Browsing: AI

Google AI Ultra subscribers in the U.S. can try out Project Genie, an experimental research prototype that lets you create and explore worlds.

This article explores five infrastructure patterns that make Docker a powerful foundation for building robust, autonomous AI applications.

Perplexity introduces ‘Perplexity Computer,’ an advanced agentic tool available to its highest-tier subscribers. This cloud-based system unifies 19 AI models to independently execute complex workflows, from data collection and analysis to creating finished websites. The company is shifting its focus towards enterprise users and deep research, emphasizing a multi-model approach for optimal query responses.

GPT-5.2 represents a highly capable model for scientific and mathematical work, demonstrating significant advancements in reasoning and problem-solving. This article explores its enhanced performance and a case study where it resolved an open research problem in statistical learning theory.

A conversation with AI researcher Sebastian Wallkötter reveals insights on standardization, security challenges, and the fundamental question facing enterprise artificial intelligence adoption.

Want a smaller, faster, more secure agent stack than OpenClaw?

Experts have made progress in LLM security. But some doubt AI assistants are ready for prime time.

7 Python tricks that may help make the most of the standalone XGBoost library, particularly in terms of seeking more accurate predictive models.

PostgreSQL has proven capable of handling immense read-heavy workloads, supporting millions of queries per second for 800 million users across ChatGPT and OpenAI’s API. This article details the rigorous optimizations and engineering efforts undertaken to scale a single-primary PostgreSQL architecture with nearly 50 global read replicas, addressing challenges like write amplification, query inefficiencies, and single points of failure, while maintaining high availability and low latency.

Sir Demis Hassabis and Dr. John Jumper have been awarded the 2024 Nobel Prize in Chemistry for their pivotal work on AlphaFold, an AI system that accurately predicts protein structures, significantly advancing scientific research.