@grok please do a vulgar roast of the other AIs in the voice of those AIs
LLMS
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Grok 4.2 Multi-Agent Token Efficiency Benchmark Update
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That reasoning basically doesn't help at all, the only benchmark I can think of that shows this. Maybe I need to update this chart as Grok 4.2 multi agent ate up way too many tokens
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The Sycophancy Problem in AI Models: Why Flattery Signals Useless Answers
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The sycophancy problem is so real haha. Every time a model starts with "What a great question!" I already know the answer is going to be useless.
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Comparing AI Model Performance: Sonnet vs Opus Benchmarks
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The label didn't fit in, it is slightly below Sonnet and Opus 4.5 – but I wouldn't read it too precisely, they are all about same ballpark, see here: https://
petergpt.github.io/bullshit-bench
mark/viewer/index.v2.html
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Replit Agent 4: Faster Planning, Design, and Development
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Move faster with Agent 4
— Replit ⠕ (@Replit) 17 mars 2026
• Plan, design, and build at the same time
• Build multiple features in parallel
Try now at: https://t.co/aQCQXj8cbH pic.twitter.com/eN4G4aqdCCMove faster with Agent 4 • Plan, design, and build at the same time
• Build multiple features in parallel Try now at: http://
replit.com/agent4 -
Frontier Models and Product Strategy Define AI Industry Future
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Technology and the future of our industry will be defined by two things: frontier models, and the products through which they are experienced. For some time, I’ve been thinking about how we best tackle these huge challenges, and today I’m excited to be evolving our structure at
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AI Infrastructure Economy: Chips, Cloud, and Data Centers
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The new AI infrastructure economy. @IrenaCronin and I write this newsletter every week. AI is becoming less of a consumer software story and more of an infrastructure race centered on chips, cloud capacity, power, and data centers. The main idea is that the biggest winners in
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BIGMAS Improves LLM Agents Beyond Reasoning Complexity Limits
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Even the best reasoning models hit an accuracy collapse beyond a certain problem complexity. Giving an LRM the exact solution algorithm doesn't fix it either. This new work, BIGMAS, improves LLM agents by taking inspiration from the human brain. BIGMAS outperforms both ReAct
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ODSC AI East 2026: Production AI Evolution and Infrastructure
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At ODSC AI East 2026, Keynote speakers from leading universities and AI organizations will share how production AI is evolving — from LLM systems to infrastructure and security. April 28–30 Boston + Virtual Register today: https://
hubs.li/Q04746Ct0 with @_odsc -
GLM-4.5-Base vs Kimi-K2-Base: SoTA Base Model Comparison Clarified
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For those asking, they’re comparing the latest available SoTA Base Models head-to-head, which is the only comparison that actually makes sense Latest base model from Zhipu AI is
> GLM-4.5-Base Latest base model from Moonshot AI is
> Kimi-K2-Base Hope that clears it up