AI
Large language models can ace math benchmarks yet still stumble on simple number sense because they treat numbers like ordinary words. This work fixes that by giving models a value-aware way to read numbers. How it works: whenever a number appears, the input is augmented with a tiny prefix token
AI
What if AI could think with pictures? Omni-R1 is a new multimodal AI that doesn’t just “talk through” problems—it draws its intermediate steps. Instead of relying on one fixed reasoning style, it unifies many skills (like zooming into regions, pointing to objects, or marking paths) by generating small
AI
Big business decisions often rely on complex optimization models, but building them is slow and manual. Meet LEAN-LLM-OPT, a lightweight, multi-agent AI that auto-formulates large-scale optimization models from a plain-English problem description and datasets. How it works: two planner agents design a step-by-step workflow for similar problems; a builder agent
Robotics
Humanoid robots need to coordinate physically with people—lifting, handing over, steadying—but we lack data of humans interacting with robots. What if they learned from humans interacting with humans? The catch: simply mapping human motions onto a robot often breaks crucial touches and supports. The team proposes PAIR (Physics-Aware
LLM
Want private AI without cloud risk or spend? This study shows SMEs can run production LLMs on NVIDIA Blackwell consumer GPUs (RTX 5060 Ti, 5070 Ti, 5090). * Cost: $0.001–$0.04 per million tokens (electricity only) — 40–200x cheaper than budget cloud APIs. * ROI: Hardware can pay for itself
LLM-based apps—from chatbots to code-running agents—are creating a new playground for attackers. A new paper by Ben Nassi, Bruce Schneier, and Oleg Brodt argues these aren’t one-off "prompt injections," but full-on malware campaigns they call promptware. They map attacks to a five-step "kill chain&
AI
AI discovers better ways to fast-charge batteries Charging batteries quickly without wearing them out is hard—and testing each new idea takes time and money. Researchers show that large language models (the tech behind chatbots) can help design smarter charging “recipes.” * Two approaches: Prompt-to-Optimizer (P2O), where an AI writes small
AI
TL;DR An LLM acts as a coach to prune another LLM, shrinking it ~45% while preserving key knowledge and accuracy. Traditional pruning uses fixed rules and often wipes out facts. This paper lets a foundation model adaptively choose which layers to trim each round. It reads layer sensitivity snapshots—
AI
AI is turbocharging factories, supply chains, and maintenance—but it also widens the ethical playing field. This chapter maps where industrial AI meets ethics: transparency, accountability, fairness, data sharing, and responsible R&D. Core message: building ethics into systems from day one accelerates innovation and trust. Ethics isn’t
What if a speech AI could pause and double-check its hearing when the sound gets messy? That’s the idea behind Speech-Hands, a new voice-agentic framework that teaches models to know when to trust themselves—and when to ask for help. Instead of blindly mixing speech recognition with external audio
AI
TL;DR Debiasing big language models is costly. This study shows compact “BabyLMs” can mimic how larger BERT-style models learn biases—so researchers can test ideas faster and cheaper. * BabyLMs (small, BERT-like models on tiny, editable corpora) track the same bias and performance patterns as standard BERTs. * Correlations hold across
AI
Can AI read ancient coins? Ancient Roman coins are tiny time capsules—but there are millions, and decoding their symbols is slow work. A new study by David Reid and Ognjen Arandjelovic tests whether modern AI can spot coin motifs (like emperors, gods, altars) more reliably. The team compared classic