The Archive

Gemini app integrates Lyria 3 music generation model, enabling 30-second track creation from text or image prompts.

As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost... As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost requirements. Running models with tens of billions of parameters in production, especially for conversational or voice-based AI agents, demands high throughput, low latency, and predictable service-level performance. Source

OpenAI and Paradigm introduce EVMbench, a benchmark for evaluating AI agents on smart contract vulnerability detection and exploitation.

Anthropic and Rwanda government sign MOU to deploy AI in health and education sectors.

Anthropic releases Claude Sonnet 4.6 with frontier performance in coding, agents, and professional applications.

Enterprise data is inherently complex: real-world documents are multimodal, spanning text, tables, charts and graphs, images, diagrams, scanned pages, forms,... Enterprise data is inherently complex: real-world documents are multimodal, spanning text, tables, charts and graphs, images, diagrams, scanned pages, forms, and embedded metadata. Financial reports carry critical insights in tables, engineering manuals rely on diagrams, and legal documents often include annotated or scanned content. Retrieval-augmented generation (RAG) was created to ground… Source

Google DeepMind launches National Partnerships for AI initiative in India to scale AI applications in science and education.

Anthropic partners with Infosys to develop AI agents for telecommunications and regulated industries.

Import AI 445 examines superintelligence timeline predictions, frontier math theorem solving, and new ML research benchmark.

Anthropic opens Bengaluru office and announces partnerships across India to expand regional presence.

Anthropic partners with CodePath to integrate Claude into US's largest collegiate computer science program.

Chris Liddell appointed to Anthropic's board of directors.

GPT-5.2 proposes novel gluon amplitude formula in theoretical physics, later formally proved by OpenAI and academic collaborators.

OpenAI introduces Lockdown Mode and Elevated Risk labels in ChatGPT to defend against prompt injection and data exfiltration attacks.

OpenAI releases GABRIEL, an open-source toolkit using GPT to convert qualitative text and images into quantitative data for social science research.

OpenAI describes real-time access infrastructure combining rate limits, usage tracking, and credits for Sora and Codex.

Cohere and SAP expand partnership to deploy sovereign AI solutions for European enterprises through SAP Sovereign Cloud.

Anthropic raises $30B Series G at $380B valuation; $14B run-rate revenue growing 10x annually.

Gemini 3 Deep Think updated for specialized reasoning in science, research, and engineering problem-solving.

Anthropic donates $20 million to Public First Action.

OpenAI releases GPT-5.3-Codex-Spark, a real-time coding model with 15x faster generation and 128k context, in research preview.

Anthropic covers electricity cost increases from its data centers.

OpenAI technical staff discuss engineering patterns for building agent systems with Codex as foundation model.

Building robust, intelligent robots requires testing them in complex environments. However, gathering data in the physical world is expensive, slow, and often... Building robust, intelligent robots requires testing them in complex environments. However, gathering data in the physical world is expensive, slow, and often dangerous. It is nearly impossible to safely train for real-world critical risks, such as high-speed collisions or hardware failures. Worse, real-world data is usually biased toward “normal” conditions, leaving robots unprepared for the… Source

Scientists and engineers who design and build unique scientific research facilities face similar challenges. These include managing massive data rates that... Scientists and engineers who design and build unique scientific research facilities face similar challenges. These include managing massive data rates that exceed current computational infrastructure capacity to extract scientific insights and driving the experiments in real time. These challenges are obstacles to maximizing the impact of scientific discoveries and significantly slow the pace of… Source

NVIDIA TensorRT LLM enables developers to build high-performance inference engines for large language models (LLMs), but deploying a new architecture... NVIDIA TensorRT LLM enables developers to build high-performance inference engines for large language models (LLMs), but deploying a new architecture traditionally requires significant manual effort. To address this challenge, today we are announcing the availability of AutoDeploy as a beta feature in TensorRT LLM. AutoDeploy compiles off-the-shelf PyTorch models into inference-optimized… Source