Three former DeepMind researchers who created an AI that beat humans at poker have now applied the same technology to trading stocks — and the bet appears to be paying off. Their Prague-based AI lab, EquiLibre Technologies, is now valued at $500 million after raising an undisclosed-sum Series A, TechCrunch learned.

The round was led by Creandum, and, although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed that it was the largest single investment the firm “has ever made in one go into a company,” he told TechCrunch.

The common denominator between poker and Wall Street is that they are well suited for reinforcement learning, an AI training technique where self-learning models are incentivized by rewards. According to Martin Schmid, EquiLibre CEO, “The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?”

This isn’t just game money. In partnership with quant firm Tower Research Capital, EquiLibre’s algorithms have been trading billions in daily volume across the S&P 500 and NASDAQ. The startup claims its agents have been doing well since their rollout on crypto markets in 2025, and now on stock exchanges, with “a perfect record of zero negative months since inception,” meaning they have finished each month with their investments up overall.

By applying its AI to quant hedge funds, the startup is in a field where automation is commonplace and, if successful, improvements can quickly turn into cash. That made the startup appealing to Creandum, Sellers said.

“The potential total addressable market of trading in the financial markets is one of the biggest on earth, and there are countless funds over the years that have generated quantums of profit that make most venture-backed successes look small,” Sellers said. But he noted that EquiLibre explicitly defines itself as “a lab first, not a finance firm.”

Schmid and his two founders — CTO Rudolf Kadlec and CSO Matej Moravcik — don’t have a background in finance, and it is not what drives them, he told TechCrunch. “I’m not doing this because I’m excited about making markets efficient. I’m doing this because we are all excited about building new things that have never been built before, and this is a lot of fun to build,” Schmid said.

The prospect of frontier AI by by DeepMind alumni is an area of hot pursuit by VCs as well. Another recent such example is Ineffable Intelligence, which recently raised 1.1 billion. Most of these are based in the U.K., but there are notable exceptions, including EquiLibre. 

In the case of EquiLibre’s founding trio, they were visiting PhD students at the Google-owned company’s first international AI research office in Edmonton, Alberta, Canada (which Alphabet shut down in 2023.) While there, they built DeepStack, the first AI program to defeat pro players at no-limit poker, also known as Texas hold’em. They also worked with professors who are now part of the startup’s high-profile advisory board — including Rich Sutton, who went on to receive the Turing award in 2024 for his work on reinforcement learning.

To build their startup, EquiLibre’s founders decided to move back to their home country, Czechia. “This is where we had a lot of people we had worked with, and there was a large Czech diaspora at Google and other places,” Schmid said. “These were our friends, so we told them, “Hey, guys, we are moving back to Prague, do you want to join us?”

That helped EquiLibre build its initial team back in 2022 and reach its current headcount of 25 people; but according to Schmid, that choice of location keeps paying dividends. Compared to San Francisco, “It’s much easier to keep the good people here, because there’s not a new sexy AI thing happening every two months.”

Not that EquiLibre is the only hot AI startup in town. BottleCap AI is based in the same building.

Still, this is one of the more notable AI companies in the region for talent. It next plans to scale its compute infrastructure, bringing online what it expects will be one of the largest compute clusters in Central and Eastern Europe (CEE).

While the startup also declined to disclose its total funding to date, Schmid said it previously raised two other funding rounds, with pre-seed backers including CEE-focused VC firm Credo, which also backed ElevenLabs and UiPath. According to Dealroom data, Equilibre’s $10 million seed round was led by Blossom Capital at a $140 million valuation.

Sellers confirmed that the Series A $500 million valuation was a big jump. But it also comes after the winds have changed favorably for reinforcement learning (RL), including in trading. “When we started, people were skeptical,” said Schmid. But now RL is the standard. “Because we started four years back, we believe we are ahead.”

Still, there is a risk that the startup will get leapfrogged by competitors. Trading giant Jane Street, for instance, states it already uses RL with LLMs, “or whatever else we need to train good models.” It also claims it has “tens of thousands of high-end GPUs,” while EquiLibre is seeking to squeeze more compute out of way fewer chips and “get more from less,” Schmid said.

Considering how profitable Jane Street is, EquiLibre will have to play its cards well in order to reach its goal to be known as “the AI lab in trading.” But this isn’t poker, and there might be no losers. Says Schmid: “This is not a winner-takes-all market.”

For fusion startups, the hard part is over: thanks to a groundbreaking experiment in 2022, we know that controlled nuclear fusion reactions can generate more power than they consume. But now companies need to prove their reactors can make enough electricity to be profitable.

One option is to simply turn up the temperature, generating more heat to produce more steam to spin a bigger turbine. Another is to harvest electricity directly from the fusion reactions themselves, an approach that promises to be more efficient.

Realty Fusion announced that an experiment it conducted on June 19 successfully powered a lightbulb using electricity harvested directly from WHAM, its demonstration fusion device. The Wisconsin-based startup believes it is the first private company to publicly demonstrate such a feat.

“We can take power from a plasma,” Kieran Furlong, co-founder and CEO of Realta Fusion, told TechCrunch. The milestone shows “what’s possible,” he added.

Realta plans to use direct electricity conversion to heat the plasma in its reactor, a process that requires a lot of energy. Furlong estimates that direct conversion is about 90% efficient, meaning it will convert 90% of the potential energy into electricity. By comparison, steam turbines in today’s fission reactors are about 33% efficient. The more energy the company is able to harvest, the quicker it will get to profitability.

Every power plant consumes some of the power it produces simply to operate, and fusion reactors are no exception. The big challenge fusion startups face today is building reactors that can produce more energy than they consume. The efficiency boost from direct energy conversion should make clearing that hurdle easier.

About 20% of the energy from fusion reactions fueled by deuterium-tritium, the kind Realta plans to use in its commercial reactors, are charged helium nuclei known as alpha particles. The startup built a prototype electricity converter and attached it on the end of its reactor. There, it was able to harvest enough “alpha power” to generate multiple amps of electricity at 100 volts, powering a few lightbulbs.

On a commercial scale power plant, the direct energy converters should provide enough energy to heat the plasma. “You’re basically able to recirculate the electricity,” Furlong said. 

Ultimately, Furlong estimates that circularity could boost a commercial scale power plant’s total output by 20% to 30%. “Spinning a flywheel of electricity, if you like, is very beneficial.” he said.

Though it might be the first to demonstrate direct energy conversion, Realta isn’t the only startup planning to deploy that technology in is reactor. For Helion, the startup backed by Sam Altman, direct energy conversion is key to its plans, though it has yet to demonstrate it publicly.

Harvesting electricity directly from the fusion reaction “really helps with the economics” of a reactor’s design, Furlong said.

Realta previously raised $36 million in a Series A led by Future Ventures in 2025. Furlong said the company is in the midst of raising a new round.

Google on Tuesday released Nano Banana 2 Lite, the newest version of its in-house AI video and image generator. This version is significantly faster and more affordable than its previous release, the company claims.

The model has much lower latency and can produce images in 4 seconds, which makes it a good option if you need to workshop images and produce a large number of them in quick succession, Google says. It costs $0.034 per 1,000 images, which makes it quite affordable for people looking to draft and perfect their content at scale.

The release follows last summer’s launch of the original Nano Banana, powered by Gemini 3.1 Flash, and the February release Nano Banana 2. The latter introduced new powers for the generator, including the ability to create more realistic images. The company also offers Nano Banana Pro, which is described as a more powerful (and more expensive) model for advanced use cases.

While Nano Banana 2 is referred to as a “generalist workhorse,” Banana 2 Lite is optimized for high-volume workflows that need to occur at a rapid pace, Google claims.

Despite consumer backlash over so-called AI slop created by image models, companies continue to invest heavily in AI tools that can generate imagery and videos. However, Google often markets its models as convenient tools that can assist with the creation of advertisements.

That said, the ties between Hollywood and AI companies continue to tighten — much to the consternation of some creative communities and audiences. Indeed, Google just struck a $75 million deal with the much-beloved indie studio A24 — a partnership that has suffered significant criticism from fans.

Nano Banana 2 Lite is now available through Google AI Studio and the Gemini API, as well as Google’s Gemini Enterprise Agent Platform. Google says it serves as a replacement for Nano Banana, which the company now refers to as its “legacy model.”

Also on Tuesday, Google announced a wider release of Gemini Omni Flash, which was initially introduced at Google I/O earlier this year. Flash costs $0.10 per second of video output. Plus, Google showed off a new demo app, Omni Product Studio, which it says can take static images generated by Omni and transform them into “cinematic e-commerce videos.”

“Building with generative media is often about creative iteration,” the company said in a blog. “With these two models, developers can build comprehensive, end-to-end multimedia experiences that connect rapid image generation with video creation and editing.”