Who’s Going to Make Money in AI and Machine Learning? We’re currently experiencing an AI gold rush. Billions are being invested. AI startups abound. Google, Amazon, and Microsoft are duking it out for AI supremacy. Corporations are scrambling to ensure they adopt AI ahead of their competitors while looking over their should at startups. The winners will be the picks and shovels of this gold rush. They are the tech giants that have the scale of data, talent, capital and distribution to power the AI revolution. But enterprises stand to create nearly $4 trillion in value from AI by 2022. But to get AI and data science projects out of experimentation and into use across the organisation requires mobilising and engaging the executive team. AI startups that are looking to scale also need to cross the commercial divide from technology to the enterprise.
201904 How will AI and machine learning transform local search and SMBs? Simon Greenman
From the SIINDA localcomm 2019 conference. We’re currently experiencing an AI gold rush. Billions are being invested. AI startups abound. Google, Amazon, and Microsoft are duking it out for AI supremacy. Corporations are scrambling to ensure they adopt AI ahead of their competitors while looking over their shoulder at startups. And countries are vying for AI supremacy. The question is where does local fit into this new frontier. This session will provide a non-technical introduction to AI and show how value is being created across industries and functions. It will take a deep dive into local and show how AI can be used to drive sales, marketing and customer service; drive efficiencies; deeper insights and competitive differentiation. Weaving in practical case studies it will also look at how the tech giants are becoming AI first companies.
The 4 Top Artificial Intelligence Trends For 2021Bernard Marr
Artificial Intelligence (AI) has been a mega-trend in 2020. The current pandemic has only accelerated the relevance and adoption of AI and machine learning. Here we look at some of the top AI trends for 2021.
Artificial Intelligence In Automotive Industry: Surprisingly Slow Uptake And ...Bernard Marr
Artificial intelligence has been a hot topic in the automotive industry for years, and we have seen rapid advances in things like autonomous driving. It, therefore, comes as a bit of a surprise that new research shows a slower than expected AI adoption rate. Let’s look at why.
The 5 Biggest Technology Trends Disrupting Engineering And Design In 2020Bernard Marr
There are many changes to design and engineering being ushered in by today's new technologies from digital twins to artificial intelligence (AI). The human professionals in these industries are being challenged to acquire new skills, be comfortable with change, and to adapt to collaborating with machines. Here are 5 of the biggest technology trends disrupting engineering and design.
Overcoming AI Challenges with IBM’s AI LadderBernard Marr
With $16 trillion up for grabs by 2030, there’s a race to be leaders and pioneers in the brave new world of AI and automation. Across every industry, we see an acceleration in the rollout of smart, cognitive systems that promise improved customer experience and streamlined more efficient business processes.
The Amazing Ways eBay Is Using Artificial Intelligence To Boost Business SuccessBernard Marr
Multinational e-commerce site eBay has used artificial intelligence (AI) for the last decade by training the algorithms with data sets from the previous two decades. Recent developments and enhancements to the company's services and tools have benefited from the AI algorithms getting smarter and by leveraging deep learning. Here we look at a few ways eBay uses artificial intelligence and machine learning.
Data science provides businesses with advanced tools and technologies that allow them to automate complicated business processes linked with extracting, analyzing, and presenting raw data.
With so much happening in the technical field, and the data being generated at a rapid speed, it is crucial to know about the latest as well as the upcoming trends in data science.
201904 How will AI and machine learning transform local search and SMBs? Simon Greenman
From the SIINDA localcomm 2019 conference. We’re currently experiencing an AI gold rush. Billions are being invested. AI startups abound. Google, Amazon, and Microsoft are duking it out for AI supremacy. Corporations are scrambling to ensure they adopt AI ahead of their competitors while looking over their shoulder at startups. And countries are vying for AI supremacy. The question is where does local fit into this new frontier. This session will provide a non-technical introduction to AI and show how value is being created across industries and functions. It will take a deep dive into local and show how AI can be used to drive sales, marketing and customer service; drive efficiencies; deeper insights and competitive differentiation. Weaving in practical case studies it will also look at how the tech giants are becoming AI first companies.
The 4 Top Artificial Intelligence Trends For 2021Bernard Marr
Artificial Intelligence (AI) has been a mega-trend in 2020. The current pandemic has only accelerated the relevance and adoption of AI and machine learning. Here we look at some of the top AI trends for 2021.
Artificial Intelligence In Automotive Industry: Surprisingly Slow Uptake And ...Bernard Marr
Artificial intelligence has been a hot topic in the automotive industry for years, and we have seen rapid advances in things like autonomous driving. It, therefore, comes as a bit of a surprise that new research shows a slower than expected AI adoption rate. Let’s look at why.
The 5 Biggest Technology Trends Disrupting Engineering And Design In 2020Bernard Marr
There are many changes to design and engineering being ushered in by today's new technologies from digital twins to artificial intelligence (AI). The human professionals in these industries are being challenged to acquire new skills, be comfortable with change, and to adapt to collaborating with machines. Here are 5 of the biggest technology trends disrupting engineering and design.
Overcoming AI Challenges with IBM’s AI LadderBernard Marr
With $16 trillion up for grabs by 2030, there’s a race to be leaders and pioneers in the brave new world of AI and automation. Across every industry, we see an acceleration in the rollout of smart, cognitive systems that promise improved customer experience and streamlined more efficient business processes.
The Amazing Ways eBay Is Using Artificial Intelligence To Boost Business SuccessBernard Marr
Multinational e-commerce site eBay has used artificial intelligence (AI) for the last decade by training the algorithms with data sets from the previous two decades. Recent developments and enhancements to the company's services and tools have benefited from the AI algorithms getting smarter and by leveraging deep learning. Here we look at a few ways eBay uses artificial intelligence and machine learning.
Data science provides businesses with advanced tools and technologies that allow them to automate complicated business processes linked with extracting, analyzing, and presenting raw data.
With so much happening in the technical field, and the data being generated at a rapid speed, it is crucial to know about the latest as well as the upcoming trends in data science.
The major players covered in the global HR advisory services market are IBM Corporation, Mckesson Corporation, Dell, Tata Consultancy Services, Infosys Limited... @ http://bit.ly/2Pfuwt9
The Amazing Ways That L’Oréal Uses Artificial Intelligence To Drive Business ...Bernard Marr
L’Oréal, the world's largest beauty brand, continues to invest in technology and artificial intelligence to enhance its operations, products, and customer experience. From its technology incubator that focuses on how to best use technology to support the beauty industry to its innovative products such as an AI-powered skin diagnostic, L’Oréal uses artificial intelligence to its advantage.
3 Important Ways Artificial Intelligence Will Transform Your Business And Tur...Bernard Marr
Artificial Intelligence (AI) is likely to be the most powerful technology humans have ever had access to. Here we look at the three main ways AI can be used in businesses to deliver success
The Amazing Ways Toyota Is Using Artificial Intelligence, Big Data & RobotsBernard Marr
Toyota is preparing for the 4th industrial revolution with investments in artificial intelligence (AI), big data and robots. They are enhancing AI technology to power autonomous vehicles, create better connection between humans and machines, provide solutions that enhance the life and work of humans and more.
The Biggest Artificial Intelligence Milestones Of The Decade So FarBernard Marr
We are only a few years into the '20s, but by any measure, it's been an eventful decade so far. It’s frequently been said that we’ve already seen five years’ worth of technology-driven change packed into the last 18 months, mostly out of necessity, since the start of the Covid-19 pandemic. And artificial intelligence (AI) development certainly hasn’t lagged behind.
Back in 2019, in what seems like another lifetime, I had a stab at picking out what I thought were the most significant developments so far in the history of AI. With everything that has developed since then, I thought it would be a good idea to round up the biggest breakthroughs and most significant developments of the current decade.
Unsurprisingly, many of the biggest and most headline-grabbing developments have been in the area of healthcare. However, ongoing research has also pushed boundaries of what is possible with natural language processing and vehicle autonomy.
How To develop An Artificial Intelligence Strategy: 9 Things Every Business M...Bernard Marr
An artificial intelligence (AI) strategy has become a vital tool every organisation needs. Based on my experience helping companies develop their AI strategies, I share my nine things every AI strategy must include.
The Amazing Ways Telecom Companies Use Artificial Intelligence And Machine Le...Bernard Marr
The telecommunications industry uses artificial intelligence (AI) and machine learning to benefit many aspects of their business from improving customer service to predictive maintenance. The most common applications used by telecoms make it clear that adopting AI and machine learning was essential for each company’s survival and ability to stay competitive.
Rapidly evolving technology is creating many opportunities for strategic technologies to rise in the market. As the demand for specific skills increases, let's look at the current trends for an IT professional to follow.
This is a presentation delivered by Katie King at the UKInbound tourism conference, on "How can marketing professionals adapt to survive & thrive in a world of AI?"
https://www.ukinbound.org/events/tourism-marketing-in-a-digital-age-seminar/
How To Get Started With Your AI JourneyBernard Marr
Artificial intelligence (AI) and automation will create $15.7 trillion in value for businesses over the next decade. Make no mistake, this is the new gold rush, and companies that are able to understand, adapt and leverage this world-changing technology to meet their goals have the potential to achieve huge growth.
We have spent the last three months speaking with over 40 leading Artificial Intelligence (AI) and Machine Learning (ML) companies in Europe and Israel to gain detailed insight and understanding of the development of the market and the future direction
We are pleased to share our work and findings with you and the broader community.
You can read our report ‘International AI and ML Landscape’ here.
A prelude for FutureScapes 2018 which kicks off in Asia/Pacific on November 3rd, revisit last year's set of Predictions and see how IT and business have changed since then. How many did we get right? #IDCFutureScapes
Business 4.0 - How can PR professionals prepare, evolve and thrive in a new ...Zoodikers
Delivered at the ICCO Global PR summit in Helsinki, this presentation introduces the audience to the world of AI and its impact on the PR and wider marketing industry. It considers the encroachments of AI in our personal lives and provides a number of ways to prepare for the future.
Insurance companies looking to differentiate themselves must be aware of 5 technology trends that will characterize the post-digital future. Read more.
The New Global AI Arms Race: How Nations Must Compete On Artificial IntelligenceBernard Marr
As governments race to unlock AI’s potential within their countries, who is leading the pack, and who is falling behind? Get the latest research and advice about what it takes to get an advantage in the global AI arms race.
10 Reasons To Use Psychometric Testing - Big 5 Assessmentspaulmnewman
In this presentation, we look at 10 different reasons as to why Hiring Managers, Recruiters and HR professionals might like to use Psychometric Testing within their recruitment process.
The 10 Best AI And Data Science Undergraduate Courses For 2021Bernard Marr
Artificial Intelligence (AI) and data science skills are in huge demand. A global skills shortage in these fields means the job prospects for anyone with skills in AI and data science is massive. Here we look at the top ten undergraduate degree courses available today.
Innovation is Key to Growth - Big ideas - 2019 - ARK InvestPaulo Ratinecas
Why Invest in Disruptive Innovation?
ARK believes that disruptive innovation is key to growth.
We aim to identify large-scale investment opportunities
by focusing on public companies that are the leaders,
enablers, and beneficiaries of disruptive innovation.
Opportunities resulting from disruptive innovation are
often undiscovered or misunderstood by traditional
investment managers who are focused on sectors,
indexes, short-term earnings and price movements.
ARK’s research spans across sectors, industries, and
markets to gain a deeper understanding of the
convergence, market potential, and long-term impact
of disruptive innovation.
DISRUPTIVEINNOVATION
ARK defines ‘‘disruptive innovation’’ as the introduction
of a technologically enabled new product or service
that should transform economic activity by creating
simplicity and accessibility while driving down costs.
The major players covered in the global HR advisory services market are IBM Corporation, Mckesson Corporation, Dell, Tata Consultancy Services, Infosys Limited... @ http://bit.ly/2Pfuwt9
The Amazing Ways That L’Oréal Uses Artificial Intelligence To Drive Business ...Bernard Marr
L’Oréal, the world's largest beauty brand, continues to invest in technology and artificial intelligence to enhance its operations, products, and customer experience. From its technology incubator that focuses on how to best use technology to support the beauty industry to its innovative products such as an AI-powered skin diagnostic, L’Oréal uses artificial intelligence to its advantage.
3 Important Ways Artificial Intelligence Will Transform Your Business And Tur...Bernard Marr
Artificial Intelligence (AI) is likely to be the most powerful technology humans have ever had access to. Here we look at the three main ways AI can be used in businesses to deliver success
The Amazing Ways Toyota Is Using Artificial Intelligence, Big Data & RobotsBernard Marr
Toyota is preparing for the 4th industrial revolution with investments in artificial intelligence (AI), big data and robots. They are enhancing AI technology to power autonomous vehicles, create better connection between humans and machines, provide solutions that enhance the life and work of humans and more.
The Biggest Artificial Intelligence Milestones Of The Decade So FarBernard Marr
We are only a few years into the '20s, but by any measure, it's been an eventful decade so far. It’s frequently been said that we’ve already seen five years’ worth of technology-driven change packed into the last 18 months, mostly out of necessity, since the start of the Covid-19 pandemic. And artificial intelligence (AI) development certainly hasn’t lagged behind.
Back in 2019, in what seems like another lifetime, I had a stab at picking out what I thought were the most significant developments so far in the history of AI. With everything that has developed since then, I thought it would be a good idea to round up the biggest breakthroughs and most significant developments of the current decade.
Unsurprisingly, many of the biggest and most headline-grabbing developments have been in the area of healthcare. However, ongoing research has also pushed boundaries of what is possible with natural language processing and vehicle autonomy.
How To develop An Artificial Intelligence Strategy: 9 Things Every Business M...Bernard Marr
An artificial intelligence (AI) strategy has become a vital tool every organisation needs. Based on my experience helping companies develop their AI strategies, I share my nine things every AI strategy must include.
The Amazing Ways Telecom Companies Use Artificial Intelligence And Machine Le...Bernard Marr
The telecommunications industry uses artificial intelligence (AI) and machine learning to benefit many aspects of their business from improving customer service to predictive maintenance. The most common applications used by telecoms make it clear that adopting AI and machine learning was essential for each company’s survival and ability to stay competitive.
Rapidly evolving technology is creating many opportunities for strategic technologies to rise in the market. As the demand for specific skills increases, let's look at the current trends for an IT professional to follow.
This is a presentation delivered by Katie King at the UKInbound tourism conference, on "How can marketing professionals adapt to survive & thrive in a world of AI?"
https://www.ukinbound.org/events/tourism-marketing-in-a-digital-age-seminar/
How To Get Started With Your AI JourneyBernard Marr
Artificial intelligence (AI) and automation will create $15.7 trillion in value for businesses over the next decade. Make no mistake, this is the new gold rush, and companies that are able to understand, adapt and leverage this world-changing technology to meet their goals have the potential to achieve huge growth.
We have spent the last three months speaking with over 40 leading Artificial Intelligence (AI) and Machine Learning (ML) companies in Europe and Israel to gain detailed insight and understanding of the development of the market and the future direction
We are pleased to share our work and findings with you and the broader community.
You can read our report ‘International AI and ML Landscape’ here.
A prelude for FutureScapes 2018 which kicks off in Asia/Pacific on November 3rd, revisit last year's set of Predictions and see how IT and business have changed since then. How many did we get right? #IDCFutureScapes
Business 4.0 - How can PR professionals prepare, evolve and thrive in a new ...Zoodikers
Delivered at the ICCO Global PR summit in Helsinki, this presentation introduces the audience to the world of AI and its impact on the PR and wider marketing industry. It considers the encroachments of AI in our personal lives and provides a number of ways to prepare for the future.
Insurance companies looking to differentiate themselves must be aware of 5 technology trends that will characterize the post-digital future. Read more.
The New Global AI Arms Race: How Nations Must Compete On Artificial IntelligenceBernard Marr
As governments race to unlock AI’s potential within their countries, who is leading the pack, and who is falling behind? Get the latest research and advice about what it takes to get an advantage in the global AI arms race.
10 Reasons To Use Psychometric Testing - Big 5 Assessmentspaulmnewman
In this presentation, we look at 10 different reasons as to why Hiring Managers, Recruiters and HR professionals might like to use Psychometric Testing within their recruitment process.
The 10 Best AI And Data Science Undergraduate Courses For 2021Bernard Marr
Artificial Intelligence (AI) and data science skills are in huge demand. A global skills shortage in these fields means the job prospects for anyone with skills in AI and data science is massive. Here we look at the top ten undergraduate degree courses available today.
Innovation is Key to Growth - Big ideas - 2019 - ARK InvestPaulo Ratinecas
Why Invest in Disruptive Innovation?
ARK believes that disruptive innovation is key to growth.
We aim to identify large-scale investment opportunities
by focusing on public companies that are the leaders,
enablers, and beneficiaries of disruptive innovation.
Opportunities resulting from disruptive innovation are
often undiscovered or misunderstood by traditional
investment managers who are focused on sectors,
indexes, short-term earnings and price movements.
ARK’s research spans across sectors, industries, and
markets to gain a deeper understanding of the
convergence, market potential, and long-term impact
of disruptive innovation.
DISRUPTIVEINNOVATION
ARK defines ‘‘disruptive innovation’’ as the introduction
of a technologically enabled new product or service
that should transform economic activity by creating
simplicity and accessibility while driving down costs.
Technology will continue to play a big role in terms of the global economy. Countries need to revisit their various policies as part of supporting the technology sector in their country.
B2B Tech Trends 2019
Read the full post on B2B TECH TRENDS 2019 at fourquadrant.com/tech-trends-for-b2b-marketers/
Included in this SlideShare Deck is:
Trend No. 1: Autonomous Things
Trend No. 2: Augmented Analytics
By 2020, more than 40% of data science tasks will be automated
Trend No. 3: AI-Driven Development
Trend No. 4: Digital Twins
Trend No. 5: Empowered Edge
Trend No. 6: Immersive Technologies
By 2022, 70% of enterprises will be experimenting with immersive technologies for consumer and enterprise use, and 25% will have deployed to production
Trend No. 7: Blockchain
Blockchain Will Create $3.1T in Business Value by 2030
Trend No. 8: Smart Spaces
Trend No. 9: Digital Ethics & Privacy
Trend No. 10: Quantum Computing
============================================================
FOR ADDITIONAL GO TO MARKET RESOURCES VISIT www.fourquadrant.com
============================================================
Read the full post on B2B TECH TRENDS 2019 at fourquadrant.com/tech-trends-for-b2b-marketers/
CMO Spend Survey, fourquadrant.com/cmo-spend-research-results-2018-2019/
Go to Market Resources @ fourquadrant.com
Predictive Marketing Analytics Buyer’s Checklist, fourquadrant.com/go-to-market-planning-templates/predictive-marketing-analytics-buyers-checklist/
Free Downloads @ fourquadrant.com/free-marketing-templates/
Go to Market Insights @ fourquadrant.com/go-to-market-planning-templates/
2018 was a big year for innovation in emerging technologies and the trend will continue in 2019 with lots of exciting opportunities looking forward for us to grow tremendously. Let us look into technologies that will shake the market up.
Artificial Intelligence (AI) will create $13 trillion in value by 2030, according to McKinsey. That's a pretty good reason to take a closer look at the AI market and see what's under the hood. And that's exactly what I did in the Enterprise VC: 2019 AI Market Review deck.
Manufacturing is changing at a rapid pace and Industrial Tech startups are popping up everywhere.
What do you need to benefit from these developments and to ride the wave of change in manufacturing.
Information Technology Is Now Being Reshaped By Many Advance Technologies Rapidly Growing In The Market. Starting From Small Pin To Huge Machines These Innovative technical Trends Are Being Used Daily.
Artificial Intelligence is trendy. Every event, every strategy meeting and every consulting firm talks about it. This whitepaper aims to separate actual facts and important background information from the overarching marketing buzz.
You will get a short but information-rich wrap up about: What causes the current hype? Where are we today? What are the innovation leaders doing with AI? And what are immediate action points to focus on by applying artificial intelligence to your business?
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
Learning Objective: Discover the upcoming trends of information technology
This seminar looks at technology trends that should be on your radar. As a technology professional, staying on top of trends is crucial. Join us as our expert panelists discuss the upcoming trends and game-changing technologies of the future.
At the end of this seminar, participants will:
a. Learn how to identify the areas where technology changes are likely.
b. Identify resources to use to keep abreast of technology changes in their industry.
c. Learn how to analyze trends for opportunities to grow their careers.
From the changing landscape of ICT infrastructure to tackling tricky supply chain issues, we explore every corner of the IT industry in issue 002 of the Probrand Group magazine: http://www.probrand.co.uk/imag/issue02/index.html
How artificial intelligence use to manufacturing companieskoteshwarreddy7
Artificial intelligence (AI) is transforming the manufacturing industry in pretty dramatic ways, from driving efficiencies, increasing defect detection rates, and reducing scrap waste to improving sales forecasts and even giving company leaders the information they need to renew business models.
The aims of the presentation are to:
- Present what leading analysts say on trends in 2015
- Outline what new skills will be required in 2015+
- Suggest some market niches for growth
with focus on IT market.
Over the last seven years, MENA and CEE have received total capital investment of more than $5 billion. We see the results with prominent exits in the regions; some of the big winners are UIPATH (CEE), Trendyol (Turkey), and Careem (MENA).
There is even more potential for significant returns to come. Check it out inside.
Similar to 2019 London Data Science Festival. Making Money in AI, Machine Learning and Data Science. (20)
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Ch03-Managing the Object-Oriented Information Systems Project a.pdf
2019 London Data Science Festival. Making Money in AI, Machine Learning and Data Science.
1. Who’s going to make
money in AI?
The secrets of successful AI and
data science in the real world
Simon Greenman
Partner, Best Practice AI
@simongreenman
www.bestpractice.ai
2. (c) 2019 Best Practice Artificial Intelligence Ltd
Simon Greenman, Partner Best Practice AI Ltd
2
• BA in Computing & Artificial Intelligence from the University of
Sussex
• Co-founder of the early AI-enabled mapping service
MapQuest.com
• Chief Digital Officer, GM, CEO with over twenty years of
leading digital transformations internationally through
technology, data science and AI
• Highly active in the early stage eco-system as Co-President
of the Harvard Business School Alumni Angels of London, an
advisor at DN Capital, and AI Expert in Residence at
Seedcamp
• Board advisor at Seldon, a ML deployment company
• Member World Economic Forum Center for 4th Industrial
Revolution - AI.
S I M O N G R E E N M A N
Partner, Best Practice AI Ltd
AI Management Consultancy
www.bestpractice.ai
Create Competitive Advantage with AI
2
3. (c) 2019 Best Practice Artificial Intelligence Ltd 3
https://www.forbes.com/sites/artimanmanage
ment/2014/10/28/drone-technology-
investment-bet-on-the-picks-and-
shovels/#7bb7b4cc5313
4. (c) 2019 Best Practice Artificial Intelligence Ltd 4
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
5. (c) 2019 Best Practice Artificial Intelligence Ltd 5
So. Are you ready for another AI gold rush?
https://www.forbes.com/sites/artimanmanage
ment/2014/10/28/drone-technology-
investment-bet-on-the-picks-and-
shovels/#7bb7b4cc5313
6. (c) 2019 Best Practice Artificial Intelligence Ltd 6
AI is a story of many boom and busts
Within a generation…I am
convinced…the problems of
creating artificial intelligence
will be substantially solved.
“
M a r v i n M i n s k y
M I T
Within our lifetime machines
may surpass humans in
general intelligence
“
1961 1967
7. (c) 2019 Best Practice Artificial Intelligence Ltd 7
But is it different now? The power of exponential!
ESTIMATE OF AMOUNT OF DATA BYTES
THAT WILL BE CREATED EVERY SECOND
BY EVERY PERSON ON THE PLANET IN 2020
1 , 7 0 0 , 0 0 0
B Y T E S / S E C
1. Data
THE SPEED OF A CAR TODAY IF ITS
SPEED HAD IMPROVED AT THE SAME
RATE AS COMPUTATIONAL CHIPS
SINCE 1971
4 2 0 , 0 0 0 , 0 0 0
M P H
2. Comp Power
THE COST OF MANY OF THE AI
FRAMEWORKS, LIBRARY AND
TOOLS
$ 0
3. Software
THE COST OF MANY OF THE AI
FRAMEWORKS, LIBRARY AND
TOOLS
$ 0
8. (c) 2019 Best Practice Artificial Intelligence Ltd
Your are the champions of change
Bringing AI and data science to the enterprise
and society
8
10. (c) 2019 Best Practice Artificial Intelligence Ltd 10
Enterprise
Solutions
4
Chips &
hardware
1
Platform &
infrastructure
2
Vertical
Industry
Solutions
5
Corporates6
Healthcare & Life
Sciences
Finance &
Insurance
Agriculture Automotive Legal &
Compliance
Industrials, Robotics
& Logistics
Frameworks &
algorithms
3
Nations7
* Excludes SMB sectors. The companies noted are
representative of larger players in each category but in no
way is this list intended to be comprehensive or predictive.
** Acquired by Cisco and Google respectively.
Conversational
agents**
VisionCore
Algorithms
NLP &
Semantics
Speech
There is a huge race going on in AI from the chip makers to enterprise
software providers to corporates to countries with $billions being invested
AutomotiveFinance &
Insurance
Healthcare Agriculture Legal &
Compliance
Industrials, Retail, media,
other
Tech & Telco
Customer
Management
Intelligence &
Analytics
CybersecurityMarketing &
Sales
HR & Talent RPA,
Other
ConsultantsTools
Sources: CBInsights,
Crunch Base, and
misc. others
AI is going to be ubiquitous and woven into the fabric of society and organisations globally
11. (c) 2019 Best Practice Artificial Intelligence Ltd 11
Chips &
hardware
1
Platform &
infrastructure
2
* Excludes SMB sectors. The companies noted are
representative of larger players in each category but in no
way is this list intended to be comprehensive or predictive.
** Acquired by Cisco and Google respectively.
Frameworks &
algorithms
3
Conversational
agents**
VisionCore
Algorithms
NLP &
Semantics
Speech
The picks and shovels of this gold rush will be the tech giants
Sources: CBInsights,
Crunch Base, and
misc. others
“This Tech Company May Be Near a
‘Tipping Point’ in Dominating Artificial
Intelligence.” Barron’s on Nvidia Sep 30th
2018
1 2
“There are 1.2 million
developers using our cognitive
services while 300,000 use
conversational AI.”
Microsoft’s GM of AI, David
Carmona
3
The providers of chips, platform and the frameworks / algorithms will power everyone who is
looking to find gold with AI services regardless of who finds it
12. (c) 2019 Best Practice Artificial Intelligence Ltd 12
* Excludes SMB sectors. The companies noted are
representative of larger players in each category but in no
way is this list intended to be comprehensive or predictive.
** Acquired by Cisco and Google respectively.
The AI enterprise & vertical solution provider race is intense
Sources: CBInsights,
Crunch Base, and
misc. others
Enterprise
Solutions
4
Vertical
Industry
solutions
5
Healthcare & Life
Sciences
Finance &
Insurance
Agriculture Automotive Legal &
Compliance
Industrials, Robotics
& Logistics
$156M
$25M
$93M
$137M
$448M
$104M
$230M
$108M
<
$202M
$1000M
$217M
$95M
$77M
$182M
“Salesforce Strengthens Its
AI Capabilities With an $800
Million Purchase [of
Datorama],” July 16th 2018
“SAP Acquires Recast.AI
to Accelerate Natural
Language Processing
Capabilities,” 22nd Jan
2018.
$557M
Customer
Management
Intelligence &
Analytics
CybersecurityMarketing &
Sales
HR & Talent RPA,
Other
ConsultantsTools
$147M
The winners will be the incumbents and those start-ups who gain category leadership with scale
of customers, data, capital and talent
13. (c) 2019 Best Practice Artificial Intelligence Ltd 13
* https://towardsdatascience.com/the-secrets-of-successful-
ai-startups-whos-making-money-in-ai-part-ii-207fea92a8d5
But watch out for fool’s gold
• MMC Ventures noted 40% of 2,830 so
called AI startups in Europe are not really
using AI
“Tech companies benefit from the
perception that they’ve built sophisticated
automation and A.I., rather than a system
that relies on manual labor.
Nearly every startup today claims to be an AI powered company
15. (c) 2019 Best Practice Artificial Intelligence Ltd 15
https://www.forbes.com/sites/alexknapp/2018/04/25/gart
ner-estimates-ai-business-value-to-reach-nearly-4-
Gartner Research predicts AI-derived business value will reach up to $3.9
trillion by 2022
16. (c) 2019 Best Practice Artificial Intelligence Ltd 16
Source: Capgemini Digital Transformation Institute, State of AI survey, N=993 companies that are implementing AI, June 2017
https://www.capgemini.com/gb-en/wp-content/uploads/sites/3/2017/09/dti-ai-report_final1-1.pdf
Revenue
75% of
organisations
implementing AI
increase sales of
products and
services by more
than 10%
Deeper
Insights
79% of
organisations
implementing AI
generate new
insights and
better analysis
There are four main business benefits of AI
Customer
Engagement
75% of
organisations
using AI enhance
customer
satisfaction by
more than 10%
Automation
& Operational
Efficiency
78% of
organisations
implementing AI
increase
operational
efficiency by more
than 10%
17. (c) 2019 Best Practice Artificial Intelligence Ltd 17
To help leaders better understand the value of AI, Best Practice AI
created the world’s largest AI use case and case study library
Free at www.bestpractice.ai
6 0 0 +
Use Cases
1 0 0 0 +
Case Studies
6 0 +
Territories
3 0 0 0 +
Vendors
U s e
c a s e
KPIs
Technology
Data
Vendors
C a s e
s t u d y
Geography
Players
Impact
Data
Vendors
M e m b e r o f
W o r l d E c o n o m i c F o r u m A I p r o g r a m &
U K A l l P a r l i a m e n t a r y G r o u p o n A I
18. (c) 2019 Best Practice Artificial Intelligence Ltd 18
In node graph format - functions and use cases
19. (c) 2019 Best Practice Artificial Intelligence Ltd 19
Most case studies contain details on the reported project details,
ROI, data and technology
20. (c) 2019 Best Practice Artificial Intelligence Ltd
We created a heat map of where AI technology can be used to
create value today
Predict future customer demand - Help screen CVs - Optimise supply
chain purchasing - Reduce cyber risks - Improve customer service -
Automate data entry with RPA - Better market and engage prospective
customers - Improve product offerings - Predict customer churn -
Score top customer prospects
20
21. (c) 2019 Best Practice Artificial Intelligence Ltd
There is also an AI arms race
across nations
21https://www.gartner.com/technology/pressRoom.do?id=3872933
22. (c) 2019 Best Practice Artificial Intelligence Ltd 22
Countries are vying for AI supremacy
https://www.prnewswire.com/news-releases/london-tech-week---london-is-named-artificial-intelligence-ai-capital-of-europe-by-new-report-
685101231.html
https://medium.com/creation-being-human/who-will-win-the-ai-arms-race-187ac2ae8927
• France announces a $1.85B AI investment over the next five and that foreign take over
of AI companies will require government approval
• UK announces a $1.3B corporate and government AI investment
• Europe announces a $22B AI investment
• And then the Chinese city of Tianjin announces it is setting up a $16B AI fund
• China has developed the ‘Big Fund’ estimated total investment at ~$140B to grow their
semiconductor industry.
China has an explicit goal developed at the highest level of government to make itself
the global leader in AI by the year 2030 with more favourable structural environment
including looser data and privacy regulation
23. (c) 2019 Best Practice Artificial Intelligence Ltd 23
“China is the Saudi Arabia in data” Kai Fu-Lee
https://www.slideshare.net/AIFrontiers/kaifu-lee-at-ai-frontiers-the-era-of-artificial-intelligence?from_action=save
Watch China closely in the battle for AI supremacy
24. (c) 2019 Best Practice Artificial Intelligence Ltd 24
To learn more search for this article
25. (c) 2019 Best Practice Artificial Intelligence Ltd 25
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
26. (c) 2019 Best Practice Artificial Intelligence Ltd
Achieving real business outcomes
from AI and data science
26https://www.gartner.com/technology/pressRoom.do?id=3872933
27. (c) 2019 Best Practice Artificial Intelligence Ltd 27
Getting to POC is the tip of the AI transformation iceberg
Above the waterline proving AI works requires:
• AI talent
• Data wrangling and training set labelling
• Frameworks and algorithms
• Compute access
• Project support management including subject
matter expertise.
28. (c) 2019 Best Practice Artificial Intelligence Ltd 2 8
Below the waterline much more needs to be done to capture value
Biggest challenge faced by organisations operationalising AI:
1.Lack of results and efficacy - ROI
2.Lack of technology maturity especially chatbots
3.Change management – getting humans workers
comfortable and educated on AI solutions
4.Business process redesign - how is AI integrated with
humans in business processes
5.Technology integration and scale-up – difficult to
integrate cognitive projects with existing processes and
systems
6.Technology deployment - difficult to deploy and update
the technology in production.
h t t p s : / / b i t . l y / 2 F F G F y T
If the business is not bought in then technology will
struggle to deliver
29. (c) 2018 Best Practice Artificial Intelligence Ltd
People challenges are reported as the greatest barrier to becoming data-
driven organisation
2018 New Vantage Partners survey of executives including Bank of America, Goldman Sachs, Capital
One, Morgan Stanley, UBS, Travelers
2 9
h t t p : / / n e w v a n t a g e . c o m / w p - c o n t e n t / u p l o a d s / 2 0 1 8 / 0 2 / B i g - D a t a - E x e c u t i v e - S u r v e y - 2 0 1 8 - F i n d i n g s . p d f
“58% of executives cite insufficient organisational
alignment or cultural resistance as the biggest barrier
to business adoption of data driven organisation
AI and data science is a team sport
30. (c) 2019 Best Practice Artificial Intelligence Ltd 30
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Agree a Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
31. (c) 2019 Best Practice Artificial Intelligence Ltd 31
Find strong use cases that will resonate with executives
For example fraudulent activity using unusual payment transaction patterns and other
data
HSBC automated its anti-money
laundering (AML) investigations to
increase efficiency and
effectiveness in its regulatory
compliance. Historically AML was
carried out by humans but the bank
has turned to Ayasdi and its
machine learning software to
monitor transactions and automate
identification of potential criminal
activity.
https://www.bestpractice.ai/studies/hsbc_reduces_false_pos
itives_for_money_laundering_detection_by_20_using_ai_to
_automate_the_system_rules
Danish Danske Bank had a problem
with false positives in its payment
fraud detection that was
approaching 99.5%. Using
advanced machine learning they
were able to increases fraud
detection in real-time by 60% and
reduce false positives by 50%.
https://www.bestpractice.ai/studies/danish_danske_bank_increases
_payment_fraud_detection_by_60_and_reduces_false_positives_b
y_50_with_machine_learning
OCBC bank of Singapore analyses
transaction activity to identify unusual
payments that might be financial
crime. In a pilot OCBC was able to
reduce the number of false positives
by 35% by using machine learning.
They were also able to classify
transaction alerts into 48 unique risk
clusters allowing the compliance
team to better prioritise based on risk.
https://www.bestpractice.ai/studies/ocbc_bank_reduces_nu
mber_of_false_positive_financial_transaction_alerts_by_35_
with_machine_learning
32. (c) 2019 Best Practice Artificial Intelligence Ltd 32
Find out what your competition is doing
McKinsey found the largest motivator for a European company to adopt AI is competition
McKinsey Global Institute - Notes from the AI frontier
Tackling Europe’s gap
33. (c) 2019 Best Practice Artificial Intelligence Ltd 33
Ensure you quantify the potential business benefits
AI delivers different potential benefits by function. Manufacturing, Operations and Supply
Chain offer significant cost saving potential, Marketing and sales revenue.
34. (c) 2019 Best Practice Artificial Intelligence Ltd 34
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science project success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
35. (c) 2019 Best Practice Artificial Intelligence Ltd 35
The challenge of senior management understanding and buy-in
Source:McKinsey, June 2017;Deloitte, May 2018
“41 percent of the 3,000
executives surveyed in a
recent McKinsey Global
Institute study admitted
they’ve yet to adopt AI
because they’re unsure about
how it can help their
organisation.”
“Half of respondents do not
believe their organisation’s
leadership has a clear
understanding of AI”
Deloitte UK survey 2018
36. (c) 2019 Best Practice Artificial Intelligence Ltd
But what is AI?
36
You need to educate, excite but set expectations
with your executives
37. (c) 2019 Best Practice Artificial Intelligence Ltd 37
Deep neural networks are being used for unfathomably complex statistical pattern recognition
The big breakthrough in AI - deep learning (ML)
https://www.youtube.com/watch?v=3JQ3hYko51Y
#1 AI is Data Science on steroids
38. (c) 2019 Best Practice Artificial Intelligence Ltd 38
#2 AI is Sensing and Cognition
* Thomas Davenport, AI Advantage,
https://mitpress.mit.edu/books/ai-advantage**
Diagnose diseases from MRIs
Identify persons with facial recognition
Recognise spoken words
Analyse text of legal documents
Identify defects on production line
Improve customer services with bots
Seeing, Hearing, Reading, Understanding, Reasoning
39. (c) 2019 Best Practice Artificial Intelligence Ltd 39
#3 AI is Creativity
* Thomas Davenport, AI Advantage,
https://mitpress.mit.edu/books/ai-advantage**
https://www.theverge.com/2017/10/30/16569402/ai-generate-fake-faces-celebs-nvidia-gan
The era of automated content generation…and deep fakes
40. (c) 2019 Best Practice Artificial Intelligence Ltd 40
#4 AI is Robotics
* https://www.youtube.com/watch?v=g0TaYhjpOfo
41. (c) 2019 Best Practice Artificial Intelligence Ltd 41
#5 AI is Robotic Process Automation (RPA)*
https://youtu.be/FV8lM9SIFQ8
* maybe
RPA allows anyone today to configure computer software, or a “robot” to emulate and integrate the
actions of a human interacting within digital systems to execute a business process.
42. (c) 2019 Best Practice Artificial Intelligence Ltd 42
Management can set frothy expectations…
"I would actually welcome a correction in public
opinion about what AI can and cannot do. This
has happened to me multiple times, where I
would listen to a CEO on stage make an
announcement about what their company is
doing with AI, and then 20 minutes later I’d talk
to one of their engineers, and they’d say, “No,
we’re not doing that, and we have no idea how
to do it.”
Andrew Ng, ex-Google Brain, ex-Baidu
quoted in the WSJ
43. (c) 2019 Best Practice Artificial Intelligence LtdSource: https://arxiv.org/pdf/1811.11553.pdf
Set expectations - AI is far from “solved”
School Bus
100%
Garbage Truck
99%
Punching Bag
100%
Snow Plough
92%
What happens when AI fails?
There are many legal and ethical issues around AI failures, such as autonomous vehicle crashes
43
For example deep learning has no human like concept of objects
44. (c) 2019 Best Practice Artificial Intelligence Ltd 44
Skills remain a key challenge for projects
Survey of O’Reilly subscribers
45. (c) 2019 Best Practice Artificial Intelligence Ltd 45
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
46. (c) 2019 Best Practice Artificial Intelligence Ltd 4 6
Big trends we are seeing in ML - data science tech
1. Cloud-native - Serverless, containerisation
and microservices
2. Automation of data science tasks with
Gartner Research estimating that by 2020
more than 40% of data science tasks will be
automated
3. Rise of ML as a platform and service model
4. The introduction of AutoML - a system for
automatically searching and discovering model
configurations (algorithm, feature sets, hyper-
parameter values, etc.) and automatically build
the production data pipelines to generate the
features and labels
5. NLP and conversational analytics
6. Explainable AI
7. Increasing control and empowerment of
data science with the business.
h t t p s : / / a i - a u d i t i n g f r a m e w o r k . b l o g s p o t . c o m / 2 0 1 9 / 0 3 / a n - o v e r v i e w - o f - a u d i t i n g - f r a m e w o r k - f o r _ 2 6 . h t m l
Example of an ML platform to
help manage end-to-end
workflow (Algorithmia)
47. (c) 2019 Best Practice Artificial Intelligence Ltd 4 7
Start-up experience of enterprises can be challenging
Start-ups often underestimate corporate complexity
h t t p s : / / a i - a u d i t i n g f r a m e w o r k . b l o g s p o t . c o m / 2 0 1 9 / 0 3 / a n - o v e r v i e w - o f - a u d i t i n g - f r a m e w o r k - f o r _ 2 6 . h t m l
Speed is an issue
• Why cannot they move as fast as us?
• How long to get sign-off? Contract finalized? Payments made?
Decisions feel needlessly complicated
• Why cannot things be agreed on the spot?
• How many committees / stakeholders do we need to respond to?
• Did we not answer all those questions from compliance 3 months ago?
Corporate ability to implement a challenge
• How many systems do we need to interface with?
• Do we need to work through these internal resources (who are over-worked already)?
• How much communication do we need to do?
Resource imbalance
• There is only so long that the CEO / CTO / key data scientist can be focused in one place
• One-off implementation costs (e.g. legal fees) can be a real challenge
48. (c) 2019 Best Practice Artificial Intelligence Ltd 48
Procurement frameworks are being created to help
ensure effective and responsible AI supplier solutions
For example the WEF is working with UK Government on a new framework
Example: The Institute for Ethical AI & Machine Learning
49. (c) 2019 Best Practice Artificial Intelligence Ltd 49
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
50. (c) 2019 Best Practice Artificial Intelligence Ltd 5 0
Scaling and managing ML models in production is really hard
Data scientists are facing many roadblocks spending much of their time on infrastructure,
deployment and data engineering across the ML end-to-end workflow
h t t p s : / / b i t . l y / 2 F F G F y T
“38% report difficulty in deploying models to the
needed scale as result of resource challenges in
DevOps, lack of infrastructure, etc
“30% report challenges in supporting
different programming languages and
frameworks”
“30% report challenges in model management
tasks such as versioning and reproducibility”
51. (c) 2019 Best Practice Artificial Intelligence Ltd 51
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
52. (c) 2019 Best Practice Artificial Intelligence Ltd 52
Much of AI Ethics is not really about the AI
Data issues reflecting broader societal issues such as mirroring our language
Engineering
IncentivesStakeholders
Bluff / crooks
Ethics
Mirror
Uber crash
Tesla automation
IBM Watson healthcare
Boston bus
Job automation
Google Duplex calls
Admiral Insurance
Cadillac Fairview
facial recognition
FB newsfeeds
You Tube video
ranking
Amazon HR
Microsoft’s Tay
US judicial system
Cambridge Analytica
“20% of AI start-ups
have no AI”
Did the
technology
go wrong?
Yes
No User issues
Builder
issues
Were
Human
motives
wrong?
No
53. (c) 2019 Best Practice Artificial Intelligence Ltd 53
Multiple Ethical AI frameworks being created
Over 30 such examples by our recent count
Example: The Institute for Ethical AI & Machine Learning
54. (c) 2019 Best Practice Artificial Intelligence Ltd 5 4
And the regulators are stepping into the fray
The ICO just announced a draft AI audit framework for comment
Under GDPR today there are clauses that are
relevant to the use of AI. For example:
• Article 22(1) of the GDPR limits the
circumstances in which you can make solely
automated decisions, including those based
on profiling, that have a legal or similarly
significant effect on individuals. (e.g.
employment and loan decisions)
• Decisions need to be explainable and
individuals have the right to opt out.
The ICO has just released this AI audit
framework for comment. Designed to:
• Support the work of the ICO investigation
and assurance teams to assess data
controller compliance
• Help guide organisations on the
management of data protection risks arising
from AI applications
h t t p s : / / a i - a u d i t i n g f r a m e w o r k . b l o g s p o t . c o m / 2 0 1 9 / 0 3 / a n - o v e r v i e w - o f - a u d i t i n g - f r a m e w o r k - f o r _ 2 6 . h t m l
h t t p s : / / i c o . o r g . u k / f o r - o r g a n i s a t i o n s / g u i d e - t o - d a t a - p r o t e c t i o n / g u i d e - t o - t h e - g e n e r a l - d a t a - p r o t e c t i o n -
r e g u l a t i o n - g d p r / a u t o m a t e d - d e c i s i o n - m a k i n g - a n d - p r o f i l i n g / w h a t - d o e s - t h e - g d p r - s a y - a b o u t -
a u t o m a t e d - d e c i s i o n - m a k i n g - a n d - p r o f i l i n g /
55. (c) 2019 Best Practice Artificial Intelligence Ltd 55
Successful AI-driven projects needs more than just data science
AI & data science requires alignment of six factors to ensure it realises
its value across an operation
Have the
right plan
Mobilise
the right
people
Have the
data
Deploy
the right
tech
Make it
operat-
ional
Manage
the risks
Agree project
ownership +
governance /
oversight
Ensure domain
expertise and
cross-functional
buy-in in place
Ensure skilled
team in place –
whether
internal or
vendor
Plan how to get
the right data at
right stage of
preparation
(e.g. labeled
and complete)
Consider what
bias issues
potentially
faced
Ensure relevant
regulations
complied with
Plan approach,
testing and
refinement of
key
algorithm(s)
Ensure right IT
architectural
stack in place
Check impact of
tech choices on
broader tech
stack
Decide how
prediction will
lead to action
(degree of
automation)
Ensure
measurement
and feedback
loops in place
Map and
manage
barriers to
deployment
Ensure key
staff bought in
Identify
potential
regulatory /
legal issues (eg
GDPR)
Map
stakeholder set
and prepare
clear comms
plan
Ensure
alignment and
information to
empowered
’ethics’
governance
Be very clear
what you want
to achieve
Understand
what you need
to predict /
optimise – and
levels of
confidence
required
Agreed metrics
that measure
success
1 2 3 4 5 6
56. (c) 2019 Best Practice Artificial Intelligence Ltd 56
Agenda
• The AI Gold Rush - who’s making money in AI?
• Ensuring corporate AI and data science business success:
A. Plan
B. People
C. Data
D. Technology
E. Operationalisation
F. Risk Management
• The secrets of successful AI and data science start-ups.
The secrets of success with AI and data science
57. Can your startup cross the commercial divide from
technology to the enterprise?
58. (c) 2019 Best Practice Artificial Intelligence Ltd 58
Raising money - AI is a different beast for most UK investors
VCs are not that comfortable evaluating AI opportunities but are getting better
The past five years of VC investing has really been focused on B2C marketplaces, commence and mobile
AI investment opportunities are harder to evaluate. Why?
• They are often based on academics and their research which is a DNA anathema to VCs
• They are often“deep tech” and it is hard to find real experts to opine
• Go-to-Market (GTM) is enterprise and not consumer digital marketing funnel
• The market dynamics are evolving very quickly
• Massive talent war
• Scale is critical to AI startups and data scale is often with incumbent corporates
• Long product development cycles with hard to measure progress.
59. (c) 2019 Best Practice Artificial Intelligence Ltd 59
Make it easier for VCs to evaluate your AI startup
1.What is the business use case you are solving?
2.Is it a valuable use case?
3.Can your AI company be a global leader and not be squashed by tech giants?
4.Do you have unique domain knowledge?
5.Do you have access to unique, large and quality data sets?
6.Do you have access to AI talent?
7.Do you have a unique and proprietary technology? Why is it good?
But make sure your VCs have patience and are smart about deep tech investment profiles.
60. (c) 2019 Best Practice Artificial Intelligence Ltd 60
The foundations of most AI startups
(1)
Get Data
(2)
Get
Talent
(3)
Get
Domain
Expertise
61. (c) 2019 Best Practice Artificial Intelligence Ltd 61
Cross the AI commercial divide from technology to the enterprise
Six key factors for success:
1. Don’t move too fast and break things; embrace responsible AI
2. Solve really high value use cases, not nice to haves
3. Master B2B enterprise sales and learn calculated patience
4. Translate AI for the real world
5. Lower the barriers to a trial
6. Technical founders need to hire business people.
62. (c) 2019 Best Practice Artificial Intelligence Ltd 62
To learn more search for this article
63. (c) 2019 Best Practice Artificial Intelligence Ltd
AI Management Consultants
Helping you create competitive
advantage with AI
Simon @ bestpractice. Ai
+44 7824 557979
63
www.bestpractice.ai
@simongreenman
Editor's Notes
1960s mathematical symbolic AI hype followed by 1970s bust
1980s expert systems hype followed by 1990s and 2000s bust
2010s AI is back!
AI - no one is quite sure what is AI. How real is it?
They are painting their own picture on blank canvas
From the media we have a dystopian view - 30-40% job loss, existential threat, biased AI hiring,
Others a more utopian view that AI will free us from all the mundane and boring in the job; and we will no longer need to drive as autonomous vehicles will free our time and clear the city streets
CEOs say their companies will transform from AI, then you talk to the practioncers and they say “no idea”
So what is AI. AI has been around for a long time.
So where is the value being created with AI?
As I started thinking about who was going to make money in AI I ended up with seven questions. Who will make money across the (1) chip makers, (2) platform and infrastructure providers, (3) enabling models and algorithm providers, (4) enterprise solution providers, (5) industry vertical solution providers, (6) corporate users of AI and (7) nations? While there are many ways to skin the cat of the AI landscape, hopefully below provides a useful explanatory framework — a value chain of sorts. The companies noted are representative of larger players in each category but in no way is this list intended to be comprehensive or predictive.
So where is the value being created with AI?
As I started thinking about who was going to make money in AI I ended up with seven questions. Who will make money across the (1) chip makers, (2) platform and infrastructure providers, (3) enabling models and algorithm providers, (4) enterprise solution providers, (5) industry vertical solution providers, (6) corporate users of AI and (7) nations? While there are many ways to skin the cat of the AI landscape, hopefully below provides a useful explanatory framework — a value chain of sorts. The companies noted are representative of larger players in each category but in no way is this list intended to be comprehensive or predictive.
“ThDigitalGenius raised $25M including from Salesforce
Ziprecruiters raises $156M to build AI and ML tools for recruitment
HireVue raised $93M to accelerate video interviewing of candidatesUiPath, a RPA, has raised $400M to automate many data entry tasks
DigitalReasoning has raised $104M to provide corporate intelligence
DarkTrace has raised $230M to help guard against cyber threats
Tools company Petuum has raised $100M to accelerate enterprise AI
And consultancies proliferate
ZestFinance has raised nearly $217M to help improve credit decision making that will provide fair and transparent credit to everyone
Affirm, offers loans to consumers at the point of sale, and has raised $720M
Babylon health has raised over $57M
Drive.ai has raised over $77M
Benson-Hill has raised over $95M
Anki has raised over $182M
And the cheque books go on and on…
“Announcing new AI and mixed reality business applications for Microsoft Dynamics [Sales and Customer Service]”, Microsoft Sep 18th, 2018
“Salesforce Strengthens Its AI Capabilities With an $800 Million Purchase [of Datorama],” July 16th 2018
“SAP Acquires Recast.AI to Accelerate Natural Language Processing Capabilities,” 22nd Jan 2018.
“Google announces a suite of updates to its contact center tools,” July 2018.
“Google acquires AI customer service startup Onward,” October 2nd 2018.
“ThDigitalGenius raised $25M including from Salesforce
Ziprecruiters raises $156M to build AI and ML tools for recruitment
HireVue raised $93M to accelerate video interviewing of candidatesUiPath, a RPA, has raised $400M to automate many data entry tasks
DigitalReasoning has raised $104M to provide corporate intelligence
DarkTrace has raised $230M to help guard against cyber threats
Tools company Petuum has raised $100M to accelerate enterprise AI
And consultancies proliferate
ZestFinance has raised nearly $217M to help improve credit decision making that will provide fair and transparent credit to everyone
Affirm, offers loans to consumers at the point of sale, and has raised $720M
Babylon health has raised over $57M
Drive.ai has raised over $77M
Benson-Hill has raised over $95M
Anki has raised over $182M
And the cheque books go on and on…
“Announcing new AI and mixed reality business applications for Microsoft Dynamics [Sales and Customer Service]”, Microsoft Sep 18th, 2018
“Salesforce Strengthens Its AI Capabilities With an $800 Million Purchase [of Datorama],” July 16th 2018
“SAP Acquires Recast.AI to Accelerate Natural Language Processing Capabilities,” 22nd Jan 2018.
“Google announces a suite of updates to its contact center tools,” July 2018.
“Google acquires AI customer service startup Onward,” October 2nd 2018.
AI - no one is quite sure what is AI. How real is it?
They are painting their own picture on blank canvas
From the media we have a dystopian view - 30-40% job loss, existential threat, biased AI hiring,
Others a more utopian view that AI will free us from all the mundane and boring in the job; and we will no longer need to drive as autonomous vehicles will free our time and clear the city streets
CEOs say their companies will transform from AI, then you talk to the practioncers and they say “no idea”
So what is AI. AI has been around for a long time.
But the big breakthrough over the past five years has been deep learning where machines teach themselves based on training set
Deep neural networks are being used for unfathomably complex statistical pattern recognition
This is a beautiful illustration of that - you SHOW as INPUT an object as a digit 0 - 9
And then inside the machine there are layers upon layers of neurons / nodes that are interconnected (like the brain)
As it sees the digit activates different neurons and connections that fire together resulting in the OUTPUT a recognition of a digit
Now imagine this in thousands, 10Ks, 100Ks, 1M, 1B interconnections and something magic happens
So really what AI has become is DATA SCIENCE on steroids - statistics and pattern recognition on steroids
And it being used to PREDICT customer churn, OPTIMISE ad portoflio, IDENTIFY ad types, ANALYSE ROI, EVALUATE presence
AI is also Sensing and Cognition
These are CAPABILITIES often associated with humans and animals - seeing, hearing, reading, understanding and reasoning
Look at this autonomous vehicle - as drive down streets it needs to “see” the objects around it - trees, sidewalk, center of the road, other cars, pedestrations, stop signs
It has to talk all of this information and decide what to do - speed up, break, stop, turn left, avoid hitting a dog…
No wonder Tim Cook, Apple CEO, calls this the “mother of AI problems”
Don’t believe the hype that are cars are going anywhere soon
Another set of AI technologies give rise to creativity
How about automatic generation of ad copy, banner ads, content marketing, etc
But this is also giving rise to deep fakes
This is a GAN trying to create life-like faces - it is actually in a massive battle over time between two deep nerual networks. One that generates a face and one that tries to determine if it is fake or not. Do this millions of times and you come up with some pretty realistic faces.
Lots of big societal issues to come here.
And another set of AI technologies is robotics…
I’ll let the video speak for itself…
And another set of AI technologies is robotics…
I’ll let the video speak for itself…
However don’t let anyone tell you that all the problems have been solved - we are so far from it
There is a school of thought that we need to start again on deep neural networks -