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Quantum Tech Startups Brave Market Turmoil to Go Public, Betting on Breakthroughs and Commercial Push

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Even as global markets reel from geopolitical tensions and a fresh wave of volatility, a handful of quantum technology companies are pushing ahead with public listings this year.

They are determined to tap fresh capital and accelerate the long-promised shift from laboratory curiosity to real-world applications, according to a CNBC report.

The latest example came Friday when Toronto-based Xanadu Quantum Technologies, a pioneer in photonic quantum computing and a partner of chipmaker Nvidia, began trading on both the Nasdaq and Toronto Stock Exchange following a merger with blank-check company Crane Harbor Acquisition Corp. Shares opened rocky but rallied to close up about 15 percent in New York trading at around $11.50, though they gave back some ground in after-hours action.

Xanadu’s debut followed closely on the heels of Singapore’s Horizon Quantum Computing, which started trading on Nasdaq under ticker HQ after merging with dMY Squared Technology Group and raising roughly $120 million. Earlier in February, neutral-atom specialist Infleqtion became the first company focused on that approach to list publicly via a SPAC deal with Churchill Capital, pulling in more than $550 million.

These moves echo the path blazed by IonQ back in 2021, when dMY Technology Group took the pure-play quantum computing firm public. SPACs, shell companies that raise money through an IPO and then merge with a private target, have emerged as the favored shortcut for quantum startups seeking faster access to public markets with lighter regulatory hurdles than a traditional IPO.

Markets remain jittery over the ongoing U.S.-Israeli conflict with Iran, oil price spikes, and broader economic uncertainty — precisely the sort of environment that usually punishes speculative, long-horizon bets like quantum computing. Xanadu’s shares slipped more than 10 percent after hours Friday, Horizon Quantum has shed around 18 percent since its debut, and Infleqtion’s stock has plunged over 30 percent since mid-February.

Yet company executives argue the window is actually ideal. “It’s an interesting time to be entering the public markets, of course, with everything happening in the world,” Horizon Quantum founder and CEO Dr. Joe Fitzsimons told CNBC. “But for quantum computing, it’s actually a very ideal time to be coming out. We’re really starting to hit something of an inflection point.”

That inflection stems from a string of tangible scientific advances over the past 18–24 months. Researchers have demonstrated meaningful progress in quantum error correction — the critical technique for protecting fragile quantum information from noise and decoherence. Milestones include higher qubit counts, longer coherence times, and early signs that logical qubits (error-protected units of quantum information) can outperform raw physical ones in real computations.

Industry observers point to demonstrations of up to dozens of logical qubits with error rates low enough to show “beyond break-even” performance. Bain & Company partner Velu Sinha noted that practical quantum advantage, where quantum machines solve useful problems faster or better than classical supercomputers, could emerge around 100 logical qubits by 2028–2029.

Commercially transformative applications in drug discovery, materials science, logistics optimization, or financial modeling will likely require 1,000 to 10,000 logical qubits, a threshold many expect in the mid-2030s.

“The narrative has shifted from science project to commercial trajectory,” Sinha said. “Quantum is one of a small number of technology categories investors view as structurally inevitable.”

At full maturity, the addressable market could reach $100–250 billion, giving patient capital reason to look past near-term volatility.

Early revenue pathways are already appearing. Horizon Quantum has concentrated on software tools that bridge classical and quantum systems, allowing developers to prepare code that can run on future hardware while generating income today. The company plans to expand its research team and roll out an early version of its platform to select users later this year.

Xanadu, which uses photons (particles of light) for its qubits, has developed cloud-based platforms where developers can experiment with quantum algorithms on existing hardware. The firm has set an ambitious goal of helping deliver one of the world’s first practical quantum data centers by 2030 and boasts strong engagement from partners in automotive, aerospace, and finance.

Infleqtion’s CEO Matthew Kinsella emphasized that neutral-atom technology is moving from pure scientific progress toward commercial relevance, particularly in quantum sensing and networking alongside computing.

“Going public gives us the capital to accelerate commercialization and invest behind the markets where we already see customer demand,” he said. “We think commercialization will happen in stages.”

Governments have long bankrolled the heavy lifting in quantum R&D, with the U.S., China, and the European Union each committing billions to secure strategic edges in computing power and cybersecurity. National labs and universities remain central. But the current wave of listings signals a clear pivot: private companies are now chasing market traction, even if widespread consumer-facing quantum devices remain decades away.

As Counterpoint Research director Marc Einstein put it, quantum computers could one day perform trillions of operations instantaneously, revolutionizing fields from cryptography to complex simulations. Large organizations are far more likely to own or access the hardware as a service in the coming years than individuals will ever have desktop quantum machines.

For now, these newly public quantum firms must prove they can convert scientific momentum into sustainable revenue while navigating the unforgiving realities of public markets. The road from lab breakthrough to broad commercialization is still long and capital-intensive. But with error correction improving, qubit scales rising, and real customer interest emerging in optimization and simulation, the sector’s leaders are betting that going public is the best way to fund the next leg of the journey.

Midas Raises $50M in a Series A Funding Led by RRE Ventures and Creandum 

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Midas, a German startup specializing in tokenized real-world assets (RWA) and on-chain investment products, has raised $50 million in a Series A funding round.

The round was led by RRE Ventures and Creandum, with participation from a strong mix of crypto-native and traditional finance investors, including: Framework Ventures, HV Capital, Ledger Cathay, Franklin Templeton, Coinbase Ventures, M1 Capital, Anchorage Digital, FJ Labs, North Island Ventures and GSR.

This brings Midas’ total funding to about $58.75 million, following an $8.75 million seed round in 2024. Midas turns institutional-grade yield strategies such as those involving treasuries or other assets into blockchain-based tokens often called mTokens. This provides on-chain transparency, composability, and yield while bridging traditional finance with decentralized infrastructure.

The company has already issued over $1.7 billion in assets, with more than $500 million in TVL and $37 million in yield paid out to 20,000+ holders. A major pain point in tokenized RWAs has been liquidity and redemption delays—many vault-style structures lock up capital, forcing slow liquidations or long wait times when investors want to exit.

To address this, Midas is launching the Midas Staked Liquidity (MSL) system—a standalone liquidity layer that enables instant redemptions by using pre-allocated funds, without needing to unwind underlying positions gradually. The initial capacity for MSL is up to $40 million, and the new capital will help scale this infrastructure.

This positions Midas to support broader institutional adoption of on-chain products by offering faster exits while maintaining transparency and yield. The involvement of Coinbase Ventures (crypto infrastructure) and Franklin Templeton (a major traditional asset manager active in digital assets and tokenization) highlights growing convergence between TradFi and crypto in the RWA/tokenization space.

It’s a notable raise for a relatively young European company in a market that’s still maturing. Midas’ CEO and co-founder, Dennis Dinkelmeyer, emphasized advancing on-chain investing with full transparency, instant redemptions, and native composability.

This announcement comes amid broader interest in tokenized assets, where liquidity remains a key bottleneck for scaling beyond early adopters. Midas Staked Liquidity (MSL) is a dedicated, standalone liquidity layer designed to solve one of the biggest pain points in tokenized real-world assets (RWAs) and on-chain yield products: slow or illiquid redemptions.

Traditional vault-style tokenized strategies often require unwinding underlying positions when investors want to exit, which can take days/weeks, introduce slippage, or force queues. MSL decouples liquidity provision from the core investment strategy, enabling instant, atomic redemptions while keeping the strategy capital fully deployed and yield-generating.

MSL acts as a centralized but on-chain and transparent liquidity facility shared across all Midas mTokens. Capital providers (LPs) deposit into MSL. This capital is not idle cash — it is actively allocated to low-risk, investment-grade strategies, primarily U.S. Treasury bills and prime lending markets. This generates a base yield for MSL participants.

Instant (Atomic) Redemptions: When a user chooses instant redemption for an mToken: The smart contract checks the current Net Asset Value (NAV). It burns the user’s mTokens. It immediately transfers stablecoins from the MSL pool to the user’s wallet — all in a single on-chain transaction. This happens at par (NAV), net of a fixed instant redemption fee.

No need to wait for underlying asset settlement or gradual liquidation. It’s atomic: settlement occurs instantly without counterparty or settlement risk. Liquidity comes from the external and shared MSL pool, not by holding unproductive cash inside each product. Higher net yields for token holders and better capital efficiency.

This layered approach prevents over-reliance on any single source and maintains robustness. Instant liquidity for investors without compromising yields. No settlement risk — fully on-chain, no third-party dependency for the instant leg. mTokens become better collateral in DeFi because of reliable redemption.

Shared pool avoids fragmenting liquidity across every product. As of recent data, MSL has around $12.89M in instant liquidity available, with per-token capacities. Initial targeted capacity mentioned in announcements was up to $40M, which the Series A funding helps expand.

Instant redemption: Immediate, subject to available MSL capacity, with a fixed fee. Toggleable in the interface; smart contract enforces capacity limits and compliance checks. Background verifications run continuously and can cause transactions to fail if conditions aren’t met.

MSL itself assumes no underlying investment risk from the mToken portfolios — it functions purely as a liquidity provider. Allocations stay in high-quality, liquid assets. Capacity limits, fees, and layered backstops manage drawdown risk. Full on-chain transparency and audited smart contracts.

This setup positions Midas products as more liquid yield tokens— combining real yield strategies with DeFi-like immediacy and composability, which is attractive for both retail and institutional users.

Starcloud Raises $170m to Hit $1.1bn Valuation as Investors Bet on Orbital AI Infrastructure

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Space-compute startup Starcloud has vaulted into unicorn territory, securing a $1.1 billion valuation in one of the fastest climbs from Y Combinator demo day to billion-dollar status.

The company’s Series A round, led by Benchmark and EQT Ventures, raised $170 million and brought total funding to $200 million, according to the company and investors. The fundraise comes just 17 months after its YC debut, underscoring the surging investor appetite for infrastructure plays tied to the artificial intelligence boom.

The enthusiasm has remarkably been sustained by a bold thesis to move power-hungry AI data centers off Earth and into orbit.

As hyperscalers race to build capacity for generative AI workloads, terrestrial data center expansion is increasingly constrained by power shortages, land scarcity, water use concerns, and regulatory bottlenecks. Starcloud is pitching orbit as a solution, where near-continuous solar power and the vacuum of space could, in theory, transform the economics of compute.

The company has already moved beyond concept.

In November 2025, Starcloud launched its first satellite carrying an Nvidia H100 GPU, becoming one of the first companies to deploy a state-of-the-art terrestrial AI chip in orbit. The satellite was used to perform inference and early AI model training tasks in space, a milestone that helped validate the technical premise behind orbital computing.

“An H100 is probably not the best chip for space, to be honest, but the reason we did it is we wanted to prove that we could run state of the art terrestrial chips in space,” he told TechCrunch.

Later this year, Starcloud plans to launch a second, more advanced spacecraft equipped with multiple GPUs, including an Nvidia Blackwell chip, an Amazon Web Services server blade, and even a bitcoin-mining computer.

That second mission is designed less as a demonstration and more as an engineering testbed, particularly for thermal management and power systems. Cooling remains one of the most difficult problems in orbital computing because high-performance chips generate significant heat and cannot rely on conventional air-based cooling systems.

Chief executive Philip Johnston says the next-generation spacecraft will carry what is expected to be the largest deployable radiator yet flown on a privately owned satellite, a critical step in making space-based computing viable at scale.

The longer-term ambition is far larger.

Starcloud is developing Starcloud 3, a three-ton, 200-kilowatt orbital data center spacecraft intended for deployment via SpaceX’s Starship system. The design is meant to fit the launch company’s “pez dispenser” deployment architecture originally built for Starlink satellites.

If launch costs fall to roughly $500 per kilogram, Johnston believes the platform could deliver electricity costs near five cents per kilowatt-hour, placing it in direct competition with land-based data centers.

That assumption, however, rests heavily on Starship becoming commercially operational by 2028 or 2029. This is where the investment case becomes more speculative.

Starship has yet to begin routine commercial flights, and many analysts believe the high-frequency launch cadence required to make orbital data centers economically viable may not emerge until the 2030s. Until then, the cost of lofting powerful compute hardware into orbit remains a significant barrier.

Johnston acknowledges as much, saying the company will continue deploying smaller systems on SpaceX’s Falcon 9 if Starship timelines slip.

“If it ends up being delayed, we’ll just carry on launching the smaller versions on Falcon 9,” Johnston said. “We’re not going to be competitive on energy costs until Starship is flying frequently.”

The economics also highlight how early this market remains. While Starcloud’s ambitions include an 88,000-satellite compute constellation, the entire global installed base of advanced GPUs in orbit is still measured in the dozens. By contrast, Nvidia is estimated to have shipped nearly four million advanced GPUs to terrestrial hyperscalers in 2025 alone.

The gap is even starker in power terms.

SpaceX’s Starlink constellation, currently the world’s largest satellite network with roughly 10,000 spacecraft, is estimated to generate around 200 megawatts of energy. On Earth, more than 25 gigawatts of data-center capacity are under construction in the United States alone.

This makes Starcloud less a direct competitor to terrestrial hyperscalers today and more a strategic infrastructure bet on where AI computing may go next.

Its near-term business model reflects that reality.

Rather than immediately replacing ground-based cloud services, the company is focused first on selling processing power to other spacecraft operators. One example already in use is the processing of Earth observation data from Capella Space’s radar satellites.

In the longer term, Starcloud hopes to position itself as an energy and compute infrastructure provider to hyperscalers seeking overflow or distributed AI workloads.

Competition is intensifying.

Alongside Starcloud, companies such as Aethero, Aetherflux, and Google’s Project Suncatcher are exploring adjacent orbital infrastructure models. Meanwhile, SpaceX itself has reportedly sought regulatory approval for a million-satellite distributed compute network, potentially making it the most formidable rival in the field.

That looming presence is the elephant in the room.

Still, Johnston argues the two companies are addressing different markets, with SpaceX likely prioritizing internal workloads tied to xAI’s Grok and Tesla systems, while Starcloud positions itself as an independent infrastructure player.

“They are building for a slightly different use case than us,” he told TechCrunch. “They’re mainly planning on serving Grok and Tesla workloads. It may be at some point that they offer a third party cloud service, but what I think they are unlikely to do is what we’re doing [as] an energy and infrastructure player.”

Investors are betting that if launch costs collapse and orbital compute becomes technically scalable, Starcloud could sit at the intersection of two of the decade’s biggest themes, space infrastructure and AI.

Gas-Led Recovery Lifts $17.98m Foreign Capital into Nigeria’s Hydrocarbon Sector, but Inflows Remain Far Below Potential

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Nigeria’s oil and gas sector recorded a sharp rebound in foreign capital inflows in 2025, with fresh investments rising to $17.98 million from $5.12 million a year earlier, underscoring renewed interest in the country’s hydrocarbon industry as policymakers intensify their push for gas-led growth.

The latest figures from the National Bureau of Statistics (NBS) show that capital inflows into the sector more than tripled year-on-year, even as the broader Nigerian economy saw a strong recovery in foreign capital importation. Total capital inflows into the country climbed to $6.01 billion in the third quarter of 2025 alone, a 380.16 percent jump from the corresponding period of 2024.

The improvement in the oil and gas segment, though modest in absolute terms, points to a gradual restoration of investor confidence after years of policy uncertainty, foreign exchange constraints, and security concerns in producing regions.

This recovery has been largely buoyed by natural gas.

Gas export earnings rose 21 percent to $10.51 billion in 2025 from $8.66 billion in 2024, according to Central Bank of Nigeria data cited in the report, reinforcing the sector’s growing role as a critical source of foreign exchange. This comes as Nigeria increasingly positions gas as a transition fuel and a strategic economic asset amid the global energy transition.

The renewed investor appetite also coincides with a series of policy reforms aimed at improving the investment climate.

Most recently, the Central Bank of Nigeria eased foreign exchange rules for oil exporters, allowing international oil companies to retain and repatriate 100 percent of their export proceeds immediately, a move widely seen as designed to improve liquidity and restore confidence in the market. The policy shift forms part of broader reforms to deepen the FX market and attract investment.

For years, access to foreign exchange and restrictions on dollar repatriation have ranked among the biggest deterrents to large-scale upstream and midstream investments. By removing the previous cash-pooling rule, the CBN has effectively reduced one layer of risk for foreign operators and financiers.

The latest inflow numbers also align with the Federal Government’s long-running “Decade of Gas” strategy, which seeks to monetize Nigeria’s vast reserves and shift emphasis from crude dependence to gas-led industrialization.

Nigeria holds more than 200 trillion cubic feet of proven gas reserves, among the largest in Africa, yet a substantial portion remains commercially undeveloped. The Nigerian Upstream Petroleum Regulatory Commission’s recent Gas Development Roadmap, targeting the commercialization of over 55 trillion cubic feet of stranded reserves, is intended to unlock investment across exploration, processing, pipeline infrastructure, and export terminals.

The Nigerian National Petroleum Company Limited has set even more ambitious targets, saying it plans to expand reserves to 600 trillion cubic feet and attract as much as $60 billion in sectoral investment over time. Its Gas Master Plan 2026 aims for daily production of 10 billion cubic feet, with the objective of supporting domestic industrialization, power generation, and export earnings.

Still, the headline increase in inflows needs to be read with caution. While the jump from $5.12 million to $17.98 million is statistically significant, the absolute amount remains extremely small for a sector that historically accounts for the bulk of Nigeria’s export earnings and fiscal revenues.

By comparison, the country’s total capital importation runs into billions of dollars, with banking, financing, and portfolio flows continuing to dominate foreign investment receipts.

This suggests that the oil and gas sector’s recovery, while encouraging, remains in its early stages.

Analysts say the modest scale of inflows relative to Nigeria’s resource base highlights persistent structural issues, including pipeline vandalism, oil theft, delayed project closures, and investor caution toward long-cycle fossil fuel assets in an era of decarbonization.

That said, gas appears to be emerging as the more resilient story.

With Europe and parts of Asia still seeking diversified LNG supplies, Nigeria’s gas assets are increasingly viewed as commercially attractive, especially where projects are tied to export infrastructure and domestic industrial demand.

The sector’s improving numbers also come against a backdrop of a broader shift in Nigeria’s export composition. Non-oil exports reportedly rose to N12.36 trillion in 2025 from N9.09 trillion in 2024, driven by agriculture, manufacturing, and solid minerals, indicating that while hydrocarbons remain central, the economy is slowly broadening its external earnings base.

The rise in inflows signals that reforms may be beginning to gain traction, particularly in gas. But the figures also underscore how much ground remains to be covered if Nigeria is to unlock the scale of investment required to fully monetize its hydrocarbon assets and strengthen external reserves.

In short, investor interest is returning, but the sector is still operating well below its capacity. The real test, economists note, will be whether policy stability, FX liberalization, and gas infrastructure development can convert this early rebound into sustained multi-billion-dollar inflows over the coming years.

Anthropic’s Claude Mythos Details Leaked Via a Misconfigured Content Management System 

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Anthropic’s Claude Mythos details leaked via a misconfigured content management system (CMS) data store, exposing draft blog posts and other internal assets. Security researchers discovered that nearly 3,000 unpublished files—including draft blog posts, PDFs, and memos were publicly accessible due to a configuration error.

One key draft described a new model called Claude Mythos, positioned as a major step change above Anthropic’s current Opus tier. It claimed the model is by far the most powerful AI model we’ve ever developed, with dramatically higher performance in coding, academic reasoning, and especially cybersecurity-related tasks.

Anthropic confirmed the leak to Fortune and others, acknowledging they have completed training on the model sometimes referred to interchangeably with “Capybara” in drafts and are testing it with select early-access customers. They described it as their most capable model to date but highlighted unprecedented cybersecurity risks: the model is far ahead of any other AI model in cyber capabilities” and could enable attacks that far outpace the efforts of defenders.”

The company reportedly plans restricted early access for cyber defense organizations to help bolster protections before broader release. Cybersecurity stocks dropped sharply on March 27, 2026, as investors interpreted the leak as signaling a coming wave of more sophisticated AI-powered attacks: CrowdStrike (CRWD): ~7% drop. Palo Alto Networks (PANW): ~6-7.5%. Zscaler (ZS), SentinelOne (S), Okta (OKTA), and others: 4-8% declines.

Broader sector ETFs also fell several percent, with reports of ~$14.5 billion in combined market value erased in one day. This isn’t the first time AI cyber capabilities have pressured the sector—similar dips occurred after prior Claude updates with vulnerability-scanning features.

Frontier models are advancing rapidly in agentic capabilities (autonomous task execution, chaining exploits, etc.). If Mythos excels at identifying and weaponizing vulnerabilities faster than humans or current tools, it could shift the offense-defense balance in cybersecurity—making large-scale, automated attacks more feasible for sophisticated actors while defenders scramble to keep up.

Anthropic’s own warning in the draft; flagging risks and limiting access amplified the fear. That said: No model weights leaked—only descriptive documents and drafts. The actual system isn’t public. AI can also aid defense with better anomaly detection, automated patching, red-teaming. Anthropic’s plan to share early access with defenders acknowledges this dual-use nature.

Stock reactions to AI news are often short-term and volatile; they reflect sentiment more than proven long-term disruption. This fits a pattern with frontier AI labs: leaks happen (misconfigurations are common in fast-moving companies), capabilities keep scaling, and safety/cyber risks get more explicit discussion.

Anthropic has long emphasized safety, so their internal caution here is noteworthy—but also expected for a model they call a step change. The incident underscores ongoing challenges around secure internal processes at AI companies and the difficulty of keeping cutting-edge work under wraps. It may accelerate conversations about responsible release practices, government coordination on cyber-AI risks, and investment in defensive AI tools.

In short, the leak revealed an impressive but risky next-gen model that Anthropic is handling cautiously. Markets overreacted on the offense gets stronger narrative, as they often do with AI hype/fear cycles. Expect more details and probably a formal launch soon, alongside continued debate on how to manage these capabilities responsibly.