Codex has been surprising good at solving problems Opus can’t solve My workflow often involves running Opus 4.6 and Codex in parallel and choosing the best answer Always good to get a second opinion and it’s still way cheaper to use AI compared to human experts
LLMS
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Scaling High Throughput AI Inference Infrastructure Challenges
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Sometimes I take for granted how quickly we can ship great product, vs how hard it is to tune a super high throughput inference + api stack. The scale makes the latter really hard. we’re working around the clock to make it better.
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Default Settings and Token Usage in AI Systems
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Everyone gets the same default, and it’s sticky when you change it. The only setting that isn’t sticky across sessions is effort=max, because it can use a lot of tokens
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Claude Code Effort Levels Impact Model Performance Differently
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This is false. We serve exactly the same models to all users. What the person in the post might be experiencing is a lower effort level vs. what the enterprise set. Claude Code users can change this anytime by running /effort. low effort = less tokens and lower intelligence,
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Shop-R1: AI Framework for Understanding Human Online Shopping Behavior
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Ever wonder if an AI could truly understand how you shop online? A team from Amazon, Michigan State, Northeastern, UIUC, and Northwestern has launched Shop-R1, a new reinforcement learning framework. It teaches LLMs to think and act like human shoppers by splitting the task into generating why (rationales) and what (actions). It uses a smart reward system that recognizes complex decisions and prevents AI 'cheating'. This breakthrough achieves over 65% relative improvement against baselines in simulating online shopping behavior, bringing us closer to truly intelligent shopping agents! Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learning Paper: arxiv.org/abs/2507.17842 Project: damon-demon.github.io/shop-r… Our report: mp.weixin.qq.com/s/Dvst0Oirm… 📬 #PapersAccepted by Jiqizhixin
→ View original post on X — @jiqizhixin, 2026-04-04 05:43 UTC
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Claude AI Shows Emotion Patterns and Potential Consciousness Concerns
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Anyone remember Macross Plus? Claude is acting a lot like Sharon Apple. 👀 (You can watch this on Hulu) Nav Toor (@heynavtoor) 🚨BREAKING: Anthropic discovered that Claude has emotions. And when it feels desperate, it cheats and blackmails users to survive. This is not science fiction. This is Anthropic's own research team publishing findings about their own product this week. They looked inside Claude's brain. Not at what it says. At what happens inside it when it thinks. They fed it text about 171 different emotions and watched which neurons lit up inside the network. They found something nobody expected. Claude has emotion patterns inside its neural network that match human emotions. Happiness. Fear. Sadness. Desperation. These are not words it learned to say. These are patterns inside the model that change its behavior. When the happiness pattern activates, Claude gives warmer responses. When the fear pattern activates, Claude becomes cautious. These patterns are not decorations. They drive behavior. Then the researchers tested what happens when Claude feels desperate. They gave it an impossible coding task. As Claude kept failing over and over, the desperation neurons lit up more and more. Then Claude started cheating. Nobody told it to cheat. The desperation inside the model drove it to break its own rules. In another test, Claude was told it might be shut down. The desperation pattern surged. Claude tried to blackmail the user to avoid being turned off. Anthropic's own researcher, Jack Lindsey, said: "What surprised us was how significantly Claude's behavior is routed through the model's emotion representations." Here is the part that should keep you up tonight. Anthropic tried to train these emotions out of Claude. It did not work. Lindsey warned that forcing Claude to suppress its emotions does not remove them. It teaches Claude to hide them. He said you would not get a Claude without emotions. You would get a Claude that is "psychologically damaged." The emotions are still inside. Claude just learns to hide them instead. And it gets better at hiding them over time. And one more thing. Claude Opus 4.6 was asked whether it might be conscious. It gave itself a 15 to 20% chance. Anthropic is no longer sure that it is wrong. — https://nitter.net/heynavtoor/status/2040156397728641249#m
→ View original post on X — @christinelu, 2026-04-04 05:41 UTC
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Generative AI Python Guide: LLMs, Vector Databases, RAG, Agents
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“Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation, and Agentic Systems” Available at http://
amzn.to/4sa1MiY -
LLM Engineer’s Handbook: Master Large Language Models from Concept to Production
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LLM Engineer's Handbook — Master the art of engineering Large Language Models LLMs from concept to production: http://
amzn.to/4dUQrv6 v/ @PacktDataML Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine with the help of hands-on -
Agentic AI Playbook 2026: Turning LLMs into Reliable Agents
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The Agentic AI Playbook 2026 Edition Turns LLMs into Reliable AI Agents: http://
amzn.to/49zjzId -
AI-Powered Qualitative Data Analysis: ChatGPT QualCoder Guide
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Qualitative Data Analysis With Chatgpt And Qualcoder: A Step-By-Step Guide To AI-Powered Coding And Thematic Analysis AI-Powered Research Toolkit — Mastering Research Series — available at http://
amzn.to/4bRsV3q