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Simulating fault tolerance with stage skipping in pipeline-parallel training

Templar team simulated stage-skipping fault tolerance in pipeline-parallel training on the Crucible distributed pre-training platform. With a 178M model, eight replicas, and four stages per replica, validation loss stayed close to the no-failure baseline at 1% per-replica failure probability. Fixed projections shared across layers improve robustness, supporting training on unreliable compute.

r/MachineLearning ·

AstroForge Puts In-House AI in Command of Spacecraft

Asteroid-mining startup AstroForge built an in-house transformer-based autonomy stack, Solo, for its Autonomy-1 spacecraft, set to launch in 2027 on Stoke Space's first rocket with NASA backing. The company has raised $56M in venture funding, and anomalies on its two prototype spacecraft, including the loss of contact with Odin, pushed it toward onboard autonomy.

TechCrunch ·

OpenAI Urges US-China Coordination on AI Safety

OpenAI is urging US-led global standards for the most powerful AI systems, including shared safety tests and US-China coordination on serious incidents. The proposal comes just before Trump's talks with Xi, with AI risks and technological competition high on the agenda.

WZTV ·

Economics of Open-Weight Inference: Older GPUs Retain Value

A paper finds open-weight inference costs about one-fifth of comparable closed models, with self-hosting at $0.12-$0.35 per million output tokens. On gpt-oss-120b, the A100 is cheaper than the H100, and A100 five-year rental prices retain 80% of one-month prices, showing older GPU families keep multi-year earning life.

Hacker News ·
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