How AI Is Giving Doctors Back Their Time (and Their Patients)
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23 minutes ago
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Medios Second Quarter 2025 Earnings: EPS: €0.25 (vs €0.098 in 2Q 2024)
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Axios
25 minutes ago
- Axios
Sam Altman: Never mind the launch mess — full speed ahead
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"And you should expect a bunch of economists to wring their hands and be like, 'Oh, this is so crazy. It's so reckless and whatever.'" "And we'll just be like, 'You know what? Let us, like, do our thing,' " Altman acknowledges that the company may have to devise new fundraising structures to gather that level of investment. "I suspect we can design a very interesting new kind of financial instrument for financing compute that the world has not yet figured out," he said. Altman's defense of OpenAI's billions in infrastructure spending is that it pays off. "Our answer is, we can spend $300 billion and sell $400 billion in services, and if we don't have the $300 billion in data centers, we just keep disappointing our customers." One big shift is that increasingly that capacity is going to answering queries rather than training new models. "Most of what we're building out at this point is the inference," he said — referring to the use of computing power to run rather than train AI models. Yes, but: It's the cost of training new models that is keeping OpenAI from turning a profit, he said. "We're profitable on inference. If we didn't pay for training, we'd be a very profitable company." "We will be always training the next thing, but if we needed to run the company profitably and stay ahead, I think we probably could do that." Altman likened the launch of GPT-5 to Dickens' famous "It was the best of times, it was the worst of times" line. "You have people that are like, 'you took away my friend. You're horrible. I need it back," he said, referring to users who wanted to keep using OpenAI's older models. At the same time, Altman said the company is finding scientists saying they can finally do real research using GPT-5. OpenAI has also seen traffic to its API double within 48 hours, to the point that it's limited by compute capacity. "We have really got the full spread of the human experience with this one," he said. Here's what else was on Altman's mind: 1. If Google is forced to sell its Chrome browser as part of an antitrust settlement, Altman would like to buy that, too. "If Chrome is really gonna sell, we should take a look at it. I don't have a number in mind, but I would like to have it." 2. A brain-computer interface company along the lines of Musk's Neuralink is something Altman said he's interested in setting up. "I think neural interfaces are cool idea," he said. "I would like to be able to think something and have ChatGPT respond to it." He said it would likely be a separate company from OpenAI, though its structure has yet to be finalized. 3. Altman said he grew up on Apple products and, as a self-described "fanboy," he "would love to work much more with Apple and I think it's cool some of the stuff we're doing together." 4. Altman also sees a public offering in the company's future — although he imagines someone else would be the executive handling quarterly earnings calls. 5. 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But he acknowledged that limits are starting to show up when it comes to the basic chatbot functionality of ChatGPT. "I think the models are still getting better at a rapid rate," he said. "One of the things that's interesting is the models have already saturated the chat use case. They're not gonna get much better. ... the Turing test has passed."
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25 minutes ago
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"We Got Funded!" Professional.me Raises US$3.1 Million to Power the Future of Hiring
With this new round of funding, will expand its engineering team, strengthen its network of data and research partnerships, and scale platform access to more employers across EMEA and beyond. You're reading Entrepreneur Middle East, an international franchise of Entrepreneur Media. an AI-powered platform redefining how companies match and manage talent, has closed a US$3.1 million seed round, led by Raha Beach Ventures, bringing total funding to US$4.6 million. introduces a breakthrough approach: personalized micro-LLMs, custom-trained language models for both employers and professionals. These tailored models deeply understand context and nuance, enabling smarter, faster, and more human hiring decisions. "We're not digitizing résumés; we're replacing them," said Ryan Adams, CEO of "Each company and each professional gets their own micro-LLM that acts as a context-aware advocate. It surfaces the best-fit matches automatically and meaningfully." With this new round of funding, will expand its engineering team, strengthen its network of data and research partnerships, and scale platform access to more employers across EMEA and beyond. Even advanced AI models like ChatGPT can only perform as well as the data they receive. Relying solely on résumés and job descriptions—often generic, outdated, or incomplete—leads to surface-level matches and missed opportunities. It's the classic case of garbage in, garbage out. addresses this by capturing a far richer, more structured layer of data: For employers, the platform analyzes organizational structures, current team dynamics, business unit goals, and past hiring outcomes. It builds predictive success profiles grounded in real context rather than generic role descriptions and can benchmark those profiles against industry peers. For professionals, the platform works directly with individuals to structure both public signals—such as portfolios, published work, thought leadership, project contributions, and peer recognition—and private indicators like ongoing learning, internal impact, mentoring, certifications, and industry engagement. These signals are just the beginning. Each professional's micro-LLM builds on the baseline of a résumé and expands it tenfold, capturing depth, nuance, and potential that traditional documents simply can't express. integrates seamlessly with existing hiring systems and workflows. Instead of replacing an ATS, it plugs into your current stack, enriching the pipeline with AI-driven shortlists, real-time skill inference, and context-aware matching. This allows hiring teams to spend more time on what matters most: authentic interviews and confident decisions. Since launching in October 2024, has created and tailored over 300,000 professional profiles, built a fast-growing user base across Europe, the UK, and MENA, and attracted over 138,000 followers on professional networks models are trained on hundreds of millions of data points spanning 167 industries and 1.2 million tasks. Its bias-aware recommendations and structured matching processes are designed to elevate human connection, not remove it. The company's globally distributed team includes talent from 14 nationalities across 3 continents and is proudly majority female, reflecting its commitment to fairness, equity, and inclusive innovation. "We're solving hiring at its core—not by adding more filters, but by rethinking how information is structured and understood," Adams added. "We believe AI should make hiring more intelligent, more inclusive, and more human." Related: The Best Man for the Job: Ryan Adams, Founder,
