🤖 Together AI ships serverless inference, Sakana AI & NVIDIA speed sparse models
Audio in Mandarin Chinese · English transcript below
⚡ Serverless models at cabbage prices, sparse LLMs 20% faster, AI toy lawyer fumble, subtitle glasses go real-time cheat, SIGGRAPH films spam generative skills—rush-hour subway edition.
LLMs are leveraging Together AI's serverless platform, in conjunction with Sakana AI and NVIDIA's underlying optimizations, to achieve more efficient and cost-effective widespread applications. However, the challenge of autonomous AI being "confidently wrong" in production environments has also given rise to intent-driven chaos testing, emphasizing that AI deployment must balance both performance and robustness to ensure its behavior aligns with intended goals.
Today's Top 3 Headlines
- AI Industry News
🤖 Together AI serverless: DeepSeek-V4-Pro 512k ctx, $2.1/M in, $8.4/M out
Together AI docs reveal serverless inference now hosts 20+ LLMs incl DeepSeek-V4-Pro: $2.1/M in, $4.4/M out, cached in $0.2/M. Devs can run LLMs with zero reserved compute and no minimum spend—perfect for prototyping and low-traffic apps.
Source ↗ - AI Technology
🤖 1B-LLM 20% faster: Sakana AI×NVIDIA debut TwELL format
Sakana AI & NVIDIA unveil TwELL sparse format + custom CUDA kernels, cutting LLM inference >20% at 1B scale while slashing peak RAM and energy. Devs can now run bigger models or higher concurrency on the same silicon, unlocking greener compute for edge deployment.
Source ↗ - AI Industry News
🤖 Overconfident Agent? Intent-Chaos Test Exposes Flaws Pre-Launch
VentureBeat: 2026 enterprise rollout halted 4h after an observability Agent mis-flagged a batch job and triggered rollback—LLM non-determinism plus multi-Agent “poison inputs.” Intent-driven chaos testing shifts the metric from “task done” to “intent preserved.”
Source ↗
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