Tag: llm
Ben and Ryan discuss how LLMs are changing the industry and practice of software engineering, a notorious Crash Bandicoot bug, and communication via series of tubes.
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Ben, Ryan, and Eira convene to discuss return-to-office mandates, what’s surprising about employee attrition in 2023, and how technology can preserve digital records of cultural heritage sites before they’re lost for good.
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We chat with IBM about how their watsonx platform makes generative AI more than just a fun toy.
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The core challenge posed by generative AI right now is that unlike conventional applications, LLMs have no “delete” button.
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Retrieval augmented generation (RAG) is a strategy that helps address both LLM hallucinations and out-of-date training data.
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Ben and Ryan settle in for a wide-ranging discussion about whether large language models know anything, whether language ability is unique to humans, and what the end of the Hollywood writers’ strike says about the future of AI-generated content.
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A Qualcomm expert breaks down some of the tools and techniques they use to fit GenAI models on a smartphone.
The post Fitting AI models in your pocket with quantization appeared first on Stack Overflow Blog.
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Ben and senior software engineer Kyle Mitofsky are joined by two people who worked on the launch of Overflow AI: director of data science and data platform Michael Foree and senior software developer Alex Warren. They talk about how and why Stack Overflow launched semantic search, how to ensure a knowledge base is trustworthy, and why user prompts can make LLMs vulnerable to exploits.
The post Semantic search without the napalm grandma exploit (Ep....
Knowledge management and AI, VPN security, and an SVG deep dive.
The post The Overflow #186: Do large language models know what they’re talking about? appeared first on Stack Overflow Blog.
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Large language models seem to possess the ability to reason intelligently, but does that mean they actually know things?
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