Fervo Energy, the geothermal energy startup, achieved a market valuation exceeding $10 billion during its initial public offering, a surge fueled by the demand for AI data centers — and the energy necessary to operate them.

On Wednesday, Fervo raised $1.89 billion in an expanded initial public offering, initially placing its valuation at around $7.6 billion. The interest in Fervo shares was so pronounced that the company and its underwriters increased the offering multiple times, selling an extra 14.6 million shares while adjusting the price range upward twice, ultimately arriving at $27 per share.

The stock, trading under FRVO on the Nasdaq, surged another 33% at the start of trading on Wednesday, pushing its valuation above $10 billion.

“We were asked several times during the roadshow, ‘Why aren’t you raising more capital?’” Sarah Jewett, Fervo’s senior vice president of strategy, shared with TechCrunch. “As we observed the demand increasing, there were just enough indications suggesting that upsizing was not only possible, but also advisable.”

Similar to many other energy firms, Fervo has been supported by a spike in demand from data centers and AI enterprises, which are eager to secure power for their operations. It marks the second energy stock offering to receive a positive response recently, with nuclear startup X-energy securing $1 billion in its own expanded IPO. 

The fundamental idea behind geothermal energy — harnessing the Earth’s warmth for power — has existed for years, yet Fervo belongs to a new wave of startups pioneering enhanced geothermal, which drills deeper to access hotter rock formations. To maximize the effectiveness of a favorable geothermal site, Fervo employs directional drilling methods developed by the oil and gas sector.

“We’re replicating the strategy used in the shale energy industry, but with the answer key,” Jewett remarked.

Fervo’s IPO yielded the company $500 million more than it had expected, providing a financial cushion that grants the company more flexibility as it works on its Cape Station power plant in Utah, set to begin operations this year. Ultimately, the firm aims to produce 500 megawatts once Cape Station’s initial phase is completed, projected to take approximately three years.

The 500 megawatt capacity of Cape Station was determined by the size of the grid interconnection the company secured, but Fervo is authorized to develop up to 2 gigawatts of geothermal energy there, and it has applied for an increase in the size of its interconnection as well. However, even that might be a conservative projection. Jewett stated that a third-party engineer indicated sufficient heat on-site for as much as 4 gigawatts of capacity.

The additional electricity could be directed to the grid if the interconnection capacity expands. If not, Fervo has been responding to inquiries from companies interested in direct connections. “We’re observing a growing amount of behind-the-meter commercial interest,” Jewett noted.

Fervo is at an earlier stage of development on another initiative. Corsac Station in Nevada, from which Google will procure 115 megawatts of power.

One of geothermal’s attractions is its ability to deliver so-called baseload power, a source capable of generating electricity around the clock, irrespective of weather conditions. Data center operators, who prioritize high uptime, are currently willing to pay a premium for reliable power. This has transformed geothermal from merely another clean energy technology competing for grid space into a preferred choice among tech firms and, now, investors.

The Houston-based company has been racing to lower expenses by shortening the duration of drilling new wells. Fervo’s initial wells took many days to complete and cost over $1,000 per foot. Now, after drilling 14 wells, the company has decreased both drilling time and cost per foot by two-thirds.

This IPO was likely overdue, yet with growing interest in energy, its timing could not have been more opportune.

Fervo disclosed in December that it had concluded a $462 million funding round, and climate tech and energy investors that TechCrunch consulted with late last year almost universally anticipated the company’s IPO. Interest from hyperscalers, in conjunction with data from its Cape Station project, suggested that the company had successfully navigated the “valley of death.” With the IPO behind it, it appears Fervo is now firmly on stable ground.

X is evolving into a more “save-it-for-later” platform with its new History tab that aggregates your bookmarks, likes, videos, and articles into one easily accessible location.

First introduced on iOS, X’s product head, Nikita Bier, refers to this new feature as an improved method for monitoring all your preferred content, enabling you to revisit items you want to finish reading or watching at a later time.

With this update, the Bookmarks button in X’s left-side menu on the mobile app has been renamed to History. The new section categorizes your saved content into four distinct tabs — Bookmarks, Likes, Videos, and Articles — allowing for seamless navigation at any moment. While Bookmarks and Likes are intentional saves, the Videos and Articles tabs will auto-fill based on your viewing or reading activities on X. The History area keeps your data private,
Bier’s announcement states.

This enhancement gives X a more browser-like feel, where users can revisit previously viewed content even without consciously saving it. It brings together functionalities that were scattered across the app, with bookmarks located in the main menu and likes tucked away in a tab on the user profile.

This initiative may also promote increased utilization of X’s long-form article feature, which the company has been promoting as a means for businesses and creators to share updates that extend beyond the typical post limit of 280 characters. X users can keep track of the articles they discover while scrolling, crafting a customized news reader experience within the app.

The update arrives as web publishers face a downturn in referral traffic from platforms such as Facebook and Google, influenced by evolving algorithms and AI-driven experiences that have diminished external site clicks. X regards this evolution as a chance to attract more publishers and creators to produce content directly on its platform, where distribution and discovery are inherently integrated.

On Wednesday, Instagram revealed its global rollout of “Instants,” a novel feature designed for sharing genuine, transient photos after trialing it with a limited audience. This feature allows users to send disappearing photos to their close friends or mutual followers that can be viewed just once and will stay accessible for 24 hours.

The application draws inspiration from social media platforms like Snapchat, Locket, and BeReal, emphasizing genuine and fleeting content.

In contrast to Instagram, which centers on curated and polished content, Instants caters to quick, real-life snapshots. With Instants, you can take a photo using Instagram’s built-in camera with no editing permitted. The format restricts uploads from your camera, and although you can include text in your “instants,” no further modifications are allowed. Meta shared in a blog entry that the intent behind this concept is to share genuine moments in real-time.

Additionally, it’s important to note that Meta is also evaluating the Instants format as an independent application in select locations, including Spain and Italy.

To capture an Instant, tap the mini photo stack in the lower right corner of your Instagram inbox. Once you share your Instant, those who receive it can respond with emojis, reply, and send an Instant back. Meta emphasizes that recipients are unable to screenshot or record the Instants you’ve shared.

Instagram keeps your shared Instants in a private archive accessible for up to one year. You can also assemble Instants from this archive into a recap and share it via Instagram Stories.

If you accidentally share an Instant, you can tap the “undo” button and delete the Instant from your archive to retract it from friends who haven’t viewed it yet.

If you prefer not to receive Instants, you can press and hold the stack of Instants in your inbox and swipe right to temporarily halt their delivery. You also have the option to block or mute particular users.

While Instagram originally served as a means for friends to exchange moments, the platform has increasingly been inundated with influencer content and advertisements. Through Instants, the company appears to be returning to a focus on more relaxed, private interactions that revolve around photo sharing among friend groups.

Nonetheless, Instagram might be slightly late to seize the trend of casual, authentic photo sharing, as BeReal is no longer as widely favored as it used to be, and numerous users already utilize Instagram Stories for quick, informal updates, potentially questioning the necessity for a distinct app and feature.

In May 2023, Sam Altman, the CEO of OpenAI, was sworn in and presented his views on artificial intelligence regulation before Congress. Senator John Kennedy from Louisiana listened to his thoughts on licensing advanced models and inquired if Altman would be suitable to head a theoretical AI regulatory agency.

“I enjoy my present role,” Altman responded, eliciting laughter.

“You get paid well, don’t you?” Kennedy questioned.

“No, my salary is enough to cover health insurance. I don’t have any equity in OpenAI,” Altman clarified.

“You ought to consult a lawyer,” Kennedy advised.

Currently, Altman has numerous lawyers, who observed as their client underwent an intense questioning session during a federal court appearance in California on Tuesday. They were examining a similar issue as Kennedy — is Altman capable of managing the most sophisticated AI models?

“You failed to inform the U.S. Senate that you held an interest in OpenAI through a share in a Y Combinator fund, didn’t you?” Steve Molo, the aggressive attorney heading Elon Musk’s campaign to halt OpenAI’s for-profit operations, demanded.

Altman acknowledged that he indeed had financial ties to OpenAI due to his limited partner position in the Y Combinator fund. “I didn’t bring it up in that testimony, but, once more, I believe it’s well understood what being a passive owner of multiple venture funds implies,” Altman stated.

“You assumed Senator Kennedy was a highly experienced investor when he posed that question, didn’t you?” Molo retorted.

Altman’s choice to disclose that he had no equity when he could have easily avoided the question was intriguing. It is technically accurate, but Altman — who stressed his background in investing in early-stage startups — must have been aware of his financial stakes in OpenAI through Y Combinator and investments in other AI firms collaborating with OpenAI.

On Tuesday, Altman’s credibility was under scrutiny, at least from the viewpoint of the plaintiffs. OpenAI’s lawyers contended that little progress was made in support of Musk’s case, accusing the other side of defamation. Nonetheless, the jury and Judge Yvonne Gonzalez Rogers are evaluating Altman’s reliability as a crucial figure in the events being reviewed.

Molo highlighted a series of individuals who alleged that Altman lied or deceived them — including sworn statements in court from former OpenAI board members Helen Toner and Tasha McCauley, Elon Musk, and OpenAI co-founder Ilya Sutskever. He also referenced a recent New Yorker article outlining concerns regarding his integrity.

The “incident” — during which OpenAI’s board temporarily dismissed Altman and removed Greg Brockman as board chair for a perceived lack of transparency — has been a focal point of discussion at this trial. Then-board members Toner and McCauley testified that Altman had misled them, with McCauley describing “a toxic culture of dishonesty.”

“I do have reservations that was the complete reason” for his dismissal, Altman remarked. When asked again to acknowledge that the board indicated he had not been transparent, Altman responded, “They asked me to return the following morning.”

The emphasis on his firing is not solely about challenging Altman’s trustworthiness. A significant inquiry of the trial revolves around whether OpenAI’s structure aligns with its mission, especially whether the non-profit board can genuinely exert control over the for-profit entity. From Musk’s legal team’s perspective, the 2023 incident serves as evidence that Altman’s power within the company surpassed that of its board of directors.

Witnesses summoned by OpenAI and Microsoft have insisted that the existing non-profit board does possess authority over the for-profit. Microsoft CEO Satya Nadella described Altman’s dismissal as “amateur city.”

Bret Taylor, who assumed the role of chair on OpenAI’s board following Altman’s reinstatement, claimed he found nothing justifying his termination and stated that Altman has been “open with me.” Dr. Zico Kolter, the OpenAI board member focused on AI safety, affirmed that no one had hindered that initiative since he began in 2024.

However, Taylor also made it clear that the decision to bring Altman back in 2023 stemmed from the belief that his exit would have virtually shut down OpenAI, as most employees were prepared to leave with him. Now, as the jury and judge contemplate whether the present structure aligns with the organization’s mission, they will consider whether the board genuinely has the power to dismiss or discipline its CEO.

When asked if he would ever dismiss himself as CEO, Altman responded that he had no intention of doing so. When queried about his trustworthiness, he replied, “I consider myself an honest and reliable businessperson.”

As artificial intelligence starts to engage with the physical environment, innovative labs are developing world models intended for controlling physical robotics or simulating objects in tangible space. Unlike large language models, acquiring data for these models is not straightforward, leaving numerous labs in a rush to compile the needed training datasets.

Currently, a startup is emerging with an unexpected data source: the gaming industry.

This is the concept behind Origin Lab, which has just revealed an $8 million seed funding round, spearheaded by Lightspeed Ventures. SV Angel, Eniac, Seven Stars, and FPV also joined in, along with angel investments from Twitch co-founder Kevin Lin and Cruise founder Kyle Vogt.

“The AI systems currently being developed need to grasp how the physical world operates and how objects move,” co-CEO and co-founder Anne-Margot Rodde stated to TechCrunch. “That information essentially resides in video games.” The company’s other co-founders (shown above) are Antoine Gargot and Colin Carrier.

In essence, Origin Lab will function as a marketplace where labs focused on world modeling, such as Yann LeCun’s AMI Labs or Fei-Fei Li’s World Labs, can acquire high-quality licensed data. Conversely, video game companies can generate additional revenue from the digital assets they have already produced. In between, Origin Lab will transform the video game assets into a format suitable for training data — which might be as straightforward as conducting a rendering run or as intricate as automating hours of gameplay footage.

“It became evident that the video game industry was harboring some extraordinarily valuable data, but there was no genuine method or framework to effectively connect AI labs and the gaming sector,” Rodde explains. “So, we effectively constructed that bridge.”

Labs have long been intrigued by video game footage as a potential data resource, but licensing and quality issues have frequently posed challenges. In December 2024, OpenAI sparked a minor controversy when the initial iteration of its Sora video-generation model appeared to replicate footage of popular games and streamers — likely because it was trained on Twitch streams. Amazon has expressed its intent to leverage Twitch footage for training models.

Origin’s triumph in fundraising reflects a burgeoning market — not only for training data but for startups capable of being vital suppliers to prominent AI labs. Faraz Fatemi, a partner at Lightspeed who led the investment in Origin, asserts that the success of companies like Scale AI has made the opportunity too significant to overlook.

“We’ve witnessed how rapid revenue growth can be for data vendors supporting the leading labs,” Fatemi informed TechCrunch. “These are highly capitalized enterprises, and the data is the bottleneck for all of them.”

Neil Batlivala has dedicated seven years to creating a healthcare enterprise that remains largely unknown in the tech sector and caters to a patient demographic frequently overlooked by Silicon Valley. However, last month, this endeavor positioned him at the forefront of a much larger initiative.

On April 30, his organization, Pair Team, announced its acceptance into ACCESS, a Medicare initiative — one of 150 selected by the Centers for Medicare & Medicaid Services to explore what AI-enabled healthcare might entail on a national scale. The program is set to launch on July 5.

“The government is establishing frameworks for AI innovation within traditionally regulated sectors,” he mentioned during a Zoom call days later. “The optimal solution prevails, which has not been the case in regulated fields like healthcare.”

ACCESS — Advancing Chronic Care with Effective, Scalable Solutions — is a decade-long CMS initiative testing a payment framework that rewards health outcomes instead of mandatory activities (such as a specific number of check-ins). Organizations like Pair Team will receive consistent payments for managing eligible conditions and will earn the total amount only when patients achieve quantifiable health objectives, like reduced blood pressure or less pain. The program focuses on diabetes, hypertension, chronic kidney disease, obesity, depression, and anxiety.

The payment structure is the significant development.

Traditional Medicare composes reimbursements based on the duration spent with a clinician. There is no system in place to compensate an AI agent that facilitates patient monitoring between appointments, conducts check-in calls, organizes a housing referral, or ensures medication pickup. ACCESS introduces that system for the first time.

“It signifies a transformation in payment models,” Batlivala stated. “Such a thing was impossible before.”

The inaugural cohort includes a diverse array of participants — AI medical startups, virtual nutrition therapy providers, companies with connected devices, and manufacturers of wearables like Whoop. Batlivala expresses skepticism toward some of these entrants.

“I’m an avid supporter of wearables, but for an elderly individual facing food insecurity, I question how much Whoop will actually contribute,” he remarked, adding regarding his own firm, “We’ve been progressing toward this for over five years.”

Pair Team commenced operations in 2019 with a specific patient type in focus: individuals managing chronic conditions while also confronting unstable living situations, food scarcity, or limited access to transportation. Approximately a third of Americans belong to this category.

The foundation of the company was the belief that health outcomes cannot improve without considering the comprehensive context of a person’s life. Currently, it employs around 850 healthcare professionals, operates what it claims to be the largest community health workforce in California, and, according to Batlivala, generates revenue exceeding nine figures. It has secured roughly $30 million in funding from backers such as Kleiner Perkins, Kraft Ventures, and Next Ventures.

The model is supported by peer-reviewed research. A study co-authored by researchers at Pair Team and reviewed by the Journal of General Internal Medicine assessed Pair Team’s community-integrated approach, which merges medical, behavioral, and social care for Medicaid members facing high incidences of homelessness, serious mental health conditions, and chronic illnesses, showing considerable patient engagement and notable decreases in preventable emergency and inpatient usage. Batlivala claims that one out of four hospital visits and one out of two ER visits do not occur when a patient is under his company’s care.

However, for years, providing this standard of care necessitated human teams, which restricted the speed and cost-effectiveness of its expansion. Then, approximately nine months ago, Pair Team implemented a voice AI agent named Flora as its main patient-facing interface. Flora is accessible 24/7, manages intake, coordinates referrals, and ensures follow-ups that keep patients engaged between clinical appointments.

The first call that altered his perspective was with a 67-year-old woman living in her vehicle while coping with PTSD and congestive heart failure. She conversed with Flora for more than an hour. “It was both awe-inspiring and disheartening,” Batlivala recounted. “Flora was likely the only ‘individual’ she had interacted with in weeks concerning her situation.” Now, hour-long dialogues with Flora are commonplace. “That’s the companionship component,” he stated. “And it turns out that it genuinely acts as an intervention.”

The designers of ACCESS are also former startup operators. Abe Sutton, Director of the CMS Innovation Center, and Jacob Shiff, Chief AI and Technology Officer of the CMS Innovation Center, crafted the program. Previously a venture capitalist at a healthcare fund named Rubicon Founders, Sutton has a startup background, as does Shiff, who is a former healthcare entrepreneur. Both joined CMS during the Trump administration, and their startup experiences are evident in the program’s construction: outcome-driven payments, direct-to-consumer enrollment, and a concerted push for competition.

However, there are substantial risks. Participants are sharing extremely sensitive patient information — personal dialogues about housing situations and health issues — within a federal system that has a record of data breaches, including compromised Social Security numbers. For the at-risk demographics ACCESS aims to assist, this is a significant concern.

Financial risks also exist. The success rate of CMS innovation initiatives is mixed. A 2023 analysis by the Congressional Budget Office revealed that the CMS Innovation Center increased federal expenditures by $5.4 billion in its inaugural decade instead of yielding the anticipated savings. CMS is reimbursing less per patient per month than many participants had expected, indicating that the model will only be sustainable for organizations that have largely automated their patient engagement processes.

Batlivala addresses the reimbursement issue by suggesting it is a benefit rather than a drawback. “To construct a model that truly encourages the utilization of AI, the reimbursement rates must be low,” he explained. “The economics are viable only if you’re managing a streamlined, AI-focused operation.”

Pair Team claims it currently holds partnerships that provide access to approximately 500,000 potential patients, with aspirations to reach a million within three years.

Investors in healthcare are observing this closely. Digital health funding reached its peak Q1 total since the onset of the pandemic this year, with AI firms seizing the majority share. Yet, ACCESS has barely made waves beyond the health tech trade media.