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AI News‘Not built right the first time’ — Musk’s xAI is starting over again, again

‘Not built right the first time’ — Musk’s xAI is starting over again, again

9:04 AM IST · March 14, 2026

‘Not built right the first time’ — Musk’s xAI is starting over again, again

And then there were two: Of the original 11 co-founders who kickstarted xAI with Elon Musk three years ago, only two remain as the deep learning lab continues a personnel overhaul to compete with Anthropic and OpenAI. That rebuilding, insists Musk, is by design. “xAI was not built right first time around, so is being rebuilt from the foundations up,” Musksaid Thursdayon his social media platform, X. By most measures, it isn’t going all that smoothly. The most immediate pressure is competitive. This week, xAI co-founders Zihang Dai and Guodong Zhang left the outfit after Musk complained that the company’s AI coding tools were not effectively competing with Claude Code or Codex, rival programming assistants made by Anthropic and OpenAI, respectively. Musk said the company held an all-hands meeting on Wednesday that focused on how to catch up, which he predicted would be possible by the middle of this year. Coding tools matter so much because they’re where the money is. While an early-year surge of users was powered by xAI’s lax regulation of Grok’s ability to produce sexual and even abusive imagery, coding tools are seen as the key revenue-generating tech for AI labs. That makes xAI’s current lag in this area more than a perception issue; it’s a business problem. The personnel overhaul extends well beyond this week. A month ago, 11 senior engineers at xAI, including two co-founders,left the companyfollowing changes Musk described as a reorganization to suit a larger business. That effort was apparently insufficient: The Financial Timesreportedthat SpaceX and Tesla executives have parachuted into the company to evaluate employees and fire those who don’t make the grade. The two remaining co-founders, Manuel Kroiss and Ross Nordeen, along with Musk, have their work cut out for them. Musk is now casting a wider net for talent. On Thursday, he said on X that he and another colleage,Baris Akis, are currently reviewingrejected employment applicationsin the company, with an eye toward reaching out to promising candidates who should have had a chance to interview. “My apologies,” Musk added, addressing the pile of strangers he’d ghosted. For the sake of comparison, LinkedIn reports that xAI has just over 5,000 employees, compared to more than 7,500 at OpenAI and more than 4,700 at Anthropic. On the hiring front, there’s at least one encouraging sign. Andrew Milich and Jason Ginsberg are joining xAI from the AI coding tool company Cursor, where the two held joint responsibility for product engineering. Unlike xAI, Cursor depends on frontier labs for access to the AI models it runs on. Their decision to join xAI may signal the importance of direct access to LLM and computing resources to run them — and suggest that xAI’s core asset, its own frontier model, is still an attractive draw. Either way, the pressure to show results is as much external as it is internal. Now that xAI is part of SpaceX, and with a public offering of SpaceX shares anticipated, the cash-burning unit is under pressure to demonstrate real uptake on Grok, its LLM. (A stumbling AI division is not the story Musk needs investors to be reading.) Longer term, Musk is betting on something bigger than coding tools. xAI’s Macrohard project — Musk is convinced the name is “a funny reference to Microsoft” — aims to create an AI agent capable of doing anything a white-collar worker can do on a computer. Toby Pohlen, chosen to lead the project in February, left within weeks, and this week, Business Insiderreportedthat Macrohard was on pause. Musk’s response has been to draft another of his companies into the project. He revealed for the first time that Macrohard is a joint effort with Tesla, which is also developing a complementary agent dubbed “Digital Optimus” — a reference to Tesla’s Optimus humanoid robot. In Musk’sdescription, the xAI language model would direct the Tesla agent as it performs tasks. It’s ambitious; it’s also not unique. Instead, the vision is not far off from what Perplexity — an AI-powered search engine — is doing with its new “Everything is Computer” offering, which aims to offer enterprise users a dedicated “digital proxy” that can orchestrate their digital tasks. It also echoes what entrepreneur Peter Steinberger is now working on at OpenAI, after creating OpenClaw’s popular personal agents.

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Google introduces a faster, cheaper image generator with Nano Banana 2 Lite

Google introduces a faster, cheaper image generator with Nano Banana 2 Lite

Google on TuesdayreleasedNano 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 four 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 ofNano 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 overso-called AI slopcreated by image models, companies continue toinvest heavilyin 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, Googlejust struck a $75 million dealwith the much-beloved indie studio A24 — a partnership that has sufferedsignificantcriticismfrom 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 wasinitially introducedat 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 saidin 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.”

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The DeepMind trio who built a poker AI are now making money for quant hedge funds

The DeepMind trio who built a poker AI are now making money for quant hedge funds

Three former DeepMind researchers who created an AIthat beat humans at pokerhave 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 forreinforcement 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 partnershipwith 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 arenotable exceptions, including EquiLibre. In the case of EquiLibre’s founding trio, they were visiting PhD students at the Google-owned company’sfirst international AI research office in Edmonton, Alberta, Canada(which Alphabetshut downin 2023.) While there, they builtDeepStack, the first AI program to defeat pro players at no-limit poker, also known asTexas 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 theTuring award in 2024for 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 AIis 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 toDealroom 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 RLwith 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. Consideringhow profitable Jane Street is, EquiLibre will have to play its cards well in order to reach its goal to be known as “theAI lab in trading.” But this isn’t poker, and there might be no losers. Says Schmid: “This is not a winner-takes-all market.”

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OpenClaw is finally available on Android and iOS

OpenClaw is finally available on Android and iOS

The automation crustacean is crawling to a mobile device near you. By that I mean, OpenClaw — the free, open source AI agent that captivated the internet earlier this year — is finally available as an app on iOS and Android. OpenClawannouncedthe news on X on Tuesday. On both platforms, you can pair your phone with the OpenClaw Gateway, a kind of routing layer that connects your requests to AI agents and the tools and skills those agents draw on to get things done. The takeaway is that you’ll be able to run your OpenClaw agents from your pocket and, if you’ve programmed them correctly, they may be pretty helpful at getting things done. OpenClaw users haveput it to workin everything from coding to meal planning, although somehave reportedless-than-desirable results. OpenClawwent viralearlier this year around the launch of MoltBook, a social media site purportedly populated entirely by agents. In February, OpenClaw’s creator, Peter Steinberger,announcedthat he had joined OpenAI. The MoltBook spectacle was later revealed to have been partially the work of humans impersonating agents,according to researchers, effective theater that doubled as marketing for OpenClaw (whatever its credibility cost). Still, the stunt pointed toward the agentic future, which has since kept expanding. Agents are now embedded across the AI landscape and are showing up inmore places by the day, including your phone.

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Amazon launches new $1 billion FDE org, following OpenAI and Anthropic

Amazon launches new $1 billion FDE org, following OpenAI and Anthropic

As companies struggle to integrate AI, they’re increasingly ready to bring in outside help — and service providers are launching new purpose-built groups to make sure they get it. On Tuesday, Amazon Web Services (AWS)launcheda new internal organization for AI-focused forward-deployed engineers. Engineers on the new team will embed within companies to deploy purpose-built agents, focusing on fast engagements and customer self-sufficiency. In a post announcing the new org, AWS VP of Frontier AI Francessca Vasquez emphasized that the org would do more than build and maintain requested systems. “Customers leave AWS FDE deployments with both new solutions and new engineering capabilities,” the announcement reads. “Along with agentic systems running in their own AWS environment, they gain lasting AI skills, workflows, and patterns they can use to innovate independently.” Amazon says $1 billion will be committed to the new org, although the figure represents internal Amazon resources rather than a joint venture or conventional investment. Pioneered by Palantir, the forward-deployed engineer (FDE) model has become increasingly popular as a way to manage AI deployments. In a typical FDE system, an engineer from the contracting company (in this case, AWS) works for the client temporarily while the system is being established, allowing them to respond directly as internal opportunities or challenges emerge. In the FDE model, much of the relevant technology can be reused between deployments, while still being tailored to the specifics of each company’s needs and workflows. It also gives the client company an influx of expertise and puts primary responsibility for the deployment in the hands of the contractor. The biggest downside is the labor involved, since it means maintaining a full corps of FDE engineers to install and maintain the company’s technology. Both OpenAI and Anthropichave launched their own FDE joint ventures in recent months, valued at $4 billion and $1.5 billion, respectively. In those two cases, the AI labs were paired with private equity firms, which provided both the capital to launch and connections with client corporations in their portfolios.

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