March 2026

Three-layer neural networks are known to form singular learning models, and their Bayesian asymptotic behavior is governed by the learning coefficient, or real log canonical threshold. Although this quantity has been clarified for regular models and for some special singular models, broadly applicable methods for evaluating it in neural networks remain limited. Recently, a formula for the local learning coefficient of semiregular models was proposed, yielding an upper bound on the learning coefficient. However, this formula applies only […]

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We propose TerraFlow, a novel approach to multimodal, multitemporal learning for Earth observation. TerraFlow builds on temporal training objectives that enable sequence-aware learning across space, time, and modality, while remaining robust to the variable-length inputs commonly encountered in real-world Earth observation data. Our experiments demonstrate superiority of TerraFlow over state-of-the-art foundation models for Earth observation across all temporal tasks of the GEO-Bench-2 benchmark. We additionally demonstrate that TerraFlow is able to make initial steps towards deep-learning based risk […]

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A key challenge in enzyme annotation is identifying the biochemical reactions catalyzed by proteins. Most existing methods rely on Enzyme Commission (EC) numbers as intermediaries: they first predict an EC number and then retrieve the associated reactions. This indirect strategy introduces ambiguity due to the complex many-to-many mappings among proteins, EC numbers, and reactions, and is further complicated by frequent updates to EC numbers and inconsistencies across databases. To address these challenges, we present RXNRECer, a transformer-based ensemble […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The 5 Best Suits From Marvel’s Spider-Man By @joseh [ 4 Min read ] The Vintage Comic Book Suit, the Spider Armor – MK III, and the Upgraded Suit are some of the best suits in Marvel’s Spider-Man. Read More. AI GTM Strategy: Why […]

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A small Houston, Texas business just did something no mining company, no venture-backed startup, and no publicly traded hardware manufacturer has done: they brought a fully open-source touchscreen Bitcoin miner to market that outperforms every competitor in its class by a factor of two. The Bitaxe Turbo Touch. Dual BM1370 ASIC chips. 2.15 TH/s at stock. Over 3.06 TH/s overclocked. Eight dynamic displays. Every line of firmware, from the ASIC driver to the touchscreen renderer, is open source […]

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Hey Hackers! This article is the second in a two-part series on the engineering reality of Physical AI. In Part 1, titled The Next Great Engineering Frontier: The Hidden Complexity of Physical AI, I discussed how the chaotic physical world, the high stakes of failure, and the Sim-to-Real gap make using embodied AI in robotics a harder problem than generating text, images, or video via an AI chatbot. However, mastering the physics is only half the battle. The […]

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You are polishing an algorithm at 2 a.m. You paste your proprietary sorting logic into ChatGPT or Claude and ask for a tighter refactor and a clean specification. It feels completely private and highly efficient. But from an intellectual property perspective, you just triggered a Section 102 prior art event that likely killed your novelty abroad. Founders and engineers increasingly treat cloud AI like a local text editor. This is a massive operational failure. Cloud AI is not […]

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I sat down to write the pgvector section of this post—the HNSW index DDL, the reranker batching, the metadata filter shapes—and realized I kept reaching for the wrong file. The query I was proud of wasn’t the vector search. It was dedupeRagChunks. That’s the moment this post changed shape. I’d been treating retrieval as a storage problem (pick the right index, tune the right parameters) when the engineering that actually broke and got fixed was the pipeline above […]

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In Vol. 5 of our Securing GenAI Series, we introduced the concept of agentic workflows and touched on their expanded attack surface. At that time, agents were an emerging architectural pattern — powerful, interesting, but largely confined to experimental deployments. Today’s reality is different. Agentic AI has moved from research labs and proof-of-concepts into production systems. Enterprises are now deploying AI agents to automate customer support, execute database queries, manage cloud infrastructure, and orchestrate complex multi-system workflows. This shift from […]

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