The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...

Google Research recently revealed TurboQuant, a compression algorithm that reduces the memory footprint of large language ...

Andrej Karpathy, the former Tesla AI director and OpenAI cofounder, is calling a recent Python package attack \"software ...

Supply chain attacks feel like they're becoming more and more common.

As hundreds of vendors descend on San Francisco for the RSAC 2026 Conference, the sheer volume of news can be overwhelming. To help you navigate the noise, SecurityWeek is providing a daily digest of ...

Model selection, infrastructure sizing, vertical fine-tuning and MCP server integration. All explained without the fluff. Why Run AI on Your Own Infrastructure? Let’s be honest: over the past two ...

QCon London A member of Anthropic's AI reliability engineering team spoke at QCon London on why Claude excels at finding issues but still makes a poor substitute for a site reliability engineer (SRE), ...

Java has endured radical transformations in the technology landscape and many threats to its prominence. What makes this technology so great, and what does the future hold for Java?

Key Takeaways LLM workflows are now essential for AI jobs in 2026, with employers expecting hands-on, practical skills.Rather than courses that intensively cove ...

Nvidia has a structured data enablement strategy. Nvidia provides libaries, software and hardware to index and search data ...

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...