Artificial Intelligence (AI) is the new normal which is rapidly advancing the technology sector and has also significantly impacted the key aspects of businesses.

In this article, we list down AI’s power players who are also thought leaders in the area of machine learning (ML), deep learning, computer vision, and robotics and also have a massive following on their Twitter accounts. These AI giants includes industry experts, product innovators, and researchers who bring the latest insights and popular AI trends to their followers. 

Here are top twitter accounts that will help you keep a track of all exciting AI updates:

Hardmaru

A GAN for World Peace? https://t.co/DGDQvdqftc

— hardmaru (@hardmaru) December 26, 2019

David Ha, a Google researcher and one of the authors of the NeurIPS paper “Weight Agnostic Neural Networks”.

Judea Pearl

This bold defense of deep learning says that
some DL folks have yet to internalize the Ladder of Causation, eg https://t.co/KBGKcmJxM8. Can any DL-insider think of a good way to convince @Lecun that some questions cannot be answered from data alone, no matter what? #Bookofwhy. https://t.co/Kfnd2Tyj1h

— Judea Pearl (@yudapearl) December 25, 2019

Judea Pearl is a chancellor, philosopher, and a professor of computer science and statistics at UCLA, and also a distinguished visiting professor at the Technion — Israel Institute of Technology.

Pearl has authored numerous scientific papers and three seminal books — Heuristics (1983), Probabilistic Reasoning (1988), and Causality (2000, 2009). In a recent book, “The Book of Why” (2018, with Dana Mackenzie) Pearl explains the concept of cause and effect, which is a grand taboo in science and has been algorithmitized to serve in the interpretation of data.

In 2012, he won the Technion’s Harvey Prize and the ACM Alan Turing Award for the development of a calculus for probabilistic and causal reasoning.

Yann Lecun

Some folks still seem confused about what deep learning is. Here is a definition:

DL is constructing networks of parameterized functional modules & training them from examples using gradient-based optimization…. https://t.co/jmHpWZOMH8

— Yann LeCun (@ylecun) December 24, 2019

Yann Lecun is VP and Chief AI Scientist at Facebook, and also an ACM Turing Award Laureate and a silver professor of computer science, data science, neural science, and electrical and computer engineering at New York University.

François Chollet

So, "deep learning" is the idea of doing representation learning via a chain of learned feature extractors. It's all about describing some input data via *deep hierarchies of features*, where features are *learned*.

A further question is then: is the brain "deep learning"?

— François Chollet (@fchollet) December 26, 2019

François Chollet is the author of Keras – keras.io – a leading deep learning framework for Python, with over 350,000 users and 700+ open-source contributors (as of Q2 2019). Keras is in use at a considerable number of startups, research labs, including CERN, Microsoft Research, and NASA, and large companies such as Netflix, Yelp, Square, Uber, Google, etc. Keras has been chosen to serve as the high-level API of Google’s TensorFlow.

Jeremy Howard

This is both beautiful, and intimidating. I now feel just a little more inadequate than I did before… https://t.co/6NcvgPZjsQ

— Jeremy Howard (@jeremyphoward) December 21, 2019

Jeremy Howard is an entrepreneur, business strategist, developer, and educator. Jeremy is a founding researcher at fast.ai, which is a research institute dedicated to making deep learning more accessible. He is also a faculty member at the University of San Francisco, and is Chief Scientist at doc.ai and platform.ai.

Andrej Karpathy

A 4 year old child actually has a few hundred million years of experience, not 4. Their rapid learning/generalization is much less shocking/magical considering this fact.

— Andrej Karpathy (@karpathy) December 15, 2019

Karpathy is the Director of AI at Tesla and has worked as a Research Scientist at OpenAI. His courses are immensely popular and he is one of the most followed AI pioneers online as well as offline.

Demis Hassabis 

We’re heading into our 2nd decade as an established scientific org with an incredible team. Having helped set us up for long-term success @mustafasuleymn is leaving DeepMind & joining Google to work on opportunities & impacts of applied AI https://t.co/d1ADLs2r9R 2/3

— Demis Hassabis (@demishassabis) December 5, 2019

Demis Hassabis is the founder and CEO at DeepMindAI. He has completed his PhD in cognitive neuroscience from the University College London, and his doctoral studies focused on the field of autobiographical memory and amnesia. He has co-authored papers on the subject, published in nature, science, neuron, and proceedings of the National Academy of Sciences (PNAS). His work on the neurological connection between imagination and episodic memory was also cited as one of the “Top 10 Scientific Breakthroughs of the Year”.

Arvind Narayanan

If you think there's too much yelling about algorithmic bias, here's an analogy. By the mid 90s the privacy community knew there was a huge problem. But it took two decades of yelling and a million privacy disasters before the public and policy makers started taking it seriously. https://t.co/HFcBpjPhkI

— Arvind Narayanan (@random_walker) December 20, 2019

Arvind Narayanan is a Princeton professor and he uses Twitter to share his research & commentary on surveillance capitalism, infosec, cryptocurrencies, AI ethics, tech policy, & academic life.

Google AI

ALBERT is a new, open-source architecture for natural language processing that achieves state-of-the-art performance on multiple benchmarks with ~30% fewer parameters than #BERT. Learn all about it below: https://t.co/oYriFcwrQo

— Google AI (@GoogleAI) December 20, 2019

What can be better news feeder than the ones that has created the news itself? Google has been spearheading AI research over the past decade. This handle updates its followers with all the advancements in the state-of-the-art in many ML domains.

Lex Fridman

I wrote a script to manage some neural net training & added code to send me a text when a threshold of performance is reached while I go for a run. However, I forgot to limit the # of texts to 1, thereby creating my first overly attached neural network. Over 100 texts in 2 hours.

— Lex Fridman (@lexfridman) December 16, 2019

Fridman is a machine learning researcher who works on autonomous vehicles and human-centred AI. His podcast, where he interviews great minds of AI, has gained great traction owing to its high-quality content. He brings the same flavour and insights to his twitter account as well. 

Facebook AI

Pluribus, the first AI bot to beat elite poker pros in 6 player Texas Hold’em, has been named a runner-up for @sciencemagazine's Breakthrough of the Year: https://t.co/IN4TD1BBqq Congrats to @polynoamial and @CarnegieMellon!
Read more about Pluribus here: https://t.co/zId9x5dchK

— Meta AI (@MetaAI) December 23, 2019

Facebook AI twitter handle updates their followers with the latest in-house findings and other news related to advancing of ML and conducting open research.

Ruslan Salakhutdinov

Someone told me once: You can do AI or you can just talk about it. #AIDebate

— Russ Salakhutdinov (@rsalakhu) December 25, 2019

Ruslan Salakhutdinov is a professor at Carnegie Mellon University and the director of AI research at Apple and according to me, he needs no further introduction!

Hugo Larochelle

We looked into the NeurIPS 2019 data, to see if we could gain any interesting insights and inform discussion on future years. Here's our blog post on what we found out:https://t.co/yr0xpBhe3y

— Hugo Larochelle (@hugo_larochelle) December 9, 2019

Hugo Larochelle is a Google Brain researcher and a machine learning professor.

Animesh Garg

This is an upcoming collaboration on learning physics based models. Why is this interesting to Robotics? Well model based learning is efficient but model learning itself is not yet well understood.
Come chat with us later today or send us a message for collaboration https://t.co/BS83i1ZgKn

— Animesh Garg (@animesh_garg) December 14, 2019

Animesh Garg is an assistant professor of AI at the University of Toronto and a professor of ML for robotics at VectorInst. He is also associated with NVIDIA AI and Stanford and Berkeley AI department.

Rachel Thomas

To give a few examples (there are many), photos 1 & 3 are of my post, 2 & 4 are from Georgios Drakos's post on Towards Data Science. He even kept the text bolding the same, used the same graphics & quotes, etc pic.twitter.com/Yv9uPhJaFi

— Rachel Thomas (@math_rachel) December 27, 2019

Rachel Thomas is the director of the USF Center for applied data ethics at DataInstituteSF and also the co-founder of fast.ai. She tweets about deep learning ethics and software developer.

Chip Huyen

It took me a while to recap bc some papers are complex. Key points:

– Destructing black box: convergence, generalization, neural tangent kernel
– New approaches: Bayesian & uncertainty, graph, convex optimization
– Neuroscience & bio-inspired algos
– …https://t.co/o1B2Xcv1Jq

— Chip Huyen (@chipro) December 19, 2019

Chip Huyen, a writer and a computer scientist from Vietnam and now based in Silicon Valley.

He has done his graduation from Stanford University, where she created and taught the course TensorFlow for Deep Learning Research. Currently, she is with the Artificial Intelligence (AI) Applications team at NVIDIA. 

Gary Marcus

NEW post by Yoshua explicating his definition of deep learning, attached as a screenshot.

(I anticipate responding briefly, though not today).

Full archives of the continuing #AIDebate: https://t.co/Wj72yxLNew courtesy @Montreal_AI

Happy reading! pic.twitter.com/hBBYuyTzhf

— Gary Marcus (@GaryMarcus) December 28, 2019

Gary Marcus, Founder and CEO of Robust.AI, is a scientist, author, and entrepreneur. He was also the Founder and CEO of Geometric Intelligence, a machine learning company acquired by Uber in 2016. His newest book, co-authored with Ernest Davis, Rebooting AI: Building Machines We Can Trust aims to shake up the field of artificial intelligence.

Analytics India Magazine

Data breaches, Cyberattacks ??- Here are the top Open source project to be considered for the year 2020.
Full Story: https://t.co/7hGkoPxAgl#databreach #cybersecurity #cyberattacks #opensource@Google @vuls_en @IBM pic.twitter.com/eQotLNzknm

— Analytics India Magazine (@Analyticsindiam) December 25, 2019

Analytics India Magazine is India’s leading publisher chronicling advances in analytics, big data, artificial intelligence and data science. This account presents its followers with 360-degree insights from the world of AI and ML. The tweets cover hands-on tutorials, and stories on cutting edge technology, acquisitions, latest startups, interviews and many more.