Agreed — but it's also somewhat independent. E.g., think of ChatGPT outputs that eloquently reach a nonsense conclusion by confidently asserting things that don't follow. There's a "Hey, wait a minute…" effect when style exceeds reasoning.
AI
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Three Tech Predictions: Transformers, ROS2, and Indoor Farming
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“I never make predictions. I never have and I never will.” Tony Blair(?). Me neither, except: Transformers, ROS2, and Indoor Farming.
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Stanford Buffalo Universities Advance Language Modeling State Space Models
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Stanford & Buffalo U Advance Language Modelling with State Space Models https://
syncedreview.com/2023/01/03/sta
nford-buffalo-u-advance-language-modelling-with-state-space-models/
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AI Dungeon’s Role in the Birth of LLM Prompt Engineering
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LLM prompt engineering was born in academia, but AI Dungeon was its cradle. Many people, including me, used GPT-3 for the first time via this game. Many useful prompting techniques were discovered by players who abused it for independent, informal research.
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Andrew Ng Thanks Contributors to The Batch Newsletter
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7/Exciting times ahead, and thank you Yoshua Bengio, @AlonHalevy
, @douwekiela
, @_beenkim
, and @Reza_Zadeh for writing for The Batch! -
Generative AI and Active Learning: AI Systems Selecting Data for Labeling
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6/Reza Zadeh sees generative AI bringing progress to active learning, where a system picks its own examples to be labeled to improve the data. With generative AI, he sees a potential revolution in algorithms generating new data to request to be labeled.
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AI Explainability: From Engineering to Fundamental Scientific Principles
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5/Been Kim discusses AI explainability. AI has taken an engineering-centric approach, where researchers devise techniques via trial and error, and she urges developing fundamental scientific principles that make explanations more trustworthy and accurate.
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Key Directions for AI: Multimodality, Safety, Data-Centric Approaches, and Evaluation
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4/Douwe Kiela points out key directions: Multimodality, grounding, and interaction so AI understands us better; alignment, attribution, and uncertainty to make models safer; data-centric AI to improve scaling; and better ways to evaluate AI models.
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AI Personal Timeline: Tracking Goals While Preserving Privacy
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3/Alon Halevy envisions AI capturing massive amounts of data from your daily life — photos, browsing, purchases — and fusing it into a personal timeline that helps you track and achieve your goals, while preserving privacy.
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Yoshua Bengio Advocates New Architectures for Conceptual Discovery
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Yoshua Bengio wants to develop new architectures that can discover and reason with high-level concepts, rather than just brute force the learning process by scaling up existing models' data and compute.