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AI in tweets – January 2020
Happy new year 2020! Below are the tweets about AI we have collected this month.
Hopes for AI in 2020
In The Batch's new year edition, @ylecun @katecrawford @kaifulee @animaanandkumar @etzioni @chelseabfinn @RichardSocher @dawnsongtweets, Dave Patterson & Zhi-Hua Zhou share their hopes for AI in 2020. Check it out (and subscribe if you haven't yet!): https://t.co/4ITeoacobl
— Andrew Ng (@AndrewYNg) January 1, 2020
Predictions for AI in 2020
Top minds in machine learning predict where AI is going in 2020 https://t.co/YAifWZNjfO by @kharijohnson
— VentureBeat (@VentureBeat) January 2, 2020
An ethically mindful approach to AI for healthcare
"Ethical review [for #AI in #healthcare] cannot be a one-off, tick-box exercise and must be repeated regularly in a consistent way."—@jessRmorley @Floridi @Turinghttps://www.thelancet.com/journals/lancet/article/PIIS0140-6736(19)32975-7/fulltext @TheLancet @oiioxford @UniofOxford pic.twitter.com/dkOXqSpePs
— Eric Topol (@EricTopol) January 23, 2020
AI career pathways by workera
Workera recently published a report on AI career pathways. It doesn't mention hardware. I also don't see the difference b/w SWE-ML & ML Engineer. But it highlights some important distinctions.
I also like @josh_tobin_ talk on the structure of AI teams https://t.co/X6eHv8sskA pic.twitter.com/KysDChOjgR
— Chip Huyen (@chipro) January 10, 2020
Principles of AI Ethics and Safety
This is such a useful resource for understanding AI Ethics and Safety and it shows so clearly that AI is a multi-disciplinary field.https://t.co/78ripHVaXr pic.twitter.com/DYKf38E2Uf
— Suzana Ilić (@suzatweet) January 28, 2020
The role of AI in achieving the Sustainable Development Goals
A study of how AI technologies impact the UN Sustainable Development Goals finds that it could enable the accomplishment of 134 targets across these goals, but it may also inhibit 59 targets – https://t.co/Ya3cKFw7hf pic.twitter.com/Uv7mFOZi56
— Nature Machine Intelligence (@NatMachIntell) January 22, 2020
On GPT-2 and the nature of Intelligence by Gary Marcus
What GPT-2 accidentally reveals about nature, nurture, and the challenge of building intelligence.
Prelude to a longer piece on how to best advance AI over the next decade 😊 https://t.co/qSbhx6Nj3R
— Gary Marcus (@GaryMarcus) January 25, 2020
Meena: the new conversational agent by Google AI
Check out Meena, a new state-of-the-art open-domain conversational agent, released along with a new evaluation metric, the Sensibleness and Specificity Average, which captures basic, but important attributes for normal conversation. Learn more below! https://t.co/QxMVstg3qQ
— Google AI (@GoogleAI) January 28, 2020
Aligning AI with human Values by DeepMind
In “Artificial Intelligence, Values and Alignment” DeepMind’s @IasonGabriel explores approaches to aligning AI with a wide range of human values: https://t.co/yEv74jFUUP pic.twitter.com/Zo81PSpwyF
— Google DeepMind (@GoogleDeepMind) January 28, 2020
Neural nets and symbolic reasoning to solve advanced mathematical problems by Facebook AI
By restructuring math expressions as a language, Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems. https://t.co/gmtbQicEz3 pic.twitter.com/IL2H8ygDYC
— AI at Meta (@AIatMeta) January 14, 2020
mBART: a new pretraining system for machine translation by Facebook AI
We're releasing mBART, a new seq2seq multilingual pretraining system for machine translation across 25 languages. It gives significant improvements for document-level translation and low-resource languages. Read our paper to learn more: https://t.co/SjAunFuujZ pic.twitter.com/tJbRcOTqik
— AI at Meta (@AIatMeta) January 24, 2020
Polygames: a new framework for training bots through self-play by Facebook AI
In a collaboration with universities in France and Taiwan, Facebook AI is releasing Polygames, a new open source framework that enables researchers to train AI systems through self-play in a wide range of strategy games. https://t.co/6UTGTjVwwP pic.twitter.com/830R89Cbnz
— AI at Meta (@AIatMeta) January 29, 2020
A library of ~200 NLP datasets
Introducing the Big Bad Database. Helping NLP and ML developers gain access to nearly 200 datasets for natural language processing. Read about it on @towards_AI.#NLProc #AI #ArtificialIntelligence #Datasets #DeepLearning https://t.co/UTMsl9w3C8
— ̷̨̨̛̛̲͎̣̞̘͈̯͚͂̈́̂̄̽̎́̽̔͑̄̏̽̏͒̾́̅̐̈́̾̎̆͆̽́͌̽̀̚̕̚̕͠͝͝ (@Quantum_Stat) January 15, 2020
CausalNet: a software designed to understand the Why behind the data by QuantumBlack
We're excited to introduce our latest open source software, CausalNex – designed to help data scientists infer causation, rather than just observing correlation. https://t.co/3AZs2vdOZ5
— QuantumBlack, AI by McKinsey (@quantumblack) January 28, 2020
Advbox: a toolbox that generates adversarial examples for deep learning by Baidu
How robust is your model against adversarial attacks? We recently released Advbox, a toolbox to generate adversarial examples that fool neural networks across DL frameworks and benchmark the robustness of ML models.
ArXiv: https://t.co/vpYW0xwrEV
GitHub: https://t.co/77FczZ8V3o pic.twitter.com/XWhfrUVuH9— Baidu Research (@BaiduResearch) January 23, 2020
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