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The Demonstration Veritasium’s Derek Muller published a video this week showing cybersecurity researchers draining $10,000 from MKBHD’s fully locked iPhone using off-the-shelf NFC hardware, a laptop, and a Python script. No passcode entered. No Face ID prompt. No unlock of any kind. The phone sat on a reader, the screen stayed dark, and $10,000 moved. https://www.youtube.com/watch?v=PPJ6NJkmDAo&embedable=true The researchers — Professors Ioana Boureanu from the University of Surrey and Tom Chothia from the University of Birmingham — walked through […]

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The gap between AI insiders and everyone else is widening, and the spending, suspicion, and even new vocabulary are starting to show it. While OpenAI is busy buying up everything from finance apps to talk shows, a certain shoe company just rebranded as an AI infrastructure play, and Anthropic unveiled a model it says is too powerful to release publicly …but apparently not too […]

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Adapter-based methods have become a cost-effective approach to continual learning (CL) for Large Language Models (LLMs), by sequentially learning a low-rank update matrix for each task. To mitigate catastrophic forgetting, state-of-the-art approaches impose constraints on new adapters with respect to the previous ones, by targeting either subspace or coordinate-wise interference. In this paper, we propose JumpLoRA, a novel framework to adaptively induce sparsity in the Low-Rank Adaptation (LoRA) blocks through the use of JumpReLU gating. The method achieves […]

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Adapter-based methods have become a cost-effective approach to continual learning (CL) for Large Language Models (LLMs), by sequentially learning a low-rank update matrix for each task. To mitigate catastrophic forgetting, state-of-the-art approaches impose constraints on new adapters with respect to the previous ones, by targeting either subspace or coordinate-wise interference. In this paper, we propose JumpLoRA, a novel framework to adaptively induce sparsity in the Low-Rank Adaptation (LoRA) blocks through the use of JumpReLU gating. The method achieves […]

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Key Highlights: The updates to Codex mark a shift in how AI tools are built and used. OpenAI doesn’t see Codex as just a coding assistant anymore, it’s turning it into a system that works across your whole computer. Recent reports say the upgraded Codex can run desktop programs, automate workflows, and keep multiple agents working in the background, so it’s more like a workplace automation engine than a single-purpose helper. Anthropic’s Claude Code jumped into the market […]

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The reported deal between OpenAI and Cerebras Systems marks a clear shift in how top AI companies are thinking about growth. They’re not just focused on making smarter models anymore; the real competition is now in the infrastructure that powers them. With demand for AI services booming around the world, having reliable and scalable compute is now a top priority. This new deal seems to build off an earlier partnership, and by tying sourcing to potential ownership, OpenAI […]

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Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and biological behavior. This survey traces four complementary paradigms, including Quantum, Descriptor Machine Learning, Geometric Deep Learning, and Foundation Models, and outlines a unified taxonomy linking molecular representations, model architectures, and interdisciplinary applications. Benchmark analyses integrate evidence from both widely used datasets and datasets reflecting industry perspectives, encompassing quantum, physicochemical, physiological, and biophysical domains. The survey examines current standards in data curation, […]

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Welcome to HackerNoon’s Projects of the Week, where we spotlight standout projects from the Proof of Usefulness Hackathon, HackerNoon’s competition designed to measure what actually matters: real utility over hype. n n Each week, we’ll highlight projects that demonstrate clear usefulness, technical execution, and real-world impact – backed by data, not buzzwords. This week, we’re excited to share three projects that have proven their utility by solving concrete problems for real users: ExpenseHut POS, FalconAI, and Risk Mirror. :::tip […]

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Edge deployment of large language models (LLMs) increasingly relies on libraries of lightweight LoRA adapters, yet GPU/DRAM can keep only a small resident subset at a time. Serving a request through a non-resident adapter requires paging its weights from storage, incurring measurable latency. This creates a two-timescale online control problem: on a slow timescale, the system selects which adapters remain resident in fast memory, while on a fast timescale it routes each request to an adapter whose context-dependent […]

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Various training algorithms in RL either make use of an occasional “explore” random action or collect initial random episodes to bootstrap the training. However a general issue with random sampling – specially for delta-time step physics simulations – is that the actions average over a middle point within the action space. This makes the agent’s “random” trajectory wiggling close to one applying the average over the action space. e.g. in CarRacing it just incoherently slams steering, throttle and […]

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