Peter Norvig

Matt Swayne writes about a Quantum Breakthrough: Qubits Can Be Cloned for Backup: Researchers at the University of Waterloo have bypassed the "no-cloning" problem, paving the way for the first secure quantum cloud storage. https://lnkd.in/egRyEgfA

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The Model Context Protocol (MCP) has been donated to the Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation. An important step towards neutral, vendor-independent open standards 👏👏👏 https://lnkd.in/eVrdz5fb

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The Emerging World of Multi-Turn Interactions in Large Language Models, NeurIPS 2025: https://lnkd.in/gnQig_rJ Artificial intelligence is entering a new stage—one where conversations with machines unfold not in single questions and answers, but in long chains of exchanges. These extended interactions, known as multi-turn conversations, are becoming central to how we use Large Language Models (LLMs) today. What Are Multi-Turn Interactions? A “multi-turn” interaction simply means a conversation or task that happens over several steps, each one building on the previous. Instead of a one-off query, the user and AI move through a sequence—much like solving an equation piece by piece, where each line depends on the one before it. This matters because real-world tasks are rarely completed in a single command. Planning a research project, guiding a piece of writing, troubleshooting software, or coordinating actions across tools all require continuity and memory. Why They Matter Now Today’s LLMs are far more capable of holding these extended exchanges than earlier systems. They can: keep track of previous steps, adapt to evolving goals, make decisions in complex environments, and manage long, dynamic conversations. As AI takes on roles that resemble digital assistants, collaborators, or even agents acting inside software interfaces, these multi-step capabilities become essential. Key Challenges Ahead Researchers are now focusing on several big questions: 1. Teaching AI to act over many steps How can we train models to operate in multi-step environments—like navigating a computer interface or using external tools—when feedback is only given occasionally? 2. Staying aligned with human goals During long conversations, an AI may drift or misinterpret intentions. Researchers want models that stay connected to what users truly need across many turns. 3. Building healthier human–AI relationships As interactions stretch over hours or days, how can AI adapt without becoming unsafe, biased, or overly confident? 4. Measuring long-term performance We need better ways to evaluate whether an AI can stay consistent, think ahead, and carry out a sequence of actions reliably. A Field Taking Shape Workshops focused on multi-turn interactions—such as the one linked below—are helping define this research direction. They provide spaces for scientists, engineers, and designers to discuss methods, share experiments, and plan the next steps for building AI systems that can truly collaborate across time.

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Do You Really Understand High Dimension? = I do not understand high dimension ... hence I read the following paper from Marc El Khoury: Counterintuitive Properties of High Dimensional Space lnkd.in/g4NTh5We This post accompanies a talk given to high school students through Splash at Berkeley. Thus intuition is prioritized over mathematical rigor, language is abused, and details are laboriously spelled out. If you're interested in more rigorous treatments of the presented material, please feel free to contact him. Here are the highlights of this insightful paper for WANNABE MATHEMATICIANS: * Escaping Spheres In dimensions two and three, the sphere is strictly inside the cube, as we've seen in the figures above. However in four dimensions something very interesting happens. The radius of the inner sphere is exactly , which is just large enough for the inner sphere to touch the sides of the cube! In five dimensions, the radius of the inner sphere is , and the sphere starts poking outside of the cube! By ten dimensions, the radius is and the sphere is poking very far outside of the cube! * Volume in High Dimensions The volume of the unit -sphere goes to 0 as grows! A high dimensional unit sphere encloses almost no volume! The volume increases from dimensions one to five, but begins decreasing rapidly toward 0 after dimension six. * Concentration of Measure As the dimension increases the coordinates become increasingly concentrated around 0. Most of the high dimensional space is EMPTY!! * Kissing Numbers Are you a Good Kisser?? It seems in dimension 24, there are at least 196560 good kissers! PS: I have advised Neel Banerjee to do more Technical Posts like this ... instead of propagating propaganda from the dreaded Agile Industrial Complex. This is the reason our book project failed as predicted by Peter Wendorff who authored the following book Politics in Software Development: Navigating Stakeholder Power and Conflict in Organizations Politics in Software Development consists of three main parts. Author Peter Wendorff begins by defining key concepts in organizational politics. He then moves on to software development processes and investigates how their design reflects stakeholder interests. In the final part, he highlights the role of political skill in software development and provides an overview of tactics that stakeholders frequently use. There is widespread competition within organizations for rewards, recognition, status, and power. It gives rise to political behavior of stakeholders, which is generally seen as a problem. This negative view of organizational politics tends to overlook its positive functions. For example, it can alsobe thought of as an arena where stakeholders with conflicting goals can argue, persuade, negotiate, bargain, and cooperate to address conflicts.

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