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Sophia Space raises $10M seed to demo novel space computers

As space companies itch to push the most advanced chips into orbit, the problem of cooling those high-powered processors is top of mind.

“It’s cold in space … [but] there’s no airflow, and so the only way to dissipate is through conduction,” Nvidia CEO Jensen Huang said when asked about space-based data centers during his firm’s most recent earnings call.

Now, Sophia Space has raised $10 million from investors, including Alpha Funds, KDDI Green Partners Fund, and Unlock Venture Partners. The company plans to prove out a new approach to passively cooling space computers on the ground, then buy a satellite bus from Apex Space and show that it works in orbit by late 2027 or early 2028.

Companies like SpaceX, Google, or Starcloud are examining traditional satellite form factors for their proposed space data center constellations, which rely on large radiators to keep chips in optimal thermal condition. But Sophia Space’s founders — CTO Leon Alkalai, CEO Rob DeMillo, and chief growth officer Brian Monnin — have a different approach.

The company’s tech comes from an unusual source: a $100-million-endowed program at Caltech to develop orbital solar plants that would beam electricity to Earth below. The researchers ultimately settled on a sail-like structure that is thin and flexible compared to boxy, traditional satellites.

While technical and regulatory challenges make producing electricity for Earth difficult, Alkalai, a fellow at the Caltech-managed Jet Propulsion Laboratory, was struck by the idea of using the design to power space-based processors. (Aetherflux, a space solar power startup, has had a similar realization.)

Sophia, an Nvidia partner, has designed modular server racks with integrated solar panels it calls TILES, which are 1 meter by 1 meter in area and a few centimeters in depth. By adopting this thin form factor, DeMillo says that processors can sit against a passive heat spreader, eliminating the need for active cooling. He expects 92% of the power it generates will go to processing, a significant gain on traditional designs. This design requires, however, a sophisticated software management system to balance activity across the processors.

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By the 2030s, Sophia hopes to be building larger space data centers out of thousands of TILEs, envisioning a 50-meter-by-50-meter structure delivering 1 MW of computing power. DeMillo argues that attempting to build space data centers with less efficient systems will not be economical and that a single structure rather than a distributed network linked by lasers will be easier to execute.

First, however, Sophia plans to begin by offering its TILEs to satellite operators that require compute solutions on orbit. Potential partners include Earth-observation satellites collecting large amounts of sensor data, missile warning and tracking systems that the Pentagon is investing billions of dollars to build, or even increasingly complex communications networks.

“The dirty little secret of the satellite industry is we’ve got all these amazing sensors up there that produce terabytes, or even petabytes, of data every few minutes, and they throw most of it out because they can’t do the computing on board and they can’t get round trip back and forth to the surface fast enough,” DeMillo told TechCrunch.

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Exclusive: Google deepens Thinking Machines Lab ties with new multi-billion-dollar deal

Former OpenAI executive Mira Murati’s startup, Thinking Machines Lab, has signed a new multi-billion-dollar agreement to expand its use of Google Cloud’s AI infrastructure, including systems powered by Nvidia’s latest GPUs, TechCrunch has exclusively learned.

The deal is valued in the single-digit billions, according to a source familiar with the matter, and includes access to Google’s latest AI systems built atop Nvidia’s new GB300 chips, alongside infrastructure services to support model training and deployment.

Google has been actively striking a number of cloud deals with AI developers as it aims to wrap together its AI computing offerings with other cloud services like storage, a Kubernetes engine, and Spanner, its database product. Earlier this month, Anthropic signed an agreement with Google and Broadcom for multiple gigawatts of tensor processing unit (TPUs) capacity (these are Google’s custom-designed AI chips for machine learning workloads). 

But the competition is fierce. Just this week, Anthropic also signed a new agreement with Amazon to secure up to 5 gigawatts of capacity for training and deploying Claude. 

Earlier this year, Thinking Machines partnered with Nvidia in a deal that included an investment from the chipmaker. But this is the first time the lab has struck a deal with a cloud services provider. The deal is not exclusive, so Thinking Machines may use multiple cloud providers over time, but it’s still a sign that Google is looking to lock in fast-growing frontier labs early. 

Murati left her job as OpenAI’s chief technologist and founded Thinking Machines in February 2025. The company, which soon afterwards raised a $2 billion seed round at a $12 billion valuation, has remained highly secretive, but launched its first product in October. Dubbed Tinker, it’s a tool that automates the creation of custom frontier AI models. 

Wednesday’s deal provided some insight into what Thinking Machines is developing. In a press release, Google noted that it can support the startup’s reinforcement learning workloads, which Tinker’s architecture relies on. Reinforcement learning is a training approach that has underpinned recent breakthroughs at labs, including DeepMind and OpenAI, and the scale of the Google Cloud deal reflects how computationally expensive that work can get. 

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Thinking Machines is among the first Google Cloud customers to access its GB300-powered systems, which offer a 2X improvement in training and serving speed compared to prior-generation GPUs, per Google. 

“Google Cloud got us running at record speed with the reliability we demand,” Myle Ott, a founding researcher at Thinking Machines, said in a statement.

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The most interesting startups showcased at Google Cloud Next 2026

Google Cloud Next is taking place this week in Las Vegas, and one clear message has emerged: Google wants AI startups on its cloud. To that end, it made several startup-related announcements.

The most significant is that the tech giant has earmarked a new $750 million budget to help its Cloud partners sell more AI agents to enterprises. This funding is available to partners ranging from startups to the big consulting firms. It can be used for costs like Gemini proof-of-concept projects, Google forward-deployed engineers, cloud credits, and deployment rebates.

Google also highlighted a long list of startups that are using Google Cloud, either newly signed or expanding their footprint. Among them are a few standout names:

Lovable is expanding its use of Google Cloud by launching a new coding agent through Google’s enterprise app marketplace. Lovable is the fast-growing vibe coding startup and was on a $400 million ARR track as of February, it said.

Notion, Silicon Valley’s favorite AI-infused document productivity app, most recently valued at about $11 billion, is using Gemini models to power its text and image generation features.

Gamma, an AI-powered PowerPoint killer recently valued at a $2.1 billion valuation, is using Google’s state-of-the-art image model Nano Banana 2 and other Google Cloud features.

Inferact, the commercial inference startup from the creators of the popular open-source project vLLM, is accessing Nvidia’s GPUs through Google Cloud, in addition to using the tech giant’s AI stack.

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ComfyUI, the popular open-source tool for creating AI-generated images and multimedia, also offers access to Nano Banana 2 and is using other Cloud features.

Other startups that received the Google Cloud shout-out this year include:

ChorusView, which makes AI-powered smart tags that track the condition and movement of goods in real time.

Emergent AI, a vibe coding platform.

ExaCare AI, which makes AI software for post-acute medical care facilities.

Insilica, which creates AI-generated regulatory-compliant chemical safety reports.

Optii, which makes AI-enhanced hotel operations software.

Parallel AI, which builds web search and research APIs built for AI agents.

Proximal Health, which makes AI-powered software that automates the insurance claims adjudication process.

Reducto, which does AI-powered document parsing.

Stord, which handles e-commerce fulfillment and parcel operations.

Stylitics, which makes AI image generation software for retailers for tasks like outfit styling and product bundles.

Temporal, a developer cloud environment built to prevent failures.

Vapi, which makes dev tools for building conversational voice agents.

Vurvey Labs, which conducts synthetic market research via AI agents.

Wand, an in-game assistant for single-player PC games.

Watershed, which makes software that helps enterprises report on and manage sustainability programs.

ZenBusiness, an all-in-one back-office tool for small businesses that includes an AI chat assistant.

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Duolingo is now giving free users access to advanced learning content

Duolingo announced on Wednesday that its advanced language learning content is now available for free across nine languages: English, Spanish, French, German, Italian, Portuguese, Japanese, Korean, and Chinese. Users can access this content through the web, iOS, and Android devices.

This advanced content is at the B2 level on the Common European Framework of Reference for Languages (CEFR), which is the international standard for language skills that schools and employers recognize. B2 level content refers to learning materials without translations, complex scenarios, and specialized vocabulary.

The new offering will include features like “Advanced Stories,” which helps with reading comprehension, and DuoRadio, a podcast-like audio experience for listening comprehension.

Now that Duolingo users can tap into this advanced learning content for free, they can level up their skills, whether that’s practicing for job interviews, prepping for studying abroad, or tackling complex news articles, films, and books without relying on translations.

The company says this positions it as the only free app to offer advanced-level learning across these nine languages at no cost. While competitors like Babbel and Busuu offer advanced courses, they typically require paid subscriptions. For instance, Busuu has some CEFR-aligned courses up to the B2 level, but the free version is pretty limited and doesn’t offer lessons like grammar explanations, so users need to pay for full access.

Previously, Duolingo only provided free courses that capped at A2 or B1 levels, mainly focusing on basic communication skills. 

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The company is positioning this free advanced learning offering as an enticing opportunity for job seekers, framing language learning as a practical pathway to improving employability in an increasingly global workforce.

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This comes at a time when the job market remains highly competitive and overall growth has slowed. Research from the American Council on the Teaching of Foreign Languages shows that learning a second language can raise someone’s employability by as much as 50%.

“Reaching job-ready proficiency in a new language used to be out of reach for most people,” Bozena Pajak, head of learning science at Duolingo, said in a statement. “It took years of expensive classes or immersive experiences that not everyone could access.”

Duolingo’s decision to offer advanced learning for free is also a strategy to increase its free user base. In its Q4 earnings report, the company stated that it has 52.7 million daily active users, demonstrating 30% growth compared to the previous year. This number is higher than its paid subscriber base, which stands at 12.2 million. However, Duolingo’s shares fell after the company projected that the year-over-year bookings growth rate for Q2 2026 is expected to experience a slight decline.

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