I'm interested to hear that some folks can find personal conversation with an AI deeply interesting. I don't think I've ever had that experience myself. I've certainly found some conversations *useful* (e.g help with code; explain something; …), but not deeply interesting.
GENERATIVE AI
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Grok AI System Requires Urgent Bug Fix
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This is not good. Grok is incredible otherwise, but they need to fix this. ASAP.
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First Non-Anthropic Model for Agentic Loops
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I didn’t word it properly, I meant it's the first non-Anthropic model I feel I can use for agentic loops.
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Kimi K2 excels at tool calling and agentic loops production-ready
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Kimi K2 is so good at tool calling and agentic loops, can call multiple tools in parallel and reliably, and knows "when to stop", which is another important property.
— Pietro Schirano (@skirano) 13 juillet 2025
It's the first model I feel comfortable using in production since Claude 3.5 Sonnet. pic.twitter.com/TcEkPlBMukKimi K2 is so good at tool calling and agentic loops, can call multiple tools in parallel and reliably, and knows "when to stop", which is another important property. It's the first model I feel comfortable using in production since Claude 3.5 Sonnet.
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Training on raw internet data without filtering risks
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They just unconditionally trained on the entire raw data of the internet, there was no cleaning or selection at all. You don’t fix this with prompting, it may require an entire new run.
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Build a GraphRAG Chatbot with SurrealDB and LangChain
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GraphRAG Chatbot Tutorial Build a powerful GenAI chatbot combining vector search and graph knowledge with SurrealDB and LangChain. This health symptoms demo shows how GraphRAG delivers more contextual AI responses. Learn to build your own GraphRAG chatbot
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Memory Feature Enables Second Nature Learning in ChatGPT
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“In English, we say something becomes "second nature" via this process, and we're missing learning paradigms like this. The new Memory feature is maybe a primordial version of this in ChatGPT”
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AI Hallucinations Scale: Expertise Required for Detection
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This is an important point – expertise & attention are required to figure out when an AI hallucinates, and the amount of effort required is increasing over time. But, models generally hallucinate less as they scale (with some exceptions), so net effect is complex, see medicine