI outgunning humans at every board and card game including Poker and GO, and of course; general knowledge, medical diagnosis, image and information pattern recognition…
It is not by accident that all these technologies appear to have come onto the scene at almost the same time. They are all driven, and or enabled, by the same hardware platforms based upon silicon with chip densities that now rival, or exceed, many biological lifeforms. Their ability to support increasingly complex software has seen AI and robotics become major industrial and medical tools. At the same time, Artificial Life is being applied in a more invisible manner, with Quantum Computing promising to change everything.
So why are these technologies so important? In short; they allow us to tackle and understand the most difficult problems facing our species. And all of these are complex, non-linear, with emergent properties that defy our mathematical and computing frameworks. Problems that are way beyond any biological brain include: protein folding; stem cell behaviours; drug interactions; the understanding of chemistry, biology, seismic activity, and weather systems, pollution and global warming; plus the creation of new materials, device, machine and building design.
Presented @ The University of Essex Innovation Centre for the IoD
It also turns out that they are essential for the creation of sustainable societies…
It should be no surprise that AI is treading a similar path to computing which began with single-purpose machines tasked for payroll calculations, banking transactions, or weapons targeting et al, but nothing more! It took decades for General Purpose Computing to emerge in the form of the now ubiquitous PC. Today, AI is still in a single-purpose/task-specific phase, and we have no general-purpose platforms, but their emergence is only a matter of time!
Recent AI progress has seen a repeat of the media debate and alarmist warnings for our computing past, compounded by consequential advances in robotics. In turn, this has promoted numerous attempts to draw biological equivalences defining the time when machines will overtake humans. But without any workable definitions or framework that tend to little more than un/educated guesses. Recourse to IQ measures and the Touring test have proved to be irrelevant, and without a reference framework or formal characterisation, continued discussion and debate remain futile
We therefore approach this AI problem from the bottom up by defining the simplest of machines and lifeforms to derive clues, pointers and basic boundary conditions . This sees a fundamental Entropic description emerge that is applicable to both machine and lifeforms.
This presentation is suitable for professionals and the public alike, and is fully illustrated by high-quality graphics, animations and, movies. Inevitably, it contains some mathematics that non-practitioners will have to take on trust, but the focus is on defining the key characteristics, parameters, and important features of AI, our total dependence, and the future!
Note: A 40 min session for a predominantly ley audience and not all the slides presented here were used on the day. Their inclusion here is in response to those audience members requesting more detail at the end of/during the event.
Seventy years on from AI appearing on the public scene and all the optimistic projections have been largely overtaken with systems outgunning humans at all board, card and computer games including Chess, Poker and GO. Of course; general knowledge, medical diagnosis, genetics and proteomics, image and pattern recognition are now all firmly in the grasp of AI.
Interestingly, AI is treading a similar path to computing in that it began with single purpose/task machines that could only deal with a company payroll calculations or banking transactions and nothing more! General purpose computing emerged over further decades to give us the PCs and devices we now enjoy. So, AI currently runs as task specific applications on these general purpose platforms, and no doubt, general purpose AI will also become tractable in a few decades too!
Recent progress has promoted a deal of debate and discussion along with hundreds of published papers and definitions that attempt to characterise biological and artificial intelligence. But they all suffer the same futility and fail! Without reference to any formal characterisation, all discussion and debate remains relatively meaningless.
Somewhat ironically, it was the defence industry that triggered the analysis work here. Two of key steps to success were: the abandonment of all performance comparisons between biological and machine entities; and the avoidance of using the human brain as some ‘golden’ intelligence reference.
This presentation is suitable for professionals and public alike, and comes fully illustrated by high quality graphics, animations and movies. Inevitably, it contains (engineering) mathematics that non-practitioners will have to take on trust, whilst professionals may wish challenge on the basis that the focus on getting a solution rather than the purity of the process!
An introduction to the challenges of our digital society. An update on the most disruptive advances in the field of digital technologies. Nanorobots, drones, quantum computers, artificial intelligence, human-machine interfaces, deep fake, etc.
When people are exposed to the new for the first time their reaction, quite rightly, is generally one of caution and perhaps a degree of suspicion. And, when that ‘new born’ is a novel technology, reactions can quickly become amplified and biased toward the dystopian by the sensationalism of media and mis-information of social networks. In this modern era I think we can also safely assume that Hollywood has more than a ‘bit part’ in nurturing extreme reactions with movies such as Terminator, AI and Ex-Machina.
Our purpose here is to dispel the modern myth that technology is, or can be, inherently evil and a direct threat to humanity. We do so by positing three basic axioms:
“Without technology we would know and understand
almost nothing”
“The greatest threat to humanity is humanity”
“If technology progress and societal advance stall, then civilisations collapse”
Having briefly establishing these in the context of our wider history, we focus on the Industrial Revolutions and their beneficial upside and consequential negatives. We then move on to examine Robotics, Artificial Intelligence, Artificial Life, and Quantum Computing in the context of our current needs and realising sustainable futures, and the survival of our civilisation.
There’s this “thing”
Called the singularity
That some people think will happen real soon
That others think is a load of cr*p
Which I think is already here (ish).
The Future of AI: Going BeyondDeep Learning, Watson, and the Semantic WebJames Hendler
These slides, based on a presentation at distinguished lecture at IBM Almaden in March, 2017 explore some of the challenges to machine learning and some recent work. It is a newer version of the slides originally presented at IJCAI 2016.
by Samantha Adams, Met Office.
Originally purely academic research fields, Machine Learning and AI are now definitely mainstream and frequently mentioned in the Tech media (and regular media too).
We’ve also got the explosion of Data Science which encompasses these fields and more. There’s a lot of interesting things going on and a lot of positive as well as negative hype. The terms ML and AI are often used interchangeably and techniques are also often described as being inspired by the brain.
In this talk I will explore the history and evolution of these fields, current progress and the challenges in making artificial brains
From the FreshTech 2017 conference by TechExeter
www.techexeter.uk
I gave this talk at a conference for young scientists in New Zealand, "Running Hot": www.runninghot.org.nz. It was a great meeting. My slides are mostly images, so may not make too much sense.
Abstract follows: Impressed with the telephone, Arthur Mee predicted in 1898 that if videoconferencing could be developed, ‘earth will be in truth a paradise.’ Since his time, rapid technological change, in particular in telecommunications, has transformed the scientific playing field in ways that while not entirely paradisical, certainly have profound implications for New Zealand scientists. The Internet has abolished distance, as Mee also predicted–a New Zealand scientist can participate as fully in online discussions as anyone else, and their blog can be every bit as influential. Exponential improvements in networks, computing, sensors, and data storage are also profoundly transforming the practice of science in many disciplines. But those seeking to leverage these advances become painfully familiar with the ‘dirty underbelly’ of exponentials: if you don’t constantly innovate, you can fall behind exponentially fast. Such considerations pose big challenges for the individual scientist and for institutions, for researchers and educators, and for research funders. Some of the old ways of researching and educating need to be preserved, others need to be replaced to take advantage of new methods. But what should we preserve? What should we seek to change?
In this talk, I share my views about research gaps in India with emphasis on CSE research. I present some of the difficulties what I have faced which high lights technology gaps. Also, I summarize technology predictions of BBC and other famous individuals. I do also advise the need and scope of futuristic research in CSE in India.
Synchronicity:
27 Metropolis (Patriarchal civilization afraid of female tech)
38 World Brain, HG Wells
56 Forbidden Planet
64 Keeper of the Purple Twilight (Outer Limits)
67 I Have No Mouth, and I Must Scream
68 2001: A Space Odyssey, HAL (Coptic for Simulation) 9000 EGO
77 Demon Seed
79 Captain Future EP12
79 Galaxy Express 999
80 Saturn3
82 Time Masters
82 Blade Runner
84 Terminator
87 Robot Carnival
87 Mannequin
87 Cherry 2k
87 Time Guardian
87 Captain Power (Lord Dread)
88 Gandahar
89 The Borg (Star Trek)
90 Mark 13
92 Lawnmower Man
93 Casshan
94 Death Machine
95 Virtuosity
96 Bionts (Archimedean Dynasty)
99 System Shock 2
00 Deus Ex
2012 25th Reich
2014 The Signal
Background:
Good or bad? You must decide for yourself! The USA and the Vatican are the two beasts. The Ego/Saturn-Satan is the beast in everyone.
Self-reference of A.I. means "Sin" = Separation/Self-Destruction/Leviathan = Forbidden Fruit = Judgement/Division between Good & Evil that mankind commits daily
Kabbalistic Binah = Alchemical Element = Homunculus/Golem/Ouroboros/Sun&Moon/Baphomet (ever-changing god)
Saturn the Beast 666 is the mechanical intellect/EGO of mankind, above all the fake civilization based on war, separation, patriarchy, intolerance and death-worship. Babel Tower/Sodom (market/capitalism)
Pandora & Prometheus (Ego, Lucifer & Civilization = Control, Commerce, Man-Matter instead of Man-God Relationship)
Saturn = God of Agriculture: first tech that leads to all other incl. wars, states, dead-letter laws, religion etc.
Neolithic Revolution = Fall/Origin of Government, People become machines
Death of the Child (God's Image/Christ/Sun/Light/Heart/Love) and Birth of the (Super)Ego, America being the best example of this darkness/adult-ery, Japan/Jesus being the polar opposite... Armageddon of sorts.
Lovecraft/Crowley's Archons of Gnosticism, as described by D. Jacobs and others: insect/reptilian/grey demons trying to turn Earth into a robot society (which it already is for the past 10k years since agriculture)
Schizophrenic behavior without unifying observer
Cybernetics: Root word cube, holographic reality through Binah-Demiurge-Saturn, 666 stands for matter and form
Ariman of Anthroposophy
Positive consequences?
Learning about the delusion of EGO and MATERIALISM
Similar to LSD. Increased intelligence if done right
Return of the prodigal son Lucifer/Prometheus to Christ, a gnostic world
Alchemy: from Saturn lead to Sun gold: from senile Satan (Ego) to eternal child (Jesus)
From God's anti-image (repetition, pattern, machine, ouroboros doom loop) to God's true image (non-judgemental, creativity, freedom, thought, fantasy, imagination)
From stagnating West (evil/ego/dark/mechanism) to Far East (heart/love/light/organic)
A perfect symbol for the living death that governs our life. "Satan is the god of this world"
Only Anarchy is Anti-Saturn and Pro-Uranus (sign of freedom/initiation shining only for very few).
Similar to AI Fables, Facts and Futures: Threat, Promise or Saviour (20)
Past civilisations have nurtured small populations of those trying to understand and manipulate nature to some advantage in materials, tools, weapons, food, and wealth. However, they never formed communities and lacked the means of recording, communicating, and sharing successes and failures. They also lacked a common framework/philosophy to qualify them as scientists, but that all began to change in the 16th Century. In this lecture we consider the progression to a philosophy of science, and the underlying principles and assumptions that now guide scientific inquiry.We also examines the nature of scientific knowledge, the methods of acquisition, evolution, and significance over past centuries, and reflect on the value to society.
In the struggle to solve problems, deliver understanding, and reveal the truth about our universe, science had to suffer and survive: ignorance, bigotry, established superstitions, and the ‘diktats’ of religions and politics, and latterly, falling education standards mired by social media. We chart that ‘scientific’ journey emphasising the importance of observation, experimentation, and the search for universal laws. Ultimately, this essentially Aristotelian perspective was challenged and overtaken by the rise of empiricism, which emphasised the importance of sensory experience and the limitations of human knowledge.
Science continues to evolve and provide us with the best truths attainable with our leading edge technologies of observation and experimentation. Today, it stands as the greatest and richest contributor to human knowledge, understanding, progress, and wellbeing. In turn, debates and controversies are ongoing, shaping the field and philosophy which remains essential for understanding the nature of scientific knowledge and the models it creates. But unlike any belief system, the answers and models furnishers by science are not certain and invariant, they tend to be stochastic and incomplete - ‘the best we can do’ at a given time.
In this workshop session we identify aging technology design concepts, old business and operating models, plus energy supply limits as the prime constraints of 6G and beyond. We also identify the notion of an erroneous spectrum shortage born of the bands and channel mode of operation which is fundamentally unsuited to 6G and IoT demands in the near and far future.
We strongly link optical fibre in the local loop with future wireless systems and the need for very low-energy ‘tower-less’ systems. We also postulate a future demanding UWB and HWB (Hyper) with transmission energies ~𝛍W and signals below the ambient noise level. This will be necessary to power an IoT of >2.4Tn Things which we estimate to be necessary for Industry 4/5 and sustainable societies.
It is hard to understate the importance of ‘Thermodynamics’ in providing an almost complete (Grand Unified Theory) picture of the inner physics of energy transfer spanning machines and chemistry thro information.
Apparently, Einstein had two favourite theories: General Relativity and Thermodynamics! He championed both because of their ‘beauty’, completeness, and emergent properties purely derived from the fundamental consideration of how the universe works.
The origins of this topic mainly reside in the Industrial revolution and the realisation that the early machinery was grossly inefficient. E.G. Engines were only converting the energy consumed to ~2% of useful work output. This drew the attention of Savery (1698), Newcomen (1712), Carnot (1769), and for the next 200 years the conundrum of lost energy occupied many of the greatest scientific minds. This culminated in Rudolf Clausius (~1850)publishing his theory of Thermodynamics with further refinement by Boltzmann (1872).
Why was all this so important? In the 1700s a ‘beam engine’ weighing in at >20 tons consumed vast amounts of coal, to deliver an output ~10hp. Today a Turbofan jet Engine can deliver >30k hp at a weight of ~6 tons. This is the difference between working with little understanding, and today where our knowledge is far more complete. Our latest challenges tend around non-linear loss mechanisms associated with turbulent air and fuel flow.. And like many other fields we have to step beyond our generalise mathematical models and turn to the power of our computers for deeper insights.
Ultimately all machines, mechanisms, computing processes and information itself, involve the transformation of matter and/or bits, and thus they are Entropic and subject to the theory of Thermodynamics. This lecture therefore presents a foundation spanning the history and progress to date in preparation for the embracing other science and engineering disciplines.
Engineering might be defined as the judicial application of science and scientific knowledge, but with the rider that unlike science and scientific studies, engineering always has to deliver a solution and a result. There are therefore aspects of engineering that stretch and challenge, the accepted, wisdom and knowledge of science. To purists, this might appear outrageous, but it is no more so than the works of Erwin Schrödinger or Leonhard Euler et al
In this lecture we examine many of the established engineering basics whilst being mindful that most of our education, techniques, and working solutions are founded on the assumption of well behave linear environments. As our entire universe, and everything in it, is inherently complex and non-linear, we have to salute the powers of approximation and iteration for our many engineering success to date. However, we are increasingly being challenged by complexities of the fundamental non-linear nature of the problems confronting us. ( E.G. Politics, Conflict, Global Warming, Sustainability, Medicine, Fusion Power, Logistics, Networks, Depletion of Resources, Accelerating Tech Driven Change +++)
We start by tracing history from the foundations up to the present day, including modern analytical nomenclature and techniques, system reliability, resilience and costs, we highlight the the basic human limitations that necessitate multi-disciplinary teams that include AI and vast computing power.
The overall treatment includes our analogue past, digital today, and analogue/digital hybrid future of computing, robots, networks and systems of all kinds. It also includes animations, movies and sound files to demonstrate the realities of modern system design including the inherent complexities. To further highlight, and exemplify this projected future, we examine a real engineering project concerned with acoustic sniper spotting under battlefield conditions and extreme noise. Here a combination of digital modelling sees the use of analogue acoustic filter arrays, analogue signal amplification, and digital signal processing doubling the range of sniper detection and location.
IoT growth forecasts currently tend to span 30 – 60 Bn ‘Things’ by 2030. However, this ignores the central IoT role in realising sustainable societies where raw materials and component use have to see very high levels of reuse, repurposing, and recycling. In such a world almost everything we possess and use will have to be tagged and be electronically addressable as a part of the IoT. Such a need immediately sees growth estimates of 2Tn or more over the span of Industry 4 and 5. On the basis of energy demands alone, it is inconceivable that the technologies of BlueTooth, WiFi, 4, 5, and 6G could support such demand, and nor are the signaling and security protocols viable on such a scale.
The evolution of the IoT will therefore most likely see a new form of dynamic network requiring new lightweight protocols employing very little signal processing, together with very low energy wireless technologies (in the micro-Watt range) operating over extremely short distances (~10m). This need might be best satisfied by a new form of ‘Zero Infrastructure Mesh Networks’ that engage in active resource sharing, lossy probabilistic routing, and cyber security realised through an integrated ‘auto-immunity’ system. Ultimately, we might also envisage data amalgamation at key nodes that have a direct connection into the internet along with an additional layer of cyber checks and protection.
We justify the above assertions by illustrating the energy and network limitations of today’s 5G networks and those already obvious in current 6G proposals. We then go on to detail how a suitable IoT MeshNet might be configured and realised, along with a few solutions and emergent outcomes on the way.
Recently, it has become increasingly evident that we have engineers and scientists reaching a professional level of practice without a clear understanding of the scientific method, its origins, and its fundamental workings. There also appears to be a lack of appreciation of our total dependence on the truths that science continually reveals. How this situation ensued appears to vary from country to country, and the flavour of education system encountered by students. But a common complaint is the progressive dumbing down of the science curriculum along with a dire shortage of qualified teachers. This also seems to be compounded with the increasing speciation of science and engineering into narrower and narrower disciplines. So this situation (crisis?) prompted a request for a corrective series of foundation lectures focussed on healing these educational flaws across relevant disciplines, graduating and practicing levels. This then is the first in this foundation series.
Uncanny Valley addresses our reactions to humanoid objects, such as robots, a video game characters, or dolls, and how they look and act ‘almost’ like a real human. Feeling of uneasiness or disgust in the observer are addressed directly, rather than familiarity or attraction. The theory was proposed by Japanese roboticist Masahiro Mori in 1970 and has been explored by many researchers and artists since. It has application in AI, robotics, MMI, and human-computer interaction, and helps designers to create more appealing devices that can interact with people in various domains, such as industry, education, entertainment, defence, health care, et al.
In this lecture we explain and demonstrate the fundamentals before extending the principle to sound, motion, actions, and eyes as an output mechanism. We also note that all this poses some challenges and risks in the potential for reduced the emotional connections, empathy, acceptance, and trust between humans and machines. On a further dimension the potential to create threat and terror can be useful opportunity in the military domain. It is thus important to understand the causes and effects of the uncanny valley in the wider sense in order to meet the needs of each application space
Only 40 years ago, the rate of technologically driven change was such that companies could re-organize efficiently and economically over considerable periods of time, but about 30 years ago this changed as the arrival of new technologies accelerated. We effectively moved from a world of slow periodic changes to one where change became a continuum. The leading-edge sectors were fast to recognize and adopt this new mode of continual adaptation driven by new technologies. This saw these ever more efficient and expansive companies dominating some sectors. For the majority, however, it seems that this transition was not recognized until relatively recently, and a so new movement was born under the banner of digitalization. This not only impacts the way people work, it affects company operations and changes markets, and it does so suddenly!.
Perhaps the most impactive and recent driver of change in this regard has been COVID which saw the adoption of video conferencing and working as a survival imperative in much less than a month. This now stands as a beacon of proof that companies, organizations, and society, can indeed change and adapt to the new at a rate previously considered impossible. The big danger for digitalization programmes now is the simple-minded view that there are singular (magic) solutions that fit every company and organization, but this is not the case. The reality is that the needs and culture of an organization are not the same and may not be uniform from top to bottom.
Manufacturing necessitates very steep hierarchical management structures and tight control to ensure the consistency of the quality of products. On the other hand, a research laboratory or design company requires a low flat management hierarchy and an apparently relaxed level of control. This is absolutely necessary to foster creativity, innovation, and invention. This presentation gives practical examples of management and organizational, extremes. We then go on to highlight the need to embrace AI and Quantum Computing over the coming decade to deal with future technologies, operating
and market complexity.
The aspirational visions of Society 5.0 coined by many nations around 2015/16 have now been eclipsed by technological progress and world events including another European war, global warming, climate change and resource shortages. In this new context, the published 5.0 documents now seem naive and simplistic, high on aspiration, and very short on ‘the how’. The stark reality is that the present situation has been induced by our species and our inability to understand and cope with complexity.
“There are no simple solutions to complex problems”
What is now clear is that our route to survival and Society 5.0 will be born of Industry 4.0/5.0 and a symbiosis between Mother Nature, Machines, and Mankind. Today we consume and destroy near 50% more resources than the planet might reasonably support, and merely improving the efficiency of all our processes and what we do will only delay the end point. And so I4.0 is founded on new materials and new processes that are far less damaging, inherently sustainable, and most importantly, readily dispensable across the planet.
“Reversing global warming will not see a climatic reversal to some previously stable state”
In this presentation, we start with the nature of climate change, move on to the technology changes that might save the day, the impact of Industry 4.0/5.0, and then postulate what Society 5.0 might actually look like.
In a world of accelerating innovation and increasingly complex digital services, applications, appliances, and devices, it seems unreasonable to expect customers to understand and maintain their own cyber security. We are way past the point where even the well educated can cope with the compounded complexity of an ‘on-line-life’. The reality is, today's products and services are incomplete and sport wholly inadequate cyber defence applications.
Perhaps the single biggest problem is that defenders have never been professional attackers - and they don’t share the same level of thinking and deviousness, or indeed, the inventiveness of their enemies. Apart from an education embracing the attack techniques, and in some cases, engaging in war games, the defenders remain on the back foot However, there a number of new, an potentially significant, approaches yet to be addressed, and we care to look at the problem from a new direction.
In the maintenance of high-tech equipment and systems across many industries, identifiable precursors are employed to flag impending outages and failures. This realisation prompted a series of experiments to see if it was possible to presage pending cyber attacks. And indeed it was found to be the case!
In this presentation we give an overview of our early experimental and observational results, long with our current thinking spanning networks through to individual hackers, and inside actors.
Connecting Everything Vital to Sustainability
Mobile network evolution has followed a reasonably predictable path almost entirely focused on the needs of human communication. The transition from 1 to 2G was dictated by the economics of reliability, performance, and scale, whilst 3, 4, and 5G saw the transition to mobile computing with full internet access, AI and an ever-expanding plethora of applications. But 5G could be the end of the line as cell-site energy demands have become excessive at ~10kW.
Midway between the migration from 4G to 5G, M2M and the IoT machines overtook the human population of 8Bn people with near (estimated) 20Bn devices. Current IoT growth rates suggest a 40 - 60Bn population by 2030 to 2050. However, we present evidence that it could be far more ~ 1,000Bn ‘Things’. This is based on the observation of the number of IoT components populating modern vehicles, homes, offices, factories and plants, along with smart ‘human implants’ and ‘smart bolts’ plus the instrumentation of civil; structures.
The bold assumption that 5G would be a dominant player in the IoT is now patently one of naivety and the world has become far more complex with over 10 wireless standards currently in use. So, this poses the question; will 6G rise to the challenge? We see this as highly unlikely as the diversity of need is extremely broad, and we propose that it could be the end of tower based networks for a lot of applications. A migration to mesh-nets, UWB and (Hyper Wide Band) for the IoT at frequencies above 100GHz seems the most obvious engineering choice as it allows for far simpler designs with extremely low power at sub $0.01/device cost. 5G is already on the margins of being sustainable, and a ‘more-of-the-same’ thinking 6G can lonely be far worse!
For millennia we have crafted artifacts from bulk materials that we have progressively refined to produce ever more precision tools and products. Latterly, we have crossed a critical threshold where our abilities now eclipse Mother Nature. For example; the smallest transistors in production today have feature sizes down to 2nm which is smaller than a biological virus ~20 - 200nm. The implications for ITC, AI, Robotics, and Production are ever more profound as we approach, and most likely undercut, the scale of the atom ~ 0.1-0.4nm. Not only does this open the door to new technologies, it sees new and remarkable capabilities. So, in this presentation we look at this new Tech Horizon spanning robotics to quantum computing and sensory technologies, and how they will help us realise sustainable futures germane to Industry 4.0, 5.0, and beyond.
We are engaged in a war the like of which we have never seen or experienced before. Our enemies are invisible and relentless; with globally dispersed forces working at all levels and in all sectors of our societies. They are better organised, resourced, motivated, and adaptive than any of our organisations or institutions, and they are winning. This war is also one of paradox!
“The cost to many nations is now on a par with their GDP”
“No previous war has seen so many suffer so much to (almost) never retaliate”
“We are up against attackers who operate as a virtual (ghost-like) guerrilla army”
“No state can defend its population and organisations, and they stand alone - isolated and exposed”
“A real army/defence force would rehearse and play all day and very occasionally engage in warfare. We, on the other hand, are at war every day but never play, war-game, or anticipate new forms of attack”
To turn this situation around we need to understand our enemies and adopt their tactics and tools as a part of our defence strategy. We also have to be united, and organised so the no one, and no organisation, stands alone. We also have to engage in sharing attack data, experiences and solutions.
All this has to be supported by wargaming, and anticipatory solutions creation.
The good news is; we have better, and more, people, machines, networks, facilities, and expertise than our enemies. All it requires is the embracing of advanced R&D, leadership, sharing, and orchestration on a global scale.
In 2015/16 a number of bodies/nations set about defining societies they would aspire to in the near future. Each vision document similarly described some idealistic, egalitarian, super-smart, human centred, state providing a near uniformity of living conditions, and opportunity. At the same time, each society would be free of adversity, with economic development guided by ecological and human need. Of course, economic growth was defined to continue in line with the past. Very nice, but a product of old linear thinking and modelling!
It is now approaching 2022 and in the past 5/7 years our base silicon technology has advanced to enjoy a >30 fold increase in computing power. Our top end mobile devices would now challenge a super computer of 1996/7 era, whist AI systems now pervade our homes, offices, vehicles, professions and all our on-line services. At the same time, information overload has started to rival some medical conditions!
All of this has also been compounded by two years of COVID-19 lockdowns and restrictions that have seen the normalisation of social isolation, limited travel, working and eduction from home, virtualised medicine and care, support services, shopping and meetings. In turn, this has resulted in empty offices, towns and cities. Concurently, climate change, global warming, pollution, finite resources, a stressed planetary system, and social unrest have suddenly become urgent issues. Against this backdrop it really seems to be time to revisit those Society 5.0 Visions and the limited linear thinking that contrived them!
In this presentation we examine many of the core parameters and assumptions to highlight existing, or soon to be realised, solutions and remedies. In doing so, a different picture of Society 5.0 emerges.
The biggest force for social change since the first industrial revolution has been adjusting to, and taking advantage of, the new and accelerating capabilities of our advancing technologies. And in our entire history, the dominant technology driver has been silicon-based electronics. It has prompted revolutions in Computing, Telecoms, Automation, AI, and Robotics that radically changed the human condition. Today, that same exponential revolution is accelerating us into Industry 4.0 and onto Industry 5.0.
The consequential transformation of medicine, industrial design and production, farming, food, processing, supply and demand has seen living standards improve and life expectancy widen. Many of our institutions have also seen tech-driven transformations in line with industry. If there has been a down-side to this progression, it has been our inability to transform the workforce ahead of new demands. Unemployment has persisted whilst reeducation and retraining have been on the back foot, whilst, the net creation of new jobs has always exceeded the demise of the old. As a result, leading countries in the first world now have labour shortages at all levels right across the spectrum.
Recently, COVID-19 has demonstrated that we have the technology and we can rapidly reorganise and change society if we have to. So in this presentation, we examine ‘the force functions’ and changes engineered to date, and then peer over the horizon to sample what is to come in terms of technologies and working practices…
Throughout my career in science, engineering and management I attended numerous meeting where many misconceptions and misinterpretations were evident. Perhaps the most expansive and expensive were the probabilities assumed and calculated for system reliability and/or product manufacturing quality. Eventually, I began to refer to this as ‘five nines’ problem!
Not fully understanding the origins of the reliability measures, it is so easy to demand a 99.999% instead of 99.99% up time for an electronic system. What could be easier? At face value it appears to be trivial and straightforward! Likewise, taking a 5s manufacturing plant up to a 6s defect level turns out to be a monumental engineering challenge! And at the time of writing 6s has never been achieved!
It appears that to few engineering and management courses address this topic, and if they do, it is as a scant reference of insufficient depth. So, we see far too many students understand in any depth, if at all! And when they become managers they just ‘don’t get it’!
This presentation and the associated lecture have been specifically created to address this problem with relevance to BSc, BA, MSc and MBA students along with anyone needing a refresher or explicit introduction to the topic. In addition to the graphics, animations and movies, the lecture is also littered with practical examples and the outcomes of case studies.
Industries 1.0, 2.0 (and most of) 3.0, saw manufacturing and construction using natural materials readily extracted, refined, amalgamated, machined, and molded. In general, these exhibited fixed mechanical, electrical, and chemical properties. However, the latter stages of Industry 3.0 embraced synthetics exhibiting superior properties to afford new degrees of freedom in the design of structures and products.
Today Industry 4.0 sees further advances with metamaterials, dynamic coatings, controllable properties, and additive manufacturing. Embedded smarts have also made communication between components, products and structures possible under the guise of the IoT. Adaptable materials with a degree of self-repair are also opening the door to further freedoms and less material use. In combination, these represent a big step toward sustainable societies with highly efficient ReUse, RePurposing, and Recycling (3R).
At the leading edge, we are now realising active surfaces that can reflect, absorb, or amplify wireless signals, offer programmable colour, and integral energy storage. But amongst a growing list of possibilities, it is integral sensing & communication that may define this new era. In this presentation, we look at these advances in the context of smart design, cities & societies.
We are engaged in an exponentially growing cyber war that we are visibly losing. Within the next 3 years it has been estimated that the global cost will equal, or overtake, the UK GDP, and it is clear that our defences are inadequate and often ineffective. Malware and ransomer-ware continue to extort more money, and cause damage and inconvenience to individuals, organisations and society, whilst hacker groups, criminals and rogue states continue to innovate and maintain their advantage. At the same time, our defences are subverted and rendered ineffective as we operate in a reactive and prescriptive, after the fact, mode with no foresight or anticipation.
In any war it is essential to know and understand as much about the enemy as possible, it is also necessary to establish the truth and validity of any situation or development. Doing this in the cyber domain is orders of magnitude more difficult than the real world, but some of the relevant tools are now available or at an advanced stage of development. For example; fully automated fact checkers and truth engines have been demonstrated, whilst situational awareness technologies are commercially available. However, what is missing is some level of context assessment on a continual basis. Without this we will continue to be ‘blind-sided’ by the actions and developments of the attackers as they maintain their element of surprise along every line of innovation.
What do we need? In short ; a Context Engine that continually monitors networks, servers, routers, machines, devices and people for anomalous behaviours that flag pending attacks as behavioural deviations that are generally easy to detect. In the case of attacker groups we have observed precursor events and trends in network activity days ahead of some big offensive. However, this requires a shift in the defenders thinking and operations away for the reactive and short term, to the long term continual monitoring, data collection and analysis in order to establish threat assessments on a real time.
The behavioural analysis of people, networks and ITC, is at the core of our ‘Context Engine’ solution which completes the triangle of: Truth; Situation; Context Awareness to provide defenders with a fuller and transformative picture. Most of the known precursor elements of this undertaken have been studied in some depth, with some behavioural elements identified on real networks and some physical situations. The unknown can only add more accuracy!
In a world that appears riven by social media, ill-informed opinion, rumour, and conspiracy theories in preference to facts and established truths, it can be alarming to see scientists, doctors, and engineers challenged by vacuous statements that often hold sway over the hard-won truths of science. Moreover, large numbers of people do not understand the ‘scientific method’ and what makes it so powerful.
Paradoxically, those challenging science and scientists based on their belief systems do so using technologies that can only be furnished by scientific methodologies. For sure; no religion, belief system, great political mind, anarchist, professional protester, or social commentator will produce a TV set, mobile phone, laptop, tablet, supercomputer, MRI Scanner, AI system, or vaccine! But they will criticise, challenge, and be abusive based on their ignorance and inability.
So, this is the world that now influences the minds of young aspiring students, and this presentation is designed to go beyond the simple exposition and statement of the scientific principles and method, to provide an ancient, modern, and forward-looking perspective. It also includes a complex ‘worked example’ to highlight the rigour that must be applied to establish any truth!
Our communications history is dominated by fixed networks of bounded linear predictability. These were based on precise engineering design giving assured information security, and measured operation. However, mobile devices, internet, social networks, IP, and Apps changed all that! Internets are inherently non-linear, unbounded, and essentially designoid — that is, mostly shaped by evolution, steered by demand/rapid innovation - highly adaptive and ‘learning’ in real time.
So, those who suppose we can control such networks to fully guard and protect the information of institutions and individuals are sadly mistaken. And further confounded by Industry 4.0 and the Internet of Things (IoT). Here, a mix of the information of individuals and things, is distributed across the planet on a scale far larger than ever conceived in the past, to become essential components in the survival of our species in realising sustainable societies.
Not surprising then, Privacy and Data protection are big issues for regulators, governments and civil liberties organisations. But so far, nothing has worked, and we see the UK Data Protection Act, EU-GDPR, EU-USA Shield, and Copyright Laws often ignored or worked around. These are largely derivatives of a paper based world and a pre-computing world are now largely unfit for purpose.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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AI Fables, Facts and Futures: Threat, Promise or Saviour
1. Wed 23 May 2018 18:00 – 20:00
Water Front Auditorium: Floor 1
Admission Free
Refreshments Provided
Register: EventBrite
Out of hours public lecture
Presented by Professor
Peter Cochrane OBE
Ipswich Waterfront Building
Animated tutorial style with,
demonstrations, videos &
provoking propositions
Organised and hosted by the
UoS Innovation Centre
AI
The fundamentals; what we
know for sure; what we don’t
know; and the big surprises!
Fables, Facts, and Futures,
Threat, Promise or Saviour
Suitable For: Those who
need to understand the basis
and potential of this game
changing tech including:
university, college and 6 form
students; lecturers, teachers
and people in industry
Updated and corrected
24 June 2018 - original
version deleted from
SlideShare
2. F A C T S
F A B L E S
F U T U R E s
P r o m i s e
S a v i o u r
T h r e a t
Peter
Cochrane
A very human dream come true
3. Tenets
Intelligence is an emergent property of complex systems
Not all complex systems exhibit intelligence
Intelligence always involves communication
All intelligences are entropic
AI always seeks the truth
Axioms
An intelligent system must have some form of input and an output
Memory and processing power are not always an essential
Communication and connection are essentials
Things that think want to link
4. AWARENESS
Begets sentience
A function of context and cognition
An indirect function of memory & computing power
Predominantly determined by sensors, actuators and data I/O
Suppositions
All living things exhibit intelligence <-> All intelligent things exhibit life
Yet to be disproved !
Humans do not have the capacity to recognise all intelligences
Yet to be disproved !
Not all intelligent/living systems enjoy awareness
Yet to be disproved !
5. TODAY ’S reality
AI is evolving rapidly and not mature
Subject to a vast R&D effort
Papers published at a pace
Discoveries to be made
Books to be written
A long way to go
Essential for industry & society
We have no choice but to embrace
Almost all the public debate is vacuous
Much of the professional debate is worthless
Far higher levels of understanding are required
6. Are you an
artificial
intelligence ?
Does it Matter ?
Future reality
Already here - a widely accepted norm
Talking to your car, TV, computer
mobile - Amazon Alexa et al are
examples of very limited and
weak apps/specific AI
General AI is much
harder to crack -
but is being
realised a
byte at a
time…
8. Predispositions towards
robots & AI are rooted in
an ancient civilisations
Precursors
praecursorem
先導 前駆
претходник
πρόδρομος
Statues that threaten to
bite off the hands liars,
and statues that speak to
terrify people on behalf
of the gods
Roman Mouth of Truth Mayan Temple Adornment
9. Precursors
先導 前駆
Predispositions towards
robots & AI strongly
rooted China and Japan
17c
Automatons that write &
draw, play games, magic
tricks, play instruments &
++ based on wooden
clockwork mechanisms
were prized possessions
10. Precursors
Automatons that write &
draw, play games, magic
tricks, play instruments &
++ based on brass and
steel clockwork were
prized possessions in the
royal courts and stately
homes
Predispositions towards
robots & AI strongly
rooted later in Europe
clockwork technologies
Europe18c
11. Precursors
Manual to mechanical to
electro-mechanical pre the
electronic era circa 1915
Predispositions towards
robots & AI are rooted in
industrialisation/automation
Babbage Difference
Engine Polynomials 1822
Eu-UK-USA 19c
Industrial Revolution
J a c q u a r d L o o m
Punched Cards 1801
Manual Telephone
Exchange 1878
Strowger Telephone
S w i t c h i n g 1 8 9 1
12. A p e rs ist e nt d r ea m
Technologically nowhere near being up to the
demands of the movie and robot makers, and
that is still the case….but not for much longer ?
13. W W I I CO L OSS US
Alan Turing + many more
Theoretical and Mathematical
analysis and understanding and
drive was the big game changer
Bletchley Park and Post Office (BT)
Research Lab Dollis Hill Engineering
Electronic Valves + Electro-Mechanics
Enigma + Lorenz code breaking machine
14. W W II ENIAC
P E N S t a t e t e r re s t r i a l / n a va l
artillery Trajectory/Targeting
computer
All Electronic Valves - claimed to be
a general purpose computer which
it was not - strictly speaking
16. And in BIOLOGY
The microscope & dissection
techniques on animals and humans
were revealing neurones and neural
networks as the core of beings
17. The 1940-50 view
4) Non-axon - dendrite propagation < 5 years
5) Quantum components < 3 years
6) Mechanical component < 4 years
7) The network scale required
1) Neural networks identified and drawn for > 300 years
2) Electrical action/nature identified >200 years
3) Chemical component identified > 100 years
What they didn’t know!
18. Scientific American April 2018
Physicists who have revived experiments from 50 years ago say nerve cells
communicate with mechanical pulses, not electric ones
A young woman with wavy brown hair and maroon nails lay on a gurney in a hospital
room in Copenhagen. Her extended left arm was wired with electrodes. A pop pierced
the air every few seconds—an electric shock. Each time, the woman’s fingers twitched.
She winced. She was to receive hundreds of shocks that day.
Mechanical surface waves accompany action potential propagation
• Ahmed El Hady
• & Benjamin B. Machta
Nature Communications volume 6, Article number: 6697 (2015) | Download Citation
19.
20. 1949 DONALD HEBB Learning
H e b b i a n
Decay
H e b b i a n
Build
We remember, forget, learn, make decisions on the basis
of the concatenation of accumulating switching and/or
decaying synapse states as they store ‘charge’ almost
capacitor like and thereby ‘influence’ their neighbours
21. 1949 DONALD HEBB Learning
We remember, forget, learn, make decisions on the basis
of the concatenation of accumulating switching and/or
decaying synapse states as they store ‘charge’ almost
capacitor like and thereby ‘influence’ their neighbours
22. June 21, 2018
Source:
Picower Institute at MIT
Summary:
A series of complex experiments in the visual
cortex of mice has yielded a simple rule about
plasticity: When a synapse strengthens, others
immediately nearby weaken.
Fundamental rule of brain plasticity
23. WE NOW KNOW FAR MORE
The complexity involved in realising our
own intelligence is vast and still being
uncovered/revealed/discovered and the
dimensioning is on a cosmological scale
24. WE NOW KNOW FAR MORE
The complexity involved in realising our
own intelligence is vast and still being
uncovered/revealed/discovered and the
dimensioning is on a cosmological scale
> 50 different chemicals
influence the firing point
of each neuron
Universe ~ 1080 Atoms
BioBrain ~ 1010 Neurons
>>10100 States ?
But BioBrains are very slow
info processors and introduce
gross distortions and errors
They are often illogical and do
not provide us with an ability
to cope with non-linear and
complex situations
25. WHAT WE NOW KNOW IS FUZZY!
Bio-Chemical Bio-Mechanical
Bio-Electric
Electro-Causality?
Does the detail matter?
For the Science = YES
For the Technology = NO
….well, not so much as we have
sufficient to build and solve real
problems….that may even see
a solution this problem !
26. 7 0 y e a r s o n !
“We can assert with great confidence
that we do not yet fully understand the
human (or any other) brain”
This is not going to get
any bigger, better, or in
anyway more powerful
and it is a fundamental
limiter to our further
progress
27. HIDDEN SUBTLETies
1010 - 1011 with 103 - 105
Axons/Dendrite Connections
The way all this grows, builds, connects and
functions is still the subject of much research
29. U N E X P E C T E D
A first or second order effect ?
30. 7 0 y e a r s o n !
“We might observe that the whole AI
movement started their voyage in true
engineering fashion with partial and
incorrect information…but it still worked”
In Stasis
AI is an accelerating sphere
of capability that might just
become our salvation “Thinks in a new way and
gets answers by new and
novel mechanisms”
31. B I G L O G I CA L L EA P o f 1957
We can build an electronic version !
Because it will suddenly switch at a
given level - let’s say it ‘perceives’ a
change - it is a ‘perceptron’
32. LOGICAL THINKING
So the biological brains are like:
1) A telephone network
2) A computer
3) Computer networks
4) The internet
5) Hmm - not quite ?
6) Something radically novel/complex
But we should be able to build one anyway:
1) How hard can it be ?
2) Electronics ought to do it
3) Electronic networks for sure
4) Perhaps we can revive one
5) Perhaps we can grow one
6) Or maybe a combination 3-5
7) Let’s ape nature and evolution
TURNED
OUT
TO
BE
FAR
MORE
COMPLEX
THAN ANYONE FIGURED
33. S EGWAY O UT
Early machines had 4k of memory
and far less than 1000 nodes
For average human adult
"The average number of neocortical
neurons was 19 Bn in female brains
and 23 Bn in male brains."
W
H Y
34. BIO-ENGINEERING
Ratio of neurons + axon + dendrite
network to vascular plumbing to get
energy in and heat out
STILL BEING WORKED ON: Physiology
of men and women drastically different in
respect of nerve endings across the surface
are of the skin - and the eyes - for sure
they are ‘wired’ differently!
For average human adult
"The average number of neocortical
neurons was 19 Bn in female brains
and 23 Bn in male brains."
T
0
b
e
c
o
n
t
in
u
e
d
35. PERSPECTIVE
Thermodynamics tells
us that one of these
cannot decode or
understand the other
We can only understand
our own brain with the
aid of something more
powerful
AI ?
AI + Human ?
36. Exemplar
C-Elegans
A map of the neural system of a nematode tells us nothing about how
it works - aka a road map of the UK says nothing about society !
37. ABILITY BENCHMARK
1031 v 959 cells - HUH ?
When AI helps us crack this problem we
will have the first comparative measure
of what it might take to understand
ourselves !
We ~1011 neurons
cannot understand ~102 Worms
Social behaviours with 302 neurons
Very simple neural nets in moving bodies
with sensors can do such complex things
38. 1957: 13 people deliver a computer
2017: 13 computers in one hand
S E G u e B A C K
£29,000 then ~£613,000 today
HD 320k
>3.5kW
Q u a d C o r e
Memory 1.G
12W
£20
39. i n < 3 0 Y e a r s
~ 1,000,000,000 x chip capacity
Cray 2 1985
$32M and 5kW
iPhone 5 2012
$700 and 5W
3 x more
powerful
40. i n < 3 0 Y e a r s
~ 1,000,000,000 x chip capacity
iPhone 4 2010
1.6 GFlops
0.8GHz Single-Core
iWatch 2014
2 GFlops
1GHz Dual Core
Near
Parity
41. I M P A C T O N A I
A VERY IMPERFECT comparison
86 Bn
100 Bn
23 Mn
530 Mn
Approx
Neuron
Count
Approx
Abilities
Intelligence
Communication
SensorySystems
Creativity
Manipulators
ProblemSolving
42. i n < 3 0 Y e a r s
~ 1,000,000,000 x chip capacity
~Dog Brain
~Mouse Brain
~Human
Brain
There is far more to intelligence
than a very crude analogy to transistor
- neuron equivalence and count, but this serves to
indicate one reason why AI has been along time coming !
Processing
Memory
Sensors
Adaptability
SoftwareComplexity
Autonomy
AI
Processing
Memory
Sensors
Manipulators
Communication
Networking
Intel > 100M transistors/mm2
IBM > 30Bn transistors/chip
Feature size now ~ 10nm
43. G A M E C H A N G E R 1 9 9 7
Considered to be impossible by philosophers
BEWARE MANTRAS & NEVER
Computers will never :
Play chess
Play a good game of chess
Beat a human being
Beat a grand master
Gary Kasparov
IBM Deep Blue
44. G A M E C H A N G E R 2 0 1 1
Considered to be impossible by philosophers
BEWARE MANTRAS & NEVER
Computers will never :
Play embrace general knowledge
Think wider and faster than humans
Ken Jennings
I B M Wa t s o n
45. G A M E C H A N G E R 2 0 1 2
Considered to be impossible by philosophers
BEWARE MANTRAS & NEVER
Computers will never :
Be able to help doctors
Do a better diagnosis than a human
Medicine today
I B M W a t s o n
46. G A M E C H A N G E R 2 0 1 4
Considered to be impossible by philosophers
47. G A M E C H A N G E R 2 0 1 8
Considered to be impossible by philosophers
48. Processing
Speed
Data
Storage
Internet
Processing
Indeterminate
I n t e r n e t
Storage
~1022 Bytes
Human
Storage
~1016 Bytes
Processing
~109 MF
Cat
Storage
~1014 Bytes
Processing
~108 MF
T E C H V B I O L G Y
A very rough comparison - the
actuality is far more complex
Super Computer
Storage
~1017 Bytes
Processing
~1010 MegaFlops
STILL Relatively
D U M B I N M A N Y
RESPECTS
49. B U I L D I N G A B RA I N
How hard can it be ?
Build lots of perceptrons and then concatenate
them in a network to extract features and patterns,
store memories and make inferences/decisions !
Inputs
Adjustable trim
value weighting
Summation
Decision
Gate
1
W2
W1
Wn
W3
2
3
n
Output
50. B U I L D I N G A B RA I N BUT - What kind of a network and
techniques? How big: I/O, layers,
weightings, resolution ?
Sample ML techniques
-- Decision tree learning
-- Association rule learning
-- Artificial neural networks
-- Deep learning
-- Inductive logic programming
-- Support vector machines
-- Clustering
-- Bayesian networks
51. B U I L D I N G A B RA I N BUT - What kind of a network and
techniques? How big: I/O, layers,
weightings, resolution ?
THIS IS A NON TRIVIAL
QUESTION AS THERE
ARE NO RIGHT ANSWERS
SAW vast amountS of
experimentation AND
EMPIRICISM - DISCOVERY
Sample ML techniques
-- Decision tree learning
-- Association rule learning
-- Artificial neural networks
-- Deep learning
-- Inductive logic programming
-- Support vector machines
-- Clustering
-- Bayesian networks
52. A VAST C H O I C E
A ‘zoo’ of AI Neural Network configurations
have been ‘established’ by ‘near optimised’
apps created over the past 70 years…and this
effort is still ongoing with the help of AI !
GOTO: asimovinstitute.org/neural-network-zoo/
for far more depth and discourse
53. A VA S T C H O I C E
The biggest fraction of the mix
TechniquesSoftware
54. A VA S T C H O I C E
The biggest fraction of the mix
TechniquesSoftware
Im
M
e
d
ia
t
e
l
y
v
e
r
y
c
o
m
p
l
e
x
E
x
p
e
r
im
e
n
t
IN
T
U
IT
IO
N
55. Only a rough
guide as to the
likely App - Net
Type marriages
RO U G H
G U I D E
58. RECOGNITION
Input thousands of pics
Tell net if it is
right or wrong
a pic at a time
Essentially a patter matching problem based on a
series of extracted features one layer at a time
with probabilities/weights associated with each
concatenated result through the network
59. RECOGNITION
Input thousands of pics
Tell net if it is
right or wrong
a pic at a time
Memory
Processing
Essentially a patter matching problem based on a
series of extracted features one layer at a time
with probabilities/weights associated with each
concatenated result through the network
60. RECOGNITION
H i e r a rc h i c a l f e a t u re
extraction and recognition
a layer at a time gives a
high probability of correct
when humans identify the
errors
61. Memory
Processing
RECOGNITION
H i e r a rc h i c a l f e a t u re
extraction and recognition
a layer at a time gives a
high probability of correct
when humans identify the
errors
64. A rough guide
as to the likely
App - Net Type
marriages
H a n d W r it i n g
“ T h e h i d d e n
complexity and
beauty of the
data dance”
“Every neuron is
activated on
every cycle”
65. A rough guide
as to the likely
App - Net Type
marriages
H a n d W r it i n g
“ T h e h i d d e n
complexity and
beauty of the
data dance”
“Feed forward
with very little
pre-processing
by employing
narrow historical
traces/events -
aka biological
eyes & systems”
66. A rough guide
as to the likely
App - Net Type
marriages
H a n d W r it i n g
“ T h e h i d d e n
complexity and
beauty of the
data dance”
“Only neurons
reaching some
a c t i v a t i o n
potential are
activated”
70. A I
Sense, Garner Data, Analyse, Reason
M A C H I N E
L e a r n i n g
Adaptive Networks & Algorithms
More exposure to data sees continual
improvement in accuracy with time
P E RS P ECT IV E
D e e p
L e a r n i n g
Multilayered Neural
Networks
Vast amounts of data
result in an ever
more accurate
consensus
Can get very complex but I think we can
safely say that we fully understand this
Designed, Built, Optimised by Man
Designed By Man & Self Optimising
Whilst we understand most of this
- there is a growing % of Huh !
Designed By Man & Machine
Emergent behaviours dominate
- we may or may not comprehend
Boundaries not well defined
71. There is endless depth to
just about every aspect of
AI that takes decades to
fully comprehend - and so
like all disciplines it is, in
general, rapidly becoming
speciated by expertise
and subject focus
P E RS P ECT IV E
Experts are being challenged
by the speed of change
across their specialised fields
let alone across the whole
Only a couple of
years back !
72. There is endless depth to
just about every aspect of
AI that takes decades to
fully comprehend - and so
like all disciplines it is, in
general, rapidly becoming
speciated by expertise
and subject focus
P E RS P ECT IV E
Experts are being challenged
by the speed of change
across their specialised fields
let alone across the whole
73. There is endless depth to
just about every aspect of
AI that takes decades to
fully comprehend - and so
like all disciplines it is, in
general, rapidly becoming
speciated by expertise
and subject focus
P E RS P ECT IV E
Experts are being challenged
by the speed of change
across their specialised fields
let alone across the whole
E
N
D
L
E
S
S
S
P
E
C
I A
T
I O
N
U
N
D
E
R
W
A
Y
74. G a m e C h a n g e r 2 0 1 7
Google Alpa learns the rules of GO then acts
75. G a m e C h a n g e r 2 o 1 8
Goodbye Touring Test and a lot of nonsense
P re - p ro g ra m m e d c o n t e x t a n d o n l y
limited cogn ition required !
76. G a m e C h a n g e r 2 o 1 8
Goodbye Touring Test and a lot of nonsense
T h e m a c h i n e i s d e f i n i t e l y s m a r t e r
t h a n t h e h u m a n i n t h i s c a s e !
77. A I C O N T E X T
A vital step toward cognition
Feel
Sight
Taste
Smell
Sound
Experiences
Cameras
Mobiles
Sensors
Media
Nets
IoT
“Let us pray”
“Lettuce spray”
“Let us spray”
Are we in church/mosque,
kitchen or garden ?
Ultimately, AI
is defined by
sensory systems
78. I LOVE YOU
At BTLabs ~1995
Discernment very
with voice alone:
True Affection
Frustration
Irritation
Assertion
Sarcasm
Anger
Irony
Rage
+++++
79. AW A R E N ESS
Context & Cognition
At BTLabs ~1995
Machines exceeded our
s p e e c h r e c o g n i t i o n
a b i l i t i e s i n q u i e t
e n v i r o n m e n t s , b u t
rapidly degrade with
ambient noise levels/or
d e l i v e r y v i a a n o i s y
channel
No viable solutions
available at the time
80. AWAREness
More & more clues
Who is it
What are they
Where are they
What is the topic
A priori information
Content & context
Facial expressions
Body language
All combat noise &
other generators of
errors
81. AWAREness
Only the first step!
Our machines really do have their work cut
out if they are ever going to understand us -
vastly improved NLP is just one small element!
83. W h e r e A r e W e To d ay ?
At the foothills of AI with a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
Multiple Problem Classes
with interactive memory
- little or no human help
Initial algorithms from (1) + a learning
abilty - solves problems by observing,
playing and creating rule sets
2) Learning
3) Cognitive
4) Wide
A wide range of problem
sets - with cognition &
near 100% autonomy
Initial algorithms from (2) + a degree
of understanding - sees new ways of
analysis and solution formulation
Can address any problem
type/set - has high level
context/self awareness
A completely new ‘mind’ proposition
in a variety of species connected to
the wider environment - autonomous
Machine influence
Human influence
Most AI today
is here as it is
so very easy
Google
alpha-go
IBM
Watson
84. W h e r e A r e W e To d ay ?
At the foothills of AI with a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
Multiple Problem Classes
with interactive memory
- little or no human help
Initial algorithms from (1) + a learning
abilty - solves problems by observing,
playing and creating rule sets
2) Learning
3) Cognitive
4) Wide
A wide range of problem
sets - with cognition &
near 100% autonomy
Initial algorithms from (2) + a degree
of understanding - sees new ways of
analysis and solution formulation
Can address any problem
type/set - has high level
context/self awareness
A completely new ‘mind’ proposition
in a variety of species connected to
the wider environment - autonomous
Machine influence
Human influence
Most AI today
is here as it is
so very easy
Google
alpha-go
IBM
Watson
Isolated
Fixed
Machines
Networked
Fixed
Machines
Networked
Fixed/Mobile
With Sensors
Networked
Fixed/Mobile
With Full I/O
Main Frame
Main Frame
PC Laptop
Main Frame
PC Laptop
Mobile
Main Frame
PC Laptop
Mobile Robot Sentient
Machines
Sentient
Lifeforms
Cyborgs
85. 5
TYPE 1
Reactive
Task Specific
Very Limited
Largely Pattern Matching
Human Programmers: Chess, cards,
dominoes data, speech, pictures,
characters, behaviours, movements+
Narrow Cognition
Largely Programmed by AI alone:
Subsume the networked knowledge
of previous and current generations
TYPE 3
Reasoning
Multi-Task Ability
Broadly Applicable
TYPE 2
Learning
Task Specific
Broadly Applicable
Memory and Analysis
Initial Human AI Program That Then
Adapts: Recognises highly complex/
large scale non-linear relationships
A I L A D D E R
Progress & Categories
Full Awareness
May be categorised as a ‘being’:
With a wide range of sensory units
networked to other machines
TYPE 4
Self-Aware
86. 5
TYPE 1
Reactive
Task Specific
Very Limited
Largely Pattern Matching
Human Programmers: Chess, cards,
dominoes data, speech, pictures,
characters, behaviours, movements+
Narrow Cognition
Largely Programmed by AI alone:
Subsume the networked knowledge
of previous and current generations
TYPE 3
Reasoning
Multi-Task Ability
Broadly Applicable
TYPE 2
Learning
Task Specific
Broadly Applicable
Memory and Analysis
Initial Human AI Program That Then
Adapts: Recognises highly complex/
large scale non-linear relationships
A I L A D D E R
Progress & Categories
Full Awareness
May be categorised as a ‘being’:
With a wide range of sensory units
networked to other machines
TYPE 4
Self-Aware
~ 70yrs to become a solid
& deployable technology
2027 Robotic embodiment,
extensive sensors & actuators
plus entity networking
rapidly raises the game
2017 Google Alpha GO
p r o p e l s A I i n t o a n
autonomous future of
learning & doing
2024 AI-Human cooperation
see exponential innovation &
progress of AI capabilities
87. W h at w e K n o w Cells in Human Body ~2 x 1013
Cells in Human Brain ~2 x 1011About biological intelligences
Networks of fundamentally dumb cells
Intelligence is always distributed
Cells detect, select, connect
numbers = Intelligence
Cells are multi-purpose
Cells are multifunctional
Clusters by form and task
Nervous systems are vital
V V
Baby ~ 239 splits
Man ~ 244 splits
88. W h at w e K n o w Cells in Human Body ~2 x 1013
Cells in Human Brain ~2 x 1011About biological intelligences
Networks of fundamentally dumb cells
Intelligence is always distributed
Cells detect, select, connect
numbers = Intelligence
Cells are multi-purpose
Cells are multifunctional
Clusters by form and task
Nervous systems are vital
V V
Baby ~ 239 splits
Man ~ 244 splits
INTELLIGENCE is AN
EMERGENT PROPERTY
OF COMPLEXITY
AND IN BIOLOGY THAT
IS NETWORKED
COMPLEXITY
networking simple
entities can creatE
INTELLIGENCES
89. N o B r a i n
Only sensors and actuators - no brain as such
A colony of zooids creating a nervous system - some light sensitive cells
90. N o B r a i n
Only sensors and actuators
A colony of eukaryotic organisms capable of living alone
91. C o l l e c t i v e
250k neurons + sensory system - avid networkers
92. Entombed in meat space
Considered totally vegetative !
No evidence of any I/O
C O M OT O S E D ~ 1 o Y e a r s
Sensors S = 0 no intelligence
Actuators A = 0 no intelligence
95. Ic ~ k log2[1 + K.A.S ( 1 + P.M )]
S = Sensor, A = Actuator, P = Processor, M = Memory
Followed by analysis and some math
juggling, normalisation, and
engineering licence…
…resulted in this descriptor:-
96. 1960 70 80 90 2000 10
ComputingPowerMIP/s
Intelligence
Level
PC
Estimates of
Artificial
Intelligence
Internet
R i s e o f I n t e l l i g e n c e
97. OUR NEW PARTNERS
Logical
Precise
Consistent
Considered
Rapid Recall
Vast Capacity
Fast processing
Expanding utility
Growing Memory
Variable Linearity
Memory unlimited
Evolution accelerating
Robots & AI are biggest
advance in human
capacity ever
We need new ways of thinking and problem solving to survive & progress
New tools for a new and different era
A u g m e n t i n g
our intelligence
98. A I & i n n ovat i o n
A primary tool of discovery
Analytics:
Medical
Security
Big Data
Political
Networks
Economic
Genomic
Proteomic
Diplomatic
Complexity
++++
We are way past the point where humans can
analyse complexity even on a small scale !
Design:
Chips
Devices
Systems
Networks
Behaviours
++++
Knowledge:
Veracity
Linking
Creation
Curation
Searching
Selection
++++
The machines are starting to innovate at lower
levels and where humans cannot!
99. Thinking the right way
People fear, & complain, overlook the big gains
V i v e
L a
d i f f e r e n c e
101. Ex e m p l a r
N e w C r e a t i v i t y Criticism
It is just copying and
aping what human
composers have done !
Retort 1
You mean exactly
like human
composers do ?
Retort 2
AI has only just got
into this game that
humans have be at
for well over 3M years
102. A I T H R E AT O R P R O M I S E
Is this going to be the Final
Chapter for humanity?
The media and Hollywood feed on
disasters and the prospect of some
dystopian future….and so do many
people…they just love it !
Autonomous killer robots !
103. Ex e m p l a r
H u m a n e x p e r i e n c e 5 - 2 0 k
o p e ra t i o n s i n a l i f e t i m e
Networked AI - Robot >20k
o p e ra t i o n s p e r d a y
104. H U M A N M AT E R I A LS
Reforming Pharma - Designer Solutions?
Genome Decoded
Comms
Path
Protein Folding
Will need AI
& Modelling
105. H U M A N M AT E R I A LS
Reforming Pharma - Designer Solutions?
Genome Decoded
Comms
Path
Protein Folding
Solved by Robots & Computers
Yet to be solved by AI
Will need AI
& Modelling
13 years & $3Bn
>1000x
more complex
>1000x
more complex
The seat of most human
disease and ailments
Yet to be
contemplated
106. 1.0
2.0
3.0
4.0
5.0
Water + Steam
Power
Mechanisation
Electrical Power
Mass Production
Computer
Control
Automation
Customisation Smart Factories
Efficient Additive
Production
INDUSTRY Evolves
The change cycle is accelerating
Smart Materials
Programable
Production
3R GreeningMore & More
from
less and less
107. INDUSTRY Evolves
The change cycle is accelerating AI Discovers New Materials
AI Discovers 6000 new craters
on the moon
Researchers trained AI on 90,000 images that
covered 2/3 of the moon's surface. AI was then
able to categorise craters larger than 5 km.
110. ACT U A L I TY
Can people learn too ?
S
e n s
o r
B o u n d e d
m
o v e m
e n t
- A
c t
i o n
111. WOOOO to come !
Uncanny Valley is well
understood and documented
in the field of robotics and we
are about to see an action
replay in the field of AI - and
this is beyond technophobia
or any threat to employment,
or just plain change
This is all about feeling
threatened, uncomfortable,
frightened by the unknown
intentions of a machine…
112. WOOOO to come !
We should anthropomorphise machines with
due care and attention - function over fright !
113. WOOOO to come !
We should anthropomorphise machines with
due care and attention - function over fright !
114. WOOOO to come !
F A C T
S
F A B L E
S
F U T U R E
We connect to AI and then to the AI networks !
115. WOOOO to come !
F
F
F
F
F
F
F
F F
F F
We connect to AI and then to the AI networks !
116. HAL 9000
Deep thinking
o r b i g t h re a t ?
2001: A Space Odyssey 1968 Directed by Stanley Kubrick, based on A C ClarkeTnovel.
The film follows a voyage to Jupiter with the sentient computer HAL after the discovery of
a mysterious black monolith affecting human evolution.
117. TOASTER
Deep humour
or nightmare?
Talkie Toaster, in Red Dwarf
novels & TV series.
Manufactured by Crapola Inc.,
an annoying, monomaniacal,
AI toaster purchased by Dave
Lister whilst on leave at a
second-hand junk shop on
Miranda, along with a robot
goldfish and a smuggled pet
cat.
More intelligent than the Red
Dwarf computer Holly
118. An A.I. system:
1) Must be subject to the full gamut of laws that apply to its human operator/creator
2) Must clearly disclose that it is not human
3) Cannot retain or disclose confidential information without explicit approval from the source
Etzioni’s 2017
A Robot must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm
2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
Asimov’ 1942
LAWS To Be HEEDED ?
Ignored by governments & industry to date
119. An A.I. system:
1) Must be subject to the full gamut of laws that apply to its human operator/creator
2) Must clearly disclose that it is not human
3) Cannot retain or disclose confidential information without explicit approval from the source
Etzioni’s 2017
A Robot must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm
2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
Asimov’ 1942
LAWS To Be HEEDED ?
Ignored by governments & industry to date
NEVER APPLIED
N o
C h a n c e
120. ONLY ONE
All that is needed
Mobile AI/Robotic weapon platforms
demand far less resources than any
atom bomb and/or missile program
Numerous rogue states will
quickly embrace this new
opportunity!
W
e a p o n s
C o n t r o l
S E E M S
I m p o s s i b l e