Has the hunt for AI compute uncovered the next Cerebras?

7:07 PM IST · May 28, 2026

The raging demand for computers to run AI models has only accelerated, but there are two major obstacles that anyone in the business needs to overcome: getting the right chips, and getting them into data centers where they can start generating revenue. General Compute, a new inference neocloud — a company that rents out AI processing power, specializing in the phase when models are running and responding to users rather than being trained — has answers to those questions that illuminate where the AI ecosystem is headed. Those answers helped it raise a $15 million seed round at a $60 million post-money valuation, led by FUSE VC with participation from Carya Venture Partners and Village Global Ventures. First, what is the right chip? The demand for GPUs has gone through the roof, but it’s becoming conventional wisdom that they aren’t the best-suited chips for running AI models once they have been trained. The phase of AI where a model is actively generating responses has different computational requirements than training, and a new class of chips is being designed specifically for it. Nvidia’s $20 billion Groq transaction in December and Cerebras’ $57 billion IPO last week point the way. With capacity strained at both those companies, the co-founders of General Compute, CEO Finn Puklowski and CTO Jason Goodison, found another option. They’re turning to specialized chips built by SambaNova, an Intel-backed chipmaker focused on inference that has fallen a bit out of the Silicon Valley conversation. That may change when SambaNova releases its new chips this year. The architecture is more flexible and uses more memory to store context during inference calculations, and SambaNova claims that it outperforms not just GPUs but also other specialized chips built by the likes of Groq or Cerebras. Puklowski says the new chips will generate 600 to 700 tokens per second, versus about 250 tokens per second for GPUs. General Compute has $300 million of the company’s SN50 chips on order and says it will be the first neocloud deploying them. These chips also help solve the second big problem—where to put them—for General Compute: They are air-cooled, not water-cooled, and consume less power, so they can be installed in existing data center facilities without new infrastructure investments. Puklowski is pursuing colocation deals — arrangements where General Compute installs its hardware in someone else’s facility — not just with data center providers, but also with crypto miners looking to repurpose their infrastructure as the cost of producing a bitcoin has often exceeded its price. General Compute launched its cloud offering last week, claiming it is already the fastest at running MiniMax 2.7, a powerful open-source LLM. Joe Hasselmann is a venture investor who got in on the ground floor of the inference boom when he invested in Groq in 2021. This year, he launched a new fund, Evercrest Capital Partners, focused on the AI space, and made General Compute his first investment. Hassleman sees in SambaNova’s partnership with General Compute parallels to Coreweave’s relationship with Nvidia — and to the pairing of Groq’s chip-making with its former cloud offering. “They do need a healthy mix of customers that are going to put their chips in environments that are going to have high growth to them,” Hassleman said. “As much as General Compute is making a bet on SambaNova, SambaNova is making a bet on General Compute.” The question is what kind of computer architecture will capture the most value in the AI future. Inference clouds are implicit bets on a world of multiple models and agents, one where no single provider dominates and speed and cost of inference become the key competitive variables. Consider the$113 million Series Braised for OpenRouter this week, reflecting the company’s ability to offer customers access to multiple models in order to optimize their token spend. Speed matters in that calculation, for price, and for capability. Puklowski wants to turn hour-long workloads for coding agents into five- or ten-minute tasks, and make audio agents for customer service, which require faster inference to converse effectively, more economical.“If you use ChatGPT and it gives you 50 tokens per second, that’s still a heck of a lot faster than we can read,” Puklowski told TechCrunch, “Now that things have moved to agent-to-agent, where agents are out there reading on our behalf or pinging databases, they need to go faster.”

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Encryption, spyware, and now Mythos: History shows why cyber export control doesn’t work

Last Friday, citing unspecified national security concerns, the White Houseordered Anthropicto restrict the export of its powerful AI models Fable and Mythos to anyone outside of the United States, as well as foreign nationals inside the country. Shortly after, the AI giant hastily pulled the plug on both models, which have now been unavailable to anyone for a week. The episode is the first real test of whether the U.S. government can use export controls to contain frontier AI the way it has tried, with very uneven results, to contain encryption and spyware before it. And dramatic as it may sound, how this standoff gets resolved could shape not just Anthropic’s access to foreign markets but the rulebook that other AI labs will have to build around. Some context first.Ever since Anthropic launched Mythos in April, the company has marketed it assome kind of Doomsday cyber machinethat could wreak havoc on the internet if released too widely — which is why, before the ban,only around 150 vetted companies and government organizationshad access to it at all. The goal was helping defenders secure their software and services before the bad guys could reach Mythos-like capabilities. So what triggered the ban? Two subsequent events, reportedly. The first: Anthropic gave a South Korean telecom access to Mythos through its limited partner program, and U.S. officials grew alarmed after identifying the company as one they suspected had ties to China. (The company,widely reportedto be SK Telecom, hasdeniedany China connection.) Amazon CEO Andy Jassy also reportedlyalerted the administrationafter Amazon’s own researchers, he said, found a way around Fable 5’s safeguards. Anthropic disputes the “jailbreak” label, calling it a narrow, already-patched issue rather than a wholesale defeat of the model’s safety measures. The result was the same: the Commerce Department issued an export control directive, and Anthropic had to scramble to immediately limit access to its products — within roughly 90 minutes of being notified, by some accounts. None of this is new, though. Governments have tried to use export controls to limit the proliferation of what they see as dangerous cyber technology for decades, but their track record has been middling at best. The U.S. government was behind what is perhaps history’s most spectacular failure of this approach in the early to mid-1990s. At the time, computer scientists were developing encryption technologies to secure data as it traveled over the internet. One of those encryption products was called Pretty Good Privacy, or PGP, a popular software that could encrypt data and make it virtually impossible to unscramble even if intercepted as it traveled to its intended recipient over the internet. The U.S. government initially saw PGP as a dangerous weapon, fearing it would prevent its intelligence agencies from snooping on emails as they crossed their wires. To stop the distribution of PGP, the U.S. Customs Serviceopened a criminal investigationagainst PGP’s creator Phil Zimmermann for allegedly violating arms export controls. He fought back by publishing PGP’s source codeas a printed book, igniting what is known today as the “Crypto Wars.” Zimmermann later won a key battle when the investigation was closed, paving the way for crucial end-to-end encryption algorithms such as the one used by billions of Signal and WhatsApp users. Later during the early 2010s, researchers began discovering Western-made spyware used against dissidents in the Middle East. In response, several governments agreed to expandthe Wassenaar Arrangement, an international treaty that limits the export of dual-use software and technologies that are used in both civilian and military applications. The idea was to classify surveillance and hacking software as dual-use, thus forcing spyware makers to get export licenses to sell their products abroad. Contact UsDo you have more information about the Mythos ban? From a non-work device and network, you can contact Lorenzo Franceschi-Bicchierai securely on Signal at +1 917 257 1382, or via Telegram and Keybase @lorenzofb, oremail. But Wassenaar has always had two inherent weaknesses. There are several countries that don’t adhere to the agreement, including Israel, which houses some of the world’s most active spyware makers. The agreement also depends on countries applying it to companies within their borders at their own discretion. For a time, the Italian government allowed one of the country’s then-top spyware makers, Hacking Team, a license to export its tools around the world, despite the company’s track record of selling spyware tooppressivegovernmentsthatused itto hack journalists and human rights activists. Since then,othercountriesin Europe have been lax with spyware makers like Italy. Despite numerous scandals, Europe, home tomany spyware and hacking tools makers, hascontinually failed to curb the export of spywareto authoritarian regimes. Critics say that a recently renewed effort across the bloc of 27 member states to tackle its growing problem of spyware exports to authoritarian states “does not go far enough.” Several spyware makers, such as Intellexa, a sanctioned consortium of spyware companies, have simply moved their operations to countries with lax export controls. Other spyware makers sought to move their operations to Saudi Arabia for similar reasons. There have been some wins. Germany-based spyware maker FinFishershut down in 2022after a multi-year investigation by German prosecutors into the company forallegedly selling spywareto Turkey without an export license. Investigators previously found the FinFisher spyware had beendeployed on the phonesof critics of Turkey’s government. As of the time of writing, the impasse between Anthropic and the Trump administration remains. There is a reasonable chance the administration will buckle and lift the restriction in the interest of keeping American AI companies competitive worldwide — a move that would amount to tacit acknowledgment that AI labs elsewhere, including in China, will likely reach similar capabilities regardless of what the U.S. restricts. Or, American AI companies could end up needing government approval before serving foreign customers at all, a compliance burden that would invariably dent their bottom line. Given the past experiences that world governments have had with trying to control the reach of software, government-mandated export controls are unlikely to be the right approach to stop malicious actors from abusing powerful dual-use cyber technologies.

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Billionaire Ambani wants AI in every call, app, and home

As India searches for a homegrown contender in the global artificial intelligence race, billionaire Mukesh Ambani is positioning Reliance Industries as a national champion, rolling out AI services for phone calls, mobile apps, and connected homes. At itsannual shareholder meetingon Friday, the Mumbai-based conglomerate announced Jio Call Agent, an AI assistant that can join phone calls to transcribe conversations, generate summaries, and perform tasks such as booking cabs, ordering food, and making reservations. The service, which can be activated by saying “Hey Jio,” is expected to launch later this year for Jio’s more than 500 million users. By embedding the service directly into its telecom network rather than offering it as a stand-alone app, Jio is betting AI assistance can become a native feature of phone calls. The approach could reduce consumers’ reliance on third-party call-assistant apps and give Reliance a powerful distribution advantage in an increasingly crowded AI market. Reliance also unveiled an AI-powered version of its MyJio app that can perform tasks on behalf of users, from activating eSIMs to selecting roaming plans, through natural-language requests. The company further introduced TeleFrame, a home display that uses AI agents to proactively surface information and recommendations, such as weather alerts, schedules, and household reminders. The product appears to echo a broader industry push toward ambient AI assistants for the home, an area being explored by companies such asAmazonandGoogle. The announcements mark the next phase of Reliance’s AI ambitions as India seeks to build domestic capabilities in a field largely dominated by U.S. and Chinese technology companies. The push follows thelaunch of Reliance Intelligencelast year, through which the conglomerate aims to develop AI infrastructure and services for consumers, businesses, and governments, including applications that support 22 Indian languages. “India should not be a mere consumer of AI created elsewhere. It must become a creator, adopter, and a global leader in AI,” Ambani, age 69, said. Reliance has been ramping up its AI ambitions through partnerships withGoogle,Meta, andNvidia. Earlier this year, the company announced plans toinvest $110 billion in AI infrastructureas it seeks to establish itself as a major player in India’s emerging AI ecosystem. At the shareholder meeting, Reliance also unveiled a suite of AI services for healthcare, education, agriculture, and small businesses. The products, branded JioHealthIQ, JioLearnIQ, JioKrishiIQ, and AI Vyapar, are designed to operate across multiple Indian languages and cater to local needs, the company said. The shareholder meeting also brought a major development for investorsawaiting Jio’s stock market debut. Ambani said Jio Platforms’ board had approved a draft prospectus for an initial public offering that would include a fresh issue of up to 270 million shares, according to a stock exchange filing. The announcements also raise questions about how Reliance will handle user data as it expands AI services across phone calls, mobile apps, and connected homes. While the company said the services would operate with user consent, it did not answer questions about whether data generated through the products could be used to train AI models or shared with technology partners. Reliance’s AI ambitions come as Indian companies remain heavily reliant on foreign AI models and cloud providers.Recent restrictions on accessto some of Anthropic’s latest models have underscored that dependency, showing how decisions made overseas can affectstartups and businessesbuilding AI products in India — the kind of supply-chain risk that’s pushing Indian conglomerates toward building their own stack rather than renting someone else’s. Last week, Reliance announced acollaboration with Meta to establish an AI data centerin the western state of Gujarat, building on Meta’s earlier investment in Jio Platforms and a joint venture launched last year to develop AI solutions for enterprise customers in India and overseas markets. Reliance is not alone in pursuing AI opportunities.Tata Consultancy Services,Infosys, and rivalAdani Grouphave also expanded their AI initiatives and partnerships with global players, including Anthropic, Google, and OpenAI, as India’s largest corporations race to secure a leading role in the country’s AI future. Nonetheless, for Reliance, the stakes are particularly high; it’s preparing Jio for a long-awaited stock market debut and needs new growth drivers, with the conglomerate’s shares down about 17% this year.

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The US banned Anthropic’s Fable 5 release, but the numbers don’t seem to care

Just as last week was ending, the US governmentforced Anthropic to pull its two newest models, Fable 5 and Mythos 5, citing national security concerns after Amazon researchers allegedly found a way to bypass Fable 5’s guardrails. Cybersecurity researchers havesince signed an open lettercalling the move dangerous, and Anthropic itself noted the same jailbreaks exist in other models. So is this a genuine security concern, or just the latest chapter in a messy relationship between Anthropic and the Trump administration? On this episode of TechCrunch’sEquitypodcast, hosts Anthony Ha, Sean O’Kane, and Rebecca Bellan unpack what the ban means for developers building on Anthropic’s platform and for anyone watching the IPO, why itmight accidentally be good for the company, and more of the week’s headlines. Listen to the full episode to hear more about: Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.

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Is the US government’s Anthropic ban accidentally helping the brand?

Loading the player… Just as last week was ending, the US governmentforced Anthropic to pull its two newest models, Fable 5 and Mythos 5, citing national security concerns after Amazon researchers allegedly found a way to bypass Fable 5’s guardrails. Cybersecurity researchers havesince signed an open lettercalling the move dangerous, and Anthropic itself noted the same jailbreaks exist in other models. So is this a genuine security concern, or just the latest chapter in a messy relationship between Anthropic and the Trump administration? On this episode of TechCrunch’sEquitypodcast, hosts Anthony Ha, Sean O’Kane, and Rebecca Bellan unpack what the ban means for developers building on Anthropic’s platform and for anyone watching the IPO, why itmight accidentally be good for the company, and more of the week’s headlines. Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.

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