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最新 AI 资讯
TCS, Vodafone Business Team Up to Drive AI-Led Digital Transformation for UK Enterprises
The partnership builds on VodafoneThree's £11 billion investment to create the UK's best network for business.
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HCLTech, NetApp Expand Partnership to Offer Hybrid Cloud Storage-as-a-Service
The companies have expanded their partnership to offer hybrid cloud storage-as-a-service, combining consumption-based infrastructure with pay-as-you-go storage.
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Microsoft Merges Copilot and Microsoft 365 Copilot Into One App, Retires Several AI-Powered Tools
Microsoft launched Copilot, its dedicated AI chatbot, in 2023. In the last three years, the app has gone through various iterations with the addition of new features and other changes. The Redmond-based tech giant used to offer two separate apps for consumers and businesses. Now, the company has announced that it is merging the two apps, Copilot and Microsoft 365 Copilot, into one platform. The new app will combine the capabilities of the apps. The tech giant will let users log in to the Copilot app using their personal, business, or both accounts, allowing them to switch between the two. On top of this, the company has announced that it is removing various AI-powered tools from the Copilot app.
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Databricks Raises $5 Bn at $190 Bn Valuation as Revenue Run Rate Tops $7 Bn
The company said Lakebase has crossed a $100 million revenue run-rate, while more than 1,000 customers now generate over $1 million in annualised revenue each.
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The Hard Part of AI Isn’t Building. It’s Running
As enterprises race to deploy agents and autonomous workflows, Prefect argues that governance, observability and operational reliability will determine which AI strategies succeed, instead of model performance.
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OpenAI Chief Revenue Officer Denise Dresser Steps Down
Dali Rajic, former President and COO of Wiz, will succeed Dresser.
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Gemini 3.7 Flash Arrives as Google’s Frontier Model Delay Continues
The model has been released just weeks after Gemini 3.6 Flash.
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Aheesa Digital Innovations Signs MoU With Tamil Nadu Govt for ₹250 Cr Semiconductor Design Centre
Aheesa recently initiated its MPW process for VIHAAN-I, its broadband networking System-on-Chip (SoC) based on the RISC-V architecture
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StratLytics Bets on Decision Intelligence to Modernise Enterprise Risk Decisioning With SLERA
StratLytics Consulting is targeting mid-market financial institutions with SLERA, an AI-native decision intelligence platform that accelerates enterprise risk decisions.
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Databricks wanted to raise $1B, investors wanted $15B. It settled on $5B at a $190B valuation.
There’s a funny kind of game that the latest of late-stage startups must play when raising money. They often have to sell more shares than they want or risk offending some of their existing VCs. This scenario recently played out with AI big-data company Databricks and its latest $5 billion raiseannouncedThursday, co-founder and CEO Ali Ghodsi (pictured above) told TechCrunch. “We wanted to raise $1 billion, but then The Information printed this article saying that Databricks is doing a big fundraise. They did that in the middle of our conference. We were heads down with our conference, and we were not actually at all focused on fundraising,” Ghodsi recalled, referring to a conference that took place in June. “As soon as that article went out, there was a long line of investors that started calling. My phone blew up. It was like the worst timing for us because we were busy with our conference,” he said. It was an enviable problem that turned the news report into a self-fulfilling prophecy. “The interest level was just insane. Just from this select group of investors that we looked at, there was $15 billion of interest,” he said. When there’s that much desire to get into a deal, telling some long-term backers no is a recipe for hard feelings. Databricks decided to issue more stock, and in July, sent out a press release announcing it had closed its new round at a$188 billion valuation. (The company didn’t disclose at the time how much it had raised.) On Thursday, Databricks shared it raised $5 billion from a paragraph worth of VCs that it let in on the deal and that its valuation pushed higher to a nice round $190 billion. The $5 billion round was led by Coatue and several others, including Blackstone, MGX, various accounts associated with various arms of T. Rowe Price, and new investor Sixth Street Growth. (Sixth Street is the firm founded by former Goldman Sachs chief investment officer Alan Waxman.) About two dozen VCs were named as participants. Why were they all so eager? Databricks seems like a sure bet. Ghodsi said his company has hit $7 billion of annualized run rate revenue, which is currently growing at 80% and is cash-flow positive. Its core product, a cloud data warehouse, is $1.5 billion of that run rate, and still growing at 100% year-over-year, he said. Plus, Databricks has the magic AI pixie dust. Its database for agents, Lakebase,launched in June, 2025, and has hit $100 million revenue run rate. Its AI chatbot tool Genie, that can do business analysis on the spot, “is insanely popular,” he said. So, if the business is doing so well, why raise more capital? The company had already raised $20 billionover the past 20 months. AI is expensive, Ghodsi said. Databricks has multibillion-dollar cloud commitments with all three of the major hyperscalers. On top of that, “AI research is very expensive,” he said, adding that the company has an AI research team of 100 people, a highly competitive area. Plus, Databricks is shopping. “We do a lot of M&A.” Ghodsi said, referencing an acquisition the companyannounced this weekof Electric, the company that makes the lightweight Postgres database PGlite, a means for agents to spin up databases (terms undisclosed). In June, itbought AI cybersecurity company Panther; in March,it bought two startups. There was a time when a $1 billion round was considered a massive and difficult raise. In this age of AI spending, wherestartups are raising $1 billion for a seed/Series Aright out of the gate, that amount is now a pittance. Still, Databricks’ private fundraising, instead of going public, has become something of a meme among the Valley. When it announced this round last month, people joked online that it has raised so many, it wasrunning out of lettersof the alphabet. Ghodsitold CNBCthat he still wants to take the company public one day. With such a giant roster of investors who will want to cash out one day, how can he promise anything else? But today, he wants to focus on investing in AI, he said. Given the expenses involved in that, perhaps doing so out of the public eye is a wise idea. Plus, when he can command an instant $15 billion of interest, and on his own terms, what’s the rush?
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Writer introduces new AI model and upgraded harness to contain token costs
Across the AI industry, users are becoming more conscious of just how expensive their deployments can be —and feeling a new urgency to cut costs. But while open source models offer significantly lower per-token costs, it can be difficult to find the right model for a given job. On Thursday,Writer, which offers AI tools and agents for marketers, launched a new flagship model called Palmyra X6, aimed at solving that problem for its users. Built as a post-training variation on Z.ai’s open source model GLM-5.2, Writer says the new system should provide deployment-ready capabilities at a much lower price. The company estimates the new model, combined with changes to the companies harness infrastructure, will cut costs for its customers by as much as 50% for basic tasks. Together with the new model, the company also released significant upgrades to its standard agentic harness. Both features will be available to Writer clients starting Thursday. “I think the enterprise is absolutely sick of chasing the next benchmark,” CEO May Habib told TechCrunch. “They want flattening cost, and it seems like nobody can deliver that.” The new approach puts particular emphasis on complex, multi-step tasks, executed faster and with fewer tokens. And Writer sees harness optimization as a crucial lever toward making that happen. A recent paper from Writer researcherslends credence to this approach, testing small changes in harness efficiency across multiple different models. The research found that, in many cases, changes in the harness were a more reliable way to reduce costs than model choice, with costs falling an average of 40% across their testing. “The harness is the one component whose efficiency multiplies across every model an organization runs—present and future,” the researchers wrote. For Writer’s clients, the experience is still model-agnostic: Palmyra X6 will sit alongside other Writer models or outside models imported through Azure or Amazon Bedrock. But Habib also sees the push to cut costs as driving a broader distrust toward major AI labs, which have a financial incentive to drive up token use. “The cost explosion here is just unprecedented for customers, and so is the degree to which CIOs are giving up on the labs,” Habib told TechCrunch, adding that the AI labs “don’t deeply understand right how to help an enterprise get benefit from AI.”
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OpenAI hires new CRO as executive shake-up continues
OpenAI has replaced chief revenue officer Denise Dresser after just nine months on the job, tapping Wiz president and chief operating officer Dali Rajic to take on frontier lab’s top sales job. The move comes as part of a broader shake-up in the organization in the last month, which has seen the departures ofCOO Brad Lightcapand the company’s No. 2 executive, CEO ofAGI deployment Fidji Simo. OpenAI co-founder and president Greg Brockman has taken a larger role in management following Simo’s departure, and announced Rajic’s arrival today in ablog post. Wiz, Rajic’s previous employer, was acquired by Googlefor $32 billionthis year in the tech giant’s largest-ever acquisition. “Denise has led our revenue organization through a formative period for the business and has worked tirelessly to get the team to where it is today,” Brockman wrote. “The way we’re deploying this technology is changing rapidly, and Dali will turn what we’ve learned into repeatable execution as we build out the full system to make AI broadly useful for people and businesses.” OpenAI says its products reach more than one billion weekly active users, and two million businesses. Despite the incredible growth and its powerful models, however, executives have suggested both privately andpubliclythat the company hasn’t hit all of its revenue goals. The company says it has filed confidentially with the SEC ahead of a potential IPO, but it’s not clear when that will take place. Private firms often try to round out their executive ranks ahead of a public markets debut. OpenAIpurchased $7 billionworth of shares from employees this week in a tender offer that allowed them to cash in on some of their equity compensation, which may suggest a delay in the public offering. Bloomberg News’coverageof the change-up referenced an OpenAI blog post that said the company needed to have a “relentless focus” on “measurable business impact,” but those comments appear to have been removed from the published version. However, this year CEO Sam Altman has spoken about focusing the company on enterprise deployment and cut back on technology projects and experiments seen as distracting from that goal.
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