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#Trends

4 today

Sep 19

Saturday

Sep 18

Friday
  1. Should you read the code, is RAG dead, and did Skills kill MCP?

    The latest GitHub Podcast examines five AI development memes. AI-generated code still needs reading and accountability, with review proportional to risk. Skills package team experience, while MCP standardises connections to tools and data; they can combine. RAG is not dead: it provides relevant information beyond training data and can coexist with agents, Skills and MCP in one workflow.

Sep 17

Thursday

Sep 16

Wednesday
  1. How workers are unlocking new ways of working

    OpenAI economic research finds workers use AI beyond traditional job responsibilities, with new activities becoming recurring parts of their work. It examines how employees actually expand their work with AI rather than limiting analysis to existing roles.

Sep 8

Tuesday
  1. The Work Now Within Reach

    OpenAI explores how more capable, affordable AI expands what individuals and businesses can accomplish and makes growth more economical. It focuses on capability gains and falling costs, explaining their effects on practical work output and business growth.

Sep 6

Sunday

Aug 31

Monday

Aug 10

Monday
  1. Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing

    Import AI 468 covers IFP's 23 proposals in seven categories for further AI R&D automation risks. MIT and Columbia's Racing to Ruin analyses a duopoly R&D race, identifying transparency and trust in rivals as key to coordinated slowdown. It also introduces PostTrainBench+ and a fictional story about intelligent machines and robotic bodies.

Jul 30

Thursday

Jul 20

Monday

Jul 7

Tuesday

Jul 6

Monday

Jun 30

Tuesday

Jun 22

Monday

Jun 8

Monday

Jun 1

Monday

May 26

Tuesday

May 16

Saturday

May 11

Monday
  1. Import AI 456: RSI and economic growth; radical optionality for AI regulation; and a neural computer

    The Institute for Law & AI proposed radical optionality in regulation: governments should avoid excessive regulation now while building information gathering, whistleblower protection, evaluation and model-weight security capabilities to respond quickly when powerful AI affects the world. A Meta and KAIST paper proposed a Neural Computer unifying computation, memory and I/O in learned runtime states.

May 8

Friday
  1. Adaptive Parallel Reasoning: The Next Paradigm in Efficient Inference Scaling

    Berkeley AI Research reviews parallel reasoning, focusing on models deciding when to decompose and parallelise independent subtasks, how many threads to generate and how to coordinate. Existing approaches including Self-consistency, Best-of-N, Tree of Thoughts, MCTS, ParaThinker, GroupThink and Hogwild! Inference mostly impose parallel structures externally rather than teaching adaptive behaviour.

May 4

Monday

Mar 31

Tuesday

Mar 12

Thursday