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.)
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.
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.
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.
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.
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.
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.
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?”
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Assistant professor of statistics, the University of Wisconsin-Madison
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.
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.
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.
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.
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.
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.
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.
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.
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.
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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Elon Musk Says He’ll Pay $11 Billion in Taxes in 2021 But Twitter Wants ‘Proof’
Elon Musk took to Twitter to clarify once and for all that he will be paying a whopping $11 billion as taxes this year.
If the number of times Elon Musk could count when someone has asked him to pay the full taxes, he would be a very rich..wait, never mind. The Tesla boss is rich beyond any private individual has been in history, reports said.
Musk has increasingly been facing criticism from many politicians and many others who insist he has not been paying taxes as compared to the profits his companies have been making. On Sunday, the SpaceX CEO took to Twitter to share that he will be paying a whopping $11 billion as taxes.
For those wondering, I will pay over $11 billion in taxes this year— Elon Musk (@elonmusk) December 20, 2021
But some of the questions did not stop. One person tweeted how they needed to see Musk’s tax returns while yet another asked how much percentage was that of his total income.
A few were, however scathing of the government who thought they will add that amount to their pockets rather than using it for some proper development.
Wow that’s enough to give each person in the world almost $2 million but instead the government will just stick it in their pockets— greg (@greg16676935420) December 20, 2021
Why not $200 billion? Asking for a Senator— litquidity (@litcapital) December 20, 2021
Earlier this week, Democratic US Senator Elizabeth Warren has tweeted to say that Musk should pay taxes and stop “freeloading off everyone else” after Time magazine named him its “person of the year”.
In response, Musk shot four tweets in which he said that the senator reminded him of a friend’s angry mom who yelled at everybody. He tweeted, ““And if you opened your eyes for 2 seconds, you would realize I will pay more taxes than any American in history this year.” “Don’t spend it all at once … oh wait you did already.”
He added further, “You remind me of when I was a kid and my friend’s angry Mom would just randomly yell at everyone for no reason.”
Musk responded by saying that he “will pay more taxes than any American in history this year”. This Twitter exchange left netizens divided as even though many supported Warren and agreed that Musk should pay more taxes, others felt that he was already doing enough.
Musk’s Tesla is worth about $1 trillion. Over the last few weeks, he has sold nearly $14 billion worth of Tesla shares.
The Tesla boss has been pushing for his colonize Mars agenda for years now, and has made it very clear in some occasions that he would rather spend the money on putting humanity on the red planet, than pay his taxes. “My plan,” the SpaceX founder tweeted about his fortune, “is to use the money to get humanity to Mars and preserve the light of consciousness.”
Twitter Admits Policy ‘Errors’ After Far-Right Abuse Its New Rules of Posting Pictures
Twitter’s new picture permission policy was aimed at combating online abuse, but US activists and researchers said Friday that far-right backers have employed it to protect themselves from scrutiny and to harass opponents.
Even the social network admitted the rollout of the rules, which say anyone can ask Twitter to take down images of themselves posted without their consent, was marred by malicious reports and its teams’ own errors.
It was just the kind of trouble anti-racism advocates worried was coming after the policy was announced this week.
“Anyone with a Twitter account should be reporting doxxing posts from the following accounts,” the message said, with a list of dozens of Twitter handles.
Gwen Snyder, an organizer and researcher in Philadelphia, said her account was blocked this week after a report to Twitter about a series of 2019 photos she said showed a local political candidate at a march organized by extreme-right group Proud Boys.
Rather than go through an appeal with Twitter she opted to delete the images and alert others to what was happening.
“Twitter moving to eliminate (my) work from their platform is incredibly dangerous and is going to enable and embolden fascists,” she told AFP.
But the rules don’t apply to “public figures or individuals when media and accompanying Tweets are shared in the public interest or add value to public discourse.”
By Friday, Twitter noted the roll out had been rough: “We became aware of a significant amount of coordinated and malicious reports, and unfortunately, our enforcement teams made several errors.”
“We’ve corrected those errors and are undergoing an internal review to make certain that this policy is used as intended,” the firm added.
Jack Dorsey Post Twitter Is Chasing His Crypto, Fintech Dream
At a packed Miami conference in June, Jack Dorsey, mused in front of thousands of attendees about where his real passion lay: “If I weren’t at Square or Twitter, I’d be working on Bitcoin.”
On Monday, Dorsey made good on one part of that, announcing he would leave Twitter for the second time, handing the CEO position to a 10-year veteran at the firm. The 45-year-old entrepreneur, who is often described as an enigma with varied interests from meditation to yoga to fashion design, plans to pursue his passion which include focusing on running Square and doing more philanthropic work, according to a source familiar with his plan.
Well before the surprise news, Dorsey had laid the groundwork for his next chapter, seeding both companies with cryptocurrency-related projects.
Underlying Dorsey’s broader vision is the principle of “decentralisation,” or the idea that technology and finance should not be concentrated among a handful of gatekeepers, as it is now, but should, instead, be steered by the hands of the many, either people or entities.
The concept has played out at Square, which has built a division devoted to working on projects and awarding grants with the aim of growing Bitcoin’s popularity globally. Bitcoin price in India stood at Rs. 44.52 lakh as of 12:50pm IST on December 1.
Dorsey has been a longtime proponent of Bitcoin, and the appeal is that the cryptocurrency will allow for private and secure transactions with the value of Bitcoin unrelated to any government.
The idea has also underpinned new projects at Twitter, where Dorsey tapped a top lieutenant – and now the company’s new CEO Parag Agrawal – to oversee a team that is attempting to construct a decentralised social media protocol, which will allow different social platforms to connect with one another, similar to the way email providers operate.
The project called Bluesky will aim to allow users control over the types of content they see online, removing the “burden” on companies like Twitter to enforce a global policy to fight abuse or misleading information, Dorsey said in 2019 when he announced Bluesky.
Bitcoin has also figured prominently at both of his companies. Square became one of the first public companies to own Bitcoin assets on its balance sheet, having invested $220 million (roughly Rs. 1,650 crore) in the cryptocurrency.
In August, Square created a new business unit called TBD to focus on Bitcoin. The company is also planning to build a hardware wallet for Bitcoin, a Bitcoin mining system, as well as a decentralised Bitcoin exchange.
Twitter allows users to tip their favourite content creators with Bitcoin and has been testing integrations with non-fungible tokens (NFTs), a type of digital asset that allows people to collect unique digital art.
Analysts see the transition as a positive signal for Square, the fintech platform he co-founded in 2009. Square’s core Cash App, after a bull run in its share in 2020, has experienced slower growth in the most recent quarter. It is also trying to digest the $29 billion (roughly Rs. 2,17,240 crore) acquisition of Buy Now Pay Later provider Afterpay, its largest acquisition ever.
But these ambitions will not pay off until years from now, analysts cautioned.
“The blockchain platform they’re trying to develop is great but also fraught with technical challenges and difficult to scale for consumers. I think he’ll focus more on Square and crypto will be part of that,” said Christopher Brendler, an analyst at DA Davidson.
© Thomson Reuters 2021
Interested in cryptocurrency? We discuss all things crypto with WazirX CEO Nischal Shetty and WeekendInvesting founder Alok Jain on Orbital, the Gadgets 360 podcast. Orbital is available on Apple Podcasts, Google Podcasts, Spotify, Amazon Music and wherever you get your podcasts.
Cryptocurrency is an unregulated digital currency, not a legal tender and subject to market risks. The information provided in the article is not intended to be and does not constitute financial advice, trading advice or any other advice or recommendation of any sort offered or endorsed by NDTV. NDTV shall not be responsible for any loss arising from any investment based on any perceived recommendation, forecast or any other information contained in the article.
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