Artificial intelligence (AI) and machine learning (ML) are going great guns in corporate America, helping with everything from smarter security to intelligent software test automation to analytics in AI operations (AIOps). If you haven't done much with these technologies yet, you will soon.
To help you get started on the learning curve, or to further increase your knowledge base, we've selected 30 people working in the AI/ML field who are talking about the topic on Twitter.
(Note: We've broken these experts down by category. There are academic researchers, practitioners, authors, tech leaders, software quality gurus, and, yes, two ethicists.)
Technology leaders
Greg Brockman
CEO, OpenAI
OpenAI has trained a neural network called DALL-E to convert text into images. The former CEO of Internet payment company Stripe, Brockman tweets about optimizing Kubernetes clusters and other technologies at scale to power AI and ML.
Jana Eggers
CEO, Nara Logics
Eggers has a long history in technology, including experience at Lycos, Intuit, and Los Alamos National Labs. On Twitter she is a self-proclaimed "applied AI nerd." Her tweets combine humor and sometimes harsh reality on the challenges presented by the competing AI technology stacks.
Demis Hassabis
CEO, Deepmind.com
Included among Time magazine's 100 most influential in 2017, Hassabis often retweets about the work coming out of Deepmind. His tweets tend to focus on applying AI to complex science problems. That might be anything from how data centers can conserve energy to finding keys to diagnose eye diseases early. With more than 200,000 followers on Twitter, he can connect you in many directions to AI.
Tessa Lau
CEO, Dusty Robotics
Computers are remarkably bad at generalized tasks such as avoiding gum on the path or recognizing that an interloper is a cat. That means that advanced robots need either AI or Isaac Asimov's positronic brain. Of course, Asimov's device was, well, science fiction.
Lau's company uses robots to lay out complex construction designs. On her Twitter feed, Lau advocates for agile methodologies to build sustainable robotics. The same feed highlights applied AI in robots to solve some of those problems of generalized intelligence.
Allie K. Miller
Global head of ML business development, startups, and venture capital, AWS
Miller reports on Twitter that she produced over 500 publications in 2020 on various topics that include AI and ML. Her thread discusses what others might consider unthinkable—low-code and no-code approaches to ML.
Ganesh Padmanabhan
Vice president, strategic partnerships, BeyondMinds
Padmanabhan speaks about scaling AI. That’s an area of some concern since, without planning, incrementally improving insights seem to require exponential amounts of power and CPU. He received his MBA from the University of Texas at the Red McCombs School for Business. He tweets about entrepreneurship and discoveries in the field of AI from Austin, Texas.
Marek Rosa
CEO, GoogleAI.com
Rosa leads the team that created Badger Architecture, an open-source framework that allows for something a bit like crowdsourced AI. With Badger, different expert systems can learn from, and communicate with, one another to understand what is happening in a complex, unstructured system, then define it as a structured system. Rosa is also the creator of a game called Space Engineers. His Twitter feed connects the community to a variety of startup companies that are leading innovation in the AI space.
Nige Willson
Founder, AwakenAI.org
Willson spent 20 years as a leader at Microsoft and co-founded We and AI, a nonprofit that helps educate people in the UK about AI. Recently he tweeted about using AI for DevOps. Another thread explored the question, "Artificial intelligence can bring Skynet from 'Terminator' to life: Reality or myth?"
Reza Zadeh
CEO, Matroid
Through Twitter, Zadeh keeps the community updated on the impact of changes being made to AI platforms—for example, deprecation of Swift support in TensorFlow, an open-source ML platform. He has served on technical advisory boards for Microsoft and Databricks.
Practitioners
Soumith Chintala
Research engineer, Facebook
At Facebook, Chintala helped to build the ML platform called PyTorch. An advocate in the open-source ML community, he has contributed to several publications on the topic of generative adversarial networks (GANs). Read his Twitter feed for information about advances in natural-language data processors and robotics.
Lex Fridman
Researcher, MIT
This AI researcher has a popular podcast where he speaks with all of the heavy hitters in AI and ML. His Twitter feed provides links to these podcasts as well as diverse content. Fridman is working on autonomous vehicles, human-robot interaction, and ML at MIT.
Chip Huyen
Professor, Stanford University, and ML lead, Snorkel
Straddling academic and professional practice, Huyen has a master's degree in computer science from Stanford, where she teaches ML system designs. That is informed by her experience at Snorkel, where she currently has a day job. That makes her comments more practical, helping bridge the gap to what programmers are working on today, such as applying ML to the software delivery pipeline.
Yan LeCun
Chief AI scientist, Facebook
In addition to his role at Facebook, LeCun is also a professor at New York University. The majority of his recent Twitter activity consists of retweets, but he is an influencer in the AI space around the globe.
Thang Luong
Scientist, Google Brain
Thang received his doctorate from Stanford University. He has many retweets connected to the AI community, and his personal tweets center on natural-language processing and deep learning.
Thomas Wolf
Lead scientist, Hugging Face
Hugging Face is where teams build and train models through open-source natural language processing (NLP) tools. On Wolf's Twitter feed, you will find tweets and retweets from many key people who work with AI and NLP models. His perspective is unique in that it stems from his physics background.
Academia
Pedro Domingos
Professor, the University of Washington
The author of the book The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Domingos tweets about the skepticism surrounding science and AI. He posits a correlation to how people think about global warming or climate change. Domingos has won awards and co-written over 200 publications on ML and data mining.
Angelica Lim
Assistant professor in the professional practice of computer science, Simon Fraser University
Lim launched a robotics lab at Simon Fraser University and recently received the inaugural School of Computing Science's Excellence in Teaching award. Her tweets are focused on educating others in the fields of robotics, machine learning, and AI. Besides Twitter, you can read her work in several issues of IEEE Spectrum Automation.
Andrew Ng
Adjunct professor, Stanford University
With over 500,000 Twitter followers, Ng challenges the community to identify the complex problems that could be solved by AI. Ng is co-founder and co-chairman of Coursera. He also founded the Google Brain project, which is developing massive-scale deep learning algorithms.
Sebastian Raschka
Assistant professor of statistics, the University of Wisconsin-Madison
The author of Python Machine Learning, Raschka has a Twitter feed that's full of connections to deep learning models and tooling. He records episodes of Deep Learning News on YouTube.
Ethics
Timnet Gebru
Co-founder, Black AI
In graduate school, Gebru used Google image data to infer political positions from populations based on simple items—for example, the breakdown of types of vehicles people owned. After completing her PhD at the Stanford AI Lab, Gebru worked at Microsoft in its Fairness, Accountability, Transparency and Ethics in AI (FATE) lab and later at Google, where she researched items such as bias in facial-recognition software.
Most recently, Gebru left Google; she claims she was fired for a critical email. Google counters that she made demands to stay employed that it chose not to meet. Because all this happened in December 2020, her Twitter feed is currently consumed by it.
Fei-Fei Li
Professor of computer science, Stanford University
Li defies categories, since she is both an academic and an ethicist. She tweets about bringing safe and responsible AI to the world. Her current focus is on computer vision research. Li is in the center of the AI world, and through her Twitter feed you can find connections to leaders in both academia and industry.
Authors
Jason Brownlee
Founding researcher, Machine Learning Mastery
Brownlee is the person behind Machine Learning Mastery, a website focused on bringing "regular" programmers into the ML field. His Twitter feed often has posts about pragmatic applications of ML. His latest book, Data Preparation for Machine Learning, allows programmers to gather data in such a way that it will be easy to parse ML systems.
Kate Crawford
Senior principal researcher, Microsoft Research
Crawford's first book, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, is due to launch in April 2021. She is the inaugural visiting chair for AI and justice at the École Normale Supérieure in Paris, and the Miegunyah distinguished visiting fellow at the University of Melbourne. Her tweets capture global points of view about AI.
Adam Geitgey
Software engineer and consultant
While a leader at Groupon, Geitgey implemented software and managed engineering teams. His Twitter focus is foundational to making ML available to everyone. Geitgey educates the community on topics such as Python and ML at lynda.com, and wrote the book Machine Learning Is Fun. He cares about the community and is passionate about getting people affordable healthcare.
Tabitha Goldstaub
Chair, the UK Government's AI Council
Goldstaub champions women in the field of AI and co-founded FutureGirlCorp to do just that. She also wrote the book How to Talk to Robots: A Girl's Guide to a Future Dominated by AI. Her tweets focus on the democratization of data and making access to data affordable.
Rana el Kaliouby
Co-founder and CEO, Affectiva
In her book Girl Decoded, El Kaliouby advocates for the advancement of women in technology. Her tweets are focused on leveraging the power of AI to transform the healthcare industry. She is a board member of the nonprofit called All Raise, which amplifies female voices. Her tweets cover topics that help humanity and support women in technology.
Gary Marcus
CEO, Robust.ai
Marcus' latest book is Rebooting AI: Building Artificial Intelligence We Can Trust, co-written with Earnest Davis. It's one of several that focus on how humans learn, and how that can be applied and reproduced. Much of the content on his Twitter feed consists of retweets. However, they are almost always related to ML and AI, which means he works as a sort of aggregator of good AI content.
Software quality
Jason Arbon
CTO, test.ai
Plenty of software test companies claim they have AI. Sadly, it is often a weaker definition of AI, where the computer automates some well-defined process. The Test.ai platform works differently, with staff actually training the software in workflows, such as "add to cart," which continue to work even if the cart button changes location or looks a little different. Arbon tweets about a domain called Test Ops, which works seamlessly with DevOps. He recently presented a keynote speech at EuroStar, where he talked about AI testing in the wild.
Jason Huggins
Creator, Tapster
The entrepreneur who founded Sauce Labs, Huggins may be best known as the original contributor and creator of the Selenium project. Successful enough to work on what he wants to work on, his current passion project is building robots at Tapsterbot. The company uses mechanical hands and AI to physically put real software devices through their paces, including test automation on mobile devices. He tweets about robotics, AI, ML, and continuous improvement of software.
Kevin Surace
CTO, Appvance.ai
Surace's tweets explore DevOps, BizOps, and other areas where AI is being applied to the software delivery process. The company he leads is focused on the benefits of AI and ML as applied to software testing. Their product, Appvance IQ, is presented as an autonomous continuous testing system.
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