SUCCESS

Figma’s stock soars after earnings beat expectations again, and the full-year outlook was raised.

Cerebras Systems, the Silicon Valley chipmaker that built the world’s largest commercial AI processor, erupted onto the Nasdaq on Wednesday, opening at $350 per share — nearly double its $185 IPO price — and rocketing past a $100 billion market capitalization in its first hours of trading. The debut instantly crowned Cerebras as one of the most valuable semiconductor companies on Earth and validated a decade-long bet that the AI industry would eventually demand a fundamentally different kind of chip.The company sold 30 million shares at $185 apiece, raising $5.55 billion in what Bloomberg reported as the largest U.S. tech IPO since Uber went public in 2019. The final pricing shattered expectations: Cerebras initially marketed shares at $115 to $125, then raised the range to $150 to $160 as investor demand surged, before ultimately pricing above even that elevated band.”This is just a new beginning,” Julie Choi, Senior Vice President and Chief Marketing Officer at Cerebras, told VentureBeat in an exclusive interview on the morning of the IPO. The company, she said, plans to pour its fresh capital into expanding the cloud infrastructure that has become the centerpiece of its growth strategy. “With this new capital, we’re going to fill more data halls with Cerebras systems to power the world’s fastest inference.”The IPO caps one of the most dramatic corporate turnarounds in recent tech history. Cerebras first filed to go public in September 2024 but withdrew the effort more than a year later amid intense scrutiny over its near-total revenue dependence on a single customer in the United Arab Emirates. The company refiled in April 2026 with a radically different business profile: new partnerships with OpenAI and Amazon Web Services, a fast-growing cloud inference service, and a revenue base that had climbed 76% to $510 million in 2025.How a dinner-plate-sized chip became the foundation of a $100 billion companyTo understand the frenzy, you have to understand the silicon.Cerebras builds something called the Wafer-Scale Engine, or WSE — a single processor that occupies an entire silicon wafer, the dinner-plate-sized disc from which ordinary chips are cut. The third-generation WSE-3 contains 4 trillion transistors, 900,000 compute cores, and 44 gigabytes of on-chip memory. It is 58 times larger than Nvidia’s B200 “Blackwell” chip and delivers 2,625 times more memory bandwidth than the B200 package, according to the company’s S-1 filing with the Securities and Exchange Commission.That bandwidth advantage matters enormously for AI inference — the process of running a trained model to generate answers. When a large language model produces text, it predicts one token at a time, and each token requires the model’s entire set of weights to move from memory to compute. This work is inherently sequential and cannot be parallelized, making memory bandwidth the binding constraint on speed. Cerebras claims its architecture delivers inference responses up to 15 times faster than leading GPU-based solutions on open-source models, a figure corroborated by third-party benchmarker Artificial Analysis.”One of the architectural principles when we built the wafer was: let’s keep compute closer together, so that compute elements can talk to each other at lower latency,” Andy Hock, VP of Product at Cerebras, told VentureBeat. “Low latency is important to AI compute. It’s a cornerstone of fast inference.”The founding insight was contrarian and, for most of the company’s life, commercially premature. Cerebras’s founders recognized in 2015 that AI workloads were communication-bound problems — speed depended on how fast data could move between memory and compute — and that the best way to accelerate that movement was to keep everything on a single massive chip. Wafer-scale integration had been attempted and abandoned repeatedly over the semiconductor industry’s 75-year history. Every previous effort had failed. Cerebras solved the problem through two key innovations detailed in its S-1: a proprietary multi-die interconnect that stitches otherwise independent die together at the wafer level during fabrication, and a fault-tolerant architecture that routes around manufacturing defects using redundant building blocks, similar to how hyperscale data centers handle server failures.Why Cerebras is betting its future on cloud inference instead of hardware salesFor most of its life, Cerebras sold hardware — massive, water-cooled AI supercomputers installed on-premises at customer facilities. That model generated $358 million in hardware revenue in 2025. But the IPO prospectus reveals a strategic pivot that will define the company’s next chapter: the transition to cloud-based inference services.Cerebras launched its inference cloud in August 2024. In less than two years, cloud and other services revenue reached $151.6 million in 2025, up 94% from $78.3 million in 2024. The company now expects this segment to comprise a significantly larger percentage of total revenue going forward, driven primarily by its enormous deal with OpenAI.”Cloud and model APIs are the preferred and natural consumption method for inference services and application developers,” Hock told VentureBeat. “So that was the natural packaging and go-to-market strategy for the inference capability.”Choi framed the cloud as a democratization play. “Whether that be an entrepreneurial developer, a startup, or a massive organization like OpenAI — the cloud has really made it easy for people to deploy and feel the fast inference, the value of it,” she said.The economics of the transition are capital-intensive. Cerebras must lease data center space, manufacture and deploy its systems, and build software to manage capacity — all before recognizing recurring revenue. The S-1 warns bluntly that gross margins will decline in the near term as the company absorbs startup costs for cloud infrastructure. The company’s gross margin already dipped to 39% in 2025 from 42.3% in 2024, driven by higher data center costs. But the demand picture appears formidable. “Every cloud system that we’ve deployed so far, each one gets gobbled up in capacity,” Hock said. “We’ve been thrilled to see the demand for fast inference from Cerebras. We want to go faster to service that market.”Inside the $20 billion OpenAI deal that transformed Cerebras overnightThe single most consequential business relationship for Cerebras is its December 2025 agreement with OpenAI, under which OpenAI committed to purchase 750 megawatts of Cerebras inference compute capacity over the next several years. The deal is valued at more than $20 billion and includes provisions for OpenAI to purchase an additional 1.25 gigawatts of capacity, potentially bringing total deployment to 2 gigawatts.The arrangement goes far beyond a standard vendor-customer relationship. OpenAI and Cerebras are co-designing future models for future Cerebras hardware — a tight feedback loop that gives Cerebras visibility into frontier model architectures before they ship and gives OpenAI inference systems optimized for its specific workloads. The partnership moved from contract to production with remarkable speed. “After we announced the partnership, we had the first model running in like 35 days,” Choi told VentureBeat. “That was Codex Spark, and the engineers over at OpenAI just were like, mind blown.”Codex Spark, OpenAI’s model designed for real-time coding, allows developers to turn natural-language instructions into working software in seconds using Cerebras infrastructure. Choi described a deep cultural alignment between the two companies. “Our teams truly vibe as engineers. We’re on the same wavelength,” she said. “There’s just no amount of speed that is enough for those guys.”To fund the infrastructure buildout, OpenAI advanced Cerebras a $1 billion working capital loan in January 2026, secured by a promissory note maturing no later than December 31, 2032, bearing 6% annual interest. The loan can be repaid in cash or through delivery of compute capacity. However, the S-1 discloses significant risk: if the MRA is terminated for any reason other than OpenAI’s material uncured breach, OpenAI can seize control of the loan funds and demand immediate repayment. OpenAI also holds a warrant to purchase up to 33.4 million shares of Cerebras Class N common stock at an exercise price of $0.00001 per share — essentially free shares that vest as Cerebras delivers committed capacity. At the IPO opening price, the fully vested warrant would be worth approximately $11.7 billion.How the Amazon Web Services partnership could bring Cerebras chips to millions of developersIn March 2026, Cerebras signed a binding term sheet with Amazon Web Services to become the first hyperscaler to deploy Cerebras systems inside its own data centers. The partnership introduces a novel architectural concept called disaggregated inference, which splits the two stages of AI inference — prefill (processing the user’s prompt) and decode (generating the response) — across different hardware optimized for each task. Under this arrangement, AWS Trainium chips handle prefill, while Cerebras CS-3 systems handle decode, connected via Amazon’s Elastic Fabric Adapter networking.According to the AWS press announcement in March, the approach aims to deliver an order of magnitude faster inference than what is currently available. Hock provided technical detail on why this works. “The interconnect requirements between prefill and decode systems actually aren’t that high, so we can use a traditional interconnect between, say, Trainium and the wafer-scale engine and still deliver that fast time to first token and that ultra-low latency token generation,” he explained. “What the Trainium wafer-scale engine combination really gives us in that disaggregated or heterogeneous inference setup is all the speed and vastly more efficiency, so we can effectively serve more tokens per unit rack space or kilowatt.”The partnership provides Cerebras something it has long lacked: massive distribution. AWS serves millions of enterprise customers worldwide, and Cerebras systems deployed through Amazon Bedrock will become accessible to any developer within their existing AWS environment. “AWS has incredible reach,” Hock said. “The partnership is really about bringing that fast inference capability — that sort of best-in-industry, fast inference capability delivered by wafer-scale engine and Trainium — to that broader market.” The term sheet also grants AWS a warrant to purchase up to approximately 2.7 million shares of Cerebras Class N common stock at a $100 exercise price, with vesting tied to product purchases beyond the initial lease.The UAE customer concentration problem that nearly derailed the IPO — and whether it’s really solvedFor all the excitement, Cerebras carries a risk that has haunted it since its first IPO attempt: customer concentration. In 2024, G42 — an Abu Dhabi–based technology conglomerate — accounted for 85% of Cerebras’s total revenue. The company’s September 2024 S-1 filing drew heavy scrutiny over this dependence, compounded by questions about export controls for advanced AI chips shipped to the UAE. Cerebras withdrew that filing.The 2025 numbers show progress but not resolution. G42’s share of revenue declined to 24%, but Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), an Abu Dhabi institution that is a related party to G42, accounted for 62% of total revenue. Together, the two UAE-linked entities still represented 86% of Cerebras’s 2025 sales. The S-1 is candid about this risk, noting that MBZUAI accounted for 77.9% of accounts receivable as of December 31, 2025, and that U.S. export licenses for Cerebras systems shipped to G42 and MBZUAI require “rigorous security and compliance obligations to prevent diversion and abuse of our technology.”Choi addressed the issue directly, pointing to the OpenAI and AWS deals as evidence of a broadening customer base. “Now with OpenAI and Amazon, those are the same type of deep partnerships,” she told VentureBeat. “We’re a deep technology company. Our technology has taken a decade to build. We go deep in how we build, and now we’re going deep with two of the biggest players — the biggest AI lab, OpenAI, and the biggest cloud, AWS.”Hock framed the customer evolution as a progression in market perception. “G42 caused the market to be intrigued and inspired,” he said. “Nobody in the business is smarter, more credible, or has greater reach than OpenAI and AWS. And so I think OpenAI and AWS caused the market to shift from intrigued and inspired to — I’ll call it curious and convinced.” Still, the S-1 warns that the OpenAI MRA itself “represents a substantial portion of our projected revenues over the next several years.” Cerebras’s business will remain dependent on a small number of very large customers for the foreseeable future — a structural feature of the AI infrastructure market where buildouts are measured in hundreds of megawatts and billions of dollars.Can Cerebras build data centers fast enough to keep up with runaway demand?With OpenAI consuming 750 megawatts of committed capacity and AWS preparing to deploy Cerebras systems in its data centers, the question is whether Cerebras can scale its physical infrastructure quickly enough to serve everyone else. Hock acknowledged the tension. “It’s a good problem to have when demand starts to outstrip supply. It doesn’t mean it’s an easy problem to address,” he told VentureBeat. “We’ve got to build these extraordinary systems. We’ve got to procure data center space. We’ve got to deploy systems there. Got to stand up software to meet our customers where they are.”The company is being deliberate about capacity allocation. “We’re trying to be really deliberate about how we allocate capacity as it’s built,” Hock said. “We’re working in deep partnership to service the highest-priority customers and highest-priority markets.” Choi argued that the constraint actually sharpens focus. “Sometimes when you have less of something, it forces you to be very deliberate,” she said. Beyond OpenAI, she named Cognition — the AI coding startup — and Block, led by Jack Dorsey, as significant customers. “Jack participated in our roadshow as well,” Choi noted. “We’re speeding up that entire money-bot AI experience within Cash App.”The S-1 discloses that Cerebras currently operates data centers in California, Oklahoma, and Canada, with plans to expand internationally. The company executed non-cancelable data center leases in late 2025 with aggregate undiscounted future minimum payments of approximately $344 million, and in March 2026 signed a Canadian data center lease with expected minimum payments of approximately $2.2 billion over a 10-year term.The IPO proceeds — combined with $1 billion from a January 2026 Series H preferred stock round and the $1 billion OpenAI loan — give Cerebras a war chest exceeding $8 billion to fund the buildout. Whether that is enough to satisfy a market where major customers are ordering capacity measured in gigawatts remains an open question.The Nvidia shadow: what Cerebras is really up against in the AI chip warsCerebras enters public markets into the teeth of the most competitive semiconductor environment in decades. Nvidia remains the dominant force in AI compute, controlling the vast majority of the training and inference infrastructure market. Its GPU architecture benefits from a deeply entrenched software ecosystem built around CUDA, the programming framework that has become the de facto standard for AI development. Cerebras’s S-1 explicitly acknowledges this, noting that “many of our competitors benefit from competitive advantages over us, such as prominent and cutting-edge technology and software stacks designed to keep out new market entrants.”But Cerebras argues the inference market is structurally different from training — and that its architecture has a fundamental advantage in the workload that matters most going forward. As AI models have shifted toward reasoning, where models perform multi-step computation during inference to think through problems, the number of tokens generated per request has exploded. Each token requires moving full model weights from memory to compute, making memory bandwidth the bottleneck. The S-1 cites Bloomberg Intelligence data projecting that Cerebras’s addressable portion of the AI inference market will grow from approximately $66 billion in 2025 to $292 billion by 2029, a 45% compound annual growth rate — significantly outpacing the 20% CAGR projected for AI training infrastructure.Nvidia has clearly taken notice of the fast-inference threat. In December 2025, Nvidia acquired Groq — a startup whose tensor streaming processor architecture more closely resembles Cerebras’s approach — for $20 billion. Months later, Nvidia announced plans for Groq-based products, signaling that even the industry’s dominant player recognizes the limitations of GPU architecture for latency-sensitive inference. Cerebras also competes with custom silicon developed by hyperscalers — including Google’s TPUs and Amazon’s Trainium chips — and a growing roster of AI cloud providers. Asked about Nvidia and Groq, Choi declined to engage. “We’re feeling pretty good right now,” she told VentureBeat with a smile.Revenue is surging, but the financial fine print reveals a more complicated pictureThe financial picture that emerges from the S-1 is one of rapid scaling with significant underlying complexity. Revenue surged from $78.7 million in 2023 to $290.3 million in 2024 to $510 million in 2025 — a more than tenfold increase over three years. The company reported GAAP net income of $237.8 million in 2025, but this figure is heavily influenced by a $363.3 million one-time gain from the extinguishment of a forward contract liability related to a preferred stock arrangement. Stripping out that gain and stock-based compensation, Cerebras’s non-GAAP net loss was $75.7 million in 2025, widening from a $21.8 million non-GAAP loss in 2024.Operating losses deepened as well. Cerebras lost $145.9 million from operations in 2025, up from $101.4 million the prior year, as the company invested heavily in research and development ($243.3 million, up 54%) and sales and marketing ($70.6 million, up 237%).The company burned $10 million in operating cash flow in 2025, a sharp reversal from the $452 million of cash generated in 2024 — a year boosted by $640 million in customer deposit inflows, primarily from G42 and MBZUAI. The S-1 warns that gross margins will face near-term pressure from startup costs for cloud infrastructure, customer warrant amortization, and pass-through data center expenses.The path to this moment was anything but smooth. Cerebras shipped its first systems in 2020 and 2021 — before the market was ready. As the founders wrote in the prospectus: the company “had built something extraordinary, but the market wasn’t ready.” The ChatGPT moment in late 2022 changed everything.By early 2025, Cerebras’s speed advantage — long a solution in search of a problem — became urgently relevant as AI coding agents, deep research tools, and real-time voice applications demanded the kind of low-latency inference that GPU clusters struggled to deliver. The S-1 describes a market where AI coding agents “barely existed in 2023” but collectively generated “billions in ARR in 2025,” and where 42% of professional code is now AI-generated or assisted.What Cerebras must prove to justify a $100 billion valuation — and what happens if it can’tLooking forward, Hock signaled that the current generation of hardware is just the beginning. “Wafer-scale engine three and CS-3 is not the end of the story. It’s just the beginning,” he told VentureBeat. “We have a multi-year technology roadmap that continues building on wafer-scale technology, accelerating performance, increasing efficiency, supporting larger scale.” The S-1 confirms that Cerebras intends to expand on-chip memory and bandwidth, improve interconnect density, and leverage future process node advances — and discloses that the company has already obtained export licenses for future CS-4 systems destined for the UAE.The company also faces a web of operational risks that would test any organization, let alone one that has never operated as a public company. It depends entirely on TSMC for wafer fabrication, with no long-term supply commitment. Its data center leases stretch for years, while its inference customer contracts are often shorter-term or consumption-based, creating a mismatch between fixed costs and variable revenue. It has identified material weaknesses in its internal controls over financial reporting. And its most important customer relationship — with OpenAI — includes exclusivity provisions that restrict Cerebras from working with certain named OpenAI competitors, potentially limiting future diversification.Whether Cerebras can sustain a $100 billion-plus valuation will depend on its ability to execute against all of these challenges simultaneously: building data centers at unprecedented speed, manufacturing wafer-scale chips at scale through a single foundry, navigating export controls on its most lucrative international relationships, and competing against an Nvidia that has shown it will not cede the inference market without a fight.But Cerebras has always been built on a willingness to attempt what others said was impossible. Wafer-scale integration had stumped the semiconductor industry for its entire existence. Now a chip the size of a dinner plate — once dismissed as an engineering curiosity — powers the fastest AI inference on the planet, serves the world’s leading AI lab, and just debuted on the Nasdaq to a valuation that dwarfs companies many times its age. The world, it turns out, was ready. As Hock put it to VentureBeat, recalling the journey from the lab to the trading floor: “The IPO isn’t the end of the story. It’s the beginning.”

Looking for help with today’s New York Times Pips? We’ll walk you through today’s puzzle and help you match dominoes to tiles.

Looking for help with today’s New York Times Wordle? Here are some expert hints, clues and commentary to help you solve today’s Wordle and sharpen your guessing game.

Wells Fargo made a significant call on interest rates six weeks ago. On May 13, its economists made a different one. And the reasoning behind the reversal says something important about how this bank reads the current inflation environment.The disagreement between Wells Fargo and two other major institutions on what comes next for the Fed is wide enough that investors cannot afford to ignore it.What Wells Fargo now expects from the Fed in 2026Wells Fargo reaffirmed on May 13 its forecast that the Federal Reserve will implement two quarter-point rate cuts in 2026, despite April’s Consumer Price Index and Producer Price Index both coming in hotter than expected.The bank’s economists attribute the current inflation pressures primarily to rising energy prices driven by geopolitical factors, specifically the Iran war and the Strait of Hormuz disruption. More Federal Reserve:Federal reserve reveals troubling reality about wealthy AmericansFidelity, Fed raise red flags on 401(k)s and IRAsThey believe those pressures are likely to be “significant but temporary,” and that a marginal softening in the labor market this summer will compel the Fed to take action to support economic growth, GuruFocus confirmed.That view marks a full reversal of Wells Fargo’s April 6 position, when the bank formally dropped its rate cut forecast for 2026 entirely. At the time, the bank said “the balance of risks has shifted to incentivize patience from the Fed.” The return to a two-cut forecast on May 13 reflects how quickly the macro picture has shifted as energy-driven inflation data came in.Why Wells Fargo sees current inflation as temporary, not structuralThe distinction Wells Fargo is making is important. Not all inflation is the same from a monetary policy perspective. Inflation driven by supply shocks, particularly energy price spikes from geopolitical disruptions, tends to be self-limiting in a way that demand-driven inflation is not. Consumers and businesses respond to higher prices by reducing consumption, which itself eases pressure over time.Wells Fargo’s view is that the April CPI and PPI prints, while uncomfortable, reflect that supply-shock dynamic rather than a broad-based reacceleration of underlying price pressures. If the energy shock eventually resolves, whether through diplomacy or market adjustment, the inflationary impulse from that source fades, leaving the Fed with room to respond to any softening in the labor market.That argument contrasts sharply with what Citigroup has been signaling. Citigroup revised its expected timeline for rate cuts due to robust employment figures and persistent inflation risks, according to GuruFocus. The disagreement between two major banks on what the same inflation data mean illustrates how contested the rate outlook has become.What JPMorgan and the Fed itself are signalingWells Fargo’s two-cut call also sits to the dovish side of JPMorgan’s current base case. JPMorgan economists project the Fed will hold rates steady for the rest of 2026 before potentially hiking a quarter point in the third quarter of 2027, according to J.P. Morgan Global Research. JPMorgan’s view holds that rate cuts are more likely only if the labor market weakens significantly or if the economic fallout from higher energy prices becomes more severe than currently projected.Fed Chair Jerome Powell has reinforced a cautious tone, indicating the central bank is in a position to “wait and see” how evolving risks, including energy shocks tied to the Middle East conflict, affect inflation and growth. That language leaves room for cuts if conditions deteriorate without committing to any specific timeline, according to the Federal Reserve.

Wells Fargo’s economists just changed their Fed position for the second time in six weeks, and the reason they gave is worth understanding.Rui/Getty Images

What the rate cut debate means for markets and investorsThe divide between Wells Fargo, Citigroup, and JPMorgan on the rate outlook reflects a genuine uncertainty about how the current macro environment will resolve. Each institution is looking at the same data and arriving at materially different conclusions about what the Fed will do. That kind of divergence is itself a signal about how elevated uncertainty is right now.For markets, the difference between two cuts, no cuts, and a potential hike by mid-2027 is enormous. Lower rates would support rate-sensitive assets including real estate, utilities, and highly leveraged companies, ease credit conditions, and reduce borrowing costs for consumers carrying floating-rate debt. A higher-for-longer scenario has the opposite effect on each of those categories.The next several months of inflation and labor market data will do more to resolve this debate than any individual bank’s forecast. If the energy shock fades and core inflation moderates as Wells Fargo expects, the two-cut view looks prescient. If inflation stays elevated, JPMorgan’s more cautious position will look like the better call. The Fed itself will be watching exactly that data before it decides.Key figures on the 2026 Fed rate outlook as of May 13:Wells Fargo forecast: Two quarter-point rate cuts in 2026, reaffirmed May 13; energy-driven inflation viewed as “significant but temporary,” according to GuruFocusWells Fargo’s prior position: No rate cuts expected in 2026, announced April 6; reversed on May 13Citigroup view: Revised expected cut timeline later due to robust employment and persistent inflation risks, according to GuruFocusJPMorgan base case: Fed holds rates steady through end of 2026; potential quarter-point hike in Q3 2027 if inflation remains elevated, according to J.P. Morgan Global ResearchFed Chair Powell’s position: “Wait and see” on evolving geopolitical and energy risks before adjusting policy, according to the Federal ReserveRecent inflation triggers: April CPI and PPI, which both came in hotter than expected, driven primarily by energy prices, GuruFocus confirmedWhy the timing of interest rate cuts matters as much as the numberWells Fargo’s forecast says two cuts are coming, but the bank points to summer labor market softening as the catalyst. That timing matters because it tells investors where to look for the trigger. If unemployment starts rising or job growth decelerates meaningfully in June and July payroll reports, that would give the Fed cover to begin easing in the fall, consistent with Wells Fargo’s timeline.Markets often move most sharply not when cuts actually happen but when the narrative shifts and traders collectively decide they believe cuts are coming. Wells Fargo is effectively saying the current pessimism on rate cuts is overdone, and that when the data turns, the move in rate-sensitive assets could be faster than the current mood implies.Whether that plays out depends on whether energy prices stabilize, whether the labor market shows the softening Wells Fargo expects, and whether core inflation decelerates enough to give the Fed confidence it has not lost control of the disinflation process. Those are three independent variables, each with its own uncertainty range. The fact that Wells Fargo is willing to call two cuts despite that uncertainty is itself a signal worth noting.Related: Fed official triggers new rate-cut warning

After years of anticipation, in April, Elon Musk confidentially filed an initial public offering (IPO) for SpaceX with the U.S. Securities and Exchange Commission.
The move positions the aerospace and artificial intelligence company, which Musk founded in 2002, to go public as soon as June. It also sets the stage for the world’s richest man to become the first CEO at the helm of two publicly traded companies with valuations in excess of $1 trillion.
Access to IPOs is traditionally reserved for institutional investors (like asset management firms, investment banks and hedge funds) and accredited investors (like people with a net worth over $1 million, excluding their primary residence, or annual income over $200,000). But there is a way for everyday investors to gain exposure to SpaceX before its public debut — at a comparatively steep price.
Here’s what to know.

SpaceX’s IPO could be the largest in history
Combining rocket launch services, a subsidiary Starlink satellite business segment and — following a recent merger with xAI — large language models, SpaceX is seeking to raise between $50 billion and $75 billion through its public offering. That would make the company’s IPO the largest in history, supplanting the $25.6 billion raised by Saudi Aramco, the owner and operator of the world’s largest oil and gas network, when it went public in 2019.
Additionally, by targeting an IPO valuation of $2 trillion, SpaceX would become the sixth-largest publicly traded company, trailing only Magnificent Seven members Nvidia, Apple, Alphabet, Microsoft and Amazon.
For context, Musk-led Tesla’s market capitalization is currently $1.4 trillion.
Part of the appeal to investors is the company’s recurring revenue model, which hinges on subscriptions for Starlink’s high-speed, low-latency space-based internet. More than 10,000 Starlink satellites are currently in orbit servicing over 10 million customers worldwide.
SpaceX is also a premier government contractor, having secured an estimated $22 billion worth of federal contracts with agencies including NASA and the U.S. Department of Defense.
The company’s recent merger with xAI incorporates a $250 billion AI company into the SpaceX fold. As a subsidiary, xAI introduces a stream of revenue that includes Colossus, the world’s most powerful AI supercomputer. As part of the merger, SpaceX is now working toward the development of space-based data centers, using solar power-equipped satellites to scale the company’s massive AI compute.
How to invest in SpaceX
While the date of SpaceX’s official public listing has yet to be announced, retail investors can gain access before its IPO via a niche investment vehicle. However, it comes with notable caveats that not everyone may be comfortable with.
The ARK Venture Fund, or ARKVX, is actively managed by Ark Invest, an investment management firm led by founder and CEO Cathie Wood (who famously invests in companies focusing on disruptive technologies). The fund aims to provide retail investors with access to venture capital-style investments, including SpaceX.
However, unlike straightforward exchange-traded funds that have surged in popularity, the ARK Venture Fund is a closed-end interval fund — a type of SEC-registered investment company that does not trade on exchanges, often invests in alternative assets like private equity and can present illiquidity challenges. Shareholders of interval funds lack the ability to freely sell until periodic repurchase windows open.
In the case of the ARK Venture Fund, those opportunities come quarterly. But a disclosure on Ark’s official website warns prospective investors and current shareholders of that illiquidity risk, stating that “You should not expect to be able to sell your Shares other than through the Fund’s repurchase policy, regardless of how the Fund performs… Although the Fund will offer to repurchase Shares on a quarterly basis, Shares are not redeemable and there is no guarantee that shareholders will be able to sell all of their tendered Shares during a quarterly repurchase offer.”
The disclosure further states that an “investment in the Fund’s Shares is not suitable for investors that require liquidity, other than liquidity provided through the Fund’s repurchase policy.”
Palash S. Islam, CEO of Synergy Financial Group, says this isn’t necessarily a red flag. But he cautions investors looking to jump in now.
“Now is way too late. They missed the boat,” he writes in an email to Money.
Islam also points to how the “retail wrapper” — using a fund to provide everyday investors with access to pre-IPO companies — removes transparency and flexibility. He adds that investing in the ARK Venture Fund simply to gain exposure to SpaceX prior to its IPO is difficult to justify, noting that “Ark will likely capitalize on the momentum and excitement to drive higher flows into the fund.”
More money moving into a fund does not directly translate to higher share prices, but it does translate to additional revenue for fund managers. (Ark Invest did not immediately respond to Money’s request for comment on this and other details.)
Another point of consideration is the fund’s annual fees, which currently amount to 3.49% and are “meaningfully higher than traditional active management,” says Islam.
For context, the average expense ratio for an actively managed ETF falls between 0.5% and 0.75%. Even after a 0.59% expense reimbursement and fee waiver offered by Ark Invest, its Venture Fund’s net expense ratio is still 2.90% — 364% higher than the average for actively managed ETFs.
For investors who can look past those conditions, shares are available via platforms like SoFi and Titan with a $500 minimum investment, according to the fund’s prospectus. Beyond SpaceX — ARK Venture Fund’s top holding, which currently accounts for 13.76% of the total portfolio — it also provides exposure to ChatGPT-maker OpenAI, Anthropic and other tech startups that could eventually see IPOs of their own.
“We have traditionally stayed away from deals like this,” Islam says. “But for some clients, if they are looking for [pre-IPO] access, this may be the only way. Hopefully they got in years ago and are not chasing returns today.”

More from Money:
Is This 2008 All Over Again? Fears of a Financial Crash Grow Among Investors

Private Equity, Crypto and Other Risky Assets Are Coming to Your 401(k). Here’s What to Know

You Can’t Buy Stock in the Startup Behind ChatGPT. But You’re Probably Invested in It Anyway

The wait for the next James Bond is officially over. Or at least the waiting-to-find-out-if-they’re-looking part.

Dignitaries, including military and government officials responsible for managing the site, have been allowed to swim there.

LinkedIn built its business around helping people find jobs, grow their careers, and connect with employers.Now, the Microsoft-owned professional networking platform is delivering difficult news to some of its own workers. This comes within weeks of Microsoft’s voluntary buyouts for its senior-level workers, which apply to 7% of eligible US employees, CNBC reported.The company is cutting jobs across several teams as it looks to reduce costs, move faster, and rethink how it operates in an increasingly AI-driven tech industry.The cuts come shortly after Microsoft reported strong quarterly results and LinkedIn posted double-digit revenue growth, creating a painful contrast for employees affected by the move.LinkedIn cuts jobs across key teamsLinkedIn plans to cut about 5% of its workforce, Reuters reported.In a memo obtained by Business Insider, LinkedIn CEO Daniel Shapero told employees the company would lay off workers and scale back some investments.The cuts affect employees across LinkedIn’s Global Business Organization, Marketing, Engineering, and Product teams.More Layoffs:E-commerce giant shuts down office as layoffs riseVerizon CEO cuts to the chase on new layoffs and AI futureCloudflare stock plummets 23% amid AI-driven layoffsThe memo did not disclose the total number of affected employees. However, LinkedIn currently has about 17,500 employees globally, so a 5% headcount cut would affect about 875 workers, TechRepublic indicated.The cuts are not limited to a single office or department.Employees in Europe, the Middle East, and Africa, as well as the Asia-Pacific region, were notified through calendar invites after the memo went out, according to Business Insider. APAC workers were expected to receive additional notifications in the following days.For a company whose platform is closely tied to hiring, recruiting, and career growth, the layoffs carry a sharper message.LinkedIn is not just another tech company cutting staff. It is one of the most visible names in the job market, and its own workforce reductions arrive at a time when many white-collar workers are already worried about job security, automation, and slower hiring.

Microsoft’s stock is down 15% year to date.Smith Collection/Gado/Getty Images

LinkedIn scales back spendingThe layoffs are part of a broader effort to reduce costs and focus on areas the company believes will bring stronger returns.In the memo, Shapero said LinkedIn would scale back spending on marketing campaigns, vendor spending, customer events, and underused office space, which means closures are expected in the near future.The company is also closing its office in Graz, Austria, as part of the changes, according to the report.Shapero told employees that LinkedIn needs to “reinvent how we work, with agile teams focused on our highest priorities, and by shifting investments toward areas such as infrastructure” to fulfill the company’s mission in the long term.The company is trying to operate more efficiently while investing in areas it believes will define the next stage of professional networking, recruiting, and workplace technology.Strong revenue growth adds to LinkedIn’s layoff painThe timing of the layoffs is notable because LinkedIn is still growing.Microsoft reported in its FY26 third-quarter earnings call that LinkedIn, which has 1.3 billion members, achieved a $450 million annualized revenue run rate for Microsoft’s agentics products used in LinkedIn Talent Solutions.LinkedIn’s revenue also increased 12% year over year, reported in the company’s fiscal third quarter ended March 31, 2026. The company said LinkedIn saw growth across all lines of business and expects 10% revenue growth going forward.Microsoft’s broader business also remained strong. In the earnings call, the tech giant reported quarterly revenue of $82.9 billion, up 18% from the same period a year earlier.The company also noted that its total headcount declined as it focuses on “building high-performing teams that operate with pace and agility.”LinkedIn’s cuts also come as many large technology companies are changing how they operate in the realm of artificial intelligence.The memo did not frame the layoffs as AI directly replacing workers. But the changes come as Microsoft continues to spend heavily on AI infrastructure and products, while companies across the technology industry push teams to become more efficient and move faster.That matters because LinkedIn sits directly at the center of the labor market.Its platform is used by job seekers, recruiters, employers, and professionals trying to understand where the economy is headed. When LinkedIn itself cuts jobs, the move sends a signal beyond the company’s own workforce.It reflects a broader shift in the white-collar labor market, where companies can still be growing while also asking workers to do more with fewer resources.And LinkedIn is not alone in this race to cut costs and streamline operations. Meta is set to cut 8,000 jobs on May 20, paving the way for increased AI spending. Cloudflare recently reported plans to reduce its headcount by 20% to become an AI-first company. Ticketmaster also recently cut 350 workers amid an AI shift.Related: Ticketing giant sees writing on the wall for 350 workers amid AI shift

Anthony Grieco, Cisco’s SVP and chief security and trust officer, did not hesitate when VentureBeat asked whether rogue agent incidents are reaching Cisco’s customer base.”A hundred percent. We see them regularly,” Grieco told VentureBeat in an exclusive interview at RSAC 2026. “I’ve heard some that I can’t repeat, but they do get to the places of, you know, agents are doing things that they think are the right things to do.”The incidents Grieco described follow a consistent pattern: authentication passes, identity checks clear. The agent is exactly who it claims to be. Then it accesses data it was never scoped to touch or takes an action nobody authorized at that level of granularity. The failure is not identity; it’s authorization.”The business is saying things like, we’re gonna have 500 agents per employee,” Grieco told VentureBeat. “The security leaders are really focused on how to make sure that we do that securely.”Cisco’s State of AI Security 2026 report found that 83% of organizations planned to deploy agentic capabilities, but only 29% felt prepared to secure them. Five vendors shipped agent identity frameworks at RSAC 2026. None closed every gap. That includes Cisco.VentureBeat mapped four authorization gaps across Grieco’s exclusive interview and five independent sources. The prescriptive matrix at the end of this story is what to do about them.The authorization gap nobody has closed yetGrieco came up through Cisco’s engineering and threat research organizations before taking a role that straddles both sides of the company’s security operation: building the products Cisco sells and running the program that defends Cisco itself. The authorization gap he described is specific and operational.”This agent here is a finance agent, but even if it’s a finance agent, it shouldn’t access all finance data,” Grieco told VentureBeat. “It should access the expense reports, and not just expense reports, but the individual expense reports at a particular time. Getting that sort of granular control is really one of the biggest things that are gonna help us say yes to a lot of the agentic developments.”Independent practitioners confirmed the pattern across RSAC 2026. Kayne McGladrey, an IEEE senior member, told VentureBeat that organizations default to cloning human user profiles for agents, and permission sprawl starts on day one. Carter Rees, VP of AI at Reputation, identified the structural reason. The flat authorization plane of an LLM fails to respect user permissions, Rees told VentureBeat. An agent on that flat plane does not need to escalate privileges. It already has them.”The biggest challenge that we see is knowing what’s going on,” Grieco said. “Being able to have identity and access control maps to those, that’s really crucial.”Elia Zaitsev, CTO of CrowdStrike, described the visibility dimension in an exclusive VentureBeat interview at RSAC 2026. In most default logging configurations, an agent’s activity is indistinguishable from a human’s. Distinguishing the two requires walking the process tree. Most enterprise logging cannot make that distinction.Five vendors shipped agent identity frameworks at RSAC, including Cisco’s Duo IAM and MCP gateway controls. None closed every gap VentureBeat identified. The four gaps below are what remains open.Standards bodies are converging on the same diagnosisThe authorization and identity gaps Grieco described are not just vendor observations. Three independent standards bodies reached parallel conclusions in early 2026. NIST’s NCCoE published a concept paper in February 2026, “Accelerating the Adoption of Software and AI Agent Identity and Authorization,” explicitly calling for demonstration projects on how existing identity standards apply to autonomous agents. The OWASP Top 10 for Agentic Applications, released in December 2025, identified tool misuse from over-privileged access and unsafe delegation as top-tier risks. And the Cloud Security Alliance launched the CSAI Foundation at RSAC 2026 with a mission of “Securing the Agentic Control Plane,” including a dedicated Agentic AI IAM framework built around decentralized identifiers and zero trust principles. When NIST, OWASP, and CSA all independently flag the same gap class in the same market cycle, the signal is structural, not vendor-specific.MCP security requires discovery before controlVentureBeat asked Grieco about the paradox of MCP, the Model Context Protocol that every vendor at RSAC 2026 embraced while acknowledging its security gaps. Grieco did not argue that the protocol is safe. He argued that blocking it is no longer realistic.”There is no saying no to that in today’s day and age as a security leader,” Grieco told VentureBeat. “And so it’s how do we manage that.”Inside Cisco’s own environment, Grieco’s team added MCP discovery, proxying, and inspection capabilities to AI Defense and Cisco Secure Access. The approach treats MCP servers the way enterprises treat shadow IT: find them before you govern them.Etay Maor, VP of threat intelligence at Cato Networks, validated that approach from the adversarial side. At RSAC 2026, Maor demonstrated a Living Off the AI attack chaining Atlassian’s MCP and Jira Service Management. Attackers do not separate trusted tools, services, and models. They chain all three. “We need an HR view of agents,” Maor told VentureBeat. “Onboarding, monitoring, offboarding.”Nearly half of the critical infrastructure is obsolete and unpatchedAgent authorization failures are harder to detect and contain when the infrastructure underneath has not received a security patch in years — and that gap compounds every other vulnerability in this story. Cisco commissioned UK-based advisory firm WPI Strategy to examine end-of-life technology risk across the US, UK, France, Germany, and Japan. The report found that nearly half of the critical network infrastructure across those geographies is aging or already obsolete. Vendors no longer patch it.”Almost 50% of the critical infrastructure across these geographies was aging, it was end of life or almost end of life,” Grieco told VentureBeat. “It means vendors are not providing security patches for them anymore.”Cisco’s Resilient Infrastructure initiative disables unused features by default and phases out legacy protocols on a three-release deprecation schedule. Grieco pushed back on the assumption that secure by default is a static achievement. “One of the things that most people don’t think about is that those are not static points in time,” Grieco told VentureBeat. “It’s not like you do it once and you’re done.”Agentic enterprise security gap matrixThe four gaps below are what security directors can act on Monday morning. Each row maps from what breaks to why it breaks to what to do about it, cross-validated by five independent sources.Sources: VentureBeat analysis of Grieco’s exclusive interview at RSAC 2026, cross-validated against independent reporting from McGladrey (IEEE), Rees (Reputation), Maor (Cato Networks), and Zaitsev (CrowdStrike). May 2026.Security Gap| What fails and what it costsWhy your current stack doesn’t catch itWhere vendor controls stand nowFirst action for your teamInfrastructure agingNearly half of critical network assets are end of life or approaching it (WPI Strategy); agents operating on unpatched systems inherit vulnerabilities no vendor will fixAnnual patching cadence cannot keep pace with threat velocity; EoL systems receive zero security updates and zero vendor supportResilient Infrastructure disables insecure defaults, warns on risky configurations, deprecates legacy protocols on a three-release scheduleInfra team: audit every network asset against vendor EoL dates this quarter. Reclassify EoL replacement from IT upgrade to security investment in next budget cycleMCP discoveryMCP servers proliferate across environments without security visibility; developers spin up agent tool connections that bypass existing governanceShadow MCP deployments bypass existing discovery tools; no standard inventory mechanism exists; Maor demonstrated attackers chaining MCP + Jira in a Living Off the AI attackAI Defense adds MCP discovery, proxying, and inspection; treats MCP servers like shadow ITSecurity ops: run an MCP server inventory across all environments before deploying any agent governance controls. If you cannot enumerate your MCP surface, you cannot secure itAgent over-permissioningAgents inherit broad human-level access on a flat authorization plane; the agent does not need to escalate privileges because it already has them (Rees)IAM teams clone human profiles for agents by default (McGladrey); no scoped, time-bound permissions exist for non-human identitiesDuo IAM registers agents as distinct identity objects with granular, time-bound permissions per tool callIAM team: stop cloning human accounts for agents immediately. Scope every agent permission to a specific data set, specific action, and specific time window. Grieco’s test: can this finance agent access only the individual expense report it needs at this moment?Agent behavioral visibilityAgent actions are indistinguishable from human actions in security logs (Zaitsev); an over-permissioned agent that looks like a human in logs is invisible to the SOCDefault logging does not capture process tree lineage; no vendor has shipped a complete cross-platform behavioral baseline for agent activitySOC telemetry integration with Splunk for agent-specific detection and responseSOC lead: update logging to capture process tree lineage so agent-initiated actions are distinguishable from human-initiated actions. If your SIEM cannot answer “was this a human or an agent?” for every session, the gap is open”Frankly, we must move this quickly and evolve this quickly to keep up with where the adversaries are gonna go,” Grieco told VentureBeat.The gaps mapped above are not theoretical. Grieco confirmed the incidents are already happening. The controls exist in pieces across multiple vendors. No single vendor has assembled the complete stack.