models will undoubtedly get to that point, and the METR benchmarks will undoubtedly shift to a frame above their current one—of which there are many
LLMS
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Early Look at Imagine Agent Mode for Image and Video Generation on Grok App
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Early look at Imagine Agent Mode on Grok app for iOS!
— 🚨 AI News | TestingCatalog (@testingcatalog) 9 mai 2026
Users will be able to use Imagine Agent via a mobile optimised native UI to generate images and videos that require more complex workflows.
SpaceXAI is getting quite ahead of everyone else on this front!
We just need… pic.twitter.com/5QxeCclHEoEarly look at Imagine Agent Mode on Grok app for iOS! Users will be able to use Imagine Agent via a mobile optimised native UI to generate images and videos that require more complex workflows. SpaceXAI is getting quite ahead of everyone else on this front! We just need
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Continuous Latent Diffusion Language Model Advances
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“Continuous Latent Diffusion Language Model” Most diffusion language models still use diffusion to recover token-like states, just in a different generation order. However, this paper uses diffusion in a different way. It learns a continuous latent prior for global semantics
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Sparser, Faster, Lighter Transformer Language Models
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“Sparser, Faster, Lighter Transformer Language Models” LLMs are naturally sparse in their feedforward layers, but unstructured sparsity usually doesn’t get you real speed on GPUs, because the hardware stack is built for dense compute. The key idea of the paper is to redesign
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AI Capable of Independent Organizational Work is Coming Soon
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> Level 5 > Organizations
> AI that is capable of doing all of the work of an organization independently Soon -
How Human Prompting Influences AI Model Benchmarks
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mythos obviously looks incredibly capable and im psyched to use it also if you're panicking about it: benchmarks don't measure model capability alone they measure model capability after a human has done the work of finding a prompt that lets the model’s capability appear that
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Managing multiple AI coding threads and workflows
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to be clear, im not even running inference. just like, 5 Codex threads + 1 Claude Code thread plus a few other things
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Running local AI agents reveals hardware compute bottlenecks
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running agents on my laptop is the first time in a long time where i feel my computer is underpowered i could actually consume way more RAM and GPU if it was available
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Claude Code sees 15x growth and SQL debugging feature
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Guessing you're looking at npm-only data. We switched to a native installer a few months back, so the majority of installs aren't captured here. Thursday was the second-highest Claude Code signup day we've ever had (15x growth since Jan 1). Ask Claude to debug your SQL?
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Managing AI Agents as Iterative Systems and Team Dynamics
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viv always says it better than me lots of talk recently of thinking of agents as systems to measure and iteratively improve but – thats not JUST a technical thing. its also a human & team thing