Comparing INT4 and NVFP4 Palettes on Real Gradient Tensors
Four-bit training quantizes every number to one of 16 values. NVFP4's menu is {0, ±0.5, ±1, ±1.5, ±2, ±3, ±4, ±6} , with one scale factor per block…
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Context window sizing for fine-tuning: how long should your training examples be?
Originally published on Loop & Retry — field notes on building LLM agents that survive production. Most fine-tuning guides answer "how many exam…
Anthropic will design its own hardware to power Claude
Anthropic and OpenAI are racing to scale up while reducing dependence on Nvidia.
Faster AI training by quietly cloning the model
A new paper introduces a method to speed up reward-based fine-tuning by having the model generate a cheap, compressed copy of itself to draft text,…
A 35-billion-parameter agent that punches like a trillion-parameter model
A 35-billion-parameter model called Agents-A1 matches trillion-parameter models on multi-step agent tasks, according to a new paper from Shanghai AI…
LLMs believe false statements even after explicit warnings that they're false
Fine-tuning tests show "bias ... toward confidently representing the claims as true."
GymStats — писал для себя, открыт для всех, кто ходит в спортзал
Был я как-то очередной раз в спортзале: делал упражнения, поглядывая на предыдущие значения из заметок и записывая новые туда же. Придя домой, я обн…
Anthropic blames dystopian sci-fi for training AI models to act “evil”
But training on "synthetic stories" that model good AI behavior can help.
Study: AI models that consider user's feeling are more likely to make errors
Overtuning can cause models to "prioritize user satisfaction over truthfulness.”