AI Infrastructure

OpenAI and Broadcom unveil LLM-optimized inference chip Jalapeño

OpenAI and Broadcom unveiled Jalapeño, a custom LLM inference chip designed from scratch with substantially better performance per watt than current accelerators. Taped out in nine months using OpenAI's own models to accelerate chip design, it will deploy at gigawatt scale starting in 2026 as part of a multi-generation platform.

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NVIDIA NeMo AutoModel: 3.7x Faster MoE Fine-Tuning with One Import Change

NVIDIA NeMo AutoModel delivers 3.4-3.7x higher training throughput and 29-32% less GPU memory for MoE fine-tuning through a single import line change. By adding Expert Parallelism as a dedicated dimension, DeepEP fused dispatch, and TransformerEngine kernels on top of Transformers v5, it makes 550B-scale full fine-tuning feasible and produces standard HF checkpoints for downstream deployment.

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Query logs and traces with SQL in Google Cloud Observability Analytics

Google Cloud unifies logs and traces under a single BigQuery-backed SQL analytics surface called Observability Analytics, letting you JOIN span and log data for aggregate queries across millions of events — especially useful for debugging AI agent tool calls, finding flaky microservices, and correlating latency with business metrics.

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Cross-Origin Storage API: Ending duplicate downloads for browser AI

If you've ever watched your browser re-download 177 MB of Whisper model weights just because a second site lives on a different origin, this article explains exactly why that happens—and how the proposed Cross-Origin Storage API fixes it using cryptographic hashes instead of URLs. Transformers.js already supports it experimentally, and you can test the whole thing today with a Chrome extension.

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Build real agentic apps using CUGA: lightweight harness, two dozen examples

CUGA (Configurable Generalist Agent) is an open-source harness from IBM that strips away the repetitive plumbing of agentic apps, letting you focus on tools and prompts. With two dozen single-file examples and built-in governance, it shows how to build agents that scale from a laptop to a governed production deployment without rewriting.

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