WHY IT MATTERS: Digital Transformation

Facial recognition is the new hot tech topic in China. Banks, airports, hotels and even public toilets are all trying to verify people’s identities by analyzing their faces. But the police and security state have been the most enthusiastic about embracing this new technology.

I reached out for help a little while ago on Twitter and on LinkedIn to assess the size and state of the global AI talent pool—a crucial issue for the entire industry going forward. Thank you to those of you from around the world who responded in large numbers. Your generous input has gone into a new report that we at Element AI have developed. We now have a more detailed picture of the size and characteristics of the pool of AI experts going into 2018. I see this report as a living document that will continue growing with others’ contributions. Our broadest measure of the global talent pool is 22,000 individuals: it remains clear that the fight for talent will continue into the foreseeable future. Below are some of my observations on what I see happening around the world. 

In May, J.P. Morgan’s quantitative investing and derivatives strategy team, issued the most comprehensive report ever on big data and machine learning in financial services.
Titled, ‘Big Data and AI Strategies’ and subheaded, ‘Machine Learning and Alternative Data Approach to Investing’, the report says that machine learning will become crucial to the future functioning of markets. Analysts, portfolio managers, traders and chief investment officers all need to become familiar with machine learning techniques. If they don’t they’ll be left behind: traditional data sources like quarterly earnings and GDP figures will become increasingly irrelevant as managers using newer datasets and methods will be able to predict them in advance and to trade ahead of their release.

Keynote at Andreessen Horowitz's annual 'Tech Summit' conference, talking about the state of tech today and what's likely to happen in the next decade: mobile, Google / Apple / Facebook / Amazon, innovation, machine learning, autonomous cars, mixed reality and crypto-currencies.

The A.I. revolution is coming—and research firm CB Insights has identified the 100 most promising artificial intelligence startups.

Deep learning has revolutionized the world of artificial intelligence. But how much does it improve performance?  How have computers gotten better at different tasks over time, since the rise of deep learning?

This paper examines the essential eight technologies that matter and what business leaders now need to do about them, and emerging technologies in general.

Something that often bothers me about sci-fi is the loner inventor trope. A guy in a garage builds a robot, or AI, or frequently both that are somehow decades beyond the technology of his day. It’s hard to even appreciate how hard this is for robots to do, because it’s hard to appreciate how difficult walking still is for humanoids. I wrote a whole piece about the problem of building walking robots back in 2011 — it wasn’t pretty back then, and it’s still a challenge for most full-sized humanoids.

It may come as no surprise that technology-centric roles stole the show among emerging jobs in the United States, but the prevalence of machine learning and data science roles and skills indicate a shift in the types of technology we can expect to be using in the near future, as well as what professionals should be preparing themselves for.

Having an academic background and a comprehensive suite of skills were also strong trends, especially among professionals who are now machine learning engineers and data scientists. Both of these roles are also often held by professionals with 10 years or more of professional experience, so for those just starting out and having trouble landing one of these titles, don’t be discouraged!

It’s always a good reminder that soft skills will always be important, no matter the profession. The ability to collaborate, be a leader, and learn from colleagues will stand out in interviews, and even more once starting a job.

In response to growing concerns about autonomous weapons, a coalition of AI researchers and advocacy organizations released a fictitious video on Monday that depicts a disturbing future in which lethal autonomous weapons have become cheap and ubiquitous. The video was launched in Geneva, where AI researcher Stuart Russell presented it at an event at the United Nations Convention on Conventional Weapons hosted by the Campaign to Stop Killer Robots. Russell, in an appearance at the end of the video, warns that the technology described in the film already exists and that the window to act is closing fast.

In an evermore connected world, large-scale cyberattacks and online threats to businesses are rising exponentially. The Cyber-Risk & Resilience special report, published in The Sunday Times, features insights into the impact cybercriminals can inflict on organisations and individuals. From chatbots spreading fake news, risks concerning personal data, biometrics and fraud, as well as tackling phishing emails, the potential dangers are unprecedented. Also included is an infographic on why hackers hack and an article on the top five ways quantum computing will change cybersecurity for good.

Dimitris Papageorgiou, Partner, People Advisory Services, Ernst & Young LLP
John Van Reenen, Professor, MIT Department of Economics and MIT Sloan School of Management
Krystyn Van Vliet, Professor of Material Science and Engineering and Biological Engineering, MIT Department of Materials Science and Engineering

The AI Index is an open, not-for-profit project to track activity and progress in AI. It aspires to be a comprehensive resource of data and analysis for policymakers, researchers, executives, journalists and others to rapidly develop intuitions about the complex field of AI.
AI is the new electricity, and is transforming multiple industries. The AI Index will help current generations track and navigate this societal transformations. It will also help future generations look back and understand the AI's rise.

Exclusive research by us at LDV Capital is the first publicly shared, in-depth analysis which estimates how many cameras will be in the world in 2022. Key Findings include:

• Most of the pictures captured will never be seen by a human eye.
• A paradigm shift will take place in the meaning and use of a camera.
• Over the next five years there will be a proliferation of cameras integrated into products across industries and markets.
• Where there is growth in cameras there will be tremendous business opportunities in the capture, analysis and interpretation of visual data.
• Depth capture will double the number of cameras in handheld cameras.
• By 2022, the number of cameras will be nearly 12X the 2012 figures.
• Your smartphone will have between 4 and 10 cameras by 2022.
• The Internet of Eyes will be larger than the Internet of Things.
• In the next five years, robotics will have 20X more integrated cameras.
• By 2022, all new vehicles will be equipped with more than 25 cameras and this does not include Lidar or Radar.

While it’s still incomplete, I thought it was important to update the map currently being sent around and reinforce the idea that this ecosystem is in constant flux. Already, our list has mushroomed from about 160 startups to over 550. Goes to show how much is happening just below our attention.

The robots are indeed already here. I work at a university where my job is teaching students and doing research and robotics and so I really what I want to convey to you today is the trends that I see robotics research going that will ultimately turn into actual products and directions that you might be able to take advantage of in the future.

A survey of AI researchers tallied predictions for when machines will start beating humans at everything from LEGO assembly to essay-writing.

The robots are coming. We (as in the people who attend TED talks and things) tend to think we will probably be fine. You know, knowledge folks and all. We might not be. What will be our coping mechanisms? What can we do to be OK?

We explore CEOs’ current perceptions of how robotics in the workplace is shaping their businesses today and in the near future. We also offer our perspectives on how robotics and automation have the potential to be truly transformative in the way they create value within organisations.

For the CIA, hedge funds and the largest retail enterprises, the confounding problem is the same: too much data. The world and its actors have never seemed more complex, and with no way to absorb a meaningful part of the information out there, events appear harder than ever to understand.

A business opportunity: We are seeing a slew of startups promoting artificial intelligence as a solution. The latest is Primer, which, backed by $14.7 million in venture funding, says it sorts millions of news sources and any other data thrown at it, and then crystallizes what's important in concise, natural language.

The Hype Cycle for Emerging Technologies provides insights gained from evaluating more than 2,000 technologies. The eight added in 2017 include 5G, Artificial General Intelligence, Deep Learning, Deep Reinforcement Learning, Digital Twin, Edge Computing, Serverless PaaS and Cognitive Computing.

Forrester says that CIOs must act as VCs and recommends they support early-stage tech companies and have their own technology scouts. As CIO Angela Yochem told me in 2015, she has set up a process to find “capabilities that are not yet commercially available” and “quickly absorb, test, and utilize emerging technologies, and discard them if they are not appropriate and don’t give us a leg up on our competition.”