All tags
Topic: "low-precision-training"
not much happened today
nemotron-3-ultra nemotron-3.5-asr claude-opus-4 mythos-preview nvidia anthropic togethercompute baseten modal vllm_project fireworksai_hq ollama wandb cline primeintellect nousresearch mixture-of-experts long-context model-quantization agentic-ai streaming-speech asr low-precision-training benchmarking recursive-self-improvement code-generation model-speedup piotrz_zelasko
NVIDIA released Nemotron 3 Ultra, a fully open 550B MoE model with 55B active parameters and 1M context, optimized for long-running agent tasks with up to 5x speedup and 30% cost reduction. It features hybrid Mamba/attention, LatentMoE, native MTP, and was pretrained on 20T tokens using NVFP4 low-precision format. Benchmarks show strong performance with 47.7 Intelligence Index and 400+ output tokens/sec. The model is supported across major serving platforms. Additionally, Nemotron 3.5 ASR is an open streaming ASR model with 0.6B parameters, supporting 40 language-locale combinations and sub-100ms latency, designed for voice agents.
Anthropic highlighted early signs of recursive self-improvement (RSI) in AI, with Claude models authoring 80%+ of merged code and engineers shipping 8x more code. Claude Opus 4 achieved 3x speedup on training scripts, while Mythos Preview reached ~52x speedup and provided better research suggestions than humans 64% of the time.