A few fundamental concepts in digital electronicsJoy Prabhakaran
A simple and fun exploration of the simple conceptual building blocks that form the bed rock of electronics. The focus is almost totally on digital electronics.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
A few fundamental concepts in digital electronicsJoy Prabhakaran
A simple and fun exploration of the simple conceptual building blocks that form the bed rock of electronics. The focus is almost totally on digital electronics.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
This article is all about what AI trends will emerge in the field of creative operations in 2024. All the marketers and brand builders should be aware of these trends for their further use and save themselves some time!
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
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- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
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Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
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The six step guide to practical project managementMindGenius
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If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
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“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
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Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Applitools
During this webinar, Anand Bagmar demonstrates how AI tools such as ChatGPT can be applied to various stages of the software development life cycle (SDLC) using an eCommerce application case study. Find the on-demand recording and more info at https://applitools.info/b59
Key takeaways:
• Learn how to use ChatGPT to add AI power to your testing and test automation
• Understand the limitations of the technology and where human expertise is crucial
• Gain insight into different AI-based tools
• Adopt AI-based tools to stay relevant and optimize work for developers and testers
* ChatGPT and OpenAI belong to OpenAI, L.L.C.
2. The Plan
● Introduction
● A few words about neurons
● Similarities to Akka actors
● How to model a neuron with Akka
● Building blocks of a neuron network
● An example:
the S.O.S. signal recognition
3. Instead… bees!
● Approximately 900,000 neurons in total
● Mostly hardwired
● Work on unreliable, insufficient data
● Still able to do amazing feats
4. Basic info about actual neurons
● Dendrites
● An axon
● Electrical and ...
● … electro-chemical
signals
● Neurotransmitters:
excitatory and
inhibitory (GABA).
5. Reactive and asynchronous
● No external supervisor
● Only reacting to stimuli
● No bigger picture
(a.k.a. what other neurons?)
9. Interesting Akka traits
● Concurrent
● Communicate through messages
● Reactive
● Sending a message takes time
● Communication is unordered
10. Local synchronization – why?
● Message time gaps cannot be controlled
● Neurons are triggered by messages
● In small interacting blocks of neurons their
sequence of responses have to be controlled
11. Local synchronization – how?
● Estimate the max time gap (an iteration)
● Simulate the refractory period
● Note that it works only for small blocks of
interacting neurons
18. Dealing with noise
Input Output Input Output
1,0,0,0,1,0,0,0,1,0,0,0 … → s 1,1,0,0,1,1,0,0,1,1,0,0 --- → o
1,0,0,0,1,0,0,0,1,0,0,1 … → s 1,1,0,0,1,1,0,0,1,0,1,0 --- → o
1,0,0,0,1,0,0,1,1,0,0,0 ..- 1,1,0,0,1,0,1,0,1,1,0,0 --- → o
1,0,0,1,1,0,0,0,1,0,0,0 .-. 1,0,1,0,1,1,0,0,1,1,0,0 --- → o
1,0,0,0,1,0,0,0,0,1,0,0 … → s 1,1,0,0,1,1,0,0,1,0,1,1 ---. → o
1,0,0,0,0,1,0,0,1,0,0,0 .. 1,1,0,0,1,0,1,1,1,1,0,0 ---. → o
0,1,0,0,1,0,0,0,1,0,0,0 .- 1,0,1,1,1,1,0,0,1,1,0,0 --.- → o
1,0,0,0,1,0,0,0,0,0,1,0 … → s 1,1,0,0,1,1,0,0,1,1,1,0 ---. → o
1,0,0,0,0,0,1,0,1,0,0,0 .- 1,1,0,0,1,1,1,0,1,1,0,0 ---. → o
0,0,1,0,1,0,0,0,1,0,0,0 -. 1,1,1,0,1,1,0,0,1,1,0,0 --.- → o
1,0,0,0,1,0,0,0,0,0,0,1 … → s 1,1,0,0,1,1,0,0,1,1,1,1 ---- → o
1,0,0,0,0,0,0,1,1,0,0,0 .- 1,1,0,0,1,1,1,1,1,1,0,0 ---- → o
0,0,0,1,1,0,0,0,1,0,0,0 -. 1,1,1,1,1,1,0,0,1,1,0,0 ---- → o
19. What have we learned (if anything)
● Considerable similarities between Akka actors
and neurons, not inspired in any way
● Time gaps as information
● Distribution: a key to intelligence?
20. Where to search for more
● Akka: http://doc.akka.io/docs/akka/2.4/scala.html
● Neurobiology: “The Astonishing Hypothesis: The
scientific search for the soul”, Francis Crick (1994)
● My own three eurocents: “Artificial Neural Networks in
Akka”, Maciej Gorywoda, Scribd and Academia.edu
23. Thank You!
You can find the project at
http://github.com/makingthematrix/ann
You can find me somewhere near coffee
or at Wire: @maciek
Editor's Notes
Hello everyone,
My name is Maciek Gorywoda, I came here from Berlin, where I'm a Scala and Android developer and I work on an internet communicator, Wire.
But my today's talk is not about my work. It's about neural networks.
I assume we all know Akka, more or less, so instead of going into that I will start with a discussion of real neurons; then we'll talk about their similarities to Akka actors; and how to implement them as such; and then there will be a simple example of a small network, with only one input neuron, recognizing the S.O.S. message from long and short bursts of signal.
The thing is, nowadays, when the topic of neural networks comes up, what usually comes to our own neural networks, the brains, is an image of a huge multi-layered perceptron playing Go or recognizing faces. The network I want to talk about today is quite the opposite.
One of my inspirations were these little creatures. A brain of a honey bee consists of a bit less than a million neurons, whereas a human brain has about 100 billion – a hundred thousand times more. Also, even though recent research shows that bees are able to learn, most of their capabilities is there in a bee from the very beginning of its life.
A bee's brain works on small chunks of very unreliable and limited data and has only split seconds to react. Yet, this is enough to avoid danger, gather food, communicate and organize.
So, I thought, maybe instead of huge M-L. Ps I could check what we can achieve with only a handful of neurons.
A typical neuron consists of a bulky core, which is not really interesting to us right now, dendrites, these are these small tentacles which are used to receive signals, and a large tentacle called an axon, which sends the signals to other neurons.
Signals can be electric, and these were the inspiration behind the traditional models of artificial neurons which send numbers between 0 and 1. But most of signals in neurons are electro-chemical, and that goes beyond this simple model. The chemical molecules transmitted from one neuron to another are called neurotrasmitters. One, which is of particular interest to us, is called GABA, gamma-amino-butyric acid, and it causes neurons to become silent. There are even special neurons which seem to send only silencing messages. Please keep it in mind. It will be important shortly.
A neuron is reactive. It acts when triggered by a signal coming from another neuron. If the signal is strong enough, or if it's a long enough series of weak signals, the neuron sends its own signal to the outside.
Another trait is something that should be obvious, in fact, but quite often it is overlooked: a single neuron does not know that it is a part of a nervous system. There is no higher-level entity controlling it. It just reacts in its own time to a stimulus coming from the outside and sends its own signals further away. It's basically asynchronous.
When we look at a multi-layered perceptron model we can see that neurons in one layer are connected to the neurons behind them. In each iteration each neuron actively looks to these neurons behind it for its signals, multiply the signals by the weights of respective commections, sums the results, checks its own threshold against it, and if the result is bigger than the threshold, it applies its activation function to the sum and presents the result of the activation function for other neurons to see. Nothing reactive about it.
And please note that for it to work, the neurons have to be activated in order, from the first layer to the last. They're synchronous.
But do you know what else is reactive and asynchronous? Akka!
Ok, to be fair, I have to mention that there are models called spiking neural networks, which actually have these features, and they can also simulate neurotrasmitters in detail. They are much closer to actually simulating a working brain than traditional models, but they tend to be very complex.
And I wanted something very simple.
If you want some code, you can imagine that this slide is a design of a class implementing an Akka actor. It can receive two types of messages: either a signal of some strength, or a silencing message. A signal is added to the buffer, and checked against the threshold. If it's not strong enough, nothing more happens. If it is stronger, the buffer is cleared, and the neuron's own signal (usually 1.0) is being send forward.
If a silencing message is received, the buffer is cleared and the neuron stops reacting to consecutive messages for a given amount of time.
Actors work concurrently to one another. Actors communicate with one another with messages and not in any other way. Actors are reactive. Their computations are triggered by incoming messages; there is no need for a supervisor entity which would iterate over them and send requests to perform computations. Sending a message takes time. Every time a message is sent, there is a considerable time gap between the moment it is sent and the moment it is received. Such time gaps exist even if the actor sends a message to itself. "Considerable" means that it has to be taken into account when designing a network. Communication is unordered. Two messages sent at the same time may reach their targets with a considerable time difference, and two messages sent one after another from one source to two different targets may be received in a different order.
So, if the comunnication is unordered, doesn't it mean that however will we design it, it will quickly descend into chaos?
Well, yes. To prevent the chaos, we need a way to enforce that a small number of interacting neurons will work in an established sequence. These blocks of neurons can then be connected asynchronously and it will work well, but on the smallest level some synchronization is necessary.
But hold on. There is no supervisor. Neurons are not aware they are a part of a bigger system. So, how to do it?
In fact real neurons already know a way to do it, although in their case it's a bit of a side effect.
Sending a signal is a drastic change in the neuron's chemistry. It needs time to recompose itself. This time is called the refractory period and during that period a neuron, even if it's stimulated, won't respond.
So, we can't control the time gap of a message, but we can estimated its maximum. And we can make our Akka actor to change its context for a moment, so that we will be sure that it triggers at most once during this max time gap. And, as it turns out, this is enough. From now on, I will call the max time gap an iteration. It will be important in a moment.
One neuron is useless. Only when we connect they start to do something. In this talk we will discuss two such "blocks" of neurons. The first of them is what I called a Signal Sum, because it... sums signals. Of course, a single neuron also sums signals, so what's the point?
In Akka, an actor knows where to send its own signals, but it does not know where its input signals are coming from. Imagine that we want to have a single neuron which would trigger only after N signals are sent to it. It means that we have to go to the neurons behind this one and manually set the weights of the connections to it. That's messy. Instead, we want a black box. We want to be able to send full force signals and only after N such signals our Signal Sum should trigger. All that logic should be inside the block.
A delay gate is the other block used in the example. It's a bit more complicated than the signal sum. When triggered by the input signal, a delay gate shuts down for a given number of iterations (maximum time gaps) and after that it releases an output signal and in the same time opens itself again to accept new input signals. It uses self-silencing in the first neuron, DG1, to shut down and so prevent any additional input signal from interfering, and a small feedback loop at DG2 with the weight being 1 over N where N is the number of iterations of the delay.
It means that it's not the signal that is important, but the time gap. If during a given amount of time nothing stops the delay gate, it will tell us about it. This is basically its message: “Hey, nothing happened during the last second!”.
But how to inform a delay gate that something happened?
The concept of a neuron block allows us to introduce a special kind of neuron: a silencing one. Remember the GABA neurotransmitters and special neurons sending them? A silencing artificial neuron is a neuron which can be triggered by any signal coming to it (a silencing one as well), and in response it sends silencing messages to all neurons it is connected to. Just as putting two neurons in a Signal Sum block lets us not to worry about the exact values of all incoming signals, adding a silencing neurons means that if we want to silence the whole block, we just have to send a signal to that neuron. We don't have to know anything about the block's internals.
OK, now that we have all the pieces in place, it's time for the example
Even though a nearly million neurons of a bee's brain is very little in comparison with our brains, it's still way too many for practical reasons. Our example has to be much simpler. So, my idea is to have a sequence of short and long signals and try to recognize if they form S.O.S.
This is also a place where the analogy of a real neuron and an Akka actor breaks a little, because we need to encode short and long sound signals into numbers. One “1” means a short signal, two “1”s mean a long signal. “0”s are actually not signals at all. They are not being sent. They are time gaps between signals.
So, we have a signal sum and a delay gate. How we can make these blocks interact in order to recognize dots and lines?. The delay gate, after receiving the first input signal, will wait for two iterations, and then it will release an output. In the same time, the signal sum will receive the same input signal and will wait for the second one to release its own output. When one block releases the output, it also sends a silencing signal to the other block. This way, if the input signal doesn't come quick enough, the delay gate wins and we will have a dot. If the second input signal comes soon enough, the signal sum wins and we will have a line. So, the gap betweeen signals is what counts, not the signals themselves. Two signals with no gap, or a very small gap in between, can be interpreted as one long signal: a line in the Morse's code. A more significant gap means that signals are distinct from each other: they are dots.
From here, the path to build the whole network is pretty straightforward. We simply add two more signal sums. The first one will be connected to the delay gate which recognizes dots. We need three dots to get an S. The other one will be connected to the signal sum recognizing lines. We need three lines to get an O.
Signals sums recognizing S and O are also connected to each other with silencing neurons, so if we get an S, all the parallel work in order to recognize O will be cancelled, and vice versa.
One of the most interesting traits of neural networks is the ability to find patterns in noise. In fact, we could make a generalization and say that all neural networks do, including our brains, is finding patterns. Please note that the silencing neurons work as an implementation of a winner-takes-all strategy: we can't get both a dot and a line in the same moment, and we can't get both S and O. Each block maintains a set of simple rules. If they are fulfilled, the block triggers, and the other one is silenced. If there is some noise in the input signal, both blocks have a bit harder to recognize the pattern, but eventually one of them should trigger and silence the other. Of course, it can also happen that the signal will be so noisy that some of the dots will be recognized as lines, and vice versa. In this case, our second line of defense comes to use: S and O blocks will as well try to recognize the signals and whichever will do it first will silence the other.
What we have learned, if anything?
First of all, I don't suspect creators of Akka of being inspired by neurons. And definitely I don't think that the brain evolution was inspired by Akka. Yes, the two are governed by strangely similar rules. I find it very interesting and worthy of further research.
Another interesting trait is that it's not signals which are important, but the time between them. Consider music. …
And, at last, but not at least, maybe intelligence is indeed a whole which is bigger than the sum of its simple parts. Neurons, networks of actors, bee hives.
About Akka… I think the Akka documentation is a great place to start. I don't think I have to say anything more about it.
When it comes to neurobiology I srongly recomment a book by Francis Crick, “The Astonishing Hypothesis”. It's a bit old, but still a very good introduction into neurobiology for mortal people. It was translated to Polish as “Zdumiewająca hipoteza”.
And if you want to read a bit more about what I have already said, you can download the article which was the basis for this talk.
But I know we are all busy people.
So at least I recommend that you go to YouTube and watch Crash Course Neurology.
So, this is all. You can find my project on GitHub. From there you can download it, read the instructions and play a little.
If you have any questions, you can ask me now, or find me on Wire.
Thank you.