Machine Learning

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Helping AI agents search to get the best results out of large language models

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, Software

Whether you’re a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you’ll find that artificial intelligence tools are becoming the assistants you didn’t know you needed. In particular, many professionals are tapping into the talents of semi-autonomous software systems called AI agents, which can call on AI

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AI companies want you to stop chatting with bots and start managing them

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI and work, AI assistants, AI benchmarks, AI coding, AI development tools, AI security, anthropic, Artificial Intelligence, Biz & IT, chatbots, Claude Code, Claude Opus, Claude Opus 4.6, code agents, Codex, Generative AI, GPT-5.3-Codex, Large Language Models, Machine Learning, OpenAI, Sam Altman

On Thursday, Anthropic and OpenAI shipped products built around the same idea: instead of chatting with a single AI assistant, users should be managing teams of AI agents that divide up work and run in parallel. The simultaneous releases are part of a gradual shift across the industry, from AI as a conversation partner to

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OpenAI is hoppin’ mad about Anthropic’s new Super Bowl TV ads

Advertising, ai, AI (Artificial Intelligence), AI assistants, AI behavior, AI Ethics, AI sycophancy, anthropic, Artificial Intelligence, Biz & IT, chatbots, ChatGPT, claude, Dario Amodei, greg brockman, Kate Rouch, Machine Learning, OpenAI, Sam Altman, Super Bowl

On Wednesday, OpenAI CEO Sam Altman and Chief Marketing Officer Kate Rouch complained on X after rival AI lab Anthropic released four commercials, two of which will run during the Super Bowl on Sunday, mocking the idea of including ads in AI chatbot conversations. Anthropic’s campaign seemingly touched a nerve at OpenAI just weeks after

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NVIDIA AI Release VibeTensor: An AI Generated Deep Learning Runtime Built End to End by Coding Agents Programmatically

agentic ai, ai, AI (Artificial Intelligence), AI Paper Summary, Artificial Intelligence, Editors Pick, Machine Learning, New Releases, Open Source, Python, Staff, Tech News, Technology, Uncategorized

NVIDIA has released VIBETENSOR, an open-source research system software stack for deep learning. VIBETENSOR is generated by LLM-powered coding agents under high-level human guidance. The system asks a concrete question: can coding agents generate a coherent deep learning runtime that spans Python and JavaScript APIs down to C++ runtime components and CUDA memory management and

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Should AI chatbots have ads? Anthropic says no.

ai, AI (Artificial Intelligence), AI advertising, AI assistants, AI business models, anthropic, Artificial Intelligence, Biz & IT, chatbots, ChatGPT, claude, Machine Learning, OpenAI, Sam Altman

On Wednesday, Anthropic announced that its AI chatbot, Claude, will remain free of advertisements, drawing a sharp line between itself and rival OpenAI, which began testing ads in a low-cost tier of ChatGPT last month. The announcement comes alongside a Super Bowl ad campaign that mocks AI assistants that interrupt personal conversations with product pitches.

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A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Machine Learning, Technology, Tutorials

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a behavior dataset from a constrained policy, and then train both a Behavior Cloning baseline and a Conservative Q-Learning agent using d3rlpy. By structuring the workflow around offline

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How to Build Advanced Quantum Algorithms Using Qrisp with Grover Search, Quantum Phase Estimation, and QAOA

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum data, construct entangled states, and then progressively implement Grover’s search with automatic uncomputation, Quantum Phase Estimation, and a full QAOA workflow for the MaxCut problem.

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The rise of Moltbook suggests viral AI prompts may be the next big security threat

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI alignment, AI Ethics, AI safety, AI security, AI self-preservation, Artificial Intelligence, Biz & IT, Cryptocurrency, Machine Learning, Moltbook, Moltbot, MoltBunker, OpenClaw, p2p, Peter Steinberger, prompt injection, prompt worm, Security

On November 2, 1988, graduate student Robert Morris released a self-replicating program into the early Internet. Within 24 hours, the Morris worm had infected roughly 10 percent of all connected computers, crashing systems at Harvard, Stanford, NASA, and Lawrence Livermore National Laboratory. The worm exploited security flaws in Unix systems that administrators knew existed but

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Expert-vetted reasoning datasets for reinforcement learning: why they lift model performance

ai, AI (Artificial Intelligence), ai training data, Artificial Intelligence, Machine Learning, Shaip Blogs

Reinforcement learning (RL) is great at learning what to do when the reward signal is clean and the environment is forgiving. But many real-world settings aren’t like that. They’re messy, high-stakes, and full of “almost right” decisions. That’s where expert-vetted reasoning datasets become a force multiplier: they teach models the why behind an action—not just

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98% Automation: Why Most Enterprise AI Projects Fail and What Actually Works

ai, AI (Artificial Intelligence), Artificial Intelligence, Enterprise AI, Generative AI, Machine Learning

A machine learning engineer at Cognizant, Raj Bhowmik, who achieved 98% automation of EDI mapping work, shares his approach to enabling GenAI systems to work with legacy infrastructure. Enterprise IT departments face a problem: their data is stored in incompatible repositories. SAP HANA runs alongside BigQuery and Azure SQL. EDI files come in dozens of

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