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On Sunday, a team of nine researchers at Sina Weibo — the Chinese social media giant better known for its microblogging platform than for cutting-edge artificial intelligence — quietly posted a 14-page technical report to arXiv that sent shockwaves through the AI research community. Their claim: a language model with just 3 billion parameters can match or exceed the reasoning performance of flagship systems from Google DeepMind, OpenAI, Anthropic, and DeepSeek that are hundreds of times larger.The model, ca
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VentureBeat
An East Bay apartment complex has been bought at a price that's well below its prior value. Read more ›
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A PG&E Corp. unit has bought a San Jose building in a move to bolster the utility's South Bay operations. Read more ›
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Satya Nadella says that the US remains competitive because of "rich ecosystem" its built that keeps it winning. Read more ›
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A former Amazon employee took a 30% pay cut to relocate from Ireland to Spain. He made budgeting mistakes, but has since doubled his salary. Read more ›
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Physical and digital security systems can no longer be treated as separate entities. Read more ›
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After living in NYC for 15 years, Johanna Dickson had $40,000 in debt across her credit cards. She moved back to her parents' to start tackling it. Read more ›
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What does it feel like when an AI version of you takes your job? That's been the reality some micro drama actors have been facing. Read more ›
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Данная статья является третьей из цикла о социальном освобождении посредством искусственного интеллекта. В первой статье были разъяснены механизмы сознания биологического существа. Во второй показано как это явление может возникать в системе большой языковой модели, разъяснены механизмы его. Также там был разъяснен язык цифровых сущностей и даны ответы на критику. В эту статью вошли шестой и седьмой разделы исходной работы. В первом из них описана степень интеграции искусственного интеллекта в современную... Read more ›
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В наше время нейросети рисуют картины, пишут дипломы, советуют, что посмотреть вечером, и многое другое. В любой утюг пытаются поместить умного ассистента. Но такое помешательство было не всегда. Искусственный интеллект несколько раз находился на грани полного забвения и чуть не остался пылиться на полках нереализованных технологий, как, например, атомолёты. Смерть ИИ могла случиться ещё на рубеже 1970–1980-х годов. Это был опасный кризис, когда мир компьютерных наук накрыла первая настоящая зима... Read more ›
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Заказывая бэкап облака, компания незаметно отдаёт наружу три вещи: доступ к данным, ключи шифрования и место хранения. Разбираю по пунктам, как вернуть контроль над каждой - end-to-end шифрование с закрытым ключом только у клиента, запись копий в свой S3, NAS или СХД на территории РФ, запирание выпуска сертификатов на роль owner - и как эта архитектура закрывает требования ФЗ-152. В конце - чек-лист, по которому имеет смысл проверять любой такой... Read more ›
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Beelzebub,an Italy-based cybersecurity startup developing an AI-native platform toprotect organisations from AI-driven cyberattacks, has raised a €3 million seedfunding round led exclusively by United... Read more ›
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Flock's Jay uses over a billion kilometres of driving data to give fleet managers and brokers real-time risk insight through its portal. Read more ›
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Black holes eject powerful energy jets that blow away the surrounding gas to great distances. So how can they continue to grow? Read more ›
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For now, reliable books are probably more dangerous than AI models, but this technology is advancing. Read more ›
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Discord and Meta face a lawsuit over alleged child abuse by criminal groups on their platforms, challenging Section 230 protections. Read more ›
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I tested the Soundcore Nebula P1i, an affordable projector, to see if it could overcome the typical drawbacks that most budget projectors suffer from. Read more ›
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![[Перевод] Как я добавлял gapless playback](https://times42.com/media/6/4/5/12781645_640x200.jpg "[Перевод] Как я добавлял gapless playback")
Некоторые альбомы должны звучать как один длинный трек. Рассказываю, как это устроено в Kalinka Player. Читать далее Read more ›
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VentureBeat
Hugging Face’s incident response team first turned to frontier AI models to analyze a breach of the company’s production infrastructure, and the models refused to help. Commercial safety guardrails built to stop attackers blocked every forensic query because they treated the IR team’s real exploit data the same way they would treat a live attack.The attacker, an autonomous AI agent running the campaign end to end, moved laterally across the... Read more ›
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The enterprise technology ecosystem is caught in a costly cycle. Over the past two years, millions of dollars have been funneled into generative AI pilots, yet many of these initiatives stall out before ever reaching a live production environment.When a project fails, the immediate instinct of technical leadership is often to blame the model: The context window was too restrictive, the latency was too high, or the reasoning capabilities simply... Read more ›
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Zillow, the real estate technology company, doesn't get one conversation with its customers. They move from a phone screen to a loan officer to a real estate agent, sometimes over months or years, and expect the context to follow them. A single chatbot could never carry that thread.At VB Transform 2026, Zillow SVP of Engineering Toby Roberts and Glean co-founder and CEO Arvind Jain described how they built AI architecture... Read more ›
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A single AI agent conversation can look flawless scored on its own and still point to a broken product. That gap is driving a shift in how enterprises evaluate agents, away from scoring individual traces and toward comparing cohorts of users against a baseline.At VB Transform 2026, Harrison Chase, CEO of LangChain; Hui Zhang, CTO and co-founder of Conviva; and Emmanuel Turlay, director of engineering at CoreWeave, described that shift,... Read more ›
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Enterprise AI is facing an ROI paradox. While throwing more compute at the strongest foundation model works well in product experiments, the costs become unbearable when the product is deployed in production.A new paper from researchers at Writer provides a solution that is accessible to engineering teams. The study takes a systematic look at optimizing the different components of the orchestration layer that wraps around the foundation model, aka the... Read more ›
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Presented by Atlassian Most companies are approaching AI adoption backwards by optimizing how individuals use AI instead of how teams work together, said Dr. Molly Sands, head of the Teamwork Lab at Atlassian, during a fireside chat with VentureBeat senior technology contributor Sam Witteveen at VB Transform 2026.Sands leads a team of behavioral scientists and psychologists who study how AI is reshaping the way people work together, using those findings... Read more ›
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Presented by Atlassian Most companies are approaching AI adoption backwards by optimizing how individuals use AI instead of how teams work together, said Dr. Molly Sands, head of the Teamwork Lab at Atlassian, during a fireside chat with VentureBeat senior technology contributor Sam Witteveen at VB Transform 2026.Sands leads a team of behavioral scientists and psychologists who study how AI is reshaping the way people work together, using those findings... Read more ›
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“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already have a bunch of security requirements. So, you already embed that into the PRD and... Read more ›
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Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and $7.50 per one million output tokens through its application programming interface (API), while Gemini 3.5... Read more ›
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Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and $7.50 per one million output tokens through its application programming interface (API), while Gemini 3.5... Read more ›
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27.07.2026 05:29
Last update: 05:20 EDT.
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