Browsing: Generative AI

Small language models can serve as a more scalable, practical and efficient alternative for medical applications compared to large language models. Here we discuss the strengths and limitations, challenges and future directions of small language models in healthcare implementation, highlighting their potential to enable broader real-world adoption across diverse clinical settings.

, I have written quite a lot about RAG, starting with the Hitchhiker’s Guide to RAG with ChatGPT API and LangChain, and then exploring various topics related to RAG and AI, like chunking, hybrid search, reranking, contextual retrieval, and a three-part series on evaluating retrieval quality. In other words, we have covered a lot of…

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs. Adam Zewe|MIT News Publication Date: July 13, 2026

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The AI firm Anthropic has developed a technique that has given it the clearest glimpse yet at what’s really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving.

The role will be replaced by an executive in charge of both research and safety teams.

System prompts form the foundation of generative AI applications. A system prompt is a collection of instructions and operational context provided to a large language model (LLM) that shapes how the model behaves and interacts with users and tools. System prompts often contain proprietary information, including role definitions, behavioral guidelines, tool descriptions and usage instructions,…

At a time when AI backlash and data center protests are making headlines, Anthropic’s Claude is rolling out a new feature that subtly makes the case for why you should keep using it.

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