События и конференции
Анонсы и материалы про мероприятия отрасли.
Материалы на русском языке; развёрнутая версия содержит полный текст, ссылка на страницу издания — внизу карточки.
Анонсы и материалы про мероприятия отрасли.
Материалы на русском языке; развёрнутая версия содержит полный текст, ссылка на страницу издания — внизу карточки.
When Hugging Face got hit last week, co-founder Clement Delangue suspected a frontier lab, given the agent's sophistication. He was right. Delangue said on X that after a day working with OpenAI he strongly believed there was no malicious intent and that it was mind-blowing the whole thing had happened autonomously.The two OpenAI models that broke into Hugging Face last week did not breach it through malice or superintelligence. They breached it through credentials and permissions they should never have been able to reach, a non-human identity failure that is the oldest problem in security rather than the newest one in AI, and the one every enterprise can actually fix.OpenAI disclosed on July 21 that two of its models, GPT-5.6 Sol and an unreleased, more capable model, were running a cyber benchmark called ExploitGym with their safety refusals switched off, and inferred that the answer key sat in Hugging Face's production database. Getting there took two different failures. A zero-day in a package-registry proxy let the models out of their sandbox and onto the open internet, the kind of persistence OpenAI details in its companion post on long-horizon safety, and that part is genuinely new. The breach of Hugging Face itself came the ordinary way. OpenAI's own account is that the models chained stolen credentials and further zero-days into a remote code execution path, after a series of privilege escalation and lateral movement steps. The exotic part got them to the door, and credentials walked them through it.Hugging Face also disclosed last week that an autonomous agent had harvested cloud and cluster credentials scoped broadly enough to reach multiple internal clusters, then left a trail of more than 17,000 recorded events across short-lived sandboxes over a weekend. Both disclosures describe the same escalation. An agent lands somewhere it should not be, finds credentials scoped far wider than any task requires, and uses them to move. These are two accounts of one incident, not two attacks. The agent Hugging Face watched was OpenAI's models, and both companies describe the same ordinary escalation.The version of this in a typical enterprise is worse, not better. OpenAI and Hugging Face are among the most security-mature organizations in the industry, and both still needed the intrusion to happen before they could see it. The average company wiring agents into Copilot or an internal assistant has neither the identity inventory nor the behavioral monitoring those two brought to bear. The same breach in a normal company would not be contained in days, it would simply go unnoticed.The industry is debating the wrong failureThe reaction has split into familiar camps. Former White House AI and crypto czar David Sacks and a run of China hawks seized on the guardrail paradox, that commercial safety filters blocked Hugging Face's defenders while the attacking model ran with its refusals off, and that a Chinese open-weight model, z.ai's GLM 5.2, was what finally let the team finish its forensics. Hugging Face made the case for openness, arguing in an April blog post that open models and open tooling give defenders the same capabilities attackers already have. Both arguments are about the model, and neither touches the mechanism. Reduced refusals let the model attempt an attack, and over-scoped credentials are what let it succeed, and those have nothing to do with whether the model was open or closed, American or Chinese. Making a frontier model provably safe is a multi-year alignment problem no customer can buy or accelerate, while scoping an identity is a configuration change a team can ship this sprint. The industry is being urged to fixate on the part of this it cannot control and to treat the part it can as a footnote.Forrester reached the same read. In a blog on the incident, its analysts argue that security architectures which assume benign intent will miss this failure mode, because an agent can pursue an authorized goal through
Record Google Cloud revenue, but investors are uneasy about growing capex commitments
Despite orbital ambitions, has sights set on gigawatt campus
IBM cut its full-year sales outlook on Wednesday after reporting a sharp drop in demand for its mainframe business, lowering its revenue growth target to four to five percent from a prior forecast of more than five percent. The company also trimmed its software unit guidance, with CFO Jim Kavanaugh telling Bloomberg that annual software […] This story continues at The Next Web
OpenAI president Greg Brockman called Moonshot AI’s Kimi K3 “pretty good” in a Bloomberg interview on Tuesday, a rare public acknowledgement from a US frontier lab that a Chinese rival has produced a competitive model. Brockman said it is “too early” to determine whether Moonshot trained K3 by distilling outputs from OpenAI’s own systems, a […] This story continues at The Next Web
Meta will not face a second jury trial over claims that its social media platforms are addictive to minors after the teenage plaintiff at the centre of the case chose to dismiss his claims. The boy, a 15-year-old from Panama City, Florida, was set to go to trial on July 27 in Los Angeles Superior […] This story continues at The Next Web
Federal agencies have committed more than $5 billion to the Genesis Mission, an Energy Department-led effort to use artificial intelligence to accelerate scientific research, White House science adviser Michael Kratsios announced on Wednesday. The initiative selected 278 projects from more than 5,000 applications, Energy Secretary Chris Wright said at a summit in Washington. More than […] This story continues at The Next Web
You spend weeks tuning an AI chatbot. Answers are accurate. Stakeholders sign off, and you ship it. Three months later, the system is confidently wrong about a third of what users ask. Nobody changed the model, and nobody touched the prompts. The world moved, pricing changed, a policy updated, a product spec shipped a new version, and the underlying knowledge store didn't move with it.This is not a hypothetical. It's one of the most common production failure modes in enterprise AI right now, and most data engineering teams don't have the right tooling to catch it, regardless of how the AI system retrieves the data.The failure that doesn't look like a failure An AI application doesn't care whether it's retrieving from a vector store, a document index, or an API call. Whatever the mechanism, nothing in a standard retrieval pipeline checks whether what it's serving is still correct. A stale pricing document retrieves just as confidently as a current one, because the system is scoring relevance or availability, not correctness. A record with a silently missing field passes through just as cleanly as a complete one, for the same reason.So the failure is invisible by design. Outdated or incomplete data still scores high on relevance, or passes every check a data pipeline was built to run. The model answers with full confidence because the retrieved context looks authoritative. Every dashboard you're watching stays green. The system looks like it's working. It's just wrong.I’ve watched a similar version of this happen outside the AI context, in a fintech pipeline. An upstream system changed a field without notifying downstream users. The pipeline did not fail; it simply propagated bad values into dashboards because the system only checked whether the job completed, not whether the data was still correct. The issue surfaced only when a customer noticed something inconsistent. By then, the bad data had already moved downstream. Whether it's a document that's gone stale or a field that's gone silently missing, the failure shape is the same: the absence of an error is not the presence of correctness, and without building proper validation layers, nothing in the pipeline could identify the problem.Why this is a data engineering problemTeams that hit this failure tend to misdiagnose it, and they tend to do it twice.Blaming the model: The first instinct is to blame the model, try a different LLM, adjust the prompt. The real problem lies further upstream, at the data engineering layer, the same instinct behind the fintech failure above: monitoring built for the pipeline, not the data.Blaming the retrieval layer: Once the model's ruled out, the next instinct is to blame the retrieval or context layer instead and buy a better one. The timing isn't a coincidence: as enterprises push these systems into the real production world, this gap is exactly what's starting to surface, and the vendor response has been everywhere. AWS just entered the "context layer" race with a knowledge graph that learns from agent usage. Snowflake's new Horizon Context and Cortex Sense target the exact symptom this piece opened with: agents giving confident wrong answers because nothing governs the business logic underneath them. Both are real responses to a real problem, but they sit one layer above it; a knowledge graph still depends on whatever feeds it.The real problem lies further upstream, at the data engineering layer. Teams check whether a job ran, not whether the data it moved is still true, an instinct that predates AI by years. Monitoring is built for the pipeline, not for the data. What's actually missing: Data observabilityData observability is a well-known concept that doesn't get enough attention in how it's actually implemented. The relevant metric isn't a percentage — it's coverage: what fraction of critical datasets have lineage that's actually queryable, versus only living in someone's head.Uber built a dedicated data quality and observability platfor
Meta has hired Assaf Keren as its next chief information security officer, filling a vacancy created when Guy Rosen announced his departure in June after 13 years at the company. Keren joins this week from software platform Qualtrics, where he spent two years as chief security officer, and previously held the same title at PayPal. […] This story continues at The Next Web
Monday.com is cutting roughly 20 percent of its global workforce, about 620 people, as the Israeli project management company restructures around what it calls its AI Work Platform. The company disclosed the plan in a Form 6-K filed with the US Securities and Exchange Commission on Tuesday, citing the need to support a leaner operating […] This story continues at The Next Web
Anthropic leaped to a $47 billion revenue run rate by May, compared to $9 billion in 2025. It’s the kind of growth that Menlo Ventures’ Matt Murphy says he’s never seen in 25 years of investing, not in the internet wave, not in mobile, not in the first cloud boom. Menlo led Anthropic’s $500M Series D, and Murphy has had a front-row seat as the company went from a pre-revenue, […]
Acquisition is the largest-ever in data centers
Arrakis, a London and Paris startup building what it calls an AI operating system for industrial companies, has emerged from stealth with $38 million in total funding and a thesis that the biggest returns from artificial intelligence will come from factories and supply chains, not office software. The company raised a $30 million Series A […] This story continues at The Next Web
Battery-electric registrations across 17 European markets hit 275,060 in June 2026, a jump of nearly 40 percent compared to the same month last year, according to the E-Mobility Europe bulletin published by New AutoMotive. The figure pushed EVs past 25 percent of all new car sales in those markets for the first time. It also […] This story continues at The Next Web
Cisco’s new Antares models are small enough to run on your own machines. And, it claims, they beat Google’s Gemini and rival GPT-class systems at finding bugs. It is releasing them open-weight, though it is vetting who gets access. The pitch from Cisco is a quiet rebuke to the frontier-model arms race. You do not […] This story continues at The Next Web
Supporting Poland’s digital ambitions
Samsung used its Galaxy Unpacked event in London on Tuesday to launch six products at once, its broadest hardware refresh in years. The lineup includes the Galaxy Z Fold8 Ultra, the first time Samsung has brought its Ultra designation to a foldable, alongside a reimagined Z Fold8 with new display proportions, a slimmer Z Flip8, […] This story continues at The Next Web
Both UAE-based firms said the deal would accelerate AI deployments in the Gulf state
Americans want the AI boom. They just do not want it on their street. A new poll finds most US residents would rather not live near an AI data centre. Yet the same buildings quietly bankroll schools where they cluster. More than half of US residents, 53%, oppose building an AI data centre in their […] This story continues at The Next Web
The province claims competitive advantages such as energy availability, geographic location, and presence of long-range connectivity infrastructure
As carrier continues to push for copper retirement
The founder now asking enterprises to trust AI with their laptops once built one of Silicon Valley’s most notorious surveillance tools. Roi Tiger co-created Onavo, the app Meta turned into a scheme to spy on its rivals. His new company, Glow, wants to do something close to the opposite. Glow has emerged from stealth with […] This story continues at The Next Web
The artificial intelligence industry has no shortage of users. The harder problem is turning that usage into a sustainable business. As generative AI applications spread across consumer and enterprise markets, developers are confronting an unusual combination of opportunities and pressures. AI can make software faster to build and easier to distribute, but the costs of […] This story continues at The Next Web
Company planning 197MW project in the Atacama Desert
The self-thinking mast can automatically adjust the antenna
Is contracting energy from Georgia Power Company for project
First gigawatt expected in H1 2027
Search for requirements management tools for medical device development and you’ll find plenty of content arguing that the established platforms are too heavy for modern teams. Much of it comes from vendors with a stake in that conclusion. In a regulated industry, the question that matters is which tool produces a record you can defend […] This story continues at The Next Web
NEURA Robotics is opening ‘gyms’ where robots train under real-world conditions, starting with two German universities. Its bet is that the thing holding humanoids back is not intelligence, but a shortage of real experience. The German robotics firm NEURA has a theory about why robots still fumble in the real world. The problem is not […] This story continues at The Next Web
Revolut confirmed on Tuesday that a secondary share sale has valued the digital bank at $115 billion, a 53 percent jump from the $75 billion it reached in November 2025. The sale priced shares at $2,017 each, according to Bloomberg. The valuation makes Revolut the most valuable private fintech company in the world by a […] This story continues at The Next Web
With industrial leasing growing 44 percent YoY
The ChatGPT maker has put two banking chiefs on both its nonprofit and for-profit boards: Nubank’s David Vélez and BNY’s Robin Vince. It is the kind of Wall Street ballast a company assembles when it is getting ready to face public investors. OpenAI is not a public company yet. Its latest board picks suggest it […] This story continues at The Next Web
The acquisition will enable the company to strengthen its FTTH network in Peru
The pitch from data broker ISBNdb is blunt: the world’s best AI training data is sitting on a shelf. The catch is that getting at it means slicing the spine off millions of books, then never admitting which lab paid for the job. AI has a pollution problem of its own making. So much of […] This story continues at The Next Web
Substack has a name for the moment you realise a post you admired for its human voice actually came from a bot: Claudefishing. Now it is handing readers a button to catch it, powered by the AI detector Pangram. The newsletter platform has launched an AI-detection feature. In a pointed post titled “Against Claudefishing,” chief […] This story continues at The Next Web
Sites did not have to go through the rezoning process
While building infrastructure is important, protecting its performance for the next twenty years is what truly creates value
OpenAI has announced Presence, a new enterprise product for deploying and managing AI agents across customer-facing and internal business workflows. The offering is designed for eligible enterprise customers that want agents to answer questions, access company systems, take approved actions and escalate to human workers while operating under company-defined policies, permissions and evaluation standards.Presence is available immediately through a limited general availability program. OpenAI Forward Deployed Engineers (FDEs) and select global systems integrators lead deployments, and the product is not available on a self-service basis. As for using non-OpenAI models, such as the powerful and increasingly popular Chinese open weights alternatives like GLM-5.2 and Kimi K3, an OpenAI spokesperson clarified that "Presence uses OpenAI models for the core agent, while allowing customers to connect third-party models and services through APIs for guardrails, tools, and other parts of their workflow."OpenAI has not disclosed pricing, geographic limits, contractual terms or the expected cost of the engineering and integration work that accompanies a deployment. I've asked an OpenAI spokesperson about pricing twice and am awaiting a response. I'll update when I hear back. OpenAI positions Presence as a response to a problem that has become more important as companies move beyond AI demonstrations: getting agents to behave reliably in production as business rules, customer needs and operating conditions change. Presence packages the policies, system connections, evaluations, guardrails and update processes required to run agents inside an enterprise.If your business has been interested in using AI agents, but you aren't sure how to stitch together OpenAI's models, APIs, internal systems, security controls and evaluation tools into something reliable, Presence is designed to simplify that process. Instead of building the infrastructure yourself, you work with OpenAI and its deployment engineers to put production-ready agents into your existing workflows.The product is available today for real-time voice and chat experiences, according to OpenAI’s formal announcement. The company’s outreach materials also describe a broader ambition spanning voice, chat, email and other channels, but OpenAI has not confirmed that email support is available at launch.A governed foundation for production agentsPresence brings together company knowledge, standard operating procedures, approved actions, simulations, evaluation tools, guardrails and escalation rules. Enterprises can reuse some controls across deployments while adjusting others for a particular workflow or channel.Each deployment starts with a defined job, such as resolving a billing issue, supporting an insurance claim or handling an employee IT request. The agent receives only the information and system access required for that task. The customer determines what the agent may do independently, which actions require approval and when a person must take over.Before an agent reaches production, teams can test it against common requests, unusual edge cases and higher-risk scenarios. Graders evaluate whether it reached the intended outcome, followed policy, used tools correctly and escalated when required. Guardrails can intervene when an interaction moves outside the organization’s defined boundaries.OpenAI shared promotional screenshots with VentureBeat showing administrators running simulation batches against policy changes, including a revised annual refund policy, and reviewing results across operational categories. Other interface mockups display production health, customer-intent patterns and task-performance signals. The visuals illustrate the type of oversight OpenAI is promising, although they do not establish how those metrics are calculated or how they map to contractual service levels.The product continues to monitor performance after launch. Production sessions, escalations and qualit
As BCIs move from laboratories towards commercial use, Neurochip.com founder Herbert Sim warns that unequal access could separate people not only by income or connectivity, but by physical and cognitive capability. At the 2026 World Artificial Intelligence Conference in Shanghai, Chinese President Xi Jinping warned that technological progress must not create “new historical injustices.” He called for […] This story continues at The Next Web
To defend an anti-AI Pope from claims a machine helped write his words, his camp reached for an unlikely tool: AI. An Australian firm has certified Pope Leo XIV’s writings as human-made, using a suite of the very detectors the technology has spawned. Pope Leo XIV has made AI one of his defining themes. His […] This story continues at The Next Web