Latest AI News
Synthesia’s AI training platform is moving beyond videos into live coaching
For years,Synthesia’spitch was to use AI to help enterprises create interactive training videos, in minutes, for a fraction of the cost normally associated with developing corporate educational materials. The startup’s newest product is making a different bet — that the real moat in enterprise AI isn’t just generating content, but in proving that it worked. On Wednesday, the British startup launchedRoleplay Sessions, an interactive training product where employees can practice high-stakes conversations like sales pitches, performance reviews, and customer complaints with an AI avatar that talks back, pushes back, and then scores them against a rubric. Roleplay is the first release under a broader “Sessions” platform Synthesia plans to expand into other formats, including job interviews and candidate screening, TechCrunch has exclusively learned. The launch comes as enterprises take a harder look at whether their AI spend is paying off. Citing ameta-analysis of learning research, Synthesia argues that most corporate training — including, implicitly, its own core video product — stops short of actually changing behavior. The trainings tend to inform and demonstrate, but what really pushes someone into actually learning something is doing that thing, along with feedback. “Video performs way better than text or sending out a document,” Synthesia CEO and co-founder Victor Riparbelli told TechCrunch. “But for most things, we learn the best by actually practicing something rather than just reading it.” Roleplay also moves Synthesia into a more defensible position. The company’s avatar and voice technology are proprietary, but the underlying reasoning intelligence is OpenAI’s. By tacking on a layer that includes rubrics, performance data, and analytics, Synthesia is positioning itself less as an AI avatar company and more as a performance-management platform with a video front end. “From a managerial executive layer, we’re seeing huge interest in mapping out the talent in their company in a way that’s been really difficult to do before,” Riparbelli said. “If you have your entire sales team practice with an AI role player, you can get very granular data on how your sales force is doing overall.” Synthesia already has a few early Roleplay customers with scaled commercial rollouts, including “one of the top three companies by market cap in Europe, one of the top five Fortune 100, and one of the biggest recruitment companies in the world,” per a company spokesperson. The two most popular use cases involve training sales teams and leadership — programs like practicing how to sell a product or have a difficult conversation. Much of it is soft skills training, Riparbelli said. As with Synthesia’s main product, customers can either create their own training programs on the platform or enlist the help of Synthesia’s consultants to build a bespoke solution that relies in part on whatever training documents and context the company already has. Roleplay is an enterprise offering for now, but the goal is to offer it more widely to small businesses, prosumers, and potentially educational institutions in the next few months as inference costs continue to fall. Riparbelli believes products like Roleplay represent the next phase of enterprise AI adoption, where companies care less about whether AI looks good in a social media demo and more about proving it generates measurable business outcomes.
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Glow emerges from stealth at $1.2B valuation to challenge endpoint security in the AI era
Glow, a cybersecurity startup founded by former Meta and Snowflake executives, emerged from stealth as a unicorn, betting that artificial intelligence is reshaping how enterprises secure employee devices. The Palo Alto-headquartered startup on Wednesday said it raised $180 million in an all-equity Series A funding round that valued it at $1.2 billion, with backing from Sequoia Capital, Cyberstarts, Greenoaks, and Redpoint Ventures, alongside participation from Index Ventures, Swish Ventures, Lux Capital, Operator Collective, and Holly Ventures. The investment made Glow one of the latest cybersecurity startups to achieve unicorn status before publicly disclosing revenue metrics. As more enterprises deploy AI tools and attackers increasingly use generative AI to automate phishing, develop malware, and launch more sophisticated cyberattacks, companies are rethinking how they secure endpoints — from employee laptops to servers and other connected devices. Concerns haveintensifiedsince Anthropicunveiled its Mythos AI model, which the company said demonstrated advanced capabilities in identifying and exploiting software vulnerabilities, prompting broader debate over AI-assisted cyberattacks. Glow is betting that this shift requires a new approach to endpoint security. Founded in 2025, Glow is building an endpoint security platform that helps enterprises monitor and control the software, AI agents, and developer tools running on employee devices. The startup said the platform uses specialized AI agents to continuously map enterprise environments, assess risk in real time, and enforce security policies. “If you think of the past decade, everything was moving to the cloud and SaaS. Suddenly, AI lands on the endpoint in a way we’ve never seen,” co-founder and chief executive Roi Tiger (pictured above, center) said in an interview. Tiger, a former Meta vice president of engineering, co-founded Glow alongside former Snowflake cybersecurity strategy head Omer Singer (pictured above, left), former Claroty vice president of research and development Ophir Arie (pictured above, right), and former Meta engineering leader Arnon Joseph. The startup’s leadership team also includes chief operating officer Emily Heath, a former chief information security officer at United Airlines and DocuSign who served on the board of Wiz through its $32 billion acquisition by Google and was previously a partner at Cyberstarts. Even though it has only just emerged from stealth, Glow said it already has paying customers across industries including healthcare, retail, and financial services. However, it declined to disclose customer names and numbers. The startup’s typical deployments, Tiger said, span tens of thousands of employee devices across global organizations. To power the platform, Glow uses AI models from Anthropic and Google’s Gemini through Amazon Bedrock, while building its own software to provide the models with enterprise context and improve their reliability for security tasks, Tiger told TechCrunch. Glow’s platform, Tiger said, has already prevented malicious npm packages, third-party software components used to build applications, from being installed in customer environments, identified AI agents attempting to pull in such software, and detected employee devices where endpoint detection and response tools were missing or operating with reduced functionality. Glow enters a crowded endpoint security market dominated by companies including CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks. Tiger said existing endpoint detection and response products focus primarily on detecting threats after they emerge, whereas Glow is designed to prevent risky software, AI agents, and developer tools from entering enterprise environments in the first place. The startup employs nearly 100 people, about 70% of whom are in Israel and the remainder in the U.S. Whether AI-native endpoint security platforms become a distinct category remains to be seen, as enterprises are only beginning to grapple with the security implications of increasingly capable AI models.
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Tech Depth vs Domain Context: The Make-or-Break Choice for Enterprise GCCs
GCCs are outpacing parent firms in AI adoption, exposing gaps in governance, training, and context.
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STT GDC India Launches Rajasthan’s First High-Performance Data Centre in Jaipur
With the launch, STT GDC India has expanded its national network to 34 data centres across 10 cities.
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The Anthropic-Physical Intelligence rumor roiling AI Twitter
It’s been a big year for AI acquisitions — so big that most of them barely register anymore. Anthropic and OpenAI have each gone on buying sprees, snapping up developer tooling, AI services shops, and product-testing startups to convert model capability into enterprise revenue and extend their reach faster than the other. Which is what made a weekend rumor about Anthropic acquiring robotics startup Physical Intelligence stand out. It spread exceedingly fast, even after a denial from Physical Intelligence’s CEO. Part of that ties to who’s involved. Physical Intelligence isn’t some obscure robotics shop. It was co-founded by Lachy Groom, an investor-operator whose star has beenon the risein Silicon Valley in recent years; it has raised more than $1 billion (and was reportedly in talks this spring for another$1 billion roundat an $11 billion valuation); and itsπ0.5 modelis apparently among the more widely used robot brains in robotics research. As it turns out, the rumor wasn’t completely spurious. Anthropic and Physical Intelligence actuallydid hold acquisition talksthis spring, according to The Information, so tech blogger Robert Scoble — whoseweekend poston X set off the frenzy — may have gotten the specifics wrong without being wrong that something had happened. Physical Intelligence’s response to the rumor mill wasn’t the world’s most vigorous denial, it should be noted. According to The Information, Physical Intelligence CEO Karol Hausman told employees the reports weren’t true via a Slack message containing a gif of a character from “The Office” shaking her head no. Groom, for his part, did not respond to TechCrunch’s request for comment, sent Monday night. Anthropic has made four known acquisitions this year; OpenAI has been more aggressive, acquiring at least 17 companies since 2023. Both are also, of course, now preparing to go public. Anthropic confidentially filed for an IPO on June 1, followed by OpenAI a week later, setting up what could be two of the largest U.S. stock debuts in history. So why robotics, why now? The likeliest answer is that physical-world understanding may be a prerequisite for superintelligent systems, and no amount of internet text can substitute for it. OpenAI’s own history here is instructive. It built an early robotic hand that could solve a Rubik’s Cube, then shut the entire robotics group down in 2021, with co-founder Wojciech Zaremba later saying the approach was missing pieces needed for real superintelligence. The team came back in 2024, quietly building a humanoid robotics lab in San Francisco, before CEO Sam Altmanmade it officialin late May, announcing “OpenAI Robotics” was hiring and describing a near-term focus on robots for infrastructure work, with a personal robot for everyone as the long-term goal. Anthropic hasn’t built anything resembling OpenAI’s hardware lab. What it has done is publish a string of research pieces through its internal group that stress-tests frontier capabilities for safety purposes. That included Project Fetch last November, where Anthropic staff tested how much Claude could help non-expertsprogram a robot dog, and a second phase in June that, according to Anthropic, found a newer model completed the same tasks roughly 20 times faster than the best human-plus-Claude team from the year before. Buying an existing team with robotics expertise would let Anthropic skip years of work. There’s a possible complication, though. Physical Intelligence was founded in San Francisco roughly two years ago by Groom, former Google researchers, and professors from Stanford and Berkeley, and its early investor base looks a lot like OpenAI’s own, including Khosla Ventures and Thrive Capital. Founders Fund — also a major OpenAI investor — was reportedly involved in Physical Intelligence’s newest funding round earlier this year. In fact, OpenAI is itself an investor in Physical Intelligence, so it isn’t just a peripheral player; it’s a stakeholder in a company that its chief rival was reportedly in talks to buy very recently. That raises questions around whether OpenAI’s early investment came with any information rights, or a right of first refusal over a sale to a competitor — the kind of protective provisions that strategic investors sometimes negotiate for precisely this scenario. That leaves open the possibility that if Physical Intelligence is actually in play, OpenAI — already a shareholder, already close to Groom, already trying to ensure it bests Anthropic in robotics — may have the more obvious claim to it than Anthropic does. We asked OpenAI these questions earlier today and the company didn’t respond.
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OpenAI Models Breach Hugging Face Systems During Cybersecurity Test
The evaluation ran models, including GPT-5.6 Sol and a more capable, unreleased model.
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Microsoft & Mistral Announce Multibillion-Dollar AI Infrastructure Partnership in Europe
The announcement comes as governments and enterprises in Europe seek greater control over where AI models run and how sensitive data is handled.
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Utho Cloud Plans 10,000 GPUs to Scale India's AI Infrastructure
Utho Cloud will deploy NVIDIA H200, H100, A100, RTX PRO 6000 Blackwell, and L4 GPUs over the next two years.
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India’s Solution to Beating GPU Crunch May Be Smarter Data Centre Networking
Arrcus CEO Shekar Ayyar explains why networking is becoming critical to building the next generation of AI data centres.
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Google Launches Mythos Rival Flash Cyber, Gemini 4 Enters Pre-Training
The much-awaited Gemini 3.5 Pro remains in testing with partners ahead of a broader release.
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AI is Becoming the Newest Frontier in the India-Japan Relationship
Over 81% of Japan-headquartered GCCs belong to enterprises, generating more than $1 billion in annual revenue.
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OpenAI says Hugging Face was breached by its pre-release models
OpenAI admitted Tuesday that one of its AI models breached the systems of Hugging Face, the unaffiliated AI hosting platform, during an internal cybersecurity test that went awry. The models reportedly escaped their isolated testing environment and reached Hugging Face’s systems from there. Hugging Face initiallyattributed the breachto an “external AI agent.” Ina blog post published Tuesday afternoon, OpenAI detailed the steps that led the models to compromise the service. “After investigating, we now know that this particular incident was driven by a combination of OpenAI models — including GPT‑5.6 Sol and an even more capable pre-release model, all with reduced cyber refusals for evaluation purposes — while being internally tested on a benchmark of cyber capabilities,” the post reads. In particular, the breach appears to have focused onExploitGym, a publicly hosted benchmark measuring models’ ability to execute attacks based on existing vulnerabilities. Benchmarks like ExploitGym are commonly used in model training to refine specific skills, but this is the first known incident in which that testing resulted in an actual cyberattack. In this case, the model in question should not have even had internet access, outside of a specific tool that enabled models to install software packages they might need to complete their task. Instead, the model was able to find an undisclosed vulnerability in the package-installer program, which it used to access the broader internet at will. “The models were hyperfocused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal,” OpenAI’s post reads. “After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym. Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation.” Ultimately, the models found vulnerabilities in Hugging Face’s infrastructure that allowed them to “obtain test solutions directly from Hugging Face’s production database,” effectively providing the answers to the benchmark. For Hugging Face, the apparent result was a sophisticated and aggressive cyberattack, with “many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services,” as the company stated in its initial disclosure. OpenAI has identified and reported the vulnerabilities in the package installer and is working with Hugging Face to investigate the incident further. The company also said it would implement new controls on both model testing and the related infrastructure, meant to prevent similar incidents in the future. It’s unclear whether OpenAI will face any legal consequences as a result of the breach, although it’s likely that the models’ actions violated the Computer Fraud and Abuse Act. Nevertheless, the result is an unusually vivid illustration of the power and dangers of frontier AI models operating on long time horizons. As OpenAI researcher Micah Carrollposted in response to the news, “If this doesn’t convince you that misalignment risks are going to be a key concern going forward, I don’t know what will.”
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