overthinking. all you need is codex /review π
LLMS
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Analysis of o1 model performance and prose quality
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The regression from o1 days is something definitely worth the note. Capability went up, prose discipline went down.
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Comparing OpenAI’s Research and Consumer Product Engineering Gap
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This is probably true for research talent specifically. The product and engineering gap with OpenAI on consumer side is a different story.
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Upcoming Gemini Omni AI Video Model Spotted in Mobile App
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GOOGLE I/O : New evidence of the upcoming Gemini Omni vide model has been spotted on the Gemini mobile app. A video sample below > "Meet our new video model. Remix your videos, edit directly in chat, try a template, and more." > Based on the description, we might be
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Building an AI-Powered File Reader using RAG and LLMs
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RAG with LLM: Creating an AI-Powered File Reader! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
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The Tradeoff Between Traditional Coding and AI-Generated Code
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Stack Overflow gave you an answer you could read and understand. AI gives you code you can run without understanding it. Different tradeoff.
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Limitations of LLM-based content filtering
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A filter that works only when the model reads the title is not really a filter.
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Using Thread Automations for Persistent AI Agent Context
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thread automations are slept on they let Codex wake up inside the same thread on a schedule so instead of restarting context every time, it can keep checking, reviewing, polling, or continuing exactly where it left off tiny feature. very useful.
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Comparing AI coding model performance in practical tasks
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Two days of failure on a $200 plan followed by a one-shot Codex solution on a $100 plan is a brutal side by side.
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Discussion on AI Model Autonomy and Reliability Issues
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The autonomy issues with 4.7 probably have something to do with this. Hard to trust a model that goes off script.