AI News Archive: May 27, 2026 — Part 12
Sourced from 500+ daily AI sources, scored by relevance.
- Anthropic taps 30-year industry vet Choi Ki-young as chief of operations in Korea
Choi Ki-young, the newly appointed Representative Director of Korea for AI company Anthropic [ANTHROPIC] U.S. artificial intelligence company Anthropic appointed Choi Ki-young as the head of its Korea operations ahead of the opening of its Seoul office, the tech company said Wednesday. Established in 2021, Anthropic is the developer of AI models, namely Claude, and recently drew attention for Mythos, an model designed to identify security vulnerabilities. Although Anthropic established its Korean entity last year, it had not appointed a Korean country head and local staff had been overseeing operations on behalf of the corporation. Related Article Bifrost pitches 3-D AI training platform to Korean manufacturers Samsung will allow employees to use outside AI models starting from June NHN Cloud sells out GPU resources, unveils AI brand 'FactoryX' “According to our latest Economic Index , Koreans use Claude at more than 3.5 times the rate expected for the population size, with usage skewing heavily toward technical and creative work,” the company said. “In the coming weeks, senior leadership from Anthropic will travel to Seoul to officially open the office and meet with customers.” Before joining Anthropic, Choi served as the general manager for Korea at global cloud company Snowflake and has spent more than 30 years in the technology industry across Korea and the Asia-Pacific region. Prior to Snowflake, Choi led Korean operations for companies including Google Cloud, Adobe, Autodesk and Microsoft. The AI company Anthropic's logo is seen in this illustration [REUTERS/YONHAP] “Korea is one of the most sophisticated AI markets in the world, leading in hardware innovation, developer activity and enterprise adoption,” Choi said. “Korean organizations combine technical depth with a commitment to responsible deployment, which is exactly where Anthropic operates.” As the company's representative director of Korea, Choi will lead the AI developer in establishing customized strategies that reflect the “unique uses of Claude in Korea,” while focusing on business expansion, according to Anthropic. “Korea is one of the markets where we’ve seen the most enthusiasm for Claude, and few people understand its technology landscape the way Choi does,” said Chris Ciauri, Managing Director of International at Anthropic. “He’ll build the team and the local partnerships to support how Korean organizations are putting Claude to work.” Anthropic has been expanding its business-to-business operations across the Asia-Pacific region. Last year, the company also appointed a former Snowflake executive as head of its Japan office, continuing its recruitment of B2B specialists. This article was originally written in Korean and translated by a bilingual reporter with the help of generative AI tools. It was then edited by a native English-speaking editor. All AI-assisted translations are reviewed and refined by our newsroom. BY KIM MIN-JEONG [kim.jiye@joongang.co.kr]
- 최기영 전 스노우플레이크 한국 총괄, 앤트로픽 코리아 초대 지사장으로
앤트로픽은 한국을 클로드 활용도가 높은 시장 가운데 하나로 평가하고 있다. 지난 3월 공개된 앤트로픽의 자체 보고서에 따르면 , 한국의 클로드 사용량은 인구 규모 대비 예상치를 웃도는 수준으로 나타났으며, 기술·창작 분야를 중심으로 활용이 이뤄지고 있다고 설명했다. 앤트로픽은 이러한 흐름을 바탕으로 서울 오피스를 개소하고 국내 사업을 확대할 계획이다. 최기영 신임 대표는 지난 5월 중순까지 스노우플레이크 한국 총괄을 맡았으며, 앤트로픽 합류 이전에는 구글 클라우드, 어도비, 오토데스크, 마이크로소프트 등에서 한국 사업을 이끌었다. 약 30년간 글로벌 기술 기업에서 경력을 쌓아온 인물이다. 최기영 대표는 “한국은 하드웨어 혁신성, 개발자 생태계, 기업의 AI 도입 수준 면에서 매우 성숙한 시장”이라며 “국내 기업들은 기술적 역량과 책임 있는 AI에 대한 의지를 함께 갖추고 있어 앤트로픽이 추구하는 가치와 정확히 맞닿아 있다. 이러한 이유로 앤트로픽에 합류했으며, 장기적인 관점에서 한국 사업을 발전시켜 나가겠다”라고 말했다. 최기영 대표는 한국 시장에서 클로드가 활용되는 방식의 특성을 반영해 현지 맞춤형 전략을 세우고, 기업·개발자·연구자를 아우르는 파트너십 구축을 이끌 계획이다. 앤트로픽 인터내셔널 총괄 크리스 차우리는 “한국은 전 세계에서 클로드 관심도가 높은 시장 중 하나로, 최기영 대표만큼 한국 기술 생태계를 깊이 이해하는 인물은 드물다”라며 “최기영 대표는 서울 오피스 팀을 꾸려 한국 기업들이 클로드를 실무에 적극 활용할 수 있도록 현지 파트너십을 이끌어갈 것”이라고 밝혔다. 앤트로픽 한국 조직은 기업 및 스타트업과의 파트너십 구축, 정부 및 연구 기관과의 협력, 클로드를 활용하는 국내 개발자 커뮤니티 지원에 집중할 계획이다. jihyun.lee@foundryco.com
- Cybersecurity Evolution: How We Went From Perimeter Defense to AI-Native Security
The cybersecurity industry of 2006 barely resembled today's billion-dollar behemoth. As part of Dark Reading's 20th anniversary celebration, we trace the industry's evolution through a technology lens.
- AI-Assisted Exploit Development Outpaces Scanner Detection
Attackers are using AI to dramatically reduce the time they need to develop a working exploit for a CVE, according to new research.
Score: 00🌐 MovesMay 27, 2026https://www.darkreading.com/threat-intelligence/ai-assisted-exploit-development-scanner-detection - Innovate fast, owe less: A practical path to help reduce AI security debt
Artificial intelligence continues to evolve rapidly, with solutions emerging to enhance worker productivity , help businesses develop products more quickly, and improve business operations. Implementing these solutions, however, means introducing a bevy of new AI apps and agents –– and that means introducing security risks. “AI technology has evolved rapidly, from single modal foundation models to multi-modal to reasoning models to agentic AI,” says Vimal Navis, Principal with PwC focused on Cyber, Data and Tech Risk. “Industry frameworks, standards, and cybersecurity controls are taking time to catch up. The gap becomes debt.” It’s a tricky balancing act because employees have easy access to a slew of coding assistants and other AI tools, creating at least a couple of issues. First, as new capabilities come on board, they may make others redundant, adding to the problem of technical debt. Second, each new solution can introduce a potential security risk and, to the extent they operate without the knowledge of IT, they add to the problem of shadow IT – or shadow AI, in this case. Shadow AI, in turn, adds to the AI security debt. “Even within approved tools, new AI features are being added that IT may not be prepared for,” Navis says. Think of a new AI chatbot or query engine being added to a CRM tool, or connectors to external applications, for example. While such technologies may be useful, they also pose security challenges, such as new forms of attack that companies may not be prepared to defend against. Managing AI Starts with the Right Tools: A Look at Microsoft Microsoft is starting to treat AI agents as first-class enterprise assets that can be inventoried, governed, and monitored. That is important because AI security debt often comes from moving fast on innovation while losing track of what was deployed, what it can access, and who is accountable for it. With Microsoft Agent 365 , IT gets a view of agents that are registered and interact with the organization’s Microsoft stack. IT can set policies for who can create, onboard, and manage agents. Agent 365, together with Microsoft Defender, helps organizations observe, secure, and govern AI agents across the enterprise. It can help detect suspicious and malicious agent activity, visualize potential attack paths from agents to critical assets, and support remediation of agent misconfigurations, exposure risks, and related vulnerabilities, among other capabilities. Similarly, Microsoft Purview can be used to check for incorrect or excessive permissions on sensitive data and to enable strict controls apply to it. Purview DLP can help organizations tackle sensitive data leaking through prompts, chat histories, connectors, and retrieval paths. Additionally, Microsoft Entra now includes identity and network access capabilities that apply to AI agents – aimed at applying zero trust principles to non-human actors. Microsoft Defender for Cloud Apps can help govern agent-related SaaS and genAI usage by discovering shadow AI apps, assessing risk, controlling unsanctioned apps, governing OAuth access, and applying real-time session and data protection controls. If all this sounds like a lot to tackle, companies can turn to PwC , a Microsoft Agent 365 launch partner , for assistance. “We help companies assess the rapidly evolving threat landscape, identify where AI security debt is accumulating fastest, and translate requirements into workable controls aligned to Microsoft’s expanding capabilities,” Navis says. “We help them get a view of the threat model and help confirm their controls can keep up without compromising on the speed of innovation.” Learn more about how PwC can help you employ AI securely. Read, “Building trust in AI from the ground up: How you can secure the data behind it,” by PwC’s Vimal Navis and Joe Ponder.
Score: 00🌐 MovesMay 27, 2026https://www.cio.com/article/4177467/innovate-fast-owe-less-a-practical-path-to-help-reduce-ai-security-debt.html - 오픈AI, 한국에 ‘데이브레이크’ 도입…정부·공공기관 AI 보안 지원 본격화
오픈AI 최고전략책임자(CSO) 제이슨 권은 27일 서울에서 열린 기자간담회에서 “AI는 이제 단순한 기술 실험 단계를 넘어 경제와 사회의 핵심 인프라로 진화하고 있다”며 “한국은 AI 확산의 다음 단계로 나아가기에 매우 적합한 국가”라고 말했다. 권 CSO는 현재 AI 산업이 세 번째 단계에 진입했다고 설명했다. 그는 “첫 번째 단계는 모델 성능과 기술적 돌파구 중심이었다면, 두 번째 단계는 수십억 명의 사용자에게 AI 접근성을 제공하는 과정이었다”며 “이제는 AI가 경제와 사회의 핵심 인프라 일부로 자리잡는 세 번째 단계에 들어섰다”고 말했다. 그는 한국이 이러한 변화에 유리한 조건을 갖췄다고 평가하며, 디지털 기술 수용도가 높고 공공 부문의 AI 관심이 크다는 점, 반도체·인프라·개발자 생태계 등을 모두 갖춘 ‘풀스택 경제(full-stack economy)’라는 점 등을 이유로 들었다. 이날 기자간담회의 핵심은 사이버보안 분야 협력안이다. 오픈AI는 최근 출범한 사이버보안 프로그램 ‘ 데이브레이크 (Daybreak)’를 바탕으로, 한국 맞춤형 액션 플랜을 세 축으로 추진한다. 여기에는 ▲한국 주요 이해관계자 대상 최신 사이버 AI 역량 브리핑 및 시연 ▲‘신뢰 접근 사이버 프로그램(TAC, Trusted Access for Cyber)’을 통한 한국 정부·공공기관 및 사이버보안 당국의 접근 권한 확대 ▲주요 기업과 핵심 산업으로의 TAC 접근 확대 등이 포함된다. 권 CSO는 “지난 5월 18일 오픈AI 국가보안정책 총괄 사샤 베이커가 방한해 과학기술정보통신부, 외교부, 행정안전부, 금융위원회, 국가인공지능전략위원회, 한국인터넷진흥원(KISA) 등 정부 부처와 공공기관 관계자들을 대상으로 사이버 특화 모델 역량을 시연했다”며 “어제는 류제명 과학기술정보통신부 2차관과 사이버보안 및 국가 회복력 협력 방안을 논의했다”고 밝혔다. 보안 외 공공 분야 협력도 구체화됐다. 한국수자원공사와의 MOU를 통해 오픈AI 기술은 수재해 대응, 수자원 관리, 기후변화 적응 등 공공서비스에 적용된다. 기술보증기금과는 스타트업 비즈니스 평가와 금융 지원 의사결정 프로세스 고도화에 협력한다. 오픈AI는 이날 한국 내 AI 활용 확대 사례도 공개했다. 권 CSO에 따르면 챗GPT(ChatGPT)는 현재 전 세계 주간 활성 사용자 9억 명 이상을 확보했으며, 한국은 활성 사용자·유료 가입자·기업 고객 수 기준 글로벌 상위 10개 시장에 포함된다. 특히 코딩 에이전트 ‘코덱스(Codex)’의 한국 내 사용량 증가세가 두드러졌다. 그는 “올해 초 대비 한국 내 코덱스 주간 활성 사용자는 10배, 2월 앱 출시 이후 일간 상호작용은 30배 이상 증가했다”고 설명했다. 특이한 대목은 한국 이용자의 코덱스 요청 가운데 50%가 비(非)코딩 업무에 해당한다는 점이다. 반복 업무 자동화, 워크플로우 정리, 아이디어 구현 등 실무 전반의 도구로 자리잡고 있다는 의미다. 오픈AI는 이달 초 FDE 인력을 전면에 내세운 오픈AI 디플로이먼트 컴퍼니(OpenAI Deployment Company)를 설립 하는 등 FDE(Forward Deployed Engineer) 모델 확장에 속도를 내고 있다. FDE란 고객사 현장에 깊숙이 들어가 AI·소프트웨어를 실제 업무 환경에 맞게 구축·적용하는 엔지니어를 뜻한다. 권 CSO는 이에 대해 “오픈AI는 FDE 비즈니스를 운영하려는 것이 아니라 AI 비즈니스를 운영하려는 회사”라며 “엔터프라이즈 고객이 우리 기술에서 최대한의 가치를 끌어낼 수 있도록 돕는 것이 목표이며, FDE는 그 과정을 가속화하기 위한 수단”이라고 설명했다. 그는 FDE 모델에 대해 “매우 강한 확신(bullish)을 갖고 있다”며, 그 중심 원칙으로 ‘의존성 배제’를 제시했다. 권 CSO는 “오픈AI가 파트너와 고객에게 제공하는 FDE 서비스는 특정 기업이 오픈AI 역량에 종속되도록 만드는 것이 아니라, 해당 기업이 스스로 동일한 역량을 구축하도록 돕기 위한 것”이라고 말했다. 이어 “FDE는 단순히 기업의 AI 전환 작업을 대신 수행하는 인력이 아니다”라며 “작업을 수행하는 동시에, 향후 고객사 내부에서 같은 역할을 맡게 될 인력을 교육하는 ‘트레이너를 훈련시키는(train the trainers)’ 역할도 수행한다”고 강조했다. 즉 오픈AI FDE는 프로젝트 기간 동안 고객사 내부 인력과 함께 일하며 관련 역량과 운영 방식을 전수하고, 프로젝트 종료 이후에도 기업이 자체적으로 AI 전환을 이어갈 수 있는 자립 구조를 만드는 데 초점을 둔다는 설명이다. 권 CSO는 “이러한 배포 작업 과정에서 고객과 협력하더라도, 고객 데이터는 어디까지나 고객의 자산”이라며 “오픈AI가 데이터를 가져가거나 자동으로 처리하지는 않는다”고 강조했다. jihyun.lee@foundryco.com
- The agentic wave: Why advanced AI demands foundational security
The agentic wave The use of agentic and predictive AI in enterprise applications is arguably the fastest evolving frontier our industry has ever encountered. We are currently navigating a “mega-wave” of innovation and a period of rapid expansion where the capabilities of autonomous agents are outstripping our initial frameworks for managing them. While the technology feels revolutionary, the pattern of its arrival is remarkably familiar. History rhymes: From microservices to agents As an industry, we have stood on this shoreline before. We saw this with the rise of microservices and the containerisation movement, the birth of code pipelines, and the cultural shift of DevSecOps…and this is just one example. In the early days of those transitions, there was a palpable sense of anxiety regarding the lack of “battle-hardened” best practices. Critics argued the tech was too raw for the enterprise. But the reality is simple: there are no battle-hardened best practices until there have been battles of significance. Best practices are forged in the heat of implementation, not in the vacuum of theory. We are repeating this cycle with agentic AI. We are moving at breakneck speed to create governance and security strategies in real-time. This isn’t a sign of chaos; it is the natural state of innovation. Crucially, it is worth recognising that doing nothing is not a viable alternative. Innovation will not pause to wait for the creation of a governance framework; it will not wait for us to provide the ultimate security framework; it will continue to move forward with or without our participation. The blueprint for “careful adoption” Recently, the Australian Cyber Security Centre (ACSC), along with its Five Eyes partners, published a document on the careful adoption of agentic AI services. It is a timely reminder that while we must move fast, we must also move with intent. The guidelines reinforce a core truth: AI security is not a standalone silo. It is a subset of your existing cybersecurity strategy. To be successful, these services must be integrated into what the ACSC refers to as a Modern Defensible Architecture. This framework moves us away from reactive security and toward systems that are “secure by design”, where the architecture itself is built to withstand and recover from the inevitable compromise. The ACSC document highlights that we should not fear the agent, but we must respect its potential for autonomy by anchoring it within these resilient architectural pillars: The Principle of Least Privilege & Segmentation: Just as we did with microservices, agents must be granted only the minimum access required to perform their tasks. In a defensible architecture, this means treating every AI agent as a distinct identity, segmented from the core network to ensure that if an agent is “jailbroken” or compromised, the blast radius is strictly contained. Visibility and Logging: A key tenet of a defensible system is knowing what is happening in real-time. We must have full visibility into the “chain of thought” and the actions taken by an agent, ensuring that every autonomous decision leaves a verifiable audit trail. Human-in-the-Loop (HITL) as a Circuit Breaker: Autonomy does not mean an absence of oversight. High-stakes decisions, especially those affecting system integrity or sensitive data, require a human “green light.” This acts as the ultimate fail-safe in a resilient system, ensuring that logic remains grounded in human intent. Phased Implementation & Continuous Validation: Start with low-risk internal tasks to “earn” the right to move toward customer-facing or sensitive operations. This iterative approach allows us to test the “defensibility” of our AI integrations in controlled environments before they are exposed to the complexities of the open web. By aligning agentic AI adoption with these principles in a Modern Defensible Architecture, we aren’t just protecting a single application; we are building a resilient ecosystem that can adapt to new threats as quickly as the AI itself evolves. The best practice of today is the legacy of tomorrow In an era of significant speed, we must accept a difficult reality: the best practice today may not be the best practice tomorrow. The models are changing weekly, and the threat vectors are evolving alongside them. To thrive in this environment, we don’t need rigid, static rules. We need flexibility and leadership. One of the most enduring lessons from all of the innovation waves that our industry has endured is that security cannot exist in a vacuum. IT and Security leaders must partner with their business counterparts. And it is not enough to just be “seen” as enabling innovation; there must be leadership and objective outcomes. They must be seen to deliver competitive advantages and efficiencies. Our goal should be to build resilient systems that can withstand the “hallucinations” of a model or the sophisticated prompt injections of an adversary. We must bring our users along for the ride, educating them on the “why” behind the guardrails so that security becomes an enabler of innovation, rather than a hurdle. Moving forward with deliberate innovation The message for enterprise leaders is clear: Innovate…but do so carefully and deliberately. We need robust governance that doesn’t just say “no,” but instead asks “how can we do this safely?” We need to build systems that are modular enough to swap out models as they improve and resilient enough to fail gracefully when they don’t. We’ve navigated these waves before, from the mainframe to the cloud, and from monolithic code to microservices. The Agentic Wave is our next chapter. By applying the discipline of the past to the technology of the future, we can ensure that this wave carries us forward rather than pulling us under. To learn more, visit us here .
Score: 00🌐 MovesMay 27, 2026https://www.cio.com/article/4177900/the-agentic-wave-why-advanced-ai-demands-foundational-security.html - Erin Brockovich starts tracking AI data centers, calls on affected communities to submit issues — website shows more than 2,700 reports from across the US raising various concerns
Erin Brockovich, who made her name making a case against PG&E in the '90s that resulted in a $333 million settlement, is now looking at the impact of data center developments on communities and is recording community reports along the way.
- Salesforce revenue forecast disappoints amid AI disruption fears
Salesforce revenue forecast disappoints amid AI disruption fears The Straits Times
- Marvell’s stock climbs as ‘exceptional’ AI demand drives strong growth outlook
Marvell’s stock climbs as ‘exceptional’ AI demand drives strong growth outlook
- US agencies cite 'anti-tech extremism' amid AI backlash
US agencies cite 'anti-tech extremism' amid AI backlash Computing UK
- YouTube Will Now Automatically Label AI Videos Even When Creators Don't
YouTube today said it is introducing automatic AI detection, with automatic AI labeling applied to videos with "significant photorealistic AI use." Creators are still expected to manually disclose when realistic AI is used for videos even with the new automatic labeling system. Creators who think their content was incorrectly identified as AI-generated can update the disclosure status in YouTube Studio, but disclosures are permanent for content created with YouTube's AI tools like Veo and Dream Screen or content with C2PA metadata indicating fully generative AI. YouTube is also improving labeling for AI-generated content, making it clearer when a video has "photorealistic and meaningfully AI altered or generated content." An AI label will be shown just below the video player and above the description for long-form videos with AI content, and for shorts, the label will appear as an overlay on the video. The updated labeling applies to content that is photorealistic and may fool people, rather than unrealistic content. Disclosures for content that is "unrealistic, animated, or slightly altered" will continue to be tucked in the expanded description of the video. Separately, YouTube added a new customizable content feed that users can shape based on interests, moods, or preferred topics. Users can type in a custom prompt covering what they want to see, and a content feed will be generated. Custom content feeds have been in testing since November, but they are now rolling out to signed-in viewers in the U.S. on the YouTube mobile app and desktop. YouTube search and watch history must be turned on for the feature to work. Tag: YouTube This article, " YouTube Will Now Automatically Label AI Videos Even When Creators Don't " first appeared on MacRumors.com Discuss this article in our forums
- AI-generated YouTube content to get ‘more visible’ disclosure label, whether voluntary or not
YouTube has already paved the way for creators to upload AI-generated content, but its recent move will mean those YouTube videos get a more prominent “AI” label to let viewers know how they were created. more…
- YouTube is making it easier to spot AI-generated videos
Enough of being fooled by realistic-looking AI videos.
- Google is making it easier to find the sites you actually care about in AI Search
Preferred Sources and link carousels will now be mixed into AI Overviews.
- YouTube’s AI content labels are getting a much-needed makeover
YouTube is moving AI disclosure labels to a more visible spot and rolling out auto-detection for AI-generated content starting May 2026. Here's what changes for creators and viewers.
- YouTube taking steps to make clear when realistic videos are made by AI
YouTube said it will automatically label photorealistic content created by AI, the video platform said.
- YouTube's massive new AI change will immediately alter how your videos look
YouTube's massive new AI change will immediately alter how your videos look USA Today
- YouTube reveals major change to help you identify AI-generated content
Starting this month, YouTube may automatically apply AI labels if creators fail to disclose AI use
- YouTube to Auto-Detect AI Videos, Make Labels More Prominent
YouTube to Auto-Detect AI Videos, Make Labels More Prominent PCMag UK
- YouTube to Auto-Detect AI Videos, Make Labels More Prominent
YouTube to Auto-Detect AI Videos, Make Labels More Prominent PCMag
- YouTube to Auto-Detect AI Videos, Make Labels More Prominent
YouTube to Auto-Detect AI Videos, Make Labels More Prominent PCMag Australia
- Youtube says will flag AI-generated content
Youtube says will flag AI-generated content The Straits Times
- New ways to find your favorite sources and original content in AI Search
Illustration of a person searching on their phone
- YouTube will try to automatically flag AI videos starting this month
YouTube is tightening its AI labeling rules. Labels for photorealistic or heavily AI-altered content will now show up in more visible spots, below the player for long videos and as an overlay on Shorts. Starting May 2026, an automatic detection system will flag AI-generated content even if creators don't disclose it. Recommendations and monetization won't be affected. The article YouTube will try to automatically flag AI videos starting this month appeared first on The Decoder .
- YouTube is starting to automatically label AI-generated videos without creator input
The platform will apply labels when its systems detect significant photorealistic AI use, even if creators don't disclose it
- Nvidia CEO brands Taiwan 'epicentre' of AI revolution
Nvidia's chief executive has said the chip company plans to invest around $150 billion a year in Taiwan, terming it the "epicentre" of the AI revolution and predicting it will be the world's tech manufacturing hub for a long time.
- Nvidia to spend $191 billion a year in Taiwan, ‘epicentre’ of AI revolution, says CEO
Nvidia to spend $191 billion a year in Taiwan, ‘epicentre’ of AI revolution, says CEO The Straits Times
- Nvidia spending up to $150bn a year on Taiwan AI suppliers: Jensen Huang
Nvidia spending up to $150bn a year on Taiwan AI suppliers: Jensen Huang Nikkei Asia
- Nvidia Signals $150B Spend in Taiwan
Speaking at a launch event for Nvidia’s upcoming Taiwan headquarters, CEO Jensen Huang deemed the country the “epicenter” of the AI revolution
- Jensen Huang pledges $150 billion a year in Taiwan as Nvidia breaks ground on new HQ
The chip company's planned Constellation campus in Taipei will house 4,000 employees when it opens in 2030
- YouTube says it will flag AI-generated content
YouTube says it will flag AI-generated content The Straits Times
- Nvidia bets $150B on Taiwan as Trump's plan to make US an AI hub backfires
Nvidia will invest $150 billion a year to make Taiwan an AI “epicenter.”
- Vibe coding startup Cognition more than doubles valuation in new $1B+ round
Cognition Inc., a provider of artificial intelligence programming tools, today announced that it has raised more than $1 billion in funding. Lux Capital, General Catalyst and 8VC led the Series D round with contributions from more than a dozen others. The deal values Cognition at $26 billion, about $16 billion more than what it was […] The post Vibe coding startup Cognition more than doubles valuation in new $1B+ round appeared first on SiliconANGLE .
- Cognition just raised $1 billion at a $26 billion valuation, and 90% of its own code is written by its AI
Cognition AI has raised more than $1 billion in new funding at a $26 billion valuation, more than doubling its worth since a September round that valued the company at $10.2 billion. The round was co-led by Lux Capital, General Catalyst, and 8VC, with participation from Ribbit Capital, Atreides Management, and Peter Thiel’s Founders Fund. […] This story continues at The Next Web
- YouTube reveals major change to help you identify AI-generated content
Starting this month, YouTube may automatically apply AI labels if creators fail to disclose AI use
- AI coding startup Cognition raises $1 billion at $26 billion value
AI startup Cognition has secured over one billion dollars in a new funding round. This brings its valuation to a massive twenty-six billion dollars. Their AI agent, Devin, automates programming for engineers. This funding highlights strong investor interest in AI for software development. Cognition plans to use the funds to enhance its AI models and customer experience.
- Coding Startup Cognition Raises $1 Billion at a $26 Billion Valuation
Coding Startup Cognition Raises $1 Billion at a $26 Billion Valuation The Information
- Meta Introducing Subscription Plans for Social Media, AI Chatbot. Why the Stock Is Rising.
Meta Introducing Subscription Plans for Social Media, AI Chatbot. Why the Stock Is Rising. Barron's
- YouTube Boosts Visibility of Labels on AI-Generated Videos
The video platform is improving the visibility of labels for photorealistic videos made with AI and will automatically detect AI-generated videos.
- Meta is charging for its AI chatbot for the first time, starting at $7.99 a month
Meta is selling subscriptions to its AI chatbot for the first time, introducing two paid tiers that put it in direct competition with OpenAI and Google for consumer AI revenue. Meta One Plus costs $7.99 per month and Meta One Premium costs $19.99 per month. Both tiers give users expanded access to image generation, video […] This story continues at The Next Web
- Syncaut
The automation platform built for e-commerce agencies
- Meta Launches Paid AI Chatbot Subscriptions
Meta Launches Paid AI Chatbot Subscriptions The Information
- Meta to start testing AI subscription services, with cheapest plan at $7.99 a month
Meta confirmed Wednesday that it will begin testing two subscription plans for its AI offerings.
- Meta launches Instagram, Facebook, and WhatsApp subscriptions, with more to come, including AI plans
Meta is rolling out paid subscription plans for Instagram, Facebook, and WhatsApp worldwide, while also testing new AI, creator, and business-focused offerings under its broader “Meta One” subscription brand.
- Snowflake to burn $6B on AWS Graviton CPUs and AI accelerators
Dataware house gambles cloud conveniences, AI accelerated insights will justify the cost.
- Snowflake commits $6B to Amazon Web Services over 5 years in latest AI infrastructure deal
Snowflake committed to spend $6 billion on AWS over five years, including the use of Amazon's custom Graviton processors. The deal adds to a growing list of large-scale AI infrastructure commitments on AWS from Anthropic, OpenAI, and Meta. Read More
- Salesforce Earnings Can Put AI Fears to Bed, Give Stock a Lift
While software stocks rebound from the artificial intelligence-driven wipeout earlier this year, Salesforce Inc. hasn’t really benefited. But its earnings after the close Wednesday could pull the company’s shares out of their malaise.
- In more good news for Amazon, Snowflake signs $6B deal with AWS for AI CPU chips
Snowflake has signed a new, enormous five-year deal with Amazon to secure chips for AI usage. Nvidia is once again being put on notice.
- AI content to be automatically labeled on YouTube — but not on YouTube Kids
YouTube is making its AI labels more prominent on videos, and adding automatic labeling to fill the gaps.