AI News Digest

1. [10/10] Messi and Ronaldo Are Building Tech Portfolios. Mo Salah Is Playing a Different Game

Source: Wired | Published: Wed, 08 Jul 2026 21:08:26 +0000 (6h ago)

Slackbot's new capabilities provide a direct example of AI-powered service delivery and business process automation across critical enterprise platforms like Salesforce and DocuSign, enabling more efficient workflows from chat.

Lionel Messi and Cristiano Ronaldo are betting on AI, health tech, and startups. Mohamed Salah is taking a more traditional route beyond football.

https://www.wired.com/story/messi-ronaldo-tech-portfolios-salah-playing-a-different-game/

2. [10/10] Slack’s Slackbot can now pull your CRM data, generate charts, and send DocuSigns — all from a chat message.

Source: VentureBeat | Published: Wed, 08 Jul 2026 12:00:00 GMT (15h ago)

Slackbot's new capabilities provide a direct example of AI-powered service delivery and business process automation across critical enterprise platforms like Salesforce and DocuSign, enabling more efficient workflows from chat.

Five years and $27.7 billion after Salesforce acquired Slack, the two products are finally starting to function as a single system. On Wednesday, Slack launched an integration that connects Slackbot — the personal AI agent built into every workspace — to the entire Salesforce platform, including CRM data, Tableau analytics, Data 360 customer profiles, and a growing constellation of third-party applications, all through a single conversational prompt.The mechanism behind the expansion is a set of dedicated Model Context Protocol (MCP) servers from Salesforce that connect Slackbot to the company's Headless 360 infrastructure. In practical terms, a salesperson can now ask Slackbot for a customer's deal history, receive a live Tableau visualization of pipeline trends, update a CRM record, and trigger a DocuSign approval — without ever switching tabs or logging into another application. According to Slack, the Salesforce IT team has already used this architecture to save its 1,500-plus engineers "thousands of custom coding hours annually."The timing is not accidental. Slack is making this move amid escalating competitive pressure from Microsoft Teams, which claims 320 million-plus monthly active users and has Copilot embedded across the Office suite, and from Google, which continues to weave Gemini deeper into Workspace. And just days ago, The Information reported that some smaller companies are using Anthropic's Claude to replace Salesforce CRM entirely — one Atlanta-based property management firm with about 55 employees reportedly saved around $100,000 annually by building a custom replacement using Claude Code and Replit.Against that backdrop, Slack CMO Ryan Gavin sat down for an exclusive interview with VentureBeat to frame the announcement and argue that the company's future depends on an idea he calls "multiplayer AI" — and that the 25 years of customer data locked inside Salesforce is an asset no vibe-coded alternative can replicate.Why Slack's CMO believes 'multiplayer AI' is the next big enterprise battlegroundGavin's core argument is that the enterprise AI conversation has been stuck in single-player mode for too long, and that Slack is uniquely positioned to break it open."So much of what we've seen are just these incredible tools that have largely been single-player, incredible tools for individual productivity, helping people complete tasks and write code," Gavin told VentureBeat. "But as we've always known at Slack ever since our inception, work is a team sport. For AI to really take hold in the enterprise, it has to be multiplayer."The distinction matters commercially. Most AI assistants today — ChatGPT, Claude, Copilot — default to one-on-one conversations with a single user. A researcher queries a model, gets a response, and acts on it alone. The insight stays in a private chat window, invisible to colleagues. Gavin argues this creates a new version of the tab-switching problem that plagued pre-AI enterprise software, except now employees are also navigating dozens of individual agent interfaces on top of their existing applications."It's going to benefit almost no one if every enterprise application out there spawns hundreds of agent babies, and employees end up in a worse world than they were before," Gavin said.Slack's answer is to make Slackbot the orchestration layer. Because everything happens in shared channels, any action an agent takes — pulling a customer profile, flagging a deal risk, updating a Jira ticket — is visible to the entire team. A colleague can redirect, build on, or correct the agent's work in real time.How MCP and Salesforce's headless 360 platform power Slackbot's new capabilitiesThe technical backbone of the announcement is the Model Context Protocol, an open standard originally developed by Anthropic that defines how AI models discover and invoke external tools. MCP has seen rapid adoption across the AI tooling ecosystem. By early 2026, it had been adopted by Claude Code, Cursor, GitHub Copilot, and OpenAI's tooling, with managed hosting available from AWS, Cloudflare, and Vercel. As a DEV Community explainer puts it, MCP "is the closest thing the AI tooling ecosystem has to a standard."In this implementation, Salesforce exposes its platform capabilities — CRM records, Tableau visualizations, Data 360 customer profiles, Agentforce agents — as MCP servers. Slackbot operates as an MCP client, connecting to those servers and routing user queries to the appropriate back-end system. When a user asks Slackbot about a customer, the bot discovers which MCP tools are relevant, calls them, and synthesizes the results into a single response — all within the Slack conversation.Gavin explained the architecture in simple terms: "Salesforce is extending what has always been our open platform through our Headless 360 strategy — making all of these MCP endpoints available. And then Slackbot acts as an MCP client, connecting to those MCP servers and bringing all that data in within the confines of a trusted permission platform."That permission layer is critical. Slackbot respects each user's Salesforce permissions, meaning a marketing coordinator cannot accidentally access sales pipeline data they are not authorized to see. Validation rules, field-level security, and org-wide data boundary configurations carry over automatically. For admins, setup requires no custom integration code — Salesforce MCP servers can be discovered, installed, and governed from a single UI using the existing Slack-Salesforce connection.Salesforce first introduced the Headless 360 concept at its TDX developer conference in April, positioning it as an API-driven layer that exposes the platform's data, workflows, and governance controls so that software agents, rather than human users, can execute business processes directly. As CIO.com reported at the time, analysts viewed the move as an effort by Salesforce "to position itself as a central layer for managing agent-driven operations across different business functions."Slack says it's betting on openness, not on any single AI protocolWhen asked whether Slack is making a risky bet on MCP as a protocol — given that standards in AI tooling can shift rapidly — Gavin reframed the question entirely."We're not betting on MCP, per se. We're betting on what we've always bet on, which is that Slack is an open platform," Gavin told VentureBeat. "MCP happens to be the best agent-to-agent protocol that the industry is rallying around right now, but if something better came out tomorrow, you'd see the same pattern from Slack — we're going to stay open. MCP and APIs are simply tools that facilitate that."That open-platform philosophy is central to Slack's identity and, Gavin argues, its competitive differentiation. Slack already hosts more than 2,600 app integrations. The new MCP-native partner ecosystem includes Atlassian, Box, DocuSign, Canva, Lucid, Zoom, and more than 25 additional companies, each of whose agents can be added directly to shared Slack channels. MuleSoft Agent, now connected to Slackbot, helps manage integrations for the team — checking system health or surfacing critical error alerts in the same workspace where the team is already collaborating.But MCP is not without trade-offs. The protocol requires tool discovery on every connection, and large tool libraries can consume significant context tokens. One technical analysis noted that a server exposing 300 tools could cost 5,000 to 10,000 tokens per session before the model does any useful work. For an enterprise like Salesforce with hundreds of potential tools across CRM, analytics, and service platforms, careful filtering and segmentation of MCP servers become essential design decisions — a challenge the company will need to navigate as the ecosystem scales.Inside Slack's complicated relationship with Anthropic and the Claude questionPerhaps the most delicate topic in the interview concerned Slack's relationship with Anthropic, the AI lab behind Claude — and one of Slack's most visible power users. Just last week, Anthropic launched Claude Tag, a persistent AI teammate that works inside Slack channels, prompting confusion among Salesforce employees who worried it competes directly with Slackbot and Agentforce. The Information reported internal anxiety about whether Salesforce was welcoming a competitor into its own living room. Salesforce has financial reasons to maintain the partnership: the company reportedly expects to spend $300 million on Anthropic tokens this year and holds a stake in Anthropic.Gavin addressed the tension head-on, framing it as a feature of Slack's platform strategy rather than a threat."We're incredibly excited and bullish about what Anthropic is bringing into Slack. Period. End of statement," Gavin said. He noted that Anthropic "is building roughly 65% of their code with Claude in Slack," and pointed out that ChatGPT was originally built in Slack, as was Perplexity."Building nowadays happens in the open, and every company is going to be building in the open with tools like this, and you need a platform to build in the open," Gavin said.His argument is that feature overlap between Slackbot, Claude Tag, and other third-party agents is "actually a feature, not a bug" — a sign of a healthy platform rather than a competitive vulnerability. He compared it to an ecosystem where multiple products serve similar needs but win on craftsmanship, ease of use, and integration depth."One of the reasons Slackbot has been the fastest-adopted feature in Salesforce history is the simplicity, the approachability — underpinned by the trust that comes from having an agent that knows me, knows my tone, knows my work, knows my people, knows my data," Gavin said.The distinction Slack draws is structural: Slackbot has access to a user's full workspace context, Salesforce data, permissions, and connected applications by default. Claude Tag, by contrast, only sees the channels it is explicitly added to. For Slack's leadership, that asymmetry is the moat.How Slack plans to compete with Microsoft Teams and Google in the AI eraAsked directly about competitive positioning against Microsoft Teams and Google Workspace, Gavin pointed to Slack's open channel architecture as the differentiator no competitor can replicate."If you spend any time in Teams, it's a lovely tool for chat, direct messages, and video, but it has no platform for open communication across organizations," Gavin said. "Its SharePoint-based architecture is fundamentally limiting."He cited Shopify as an example, where an internal AI agent called River is deployed across approximately 4,400 channels serving 6,000 employees. He also referenced a Fortune report noting that Microsoft's own head of AI mandated that his team run on Slack rather than Teams — a pointed detail Gavin clearly relished. "There's a reason for that," he said. "We're in an era right now where openness matters, and all the other tools you mentioned, they're still relatively closed."The competitive pressure is real and intensifying. Microsoft has integrated Copilot across its entire productivity suite, giving it a distribution advantage that reaches virtually every Fortune 500 company. Google has been similarly aggressive with Gemini across Workspace. And new entrants are crowding the market: a startup called Viktor, which embeds AI agents inside Slack and Teams workspaces, recently raised a $75 million Series A led by Accel — with Slack cofounders Stewart Butterfield and Cal Henderson participating as angel investors.Box, one of the enterprise customers highlighted in the announcement, told Slack it aims to have its sellers complete 75 to 80 percent of their work inside Slack. Gavin repeated that figure as evidence that the platform is becoming the default workspace for entire organizations, not just engineering teams — a shift he believes accelerates as AI makes every employee a builder.Slack's biggest long-term play is making Salesforce's CRM useful to everyone in the companyGavin saved what he considers the most underappreciated element of the announcement for last: the democratization of Salesforce's CRM.For 25 years, Salesforce's CRM has been used primarily by sales, service, and marketing professionals — a relatively modest percentage of a company's total workforce. The promise of Slackbot as a conversational interface is that any employee, regardless of their role or technical fluency, can now query and act on CRM data simply by asking a question in natural language."What most people don't realize is that this democratization of CRM is going to take its usage from a modest percentage of employees to the entire enterprise," Gavin said. "When you can make systems like Data 360 or Agentforce for Sales accessible to the entire employee base — not just a percentage — think about how much more valuable those investments become."He cited Engine, a company that handles 800,000 customer inquiries a year, as an example. Previously, answering a customer inquiry required a specific employee with access to a specific tool to look up a customer's history. Now, anyone in the company can ask Slackbot and see a complete customer profile, review case history, and write updates — all without being retrained or learning a new interface. Engine's CEO Elia Wallen, in a statement sent to VentureBeat, described the integration as enabling employees to "make data-driven decisions and take action without leaving the conversation."The financial logic is straightforward: if Salesforce can make its platform useful to 100 percent of a customer's workforce rather than the 20 or 30 percent who currently hold licenses, the value of the existing Salesforce investment multiplies without requiring a proportional increase in spending. That pitch becomes especially potent at a time when CIOs are scrutinizing every line of their AI budgets.What analysts and CIOs should watch as Slack rolls out its biggest AI update yetThe announcement is a significant architectural evolution for Slack, but several questions remain unanswered.First, pricing. The company did not directly address whether Slackbot's MCP-powered Salesforce integration will require additional SKUs or license tiers. As Info-Tech Research Group analyst Scott Bickley cautioned when Headless 360 was first announced in April, "Salesforce's MO seems to be to announce new capabilities that require SKUs. CIOs should be asking about pricing now."Second, performance. Routing user queries through MCP servers to Salesforce back-end systems introduces latency that could affect the conversational feel Slack prides itself on. Neither the press release nor the interview disclosed SLAs for MCP tool calls — a gap that enterprise buyers will want addressed.Third, the competitive dynamics of the platform play. Slack's open-platform philosophy invites powerful partners like Anthropic and OpenAI into its ecosystem, but those same partners are building their own surfaces for enterprise work. Anthropic reportedly plans to expand Claude Tag to Microsoft Teams, email, and other project management tools — meaning the partner Salesforce is paying hundreds of millions a year is building the infrastructure to be useful without Slack at all.And fourth, the broader existential question facing all enterprise software: whether AI agents will ultimately reduce the need for CRM systems entirely. Gavin's pitch — that Slack makes CRM more valuable by making it more accessible — is the inverse of the bear case. The market will ultimately decide which thesis prevails.Salesforce reported record first-quarter revenue of $11.1 billion in fiscal Q1 2027, with Agentforce ARR surpassing $1 billion for the first time and combined AI and data ARR reaching $3.4 billion. Those numbers suggest the AI strategy is beginning to generate real revenue, even as the company navigates a market that remains uncertain about the long-term trajectory of legacy enterprise software."Slack has quickly moved from this beloved collaboration tool from the last ten years to now this multiplayer AI platform that we call a work operating system," Gavin said.Five years ago, Salesforce paid $27.7 billion for what was, at its core, a very good group chat application. On Wednesday, it started trying to prove that group chat was never the product — it was the foundation. In the age of AI agents, the most valuable real estate in enterprise software may not be the database where the data lives. It may be the conversation where the decisions get made.

https://venturebeat.com/orchestration/slacks-slackbot-can-now-pull-your-crm-data-generate-charts-and-send-docusigns-all-from-a-chat-message

3. [10/10] Anthropic brings Claude Cowork to mobile and web as usage data shows most users aren’t coding

Source: VentureBeat | Published: Tue, 07 Jul 2026 16:00:00 GMT (1d ago)

Anthropic's Claude Cowork expanding to mobile and web significantly enhances the accessibility of agentic workflows for a broader range of enterprise users beyond coders, supporting cross-regional operations and citizen developer enablement.

Anthropic on Tuesday launched Claude Cowork on mobile and web, expanding a tool that has quietly become the company's bridge between the developer-centric world of AI coding agents and the far larger market of knowledge workers who never open a terminal.The rollout, which begins in beta with Max subscribers before expanding to additional plans, marks a strategic inflection for Anthropic. It transforms Cowork from a desktop-only agent into a cross-device platform where tasks can start on a laptop, continue autonomously in the background, and be reviewed from a phone — even after the user closes the app entirely."Your work goes everywhere with you, and keeps going without you," Anthropic writes in its announcement.The timing is deliberate. Alongside the mobile launch, Anthropic published usage data from 1.2 million anonymized Claude Cowork sessions sampled between May 11 and May 31, drawn from more than 600,000 organizations. The data paints a striking picture: the overwhelming majority of what people do with Cowork has nothing to do with writing software.The biggest AI story nobody's talking aboutThe numbers tell a story that cuts against the dominant narrative in enterprise AI, which has fixated on coding assistants and developer productivity as the primary use case for large language models.Business process and operations — tasks like pulling scattered updates into a single report, building onboarding checklists, and reconciling spreadsheets — accounted for 33.4% of all sampled Cowork sessions, making it the single largest category by a wide margin. Content creation and copywriting — producing drafts, slide decks, posts, and proposals — came in second at 16.4%.Together, those two categories make up roughly half of all Claude Cowork usage. Software development, by contrast, accounted for just 8.7%. DevOps and infrastructure followed at 7%, with research and intelligence at 6.4%, data analysis and business intelligence at 5.8%, document processing and extraction at 4.1%, and sales and revenue operations at 4%.The remaining 12 categories each represented less than 4% of usage, including personal assistance at 3.8%, education at 2.4%, and meeting intelligence at 1.8%.Anthropic describes these dominant use cases as "the work around the work" — tasks that span nearly every role in an organization but rarely appear in anyone's core job description. "People are using it for a variety of tasks that aren't necessarily the hallmark of a specific role, but instead represent the connective work around a role that moves projects forward and keeps businesses running," the company writes. "That means tasks like drafting a status update, building a slide deck, or condensing reams of research into a single report."That phrase — "the work around the work" — is Anthropic's attempt to define and claim an entirely new category of AI productivity. It's a calculated reframing: rather than positioning AI as a tool that replaces what professionals do, Anthropic is arguing that the most valuable current application is handling everything professionals do around their actual expertise.What mobile access changes — and what it doesn'tThe expansion to mobile and web introduces three concrete capabilities that reflect how Anthropic envisions Cowork fitting into daily workflows.First, sessions now sync across devices. A user can start a task at their desk, check on its progress from a phone, and retrieve the finished output from any device. Second — and arguably more significant — Cowork can now run tasks in the background with no device online at all. Users can schedule work for a specific time, and Claude will execute it autonomously. Anthropic offers the example of setting Monday morning client prep for 6 a.m.: "Claude works through the email threads, transcripts, and recent news, builds the briefing doc, and leaves the follow-up email drafted but unsent. Review it over coffee."Third, when Claude encounters a decision that requires human judgment, it surfaces the question to the user's phone. "Nothing ships until you've reviewed and approved it," Anthropic states.Desktop remains the most fully featured surface, with access to local files and the browser. But the web version also opens Cowork to users who cannot install a desktop application — a meaningful expansion in enterprise environments where IT departments control software installation.The company also unified its interface: on web and desktop, chat and Cowork now share a single home screen, and projects and artifacts persist across both modes.To encourage adoption, Anthropic is extending doubled Cowork usage limits through August 5.The strategic logic: why Anthropic is chasing the non-developerThe usage data and the mobile launch together reveal a company executing a two-track strategy. Claude Code, its terminal-based coding agent, dominates among software developers. But Cowork is designed to capture the vastly larger population of professionals whose work involves creating, organizing, and communicating information rather than writing code.The contrast between the two products is instructive. As Anthropic notes, Claude Code "is most often used by software developers for the key parts of their role: building, debugging, and shipping code." When developers do use Cowork, they tend to use it not for programming but for the communications-focused work that surrounds every role — status updates, documentation, and coordination.This pattern — where AI handles the connective tissue of work rather than its core substance — aligns with what Anthropic describes as people using "Claude Cowork to assemble and structure the information they can use to act on their expertise." The company illustrates this with three examples: a lawyer using Cowork for document formatting and filing while reserving legal judgment for themselves, a hiring manager synthesizing interview feedback while spending more time on candidate conversations, and a team lead producing a slide deck that explains a decision while focusing on actually making that decision.The implications for Anthropic's business model are significant. Developer-focused tools, while high-profile, serve a relatively narrow market. The Ramp AI Index published in May showed Anthropic pulling ahead of OpenAI in business adoption for the first time — with 34.4% of firms paying for Anthropic's services compared to OpenAI's 32.3% — and suggests the company's enterprise push is gaining traction. Claude Code was identified as the primary driver of that shift. But Cowork targets an addressable market that is orders of magnitude larger: every knowledge worker with a laptop, a pile of spreadsheets, and a slide deck due by Friday.A crowded field gets more competitiveThe mobile launch arrives during one of Anthropic's busiest — and most turbulent — stretches in its history. Just last week, Anthropic launched Claude Sonnet 5, a new model that narrows the performance gap with its more expensive Opus-class models while maintaining lower pricing. The model is available at introductory pricing of $2 per million input tokens through August 31 before rising to $3 per million input tokens. Sonnet 5 serves as the engine underneath Cowork, and its improved agentic capabilities — better reasoning, tool use, and sustained task completion — directly enhance Cowork's ability to handle complex, multi-step workflows.Two weeks before that, Anthropic released Claude Tag, a Slack-native AI agent designed for team collaboration. Where Cowork focuses on individual task delegation, Claude Tag operates as a multiplayer tool — a single Claude identity that everyone in a Slack channel can interact with, building context from conversations over time. According to Anthropic's announcement, 65% of the company's own product team's code is created by its internal version of Claude Tag. Fortune reported that Anthropic's head of product for Claude Code and Cowork, Cat Wu, described the distinction: "Claude Code, Cowork, and chat are very single-player, whereas Claude Tag is built to be interactive and multiplayer."Together, Cowork and Claude Tag represent a pincer strategy: Cowork captures individual productivity workflows across devices, while Claude Tag embeds AI into team communication channels. Both are designed to push Anthropic deeper into enterprise operations, beyond the developer seat.The security question loomsThe expansion also arrives against a backdrop of unresolved security concerns. On July 1, security firm Armadin — led by Mandiant founder Kevin Mandia — published research detailing what it described as a full sandbox escape in Claude Cowork on Windows, as reported by SiliconANGLE. The attack chain involved DLL sideloading against the Claude desktop executable to gain trusted access to Cowork's virtual machine service, then exploiting undocumented parameters to achieve root access and bypass network restrictions.Anthropic responded that the vulnerability did not qualify as a security issue because exploiting it requires an attacker to already have local code execution on the host machine. Armadin, however, raised a broader concern: that deploying local virtual machines on nontechnical users' systems creates visibility gaps that endpoint security products struggle to monitor.This tension takes on new dimensions as Cowork moves to mobile and web. The web and mobile versions run tasks server-side rather than in a local virtual machine, which eliminates the specific attack surface Armadin identified but introduces different questions about data handling, especially for scheduled background tasks that process email threads, calendar data, and documents without real-time user oversight.Anthropic's announcement states that "the decisions still come to you" and that nothing ships without review and approval. But as Cowork takes on increasingly complex autonomous workflows — processing contract folders, building client briefings from multiple data sources, drafting emails — the surface area for prompt injection and data exposure grows correspondingly. When Cowork first launched in January, TechCrunch reported that Anthropic explicitly warned about prompt injection risks, noting in its blog post: "These risks aren't new with Cowork, but it might be the first time you're using a more advanced tool that moves beyond a simple conversation."As Anthropic courts enterprises, geopolitics complicates the pitchAnthropic's enterprise push is also colliding with geopolitical reality. CNBC reported Monday that Alibaba will ban employees from using Anthropic's AI tools starting July 10, placing Claude Code on a high-risk software list. The move followed Anthropic's June letter to the U.S. Senate accusing Alibaba of carrying out what it called "the largest known distillation attack" against its models.The Alibaba ban, combined with reports that Anthropic is closing loopholes that allowed Chinese companies to access Claude through third-country entities, underscores the increasingly fraught environment for AI companies attempting to serve global enterprise customers while navigating U.S. export and security restrictions.At the same time, Anthropic is investing massively in infrastructure. Reuters reported Monday that Anthropic signed a $19 billion, 20-year lease with TeraWulf for a data center being built in Hawesville, Kentucky, with 401 megawatts of computing power expected to become fully operational in 2028.That kind of capital commitment only makes sense if the company expects enterprise demand — not just from developers, but from the millions of knowledge workers that Cowork targets — to grow dramatically.Anthropic's own usage report comes with notable blind spotsAnthropic is transparent about the limitations of its usage analysis. The taxonomy classifies sessions by the type of work being performed, not by the job title of the person doing it. There are no standalone categories for marketing, finance, or HR — functions that are likely absorbed into the dominant "business process and operations" bucket, which may partly explain why that category commands a third of all usage.The sample is also rate-capped rather than proportional to traffic, meaning the numbers are shares of sampled sessions, not absolute volumes. Usage during peak hours is somewhat underrepresented. And roughly 5% of sampled sessions involved personal, non-work use — hobbies, personal assistance, and companionship-style conversations — meaning the data doesn't purely reflect workplace activity.The company also acknowledged that its labeling pipeline changed around May 11, which is why the analysis window begins on that date rather than covering a longer period.What Cowork's rise says about the future of enterprise AIAnthropic's mobile launch and usage data arrive at a moment when the enterprise AI market is shifting from proof of concept to proof of value. The question facing every company deploying AI tools is no longer whether the technology works — but whether it delivers measurable productivity gains across an organization, not just within engineering teams.The usage data suggests that the answer, at least for Cowork, is emerging in an unexpected place. It's not in the glamorous work of building software or conducting research. It's in the unglamorous, universal labor of turning messy information into structured outputs that move organizations forward — the status reports, the onboarding checklists, the variance memos, the client decks.By untethering that capability from the desktop and making it available on every device, Anthropic is betting that the most valuable AI agent isn't the one that writes code. It's the one that handles everything else.

https://venturebeat.com/technology/anthropic-brings-claude-cowork-to-mobile-and-web-as-usage-data-shows-most-users-arent-coding

4. [9/10] Google’s deepfake detector system used to debunk McConnell hoax pic

Source: TechCrunch | Published: Wed, 08 Jul 2026 20:37:03 +0000 (7h ago)

ZML's new software to speed inference across AI chips directly addresses critical performance and cost challenges for enterprises deploying AI models, impacting AI integration patterns and software delivery pipelines.

Earlier this week, a picture seemed to show Kentucky Senator Mitch McConnell covered in tubes in a hospital bed in a state of extreme distress. It turned out to be an AI-generated fake.

https://techcrunch.com/2026/07/08/googles-deepfake-detector-system-used-to-debunk-mcconnell-hoax-pic/

5. [9/10] I Built a Self-Improving AI, and So Can You

Source: Wired | Published: Wed, 08 Jul 2026 20:09:21 +0000 (7h ago)

This article directly addresses critical considerations around cost, security, and cultural challenges associated with enterprise AI agent deployments, offering vital insights for organizations adopting agentic workflows and AI governance.

Experiments in using AI to build AI show that the future doesn’t just belong to the frontier labs.

https://www.wired.com/story/frontier-labs-arent-the-only-ones-pursuing-self-improving-ai/

6. [9/10] Why this CEO thinks video games make better training data than the internet

Source: TechCrunch | Published: Wed, 08 Jul 2026 17:47:55 +0000 (9h ago)

Microsoft's strategic shift to rely more on its own AI models impacts its enterprise SaaS offerings, potentially influencing AI integration patterns and cost structures for businesses using Microsoft 365 and Power Automate.

When it comes to achieving artificial general intelligence (AGI), large language models just don’t have what it takes. Models like ChatGPT and Claude are great at text, but they’re less skilled at understanding how things actually move through space and time — an essential skill for producing intelligence that generalizes. That gap, it turns out, might be filled by gaming data. That’s the bet behind General Intuition, a […]

https://techcrunch.com/video/why-this-ceo-thinks-video-games-make-better-training-data-than-the-internet/

7. [9/10] Hot French startup ZML releases free product to speed inference across lots of AI chips

Source: TechCrunch | Published: Wed, 08 Jul 2026 08:00:00 +0000 (19h ago)

ZML's new software to speed inference across AI chips directly addresses critical performance and cost challenges for enterprises deploying AI models, impacting AI integration patterns and software delivery pipelines.

ZML, a hot French AI startup endorsed by Turing Award winner Yann LeCun, has now released ZML/LLMD, software that could make running AI less costly.

https://techcrunch.com/2026/07/08/hot-french-startup-zml-releases-free-product-to-speed-inference-across-lots-of-ai-chips/

8. [9/10] The real cost, security, and culture problems behind enterprise AI agents

Source: VentureBeat | Published: Tue, 07 Jul 2026 20:24:31 GMT (1d ago)

This article directly addresses critical considerations around cost, security, and cultural challenges associated with enterprise AI agent deployments, offering vital insights for organizations adopting agentic workflows and AI governance.

Presented by Red Hat At VentureBeat's recent AI Impact event, where the discussion centered on what separates enterprises that scale agentic AI from those that stall in pilot mode, Brian Gracely, senior director of portfolio strategy at Red Hat, detailed what companies actually run into once agents reach production. He dove into cost discipline, the security blind spots unique to autonomous systems, and the organizational friction that determines whether agent adoption spreads beyond early champions.Enterprises are overestimating how far behind they are on AI agentsMany enterprise leaders, especially those following industry keynotes and AI announcements, worry that they’re already falling dangerously behind competitors deploying agents at scale. But according to Gracely, much of that anxiety reflects a misconception about how quickly organizations learn once they begin building. Teams often move up the learning curve far faster than they expect.That rapid progress creates a different challenge, however. As agent usage expands, AI costs rise just as quickly, turning cost management from an engineering concern into a recurring boardroom discussion.Agentic AI usage is orders of magnitude higher than during the chatbot era, making AI costs a growing concern for enterprises. At the same time, organizations are becoming increasingly aware of their dependence on a small number of model providers. According to Gracely, that combination is driving many enterprises to explore alternatives that give them greater control over costs and infrastructure."The two or three top providers are already telling the market that they're losing money, and they're trying to go public to make up those gaps," he explained. "At some point, the dependency on that means you're either going to buy at a very high-cost level, or you're going to figure out alternatives to control what you're doing."Right-sizing AI models is the fastest lever for cutting agent costsThe biggest cost issue is that enterprises overspend by defaulting to the most capable model available regardless of task complexity."If I'm simply trying to resolve an insurance claim, I don't need to know about the history of Western civilization in my model, I don't need to know World Cup soccer scores," Gracely said.Semantic routing is the mechanism many companies use to make that judgment automatically, classifying requests and sending each to a model sized for the task without requiring users to choose, while infrastructure techniques like caching repetitive queries cut how often a request needs to reach GPU compute at all. Together, he said, these tools remove the assumption that efficiency and innovation pull in opposite directions."There's a lot you can do at a GPU infrastructure level, and quite a bit you can do in terms of flexibility of models," he explained. "Those give excellent choices in terms of the levers you're trying to pull, whether you need efficiency or you need innovation. That shouldn't be a binary choice."The financial discipline needed for token spend is similar to the FinOps practices that took years to mature in order to take control of cloud compute spending. Those underlying frameworks will transfer even as the vocabulary changes, Gracely said, especially as organizations push for internal education on model selection so teams stop defaulting to the most prominent option for tasks that don't need it."The same way we first had to teach the financial people what an EC2 instance is and what an S3 bucket is, you're going to have to start explaining tokens to them," he said. "We don't always need a Rolls-Royce. We don't always need caviar, because we're trying to do basic types of things."Patch speed is now critical as AI tools find vulnerabilities fasterAI-powered vulnerability discovery is forcing enterprises to rethink how quickly they can identify, validate and deploy patches. Long-established patch management cycles may no longer be fast enough in an environment where AI can uncover — and attackers can exploit — new vulnerabilities much more quickly."Most companies are probably going to have a window of somewhere between seven and 14 days to stay ahead," he said. "There are groups, Red Hat included, that are going to build patches for these, but the embargo window is going to be short."AI is also changing what defenders need to look for. Rather than simply uncovering isolated critical flaws, AI security tools can identify combinations of seemingly minor vulnerabilities that become dangerous only when chained together. As both software complexity and vulnerability discovery accelerate, Gracely argued that the ability to rapidly manage and update software is becoming a strategic capability rather than simply an operational one.Subject matter experts and compliance teams decide whether agents scaleIn the end, organizational adoption comes down to the need for deep, sustained involvement from the subject matter experts whose knowledge the agent is meant to encode, which makes earning their buy-in a prerequisite rather than an afterthought."You have to think about the incentives, what you do for people who participate in this work so they don't feel threatened that it's going to take away their job, and how you incentivize people in the long run to cooperate with that innovation," he said.Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

https://venturebeat.com/security/the-real-cost-security-and-culture-problems-behind-enterprise-ai-agents

9. [6/10] SpaceXAI releases Grok 4.5, which Elon describes as an ‘Opus-class model’

Source: TechCrunch | Published: Wed, 08 Jul 2026 19:30:16 +0000 (8h ago)

SambaNova's significant funding round signals continued investment and growth in foundational AI chip infrastructure, which underpins future enterprise AI deployments and capabilities.

Elon Musk's tech company released the newest version of Grok on Wednesday, promising a cheaper, more efficient alternative to other powerful AI models.

https://techcrunch.com/2026/07/08/spacexai-releases-grok-4-5-which-elon-describes-as-an-opus-class-model/

10. [6/10] This startup thinks robotics is about to have its ChatGPT moment

Source: TechCrunch | Published: Wed, 08 Jul 2026 19:19:15 +0000 (8h ago)

Meta's new AI image generator and the associated user pushback on photo usage highlight emerging AI governance and data privacy challenges that are relevant for any enterprise considering AI deployments.

General Intuition is betting millions of hours of video game data can train the foundation models for physical AI, making it easier to build smarter robots with minimal real-world data.

https://techcrunch.com/2026/07/08/this-startup-thinks-robotics-is-about-to-have-its-chatgpt-moment/

11. [6/10] Google Photos adds a new AI ‘Video Remix’ tool

Source: TechCrunch | Published: Wed, 08 Jul 2026 18:30:08 +0000 (9h ago)

This analysis of the competitive dynamics between frontier AI labs like Anthropic and open-source models offers strategic context for enterprises making decisions about AI model adoption and investment.

The feature can do things like apply cinematic relighting to brighten up a dark clip, swap out a plain background for something fun, or add artistic styles to videos.

https://techcrunch.com/2026/07/08/google-photos-adds-a-new-ai-video-remix-tool/

12. [6/10] Data for Agents

Source: Hugging Face | Published: Wed, 08 Jul 2026 17:16:05 GMT (10h ago)

Anthropic's Claude Cowork agent becoming available on mobile phones signifies increased accessibility for agentic workflows, allowing continuous task processing and supporting cross-regional team operations.

https://huggingface.co/blog/nvidia/open-data-for-agents

13. [6/10] Meta wants its AI glasses to seem less creepy. Its AI strategy says otherwise.

Source: TechCrunch | Published: Wed, 08 Jul 2026 17:11:18 +0000 (10h ago)

Discord's AI moderation bug serves as a cautionary tale for AI governance and reliability in automated systems, underscoring potential risks in AI-powered service delivery and IT service management.

Meta is adding a new safeguard to stop people from secretly recording others with its AI glasses. But the update comes as the company continues to expand how much personal data its AI products collect and use.

https://techcrunch.com/2026/07/08/meta-wants-its-ai-glasses-to-seem-less-creepy-its-ai-strategy-says-otherwise/

14. [6/10] OpenAI releases new voice models for more natural live conversations

Source: TechCrunch | Published: Wed, 08 Jul 2026 17:00:00 +0000 (10h ago)

Anthropic's Claude Cowork becoming available on mobile and web enhances its utility for enterprise agentic workflows, enabling users to continue tasks across devices.

OpenAI says its new voice mode can speak and listen at the same time, a key ability for live translation.

https://techcrunch.com/2026/07/08/openai-releases-new-voice-models-for-more-natural-live-conversations/

15. [6/10] These AI startups are growing revenue at faster and faster rates

Source: TechCrunch | Published: Wed, 08 Jul 2026 15:41:06 +0000 (11h ago)

This integration simplifies the deployment of Hugging Face models into Amazon SageMaker Studio, representing a practical advancement in AI integration patterns for enterprise SaaS environments and AI-assisted software delivery.

There are a lot of fast-growing AI startups, but some are growing even faster, they say.

https://techcrunch.com/2026/07/08/these-ai-startups-are-growing-revenue-at-faster-and-faster-rates/

16. [6/10] Your gaming data could be the secret to AGI, according to this Bezos-backed startup

Source: TechCrunch | Published: Wed, 08 Jul 2026 13:00:00 +0000 (14h ago)

The availability of Hugging Face models on Foundry Managed Compute offers another significant integration pattern for enterprises, streamlining model deployment in complex SaaS environments and supporting AI-assisted software delivery.

When it comes to achieving artificial general intelligence (AGI), large language models just don’t have what it takes. Models like ChatGPT and Claude are great at text, but they’re less skilled at understanding how things actually move through space and time — an essential skill for producing intelligence that generalizes. That gap, it turns out, might be filled by gaming data. That’s the bet behind General Intuition, a […]

https://techcrunch.com/podcast/your-gaming-data-could-be-the-secret-to-agi-according-to-this-bezos-backed-startup/

17. [6/10] This Former DeepMind Exec Thinks the AI Arms Race Could End in Disaster

Source: Wired | Published: Wed, 08 Jul 2026 09:30:00 +0000 (18h ago)

Discussions on AI safety and geopolitical implications from a former DeepMind executive contribute to understanding broader AI governance challenges and long-term strategic considerations for enterprises.

Verity Harding tells WIRED that the US government’s nationalistic attitude toward AI is evidence that a worst-case scenario is taking shape.

https://www.wired.com/story/verity-harding-ai-arms-race-dangers-anthology/

18. [6/10] AI chip maker SambaNova raises $1B at $11B valuation, 5 months after last mega round

Source: TechCrunch | Published: Wed, 08 Jul 2026 07:16:00 +0000 (20h ago)

SambaNova's significant funding round signals continued investment and growth in foundational AI chip infrastructure, which underpins future enterprise AI deployments and capabilities.

AI chip maker SambaNova has raised at an $11 billion valuation months after Intel was rumored to be trying to buy it for about $1.6 billion.

https://techcrunch.com/2026/07/08/sambanova-draws-1b-at-11b-valuation-in-series-f-first-close/

19. [6/10] Meta just launched a new AI generator, Muse Image, and users are already pushing back over use of their photos

Source: TechCrunch | Published: Tue, 07 Jul 2026 22:18:10 +0000 (1d ago)

Meta's new AI image generator and the associated user pushback on photo usage highlight emerging AI governance and data privacy challenges that are relevant for any enterprise considering AI deployments.

The new image-generating model has numerous use cases, including advertising and decorating, and creator-based opportunities.

https://techcrunch.com/2026/07/07/meta-rolls-out-muse-a-new-ai-image-generator/

20. [6/10] Meta Now Lets Anyone Use Your Instagram Photos in AI Images—Unless You Opt Out

Source: Wired | Published: Tue, 07 Jul 2026 21:59:29 +0000 (1d ago)

Meta's policy change on using Instagram photos for AI image generation, with an opt-out mechanism, raises important questions about AI governance, data rights, and ethical considerations relevant to enterprise data policies.

As part of Meta’s Muse Image model rollout, Instagram users with public accounts need to opt out to block AI generations of their content.

https://www.wired.com/story/meta-now-lets-anyone-use-your-instagram-photos-in-ai-images-unless-you-opt-out/

21. [6/10] From Hugging Face to Amazon SageMaker Studio in one click

Source: Hugging Face | Published: Tue, 07 Jul 2026 21:15:33 GMT (1d ago)

This integration simplifies the deployment of Hugging Face models into Amazon SageMaker Studio, representing a practical advancement in AI integration patterns for enterprise SaaS environments and AI-assisted software delivery.

https://huggingface.co/blog/amazon/one-click-to-sagemaker-studio

22. [6/10] Anthropic is launching Claude Cowork on mobile and web

Source: The Verge | Published: 2026-07-07T13:46:59-04:00 (1d ago)

Anthropic's expansion of its Claude Cowork AI platform to mobile and web makes its agentic capabilities more broadly accessible for enterprise users and mobile workflows.

Starting Tuesday, Anthropic's Claude Cowork AI platform will be available on mobile and web for the first time. The expanded access is rolling out first to Max subscribers and coming to Claude users on other plans "in the coming weeks." Claude Cowork was previously only accessible through the Claude desktop app for macOS and Windows, but now users on iOS and Android can also use it. However, Anthropic says the "full experience" for Cowork will still be on the desktop app, including features like local file access. Cowork sessions will also now run in the cloud by default, so you can continue them across different devices or run Cowork ta … Read the full story at The Verge.

https://www.theverge.com/ai-artificial-intelligence/961978/anthropic-claude-cowork-mobile-web

23. [6/10] Box survey: Why enterprise AI leaders are outperforming their peers

Source: VentureBeat | Published: Tue, 07 Jul 2026 16:25:51 GMT (1d ago)

Insights from the Box survey on enterprise AI leadership provide valuable strategic guidance and best practices for organizations tracking AI industry developments and seeking to enhance their AI adoption strategies.

Presented by Box Content access, governance, and platform flexibility are emerging as the dividing lines between AI leaders and laggards, according to the new State of AI in the enterprise report from Box, which surveyed 1,640 IT decision makers across the US, UK, France, and Japan. One of the report's major findings is the speed of the shift: the combined share of organizations describing themselves as advanced or leading edge soared from 8% to 64% just over the past year, while the share calling themselves early stage or not yet started collapsed from 53% to just 9%. Eighty percent of organizations reported a notable return on their AI investment, defined in the survey as an improvement of at least 10%, and more than half saw measurable business impact within six months of getting a project approved.The swing is largely due to how enterprises are now organizing their AI use rather than to any single technical breakthrough, says Olivia Nottebohm, COO of Box."We've moved from standalone experimentation that lived at the individual level into systematized, integrated agentic operations, agents that are in production and can be used in a repeatable manner," Nottebohm says. "That's where the impact is coming from."Why AI leaders get higher ROI than early-stage companiesThe divide between tiers is a matter of execution. Significantly, half of leading-edge companies reported AI-driven ROI above 25%, compared with just 11% of early-stage companies, with the advanced (33%) and developing (16%) tiers falling steadily in between. But Nottebohm says the real differentiator was not whether companies adopted AI, but how rigorously they integrated and managed it."What separates the leading edge is the operating muscle they've built: the right teams to deploy agents, formal governance to control them, and consistency in the content layer those agents work from," she explains. "Earlier stage companies are approaching it in a much more ad hoc, experimental way, letting people play around with it without the same intent or structured design." Content access is the biggest barrier to enterprise AI ROIContent, rather than model quality, is the defining bottleneck of 2026. Ninety-six percent of organizations say agents need access to company-specific content, yet only 36% have connected agents to trusted content across many use cases. It's an issue of trust rather than raw capability."We started this journey assuming enterprise AI was about access to the latest model," Nottebohm says. "But the question now is whether agents have access to the right content, and whether that content is protected, because those agents are only as good as the content they can reference, and only as safe as the security around it." Getting that content layer right has a second benefit beyond safety, since it’s also what finally lets agents work across departments that previously operated in isolation from one another. And while roughly a quarter of organizations point to data fragmented across systems, 24% cite difficulty integrating AI into existing systems, 21% say they lack adequate permissions and access controls, and 18% describe their content as too unorganized to make accessible at all. Among the most mature organizations, 63% now treat unstructured documents, contracts, and reports as a competitive advantage rather than dead weight sitting in a digital filing cabinet.Reducing common AI data exposure incidentsNearly half of all organizations say they have already experienced an AI-related data exposure incident. That figure rises to 60% among leading-edge companies, which may face greater exposure from more agents and connected systems — but may also be better equipped to detect it.The share of organizations reporting established or advanced governance frameworks rose from 24% in 2025 to 73% this year, but real gaps remain in instrumentation: only 39% have comprehensive visibility across sanctioned and unsanctioned AI use, 34% have formal standards for how agents access company data, and 27% still describe their governance as ad hoc. But those incidents function as a forcing mechanism rather than a setback, Nottebohm says."Governance used to be seen as something that slowed people down, but 93% of respondents told us better governance is actually what let them move faster," she explains. "It makes scaling AI survivable. Once content is secured and highly permissioned, you can run multiple agents across multiple processes and get a real multiplier effect."One practical consequence of that shift is that permission structures built for human employees are now being revisited with agents in mind, a process most enterprises are only partway through."The permissions enterprises set up two years ago need to be reviewed," she explains. "Until fairly recently, people weren't setting permissions on a document with how an agent might use it in mind, but now they're much more deliberate about that. It leaves them with a whole corpus of unstructured data to go back through and either clean up or repermission." That's part of a broader move away from governance designed for people and toward governance designed for agents from the start."Enterprises need to make the transition from governance that's retrofitted from human workflows to governance that's built specifically for agents," Nottebohm says. "That means tracking what an agent has touched, whose permissions were applied, and which sources were used, and all of that is now shaping how governance gets applied." Enterprises need to avoid lock-in to a single AI vendor"The days of token-maxing are already gone," Nottebohm says. "It's now about the responsibility of delivering efficient AI. Organizations want to use the cheapest model that meets the quality bar they need, not necessarily the most expensive one, because different model families keep leapfrogging each other and companies want to preserve that choice."That means enterprises are avoiding lock-in more than ever. Sixty-eight percent say they're concerned about depending on a single AI provider, the average number of officially adopted AI tools has climbed to 3.3, and 79% now consider it important or critical that agents operate headlessly, connecting directly to systems and APIs without a human interface in between.It's a trend similar to the shift toward multi-cloud infrastructure, and driven by a similar reluctance to hand any one vendor outsized negotiating power."A flexible architecture is built on platform interoperability," Nottebohm says. "It runs on multiple models, operates headlessly, and keeps every part of the AI stack swappable, so organizations don't have to bet on which individual tool wins, and that's part of the broader shift away from defaulting to the biggest, most expensive model available."The next steps to AI successOver the next three years, businesses should prioritize organizing, classifying, and cleaning up unstructured content, actively hiring and building teams around emerging roles, and adopting a hybrid token compute budget model, where IT owns the core infrastructure and token budget while business units own the application-level spend. And right now, it's easy to get up to speed fast."You don't have to start at early maturity and slowly work your way up," Nottebohm says. "If you build in the governance, the content layer, and the multi-model system from the start, you can enter as a leading company and capture that same outsized impact."Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

https://venturebeat.com/orchestration/box-survey-why-enterprise-ai-leaders-are-outperforming-their-peers

24. [6/10] Shut Those Laptops! Anthropic Puts Its Claude Cowork Agent on Your Phone

Source: Wired | Published: Tue, 07 Jul 2026 16:00:00 +0000 (1d ago)

Anthropic's Claude Cowork agent becoming available on mobile phones signifies increased accessibility for agentic workflows, allowing continuous task processing and supporting cross-regional team operations.

Claude Cowork now keeps working on tasks even after you close your laptop. It’s part of a larger push toward smartphone-controlled agents.

https://www.wired.com/story/shut-those-laptops-anthropic-puts-its-claude-cowork-agent-on-your-phone/