AI is fun, and it comes with its own share of knowledge bank. With so much happening in the industry and technology within, it becomes very hard to judge a technology – what’s hot and what’s not. That’s where Twitteratis come into action. With their accurate messaging and promotion of content that are closest to the verified truth, AI influencers make the ecosystem sound and believable. Here are top AI influencers on Twitter who know what’s baking in the Machine Learning furnace.
A former Stanford University doctorate, Adam is an Operating Partner at Khosla Ventures. He has developed deep learning software for some of the most high-performance computing systems with a team at Stanford. His deep learning expertise is used for unsupervised learning, object detection, and self-driving cars at Baidu, and Stanford AI.
“The bottleneck now is in management, implementation, and business imagination.”
Hearing this same sentiment a lot — AI managers, product designers, executives in short supply, not just engineers. https://t.co/9RerHlCpSn
— Adam Coates (@adampaulcoates) June 16, 2018
The former Director of AI at Tesla, Andrej is a multi-faceted Twitter influencer. From following research study groups to identifying the top trending technologists in AI and deep learning. Andrej keeps blogging frequently about his interactions with AI, self-driving cars, and machine learning algorithms.
— Andrej Karpathy (@karpathy) June 21, 2018
AI is a competitive ecosystem and we love to see women in tech making it to our list of top-searched Twitter celebrities in the industry. Dr. Fei-Fei Li is a co-founder of the non-profit institution for AI technologists, ai-4-all.
Dr. Li is the Chief Scientist of AI/ML and a VP at Google Cloud. From being a mentor and professor of computer vision, machine learning, AI, computational neuroscience at Stanford, Dr. Li has scripted a phenomenal journey into AI and computational theories. Her posts and Twitter followers justify the legacy.
We are excited to announce new AI products AutoML Natural Language, AutoML Translate and Contact Center AI to empower industries. It’s one year’s hard work with our team @googlecloud #GoogleNext18 https://t.co/xwnfwPbEdf
— Fei-Fei Li (@drfeifei) July 24, 2018
The creator of Keras is a Twitter influencer with strong opinions. He once tweeted how Deep Learning algorithms could look dumb from every angle, but can still solve industrial problems. It does not have to be smart to be useful. Savvy!
The key advantage of deep learning is its reliance on global optimization — it learns a hierarchy of features jointly, which solves the fundamental problem of information loss. That's also one of its main weaknesses: it makes DL extremely inefficient due a lack of modularity.
— François Chollet (@fchollet) August 7, 2018
Ian is a lead author at MIT Press. With nearly 90k+ Twitter followers 100k, the Google Brain research is a potent minefield of ‘everything AI and deep learning”. He often tweets and posts his answers on varied computational challenges and empirical papers, helping new researchers get to the core of specific AI and neural networks.
Neural networks are notoriously hard to debug. @gstsdn has developed a new debugging methodology by adapting traditional coverage guided fuzzing techniques to neural networks. pic.twitter.com/z6s2X9hmmb
— Ian Goodfellow (@goodfellow_ian) July 31, 2018
The CEO at Matroid is a cool Twitter influencer who knows the pulse of the AI revolution. His team consists of tech-friendly individuals who work with complex decision trees and deep learning algorithms.
Each "wave" of Machine Learning has technical contributions that many other subfields of ML use. For:
– Deep Learning it’s Automatic Differentiation
– Bayesian inference it’s priors
– SVMs it’s kernel trick
– Decision trees it’s ensembling
Major wins come from a mix of ideas.
— Reza Zadeh (@Reza_Zadeh) July 28, 2018
Miles can tell you everything about AI policies and how to leverage content for better decision-making in AI. Currently a Research Fellow at the University of Oxford’s Future of Humanity Institute and a Ph.D. candidate in Human and Social Dimensions of Science and Technology at Arizona State University, Mike is also associated with the Virtual Institute of Responsible Innovation (VIRI), and the Journal of Responsible Innovation (JRI). Mike publishes his insights and research papers on his privately-owned website.
As many of you know, OpenAI has been quite engaged in policy discussions for quite some time, and they were key players in producing our recent report on the malicious use of AI.
— Miles Brundage (@Miles_Brundage) August 7, 2018
Machine Learning is magical; Adam tells us how. From video-based face recognition to Google AI and ethics, Adam tweets about most contemporary topics in the industry with a flair of an experienced rodeo.
That there's actually a huge need in the machine learning field for traditional software engineers that just know how to write clean, maintainable code and build clean architectures. The machine learning bits are like 3% of the work in real projects. https://t.co/lSncyfimDN
— Adam Geitgey (@ageitgey) July 9, 2018
The co-founder of Coursera is a credible influencer on Twitter. Andrew has over 30K+ followers and he follows most research programs erupting in the AI field.
Pictures from @Stanford's CS230 (Deep Learning) poster session last Saturday. We grew from 0 to ~800 students in one academic year, including 350 in the most recent quarter. Will also post projects online soon for those interested! @kiankatan @SwatiDube pic.twitter.com/q7ml9aC4hS
— Andrew Ng (@AndrewYNg) June 12, 2018
Soumith is an AI Research Engineer in Facebook. With 46k followers on Twitter, Soumith keeps a close tab on machine-level automation, driven by NLP, bots and AI-focused research papers.
"Troubling Trends in Machine Learning Scholarship"
For the researchers in the field of ML, and in the short-term, reviewers of the NIPS Conference submissions, this is a sobering and an important read:https://t.co/RcQ6H77wrz
— Soumith Chintala (@soumithchintala) July 10, 2018
The Chief Scientist at Salesforce, Richard Socher is the next name in our list of top AI influencers on Twitter. Richard keeps his followers and community updated about “why language is AI’s greatest challenge.”
Very excited to announce the natural language decathlon benchmark and the first single joint deep learning model to do well on ten different nlp tasks including question answering, translation, summarization, sentiment analysis, ++https://t.co/R5wbnAQcC3 pic.twitter.com/4fotVhdRow
— Richard (@RichardSocher) June 20, 2018
While this is not the end-of-world list of AI influencers on Twitter, we certainly think that following these professionals could be very helpful in understanding more about the industry and the layers of deep learning beneath.