Tag: training data
-
Hacker News: Philosophy Eats AI
Source URL: https://sloanreview.mit.edu/article/philosophy-eats-ai/ Source: Hacker News Title: Philosophy Eats AI Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the evolution of software and AI, emphasizing the need for a philosophical approach in leveraging AI technologies for strategic advantage. It outlines how philosophy can influence the development, implementation, and ethical considerations of…
-
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…
-
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…
-
Hacker News: Nepenthes is a tarpit to catch AI web crawlers
Source URL: https://zadzmo.org/code/nepenthes/ Source: Hacker News Title: Nepenthes is a tarpit to catch AI web crawlers Feedly Summary: Comments AI Summary and Description: Yes Summary: The text describes “Nepenthes,” a tarpit software devised to trap web crawlers, particularly those scraping data for large language models (LLMs). It offers unique functionalities and deployment setups, with explicit…
-
Slashdot: OpenAI’s AI Reasoning Model ‘Thinks’ In Chinese Sometimes, No One Really Knows Why
Source URL: https://slashdot.org/story/25/01/14/239246/openais-ai-reasoning-model-thinks-in-chinese-sometimes-no-one-really-knows-why?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: OpenAI’s AI Reasoning Model ‘Thinks’ In Chinese Sometimes, No One Really Knows Why Feedly Summary: AI Summary and Description: Yes Summary: The behavior exhibited by OpenAI’s reasoning AI model, o1, which seemingly “thinks” in multiple languages regardless of the input language, has raised questions within the AI community. Experts…
-
Docker: Meet Gordon: An AI Agent for Docker
Source URL: https://www.docker.com/blog/meet-gordon-an-ai-agent-for-docker/ Source: Docker Title: Meet Gordon: An AI Agent for Docker Feedly Summary: We share our experiments creating a Docker AI Agent, named Gordon, which can help new users learn about our tools and products and help power users get things done faster. AI Summary and Description: Yes Summary: The text discusses a…
-
CSA: How Can Businesses Mitigate AI "Lying" Risks Effectively?
Source URL: https://www.schellman.com/blog/cybersecurity/llms-and-how-to-address-ai-lying Source: CSA Title: How Can Businesses Mitigate AI "Lying" Risks Effectively? Feedly Summary: AI Summary and Description: Yes Summary: The text addresses the accuracy of outputs generated by large language models (LLMs) in AI systems, emphasizing the risk of AI “hallucinations” and the importance of robust data management to mitigate these concerns.…
-
Hacker News: How outdated information hides in LLM token generation probabilities
Source URL: https://blog.anj.ai/2025/01/llm-token-generation-probabilities.html Source: Hacker News Title: How outdated information hides in LLM token generation probabilities Feedly Summary: Comments AI Summary and Description: Yes ### Summary: The text provides a deep examination of how large language models (LLMs), such as ChatGPT, process and generate responses based on conflicting and outdated information sourced from the internet.…