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In its latest bid to boost semiconductor production in the U.S., the Trump administration is reportedly considering a ratio-based approach that would penalize domestic manufacturers with tariffs if they don’t produce enough chips. The administration is weighing a policy that would mandate U.S. semiconductor companies to manufacture the same number of chips in the U.S. as their customers import from overseas manufacturers, the Wall Street Journal …

[Submitted on 31 Oct 2024 (v1), last revised 25 Sep 2025 (this version, v2)] View a PDF of the paper titled Understanding Optimization in Deep Learning with Central Flows, by Jeremy M. Cohen and Alex Damian and Ameet Talwalkar and J. Zico Kolter and Jason D. Lee View PDF Abstract:Traditional theories of optimization cannot describe the dynamics of optimization in …

Never miss a new edition of The Variable, our weekly newsletter featuring a top-notch selection of editors’ picks, deep dives, community news, and more. AI-powered tools tend to generate extreme reactions: on one side we have the “It’s magic!” and “best thing ever!” crowd. On the other, we find the “we’re doomed!” camp. These aren’t static or monolithic groups, of course. …

[Submitted on 22 Dec 2022 (v1), last revised 24 Sep 2025 (this version, v5)] View a PDF of the paper titled Infrared Image Super-Resolution: Systematic Review, and Future Trends, by Yongsong Huang and 3 other authors View PDF HTML (experimental) Abstract:Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks. Investigating infrared (IR) image …

[Submitted on 4 Apr 2025 (v1), last revised 24 Sep 2025 (this version, v2)] View a PDF of the paper titled DP-LET: An Efficient Spatio-Temporal Network Traffic Prediction Framework, by Xintong Wang and 2 other authors View PDF HTML (experimental) Abstract:Accurately predicting spatio-temporal network traffic is essential for dynamically managing computing resources in modern communication systems and minimizing energy consumption. …

[Submitted on 29 Jul 2025 (v1), last revised 22 Sep 2025 (this version, v2)] View a PDF of the paper titled Measuring Sample Quality with Copula Discrepancies, by Agnideep Aich and 2 other authors View PDF HTML (experimental) Abstract:The scalable Markov chain Monte Carlo (MCMC) algorithms that underpin modern Bayesian machine learning, such as Stochastic Gradient Langevin Dynamics (SGLD), sacrifice …

Google is turning its vast public data trove into a goldmine for AI with the debut of the Data Commons Model Context Protocol (MCP) Server — enabling developers, data scientists, and AI agents to access real-world statistics using natural language and better train AI systems. Launched in 2018, Google’s Data Commons organizes public datasets from a range of sources, including …

[Submitted on 15 Sep 2025 (v1), last revised 22 Sep 2025 (this version, v2)] View a PDF of the paper titled MALLM: Multi-Agent Large Language Models Framework, by Jonas Becker and 5 other authors View PDF HTML (experimental) Abstract:Multi-agent debate (MAD) has demonstrated the ability to augment collective intelligence by scaling test-time compute and leveraging expertise. Current frameworks for multi-agent …

before we dive in: I am a developer at Google Cloud. Thoughts and opinions expressed here are entirely my own. The complete source code for this article, including future updates, is available in this notebook under the Apache 2.0 license. All new images in this article were generated with Gemini Nano Banana using the proof-of-concept generation pipeline explored here. You …

problem when working with LLMs. They are a problem for two main reasons. The first apparent reason is that a hallucination naturally causes the user to receive an incorrect response. The second, arguably worse reason, is that hallucinations lower the users’ trust in the system. Without the user believing in your question answering system, it will be difficult to keep …