It's interesting how close together the feature releases are from the different coding agent tools – here's Gemini extensions from yesterday https://
x.com/googlecloudtec
/googlecloudtech/status/1975931556804935870
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LLMS
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Gemini Extensions Release Highlights Rapid Coding Agent Tool Competition
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Open weights models lag behind proprietary AI advancement
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feels like ages since a new truly paradigm shifting model released on open weights side? or am I missing something? the closest on proprietary side is gpt-5-codex
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RTX 5090 vs 4x 3090s VRAM comparison for LLM inference
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5090 has 32GB of VRAM, 4x 3090s have 96GB of VRAM when it comes to LLMs inference, we care more about memory as models are better fully offloaded into VRAM than being shared across system RAM and a single RTX 5090's VRAM
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Sequential Decoding Behavior in Diffusion Language Models
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interesting, if it is a DLM why does it seem to decode sequentially?
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Valuing Wikipedia Data in LLM Training: Copyright and Markets
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Wikipedia comprises ~1% of LLM training data, but what's its worth? Scholars are attempting to put a price tag on the URLs, books & data used by AI companies. This could aid copyright cases & create more accurate data markets. Follow the discussion here: https://t.co/rbgxicwtD0 pic.twitter.com/GIqRjZTqRM
— Stanford HAI (@StanfordHAI) 9 octobre 2025Wikipedia comprises ~1% of LLM training data, but what's its worth? Scholars are attempting to put a price tag on the URLs, books & data used by AI companies. This could aid copyright cases & create more accurate data markets. Follow the discussion here: https://
hai.stanford.edu/events/hoffman
-yee-symposium-2025
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AI Shift: From Scale to Intent-Driven UX
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the smartest shift right now is this:
AI is moving from brute-force scale → causal, local, context-aware architecture. tiny reasoning models, on-device inference, and intent-driven design are rewriting how we use tech. UX is dissolving. no buttons. no menus. just intent. -
2025’s AI shift: architecture over scale
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everyone’s chasing bigger models. trillion tokens, billion-dollar data centers, rivers of compute. but the real AI story of 2025 isn’t about scale -> it’s about architecture. while openai burns oceans training gpt-5, samsung just dropped a 7-million-parameter reasoning model
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Gemini 2.5 Deep Think Sets New Frontier Math Record
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Gemini 2.5 Deep Think consigue un nuevo record en Frontier Math, evaluado por la buena gente de Epoch