Naponta frissítve1656 ellenőrzött történetek
Source-checked AI coverage of product launches, policy shifts, safety research, and industry moves, explained in plain English by a nonprofit education team.
Every story links to the strongest available evidence: original sources when available, otherwise clearly attributed reporting.
Mi történt, miért számít, és mire kell figyelni – nincs zsargonadó.
Ha a jel gyenge, akkor nem teszünk közzé semmit, csak feltöltjük a hírfolyamot.
Ellenőrzött perspektívák egyre növekvő száma azoknak az embereknek, akiknek meg kell érteniük az AI-t anélkül, hogy felhajtást kergetnének.
Intel says it is presenting Diamond Rapids, Crescent Island and Wildcat Lake at Hot Chips 2026 as a portfolio for running agentic AI across enterprise systems, inference infrastructure, laptops and edge platforms.
A new arXiv preprint evaluates 27 frontier language-model endpoints on 534 culinary-choice tasks using a versioned scoring system and releases the data, responses and verifier for reproduction.
鉅亨網, citing The Wall Street Journal, reports that Anthropic could present a total addressable market exceeding $30 trillion and seek up to $100 billion in an IPO. The company’s plans remain under discussion and are not independently confirmed by a public filing.
Researchers at leading Indian institutions have announced two significant developments in cancer research that aim to improve how doctors detect relapse and treat malignant cells.
A four-author arXiv systematic review surveys 55 studies from 2017 to 2023 on machine learning for autism diagnosis and treatment: supervised methods dominate, deep learning is growing, and progress depends on combining genetic, clinical and sensor data. The listing gives no search method or accuracy figures.
A new arXiv preprint proposes H²EDL, a classifier that expresses uncertainty over the label taxonomy, so it can commit to a broad category while declining a specific class. It reports roughly halved calibration error on two image datasets versus cross-entropy baselines; not peer reviewed, no numbers in the abstract.
An arXiv preprint says reshaping the spectral geometry of a vision model's representations during training makes model–brain alignment more symmetric, reporting a 55% relative gain in two-way predictivity. The authors call the demonstration initial, the abstract names no neural data, and the gain is a trade-off.
A four-author arXiv preprint introduces HB-SJD, a batched speculative Jacobi decoding backend for the sample-generation step of visual on-policy distillation. The authors report shorter rollout and end-to-end training times with LlamaGen and preserved quality, but no numbers are given and it is not peer reviewed.
A preprint accepted by Studies in the History and Philosophy of Science treats the comparison between medicine and machine learning as a formal analogy rather than a slogan, and uses it to sketch a process-based account of when an ML system deserves trust. It is conceptual: no experiments, thresholds or checklists.
A single-author arXiv preprint proposes writing activation patching, gradients and Hessian-vector products as one linear measurement problem, and reports held-out tests on a toy control system, Tracr, GPT-2-small and Qwen-2.5-7B.
A 13-author arXiv preprint describes Disease Continuum Positioning, a Bayesian method placing a person on the Alzheimer's continuum, with uncertainty, from repeated diffusion tensor imaging. The authors say it beat existing progression methods on ADNI; the abstract gives no numbers, baselines or cohort details.
A single-author arXiv preprint asks whether published tricks for training physics-informed neural networks combine. On an unsteady cylinder-wake benchmark, most matched an untreated baseline alone, one pair reached 4.1% average relative error against OpenFOAM, and stacking more degraded results sharply.
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