imudojuiwọn ojoojumọ2310 daju itan
AI iroyin. Laisi ariwo.
Agbegbe AI ti a ṣayẹwo orisun ti awọn ifilọlẹ ọja, awọn iyipada eto imulo, iwadii aabo, ati awọn gbigbe ile-iṣẹ, ṣalaye ni ede Gẹẹsi nipasẹ ẹgbẹ ẹkọ ti kii ṣe èrè.
Ifowosowopo ti o ni idaniloju
Gbogbo itan ni asopọ si ẹri ti o lagbara julọ ti o wa: awọn orisun atilẹba nigbati o wa, bibẹkọ ti o han gbangba.
English itele
Kini o ṣẹlẹ, idi ti o ṣe pataki, ati kini lati wo - laisi jargon.
Ko si kikun
Nigbati awọn ifihan agbara jẹ tinrin, a jade ohunkohun kuku ju òwú kikọ sii.
Awọn itan diẹ sii
9 awọn itanỌja
NVIDIA says Groq 3 LPX AI racks enter full production after $20 billion deal
Yeni Şafak English, citing an NVIDIA announcement, reports that Groq 3 LPX AI racks have entered full production after NVIDIA’s $20 billion purchase of Groq assets. The systems are expected to be deployed by Nebius later this year, but the report’s performance and commercial claims have not been independently…en.yenisafak.comỌja
NVIDIA ṣafihan NVLink Fusion fun aṣa accelerators AI
NVIDIA sọ pe NVLink Fusion yoo jẹ ki awọn hyperscalers ati awọn ile-iṣẹ AI sopọ aṣa aṣa XPUs si netiwọki rẹ, agbeko, itutu agbaiye, agbara ati awọn amayederun sọfitiwia, ti o le dinku idiju ati akoko ti o nilo lati ran awọn eto AI ologbele-aṣa.
blogs.nvidia.comỌja
NVIDIA says Vera Rubin NVL72 delivers up to 30x higher agentic-AI throughput per megawatt
NVIDIA reports that its Vera Rubin NVL72 systems produced up to 30x more agentic-AI inference throughput per megawatt and up to 35x lower token costs than GB300 NVL72 systems in company measurements. The results used recorded coding-agent trajectories and remain pending SemiAnalysis review.
blogs.nvidia.comỌja
Intel details three architectures for agentic AI across data centers and edge devices
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.newsroom.intel.comAtunse
FlavourBench proposes an executable test for ranking frontier language models
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.arxiv.orgIle-iṣẹ
鉅亨網 reports Anthropic may seek $100 billion IPO at $2 trillion valuation
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.news.cnyes.comAtunse
Awọn oniwadi Ilu India Dagbasoke Ọpa AI Tuntun ati Oogun fun Itọju Akàn
Awọn oniwadi ni awọn ile-iṣẹ oludari Ilu India ti kede awọn idagbasoke pataki meji ninu iwadii alakan ti o ni ifọkansi lati mu ilọsiwaju bawo ni awọn dokita ṣe rii ifasẹyin ati tọju awọn sẹẹli buburu.whalesbook.comAtunse
Atunyẹwo eleto ti awọn iwadii 55 rii ikẹkọ ẹrọ autism tun da lori awọn awoṣe abojuto
Onkọwe mẹrin kan arXiv awọn iwadii atunyẹwo eto eto 55 lati ọdun 2017 si 2023 lori ikẹkọ ẹrọ fun iwadii aisan autism ati itọju: awọn ọna abojuto jẹ gaba lori, ẹkọ ti o jinlẹ n dagba, ati ilọsiwaju da lori apapọ jiini, ile-iwosan ati data sensọ. Atokọ naa ko funni ni ọna wiwa tabi awọn isiro deede.arxiv.orgAtunse
Preprint ties model uncertainty to the label tree, reporting about half the calibration error
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.arxiv.org
Alaye ti o wulo ni ọsẹ kọọkan
Tẹsiwaju pẹlu AI laisi gbigbe ninu ifunni.
Gba awọn iroyin AI ti a ṣayẹwo ti ọsẹ naa, data atilẹba, awọn irinṣẹ to wulo, awọn yiyan ẹkọ, ati awọn iṣẹ AI tuntun.
De ọdọ awọn eniyan ti o nkọ AI
Igbanisise ọjọgbọn AI kan tabi ṣe ifilọlẹ ọja AI ti o wulo? Fi si iwaju awọn eniyan ti o wa nibi lati kọ ẹkọ ati ṣe.
Firanṣẹ iṣẹ AI kanFi ohun elo AI silẹ