Top notch result from Opus 4.8 on BullshitBench, after a slight dip with 4.7. Need to start thinking of some new harder questions soon!
MACHINE LEARNING
-
WALL-WM: World Action Model using semantic events as atomic units
By
–
X Square Robot presents WALL-WM — a World Action Model that uses semantic events as atomic units, aligning language, video, and action granularities. https://t.co/JAKBdwnCKE
— 机器之心 JIQIZHIXIN (@jiqizhixin) 29 mai 2026X Square Robot presents WALL-WM — a World Action Model that uses semantic events as atomic units, aligning language, video, and action granularities.
-
Why not integrate? Anthropic banned you, use codex
By
–
What’s stopping you from integrating it right now? (I see that Anthropic banned you, codex is the better performing harness/model tho so just use that)
-
Token allocation, not model, drives multi-agent AI performance, study finds.
By
–
80% of multi-agent performance variance is just token allocation, not the model. That's from a UC Berkeley paper that decomposes any AI agent into 6 components: model, memory, context, skills, orchestration, verification. The model is one. The other 5 are where the gains
-
Hot take on AI companies after tokenmaxxing decline
By
–
Hot take on what comes next, after the sudden decline of tokenmaxxing:
– OpenAI will struggle – with the decline of tokenmaxxing Anthropic will struggle (aside from this quarter) to make a profit – Google will catch up to Anthropic – some Chinese companies might, too
– LLMs -
8B MoE Model Trained for Agentic Local Workflows
By
–
8B MoE (1B Activated) trained on 38 trillion tokens for local and agentic workflows
-
AI-Driven Agriculture System Automates Tomato Farming
By
–
#AI-Driven Agriculture System Plants, Monitors, and Harvests Tomatoes on Its Own
— Ronald van Loon (@Ronald_vanLoon) 29 mai 2026
by @sutoroveli_news#AgriTech #Innovation #Technology #TechForGood pic.twitter.com/WW1U6HO5Gr#AI-Driven Agriculture System Plants, Monitors, and Harvests Tomatoes on Its Own
by @sutoroveli_news #AgriTech #Innovation #Technology #TechForGood -
Potential OOM inefficiencies suspected in xAI’s training code
By
–
i.e I wouldn't be at all shocked to hear that there are (were?) OOM inefficiencies in xai's training code base.
-
Jax vs C: inefficient implementation comparison
By
–
IIUC the previous training code at xai was super inefficient. Perhaps the 10x is comparing to that? So it's not really "jax vs C" but "crappy jax impl vs less crappy C impl"?
-
Google’s new anything-to-anything AI model is wild
By
–
Google’s new anything-to-anything #AI model is wild
by Allison Johnson @verge Learn more: https://
bit.ly/49iHZqj #GenerativeAI #ArtificialIntelligence #MachineLearning #ML