Tag: practical implications
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Simon Willison’s Weblog: Quoting Laurie Voss
Source URL: https://simonwillison.net/2025/Jan/21/laurie-voss/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Laurie Voss Feedly Summary: Is what you’re doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it’s probably going to be great at it. If you’re asking it to convert into a roughly equal…
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Hacker News: Don’t use Session – Round 2
Source URL: https://soatok.blog/2025/01/20/session-round-2/ Source: Hacker News Title: Don’t use Session – Round 2 Feedly Summary: Comments AI Summary and Description: Yes **Short Summary with Insight**: The text is a critical analysis of the security and cryptography protocol design of the Session messaging application compared to its peers. It discusses weaknesses in Session’s cryptographic practices, such…
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Hacker News: Rust: Investigating an Out of Memory Error
Source URL: https://www.qovery.com/blog/rust-investigating-a-strange-out-of-memory-error/ Source: Hacker News Title: Rust: Investigating an Out of Memory Error Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text describes a series of events relating to an out-of-memory (OOM) issue with the engine-gateway service at Qovery. This incident emphasizes the complexities surrounding memory management in cloud-native environments, especially when…
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Hacker News: Yek: Serialize your code repo (or part of it) to feed into any LLM
Source URL: https://github.com/bodo-run/yek Source: Hacker News Title: Yek: Serialize your code repo (or part of it) to feed into any LLM Feedly Summary: Comments AI Summary and Description: Yes **Short Summary with Insight:** The text presents a Rust-based tool called “yek” that automates the process of reading, chunking, and serializing text files within a repository…
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Simon Willison’s Weblog: Lessons From Red Teaming 100 Generative AI Products
Source URL: https://simonwillison.net/2025/Jan/18/lessons-from-red-teaming/ Source: Simon Willison’s Weblog Title: Lessons From Red Teaming 100 Generative AI Products Feedly Summary: Lessons From Red Teaming 100 Generative AI Products New paper from Microsoft describing their top eight lessons learned red teaming (deliberately seeking security vulnerabilities in) 100 different generative AI models and products over the past few years.…
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Hacker News: Scaling to users requires Synapse Pro
Source URL: https://element.io/blog/scaling-to-millions-of-users-requires-synapse-pro/ Source: Hacker News Title: Scaling to users requires Synapse Pro Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the differences between Synapse Pro and the community version of Synapse for Matrix deployments, emphasizing Synapse Pro’s architecture tailored for high-scale applications. It outlines significant performance improvements through the use…
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Chip Huyen: Common pitfalls when building generative AI applications
Source URL: https://huyenchip.com//2025/01/16/ai-engineering-pitfalls.html Source: Chip Huyen Title: Common pitfalls when building generative AI applications Feedly Summary: As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case…
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Simon Willison’s Weblog: Quoting gwern
Source URL: https://simonwillison.net/2025/Jan/16/gwern/#atom-everything Source: Simon Willison’s Weblog Title: Quoting gwern Feedly Summary: […] much of the point of a model like o1 is not to deploy it, but to generate training data for the next model. Every problem that an o1 solves is now a training data point for an o3 (eg. any o1 session…