AI News Archive: June 4, 2026 — Part 11
Sourced from 500+ daily AI sources, scored by relevance.
- Google tests AI Search opt-out as publishers battle zero-click web
As AI-generated answers drive more zero-click searches, Google's proposed opt-out tool may give publishers greater control over how their content is used
- UK orders Google to improve AI search attribution, give publishers opt-out controls
UK orders Google to improve AI search attribution, give publishers opt-out controls
- UK Forces Google to Improve AI Summary Sourcing, Give Publishers an Opt-Out
UK Forces Google to Improve AI Summary Sourcing, Give Publishers an Opt-Out PCMag UK
- Google to let publishers opt out of AI Search features
Google to let publishers opt out of AI Search features Computing UK
- AI executives make rare collective warning on bioweapons threat
The Anthropic, Google DeepMind, and OpenAI bosses warned that AI systems could be used to make deadly pathogens.
- AI executives join call for stricter regulation of synthetic biology
Letter urges Congress to require DNA firms to screen orders to prevent AI-aided bioweapons
- Sam Altman joins rivals in call to prevent AI-developed bioweapons
Tech leaders sign public letter in ‘rare moment of agreement across stakeholders that are often at odds’
- Sam Altman joins rivals in call to prevent AI-developed bioweapons
Tech leaders sign public letter in ‘rare moment of agreement across stakeholders that are often at odds’
- Wary of U.S., Carney Bets on AI Strategy for Canada
The country on Thursday released a national artificial intelligence strategy that focuses on building its sovereign capability and protecting consumers.
- Canada PM unveils AI strategy, warns of foreign dominance
Canadian Prime Minister Mark Carney launched his AI strategy on Thursday, warning that his country’s slow adoption of the frontier technology had created risks and that domestic capacity needed a boost to avoid it being “weaponised against us”. Reducing Canada’s reliance on the US is a central part of Carney’s agenda, and his AI strategy nodded to concern about the influence of US tech giants. “We are highly dependent on foreign suppliers for the infrastructure that powers AI,” he said. “That...
- Carney government releases AI road map that aims to make Canada a leader
Carney government releases AI road map that aims to make Canada a leader Toronto Star
- Carney announces government's AI strategy
Carney announces government's AI strategy CBC
- Carney says Canadian AI adoption will be ‘pro-worker’
Carney says Canadian AI adoption will be ‘pro-worker’ CBC
- Canada's new AI strategy aims to serve all Canadians, Carney says
Canada's new AI strategy aims to serve all Canadians, Carney says CBC
- Canada Prime Minister Mark Carney announces questionable national AI strategy
Canada's "AI for All" plan prioritizes strengthening data protections and increasing AI adoption.
- Making Sense Of The AI IPO Tsunami Heading For Wall Street
The AI IPO wave will test whether OpenAI, Anthropic and SpaceX can turn private-market valuations into public-market trust and durable investor demand.
- Building AI understanding through partnership
Building AI understanding through partnership kellogg.ox.ac.uk
- Meta’s $200 AI Agent ‘Hatch’, Sam Altman-back Helion Valuation Hits $15.5B, Snowflake’s New AI Tools — TITV [Video]
Meta’s $200 AI Agent ‘Hatch’, Sam Altman-back Helion Valuation Hits $15.5B, Snowflake’s New AI Tools — TITV [Video] The Information
- Meta Rolls Out AI Agent for Enterprises Globally
The tool is aimed at small businesses and is part of the social media giant’s push beyond consumers.
- DeepSeek nears $7B haul in first raise
Tech giant Tencent and battery pioneer CATL are reportedly among the investors in the maiden fundraise.
- TSMC chief says AI chip demand will outpace supply for years
TSMC chief executive C.C. Wei said appetite for AI shows no signs of cooling and that keeping up with orders has become increasingly difficult.
- TSMC maintains 30% growth outlook for 2026 as AI boom rolls on
TSMC maintains 30% growth outlook for 2026 as AI boom rolls on Nikkei Asia
- TSMC boss betting big on AI growth
Taiwan's TSMC, the world's largest contract chipmaker, is confident in its growth over the next few years, thanks to robust demand for computing power and advanced semiconductors as it rides a relentless AI boom, its CEO said today.
- Kirkland & Ellis partners with Palantir for AI-driven private equity work
The world’s largest law firm by revenue, Kirkland & Ellis, has agreed to partner with tech giant Palantir to create an AI tool to use in advising private equity firms. The US-based firm, which has a large City office, said the multi-year partnership will deploy technology to share the expertise of its leading partners with [...]
- Labour MP sues Elon Musk’s AI platform over fake sexualised images
Labour MP sues Elon Musk’s AI platform over fake sexualised images The Telegraph
- UK MP sues Musk's xAI over fake sexualised images
A British lawmaker has filed a case at London's High Court against Elon Musk's xAI after its Grok chatbot tool was used to create fake sexualised images of her, including in a bikini. Jess Asato, of the ruling Labour Party, said she lodged the "High Court claim against xAI, the company behind Grok" on Wednesday.
- British lawmaker sues Musk's xAI over sexualised Grok images
Grok, distributed through Musk's social media platform X, is currently subject to regulatory probes in several countries after an outcry earlier this year over its use to create non-consensual sexualised images.
- Kodesage raises $6.6M for AI-powered legacy software modernisation
Kodesage, a startup developing anon-premise AI platform for legacy software modernisation, has raised $6.6million in a seed funding round led by VentureFriends. Existing investorPortfolion also partic...
- Innovorder secures €20M to accelerate European growth and AI development
Innovorder, a French restauranttechnology company specialising in the digitalisation of restaurant operations,has raised €20 million in a funding round led by UL Invest, the family officeof technology...
- AI video startup TrueFan raises $10 million led by Baring PE, Z3Partners
Gurugram's TrueFan AI secured $10 million, valuing it at $40 million, to fuel its AI-generated video platform. Serving over 100 enterprises like HDFC Bank and Zomato, the startup creates personalized videos at scale using celebrity and business leader avatars. This funding will drive international expansion and enhance real-time video AI agent development.
- AI Startup TrueFan Raises $10 Mn To Enter New Markets
Gurugram-based enterprise AI startup TrueFan AI has raised $10 Mn (about ₹96 Cr) in its Series A funding round led…
- Video generation startup TrueFan AI raises $10 Mn in Series A round
Video generation startup TrueFan AI has raised $10 million in a Series A funding round led by Baring Private Equity Partners India and Z3 Partners. Existing investors IAN Alpha Fund and 3Lines Venture Capital also participated in the round. The company closed the financing at a post-money valuation of $40 million. The fresh capital will support international expansion and the development of real-time AI video agents, TrueFan said in a press release. Founded in 2020 by Devender Bindal, Nimish Goel, and Nevaid Aggarwal, TrueFan AI offers an enterprise AI video platform that uses generative AI to create hyper-personalized, studio-quality videos and avatars from a single recording. The platform helps more than 100 enterprise clients scale video marketing across global markets. The Gurugram-based startup serves over 100 enterprise customers, including HDFC Bank, Bajaj Finance, Zomato, Cipla, and BharatPe. The platform enables companies to create AI-powered personalized videos at scale through celebrity avatars, business leaders, and enterprise spokespersons. TrueFan AI plans to expand beyond India into Southeast Asia, the Middle East, and the US. The company says it has already witnessed demand from these markets. Its deep-learning models synthesize facial dynamics, gestures, and voice to generate up to 500,000 localized videos per minute across more than 175 languages. The company’s flagship product, TF Studio, enables brands to create personalized messages in bulk, localize content for different markets, and deploy lifelike brand ambassador avatars. TrueFan AI reported revenue of Rs 17.1 crore (approximately $2 million) in FY25. Revenue grew 131% year-on-year.
- Lowdown: How the Supreme Court’s draft AI rules would govern Indian courts
The Supreme Court has released draft regulations that would govern AI use across India's courts while prohibiting AI from making judicial decisions. The post Lowdown: How the Supreme Court’s draft AI rules would govern Indian courts appeared first on MEDIANAMA .
- India to use AI for machine-readable standards: Consumer Affairs Secretary
Machine-readable standards translate regulatory requirements into structured digital rules that computer systems can process directly, enabling automatic compliance verification without manual intervention
- What is Dreambeans, Google’s new AI app to help users stop doomscrolling?
What is Dreambeans, Google’s new AI app to help users stop doomscrolling?
- Tencent Opens WeChat to Handset Makers’ AI Assistants
Tencent Opens WeChat to Handset Makers’ AI Assistants Caixin Global
- More US firms turn to China’s DeepSeek over pricey Silicon Valley AI
Chinese artificial intelligence start-up DeepSeek took the top spot on a major US business spending index in June, as more companies swap out expensive American options like OpenAI and Anthropic in favour of more affordable alternatives. According to a “trending software vendors” list from New York-based corporate spending platform Ramp – which tracks when businesses buy from a software vendor for the first time – DeepSeek’s rise placed it ahead of event-management platform PheedLoop and...
- DeepSeek gains traction among US businesses, report shows
DeepSeek's privacy policy states it stores and processes personal data in China.
- A Chinese robotics start-up beat Nvidia on a global AI ranking. Is a new tech war brewing?
As artificial intelligence steps out of the digital realm and into the real world, the race to build the embodied “brains” powering next-generation robots has become the newest battleground in tech competition between China and the United States. Two days after US chip giant Nvidia launched its Cosmos 3 model – designed to help physical AI “think before it acts” – a Chinese start-up stole the spotlight. On Wednesday, Hangzhou, Zhejiang province-based Spirit AI said its foundation model for...
- ChatGPT's memory is getting better, especially if you're on the free tier
OpenAI has significantly improved the chatbot's "dreaming" architecture.
- NVIDIA AI Releases Nemotron 3 Ultra: An Open 550B Mixture-of-Experts Hybrid Mamba-Transformer for Long-Running Agents
NVIDIA AI Releases Nemotron 3 Ultra: An Open 550B Mixture-of-Experts Hybrid Mamba-Transformer for Long-Running Agents MarkTechPost
- NVIDIA Nemotron 3 Ultra released: fast, intelligent, and open
NVIDIA releases Nemotron 3 Ultra, a fast and intelligent open model.
- Nemotron 3 Ultra now available on AI Gateway
Nemotron 3 Ultra from Nvidia is now available on Vercel AI Gateway . Nemotron 3 Ultra is an open Mixture-of-Experts reasoning model built for orchestrating long-running agent workflows, with a 1M token context window. The model targets multi-turn agent workflows: planning, tool use, sub-agent delegation, and error recovery. Throughput reaches up to 350 tokens per second, with up to 30% lower cost on agentic tasks. To use Nemotron 3 Ultra, set model to nvidia/nemotron-3-ultra-550b-a55b in the AI SDK . AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-provider uptime. It includes built-in custom reporting , Zero Data Retention support , dynamic provider sorting by latency and cost , and more. AI Gateway reflects provider pricing with no markup and does not charge a platform fee on inference, including on Bring Your Own Key (BYOK) requests. Learn more about AI Gateway , view the AI Gateway model leaderboard or try it in our model playground . Read more
- SEO for GTM: Scale Content with AI Workflows
Learn how SEO integrates into GTM strategies, boosts visibility, and scales content production with Copy.ai's AI-powered workflows.
- Google brings local AI agents to laptops with Gemma 4 12B
Google has released new tools that allow developers to run agentic AI workflows locally using Gemma 4 12B, a 12-billion-parameter model from Google DeepMind. In a blog post, the company said the model, combined with the Google AI Edge stack, can be used to build and test applications on everyday machines. The model-runtime combination supports capabilities such as autonomous data processing, visual insight generation, webpage creation, and tool use. The release includes Google AI Edge Gallery for macOS, where developers can use Gemma 4 12B to generate and run scripts for tasks such as data analysis. Google also said its Eloquent voice dictation and editing app now runs fully on-device on macOS, with support for local transcription and voice-driven text editing. Google has also expanded LiteRT-LM, its lightweight command-line tool for running language models locally, with a new serve command. The company said this allows the CLI to act as a local LLM server and lets developers connect Gemma 4 12B to standard tools, SDKs, and frameworks through a local endpoint. “Your data stays on your device while maintaining reliable responsiveness, utility, and cost efficiency,” the company said in the blog post. The announcement comes as enterprises are looking beyond large, general-purpose models for some AI workloads. Gartner predicted that by 2027, organizations will use small, task-specific AI models at least three times more than general-purpose large language models, citing demand for more contextualized and cost-effective AI systems. Challenges to overcome But running agents on employee devices brings a number of problems. Companies must work within the limits of endpoint hardware, which can restrict the size of models that run effectively and the number of model instances that can operate at one time. “While the AI can now fit on a laptop, enterprise IT infrastructure is largely unprepared to manage it,” said Rishi Padhi , principal analyst at Gartner. “Even highly optimized models like the Gemma 4 12B require around 16GB of unified memory or VRAM to run alongside standard applications. Many standard-issue enterprise laptops lack the memory bandwidth and NPUs/GPUs required for fluid, multi-turn agentic execution.” Anand Joshi , AI analyst at TechInsights, said local deployment also changes the nature of the workloads. On a PC, search may mean finding information across internal folders and files. In a data center, the same function could involve searching the internet or querying a large database such as SQL. “The framework for local deployment of agentic AI is different from that of a data center,” Joshi said. “The models are smaller; you can run only one instance of a large model at a time. You are limited by memory, CPU, and so on.” Security and governance are also likely to become bigger concerns as AI agents move closer to enterprise endpoints. Agentic AI is designed to take actions, creating new security risks when local models are given access to employee files or allowed to interact directly with applications and scripts. “Sandboxing these agents without breaking their utility is still a major operational challenge,” Padhi added. “And all this while enterprises need to audit AI usage for compliance and security. When inference happens entirely offline, capturing logs, tracking model drift, and ensuring employees are using the approved, compliant ways for a model becomes incredibly difficult.” The cost tradeoff Running AI agents locally could reduce some cloud inference costs, but the savings may be offset in the near term by higher spending on endpoint hardware and management. “First and foremost, it is an OpEx-to-CapEx shift, as it shifts that financial burden by forcing accelerated hardware refresh cycles for premium PCs or edge devices,” Padhi said. “It would require buying expensive, high-memory laptops for employees at a time when memflation in the hardware industry is already driving up end-user average selling prices for laptops.” Many enterprises refreshed PCs in 2025 to support Windows 11, but at that point, most AI inference still ran in the cloud, and the case for on-device AI remained unclear, Padhi said. Enterprises may therefore move cautiously, buying AI-capable PCs only where local inference has a clear business case. Over time, however, on-device AI could make enterprise AI spending more predictable by reducing exposure to variable cloud inference bills. The tradeoff is that companies may face a higher baseline cost for equipping and managing employees’ devices. Complementing cloud AI For enterprises, local AI is unlikely to replace cloud-based AI outright. Analysts said local AI is more likely to be used for workloads that benefit from endpoint processing, especially when applications must operate offline or when privacy and response times are critical. “For local agentic AI to proliferate, the use cases on edge will have to complement data center/cloud use cases,” Joshi said. “I don’t expect local agentic AI to replace cloud AI, but it has potential to take a slice away from the cloud, and models like Gemma are significant steps towards enabling that.” The market, Joshi added, is still determining where local AI fits best. “I estimate that use cases that require privacy or have strict latency needs will move to local node first, with further migration of others in the next 2-3 years,” he said. Padhi said model placement will depend on the privacy requirements of a workload, the computing power it needs, and where the relevant data resides. Tasks such as code generation or analysis of local files could increasingly run on employee devices, while enterprise-wide RAG systems and more complex AI workflows are likely to remain cloud-based. The article originally appeared on InfoWorld .
- 전력망·수도·통신망이 AI를 품는다…앤트로픽, 150개 인프라 기업에 글라스윙 문 열어
앤트로픽은 3일 AI 기반 취약점 탐지 프로그램인 ‘프로젝트 글래스윙(Project Glasswing)’에 150개 기업을 추가로 참여시킨다고 발표했다. 새롭게 참여하는 기업은 전력, 수도, 의료, 통신, 하드웨어 등 국가 핵심 인프라 분야를 중심으로 구성됐다. 분석가와 보안 업계는 이번 조치를 긍정적으로 평가했다. 취약점 탐지에 참여하는 기업이 많을수록 더 많은 보안 결함을 발견할 수 있기 때문이다. 다만 업계가 더 주목하는 문제는 현실적인 과제인 ‘병목 현상’이다. 프로젝트 글래스윙 과 주요 AI 기업들이 추진하는 유사 프로젝트가 취약점 발견 건수를 현재보다 10배 이상 늘릴 경우, 공급업체들이 이를 적시에 분류하고 패치할 수 있을지가 새로운 과제로 떠오르고 있다. 공급업체들은 그동안 알려진 보안 취약점을 수정하는 데도 느린 대응으로 지적받아 왔다. 최근에는 마이크로소프트(MS)가 보안 연구원과 공개적으로 충돌하기도 했다. 해당 연구원은 MS의 대응이 지나치게 늦다고 판단해 취약점을 공개했다. 설령 공급업체들이 증가하는 취약점 처리 속도를 따라간다고 해도, 기업 보안관제센터(SOC)가 쏟아지는 패치를 모두 소화할 수 있을지는 또 다른 문제다. 또한 자동화 기술을 활용해 패치를 생성할 경우, 최고정보보호책임자(CISO)들이 이를 별도의 수동 검증 없이 배포할 만큼 신뢰할 수 있을지도 불확실하다. 일반적으로 CISO는 자동화 결과를 쉽게 신뢰하는 편이 아니다. 앤트로픽은 신규 참여 기업 발표 블로그를 통해 “참여 기업들의 공통점은 코드베이스가 공격받을 경우 치명적인 결과를 초래할 수 있다는 점”이라며 “대부분의 파트너는 대규모 공격이 발생할 경우 1억 명 이상의 사람에게 영향을 미칠 수 있으며, 이는 국가 안보와 국제 안보 모두에 중대한 파급효과를 가져올 것으로 보고 있다”고 설명했다. 이어 “이번 확장은 AI가 모든 소프트웨어를 더욱 안전하게 만들고, AI가 사이버보안의 핵심 전제를 어떻게 바꿀 수 있는지 업계가 대비하도록 지원하기 위한 장기 전략의 다음 단계”라고 밝혔다. 프로젝트 글래스윙은 지난 4월 7일 처음 공개됐다. 초기 참여 기업으로는 아마존웹서비스(AWS), 애플, 브로드컴(Broadcom), 시스코, 크라우드스트라이크, 구글, JP모건체이스, 리눅스 재단, 마이크로소프트(MS), 엔비디아, 팔로알토네트웍스가 참여했으며, 이후 옥타(Okta)도 참여 사실을 확인했다. 패치 개발 병목 현상 패치 병목 문제는 해결하기 쉽지 않은 과제다. 아무리 규모가 큰 공급업체라고 해도 보안 취약점을 수정하고 패치를 배포하는 데 투입할 수 있는 자원에는 현실적인 한계가 있기 때문이다. AI 보안 기업 코니퍼스AI(Conifers.ai)의 CEO 톰 핀들링은 “가장 큰 문제는 적응력”이라며 “취약점이나 보안 약점이 발견되면 방어 조직은 공격자가 동일한 정보를 악용하기 전에 이를 검증하고 우선순위를 정한 뒤 수정해야 한다. 특히 검증 단계가 매우 중요하다”고 설명했다. 핀들링은 이어 “직접 해당 도구를 테스트해 본 결과 상당수의 오탐(False Positive)이 발견됐다”며 “이는 기업이 모든 탐지 결과를 즉시 조치해야 하는 사안으로 간주할 수 없다는 의미”라고 말했다. 그는 또한 “기업은 의미 있는 신호와 불필요한 노이즈를 신속하게 구분할 수 있어야 하며, 실제 문제를 중심으로 프로세스와 개발 워크플로, 패치 운영 체계를 조정해야 한다”고 강조했다. 핀들링은 “기업이 주목해야 할 가장 중요한 지표는 발견된 취약점 수 자체가 아니라 신뢰할 수 있는 문제가 확인된 이후 얼마나 빠르게 대응할 수 있는지일 수 있다”며 “일부 조직의 경우 이러한 대응 주기가 여전히 수개월에 달한다”고 설명했다. 이어 “이 대응 시간을 얼마나 단축하느냐에 따라 AI 기반 취약점 탐지가 실제로 보안 방어력을 향상시킬지, 아니면 보안 노이즈의 양과 속도만 증가시키는 결과로 이어질지가 결정될 것”이라고 분석했다. 해결이 아닌 대응의 문제 컨설팅 기업 액셀리전스(Acceligence)의 저스틴 그라이스 CEO는 프로젝트 글래스윙의 참여 기업 확대가 보안 취약점 문제가 줄어들고 있다는 사실보다, 그 문제가 어떻게 변화하고 있는지를 CISO들에게 보여주는 사례가 될 수 있다고 평가했다. 그라이스는 “사이버보안이 취약점 발견의 문제로 여겨져 왔다는 것은 잘 알려진 사실”이라며 “하지만 AI는 그동안의 진짜 문제가 취약점 발견이 아니라 대응과 해결(remediation)이었다는 점을 보여주고 있다”고 설명했다. 이어 “업계는 이미 취약점 검증, 우선순위 지정, 패치 개발, 테스트, 배포를 충분히 빠르게 수행하는 데 어려움을 겪고 있다”며 “보안팀이 취약점 탐지를 담당하고 IT 부서나 사업 부서가 실제 패치를 담당하는 구조라면 상황은 더욱 악화될 수 있다”고 말했다. 그라이스는 “AI가 인간보다 10배, 100배 빠르게 취약점을 찾아낼 수 있다면 병목 현상은 단순히 다음 단계로 이동할 뿐”이라며 “기업은 실제로 대응할 수 있는 수준을 훨씬 넘어서는 취약점을 인지하게 되는 난처한 상황에 직면할 수 있다”고 분석했다. 이어 “AI는 사이버보안을 가시성(Visibility)의 문제에서 실행(Execution)의 문제로 바꾸고 있다”고 진단했다. 또한 우려스러운 전망도 내놨다. 그라이스는 “AI는 기업을 더욱 안전하게 만드는 동시에 더 큰 부담을 안길 수도 있다”며 “기업은 전례 없이 높은 수준의 위험 가시성을 확보하게 되겠지만, 동시에 그 위험 규모가 실제로 얼마나 큰지도 확인하게 될 것”이라고 말했다. 자동화 신뢰 확보가 관건 IDC의 AI 보안 부문 연구 책임자인 그레이스 트리니다드는 기업이 직면한 병목 현상을 해결하기 위해서는 광범위한 자동화가 필요하다고 평가했다. 다만 사이버보안 담당자들의 신뢰 부족을 고려하면 공급업체들은 각 패치의 신뢰도를 수치화해 제시할 수 있는 엄격한 체계를 마련해야 한다고 강조했다. 트리니다드는 “패치에 신뢰도 점수를 함께 제공하는 것은 새로운 개념”이라며 “기업은 자사 환경에 영향을 미치는 취약점을 식별하고 우선순위를 정한 뒤 적절히 대응할 수 있어야 한다”고 설명했다. 이어 “우리는 아직 준비되지 않은 새로운 역량을 익히고 있다. 바로 자동화 기술을 어떻게 신뢰할 것인가의 문제”라며 “현재와 같은 속도로 움직여야 하는 상황에서는 신뢰가 깨지는 사례도 발생할 수 있다”고 말했다. 또한 “신뢰도 평가는 반드시 투명성을 기반으로 해야 한다”며 “사람에게 설명할 수 없을 정도로 복잡한 방식으로 신뢰도를 산정해서는 안 된다”고 강조했다. 트리니다드는 앤트로픽이 신규 참여 기업 150곳 모두가 프로젝트 접근 권한을 얻기 전에 보안 요건을 충족해야 한다고 밝힌 점도 언급했다. 하지만 그는 “어떤 보안 요건인지 아무도 알지 못한다”며 “이 같은 설명만으로는 신뢰를 높이기 어렵다”고 지적했다. 한 가지 대안으로는 보안 업체가 스스로를 평가하는 것이 아니라 신뢰할 수 있는 제3자 기관을 활용하는 방안이 제시된다. 기업용 소프트웨어 기업 워크데이(Workday)는 이미 유사한 접근법을 도입했다. 워크데이는 미터 ATLAS(MITRE ATLAS)와 같은 공개 표준을 활용하는 독립 검증 서비스를 통해 자사 플랫폼에서 운영되는 AI 에이전트의 보안성과 규정 준수 여부를 검증하고 있다. 현재는 보안 검증에 초점이 맞춰져 있지만, 향후 신뢰도 평가에도 같은 개념을 적용할 수 있을 것으로 보인다. 참여 기업 확대가 불러온 보안 우려 프리랜서 기술 분석가 카미 레비는 프로젝트 글래스윙이 참여 기업 150곳을 추가로 확대하는 것이 궁극적으로 얼마나 효과를 낼 수 있을지에 대해 보다 회의적인 시각을 보였다. 레비는 “프로젝트 글래스윙의 핵심 목적은 앤트로픽이 엄격한 검증을 거친 소수의 공급업체와 긴밀히 협력해 기존 보안 기술과 프로토콜로는 대응하기 어려운 새로운 유형의 대규모언어모델(LLM) 보안 위협에 대한 방어 체계를 구축하는 데 있었다”고 설명했다. 이어 “참여 대상을 수백 개 기업으로 확대하면 더 많은 전문가의 지식을 활용해 방어 체계를 강화할 수 있다는 장점이 있다”면서도 “동시에 정보 유출 가능성에 대한 상당한 우려도 함께 커진다”고 지적했다. 특히 “이는 이미 동일한 모델과 관련해 두 차례의 정보 유출 사례를 보고한 기업에서 나온 결정”이라고 언급했다. 레비는 “이상적인 상황이라면 앤트로픽은 이번 대규모 확장 발표와 함께 코드가 잘못된 사람의 손에 넘어가지 않도록 내부 보안 프로토콜을 강화하는 별도의 계획도 공개했어야 한다”고 말했다. 이어 “훨씬 더 많은 연구자를 참여시키는 것은 잠재적 공격자들에게 공격 대상이 크게 늘어날 것이라는 신호를 줄 수 있으며, 향후 보안 침해에 대한 우려를 해소하지도 못한다”고 분석했다. dl-ciokorea@foundryco.com
- Asana launches AI ‘chief of staff’ to keep projects on track
Asana has launched an AI personal assistant that can track various data sources to alerts users when a work project runs into problems and recommends next actions. It’s one of a range of product announcements made Thursday at the company’s Work Innovation Summit in London, including updates to its existing AI teammates product. These follow Asana’s recent acquisition of AI workflow automation software vendor StackAI for $75 million. Asana Dash is described as an “AI chief of staff” that can help users stay up to date on work projects by accessing information in Asana as well as across email, calendar and team messaging apps, said Arnab Bose, Asana’s chief product officer. “Keeping people in their ‘zone of genius’ and hooking up all of these unstructured signals to the structure of Asana — that’s what Dash does best,” said Bose. The AI assistant can access the same Asana project information as the user, and can flag when problems occur that could push a project off-track. Dash can then act to address problems, such as posting messages within Asana on behalf of the user or directing an AI teammate to take action. (Dash will ask the user before making any changes.) “Asana is building on recent acquisitions, and earlier investment in a graph database focused on human connections — the Asana Work Graph — and its position within a well-integrated flow of work to deliver to each worker an executive assistant rooted in the context of their job,” said Wayne Kurtzman, IDC research vice president. The Dash personal assistant is enabled by an expanded Asana work graph — the data model related to work carried out by teams in the application. Asana has in the past been more focused on tasks, projects, portfolios, and goals, said Bose, but the work graph now includes new sources of data, linking to employee calendars and accessing meeting transcripts, for instance, alongside other documents and databases. There are also updates to the AI teammates feature — collaborative AI agents that multiple human coworkers can interact with — which are now more powerful, said Bose. This includes additional skills and integrations with third-party apps such as Gmail, Slack, Outlook, Figma, and Canva. As for the StackAI acquisition, Bose said it allows Asana to extend the reach of AI agents into a variety of business apps more easily and reliably, building ] on Asana’s “system of action” function. The latter tracks work carried out across an organization, he said, and can automate the complex processes that make up many enterprise workflows. “If you look at StackAI’s website, the thing that they are really, really great at is building these complex, multi-step processes,” said Bose. The aim is to combine StackAI’s agent builder with integration expertise agents already available in Asana. “So, the idea is when an AI teammate or Dash recommends the next best action, they will be able to choose downstream actions based on the portfolio of approved workflows that you’ve built out in StackAI.” Overall, the announcements help Asana provide a platform that combines agents and workflow automation with AI assistance that aids humans to work more effectively, said Bose. “Our terminology for this is a ‘human-agent operating system,’ because automation, I feel, is a little reductive in the sense that there are some things that are fully automated, but a lot that you’d want a human being and an AI agent to coordinate on and align on,” he said. Asana did not immediately respond to a request for pricing and availability details for Dash.
- Apple reportedly planning to use Nvidia chips for Gemini-powered Siri
Apple's upcoming AI-powered Siri may leverage Google Cloud's Nvidia Blackwell B200 chips and Google's Gemini AI models. This strategic move aims to enhance Siri's capabilities, with Apple reportedly enabling Nvidia's confidential computing to encrypt user data during processing. The integration of these advanced technologies is anticipated for WWDC 2026.
- Nvidia’s Jensen Huang to meet Korean AI startups during Seoul visit
Nvidia’s Jensen Huang to meet Korean AI startups during Seoul visit 매일경제
- Samsung's updated Health app unsurprisingly comes with new AI-powered features
Samsung will roll out an update for its Health app before launching its new Galaxy Watches.