News & Updates
The latest news and updates from companies in the WLTH portfolio.
Canada Regulator Warns Banks About Cyber Risks of Anthropic's Claude Mythos
Canada's federal banking regulator warned the country's largest financial institutions about the risks of Anthropic's Claude Mythos and other advanced AI models, saying the new technology could increase cyber threats and reduce the time institutions have to identify and fix vulnerabilities, according to an email sent in April. The regulator, the Office of the Superintendent of Financial Institutions, sent the email to chief technology officers, chief information security officers, and chief risk officers across the financial industry, including the big banks and insurers, according to documents Reuters obtained through an access-to-information request. Regulators globally are trying to assess cybersecurity risks such as Anthropic's frontier AI model Mythos. Cybersecurity experts say Mythos, an AI model described as extremely capable at finding and exploiting cybersecurity vulnerabilities, poses significant challenges to the banking industry and its legacy technology systems. "Advanced artificial intelligence models, such as Anthropic Claude Mythos, significantly compress the timeframe for effective risk mitigation," OSFI said in the email. "Accordingly, this bulletin is grounded in our existing guidance and outlines sound practices that institutions can adopt to enhance the speed and effectiveness of risk identification, mitigation and response." Additional contents of the email were redacted due to some sections of the Access to Information Act. An acknowledgment of the risks of Mythos from OSFI could ensure Canadian banks, insurers and other regulated institutions invest in technology to protect clients from cyber risks. After Reuters sent questions to OSFI last week, the regulator on Monday posted a public bulletin on generative and agentic artificial intelligence online. "OSFI takes a technology‑neutral, risk‑focused approach to emerging technologies, including advanced artificial intelligence models such as Mythos. Our focus is not the technology itself, but how federally regulated financial institutions govern and manage the risks associated with its use," the regulator said in an emailed response to Reuters questions. In early April, Canadian bank executives met with regulators to discuss the risks posed by Mythos shortly after U.S. Treasury Secretary Scott Bessent and then-Federal Reserve Chair Jerome Powell convened an urgent meeting with bank CEOs to warn of cyber risks posed by Anthropic's latest artificial intelligence model. OSFI sent the email to company executives on April 29. Rapidly Changing Landscape OSFI is responsible for regulating and maintaining the stability of Canada's financial sector, from banks to pension funds, and identifying risks emerging from foreign interference, geopolitics and new technology. The cyber capabilities of some frontier AI systems are considered so powerful that access has been restricted, with euro zone banks currently excluded from Mythos. Anthropic has also had a tumultuous relationship with the U.S. government. A judge blocked its initial blacklisting by the Pentagon in March, and the conflict has eased following the private release of Anthropic's Mythos. Three of Canada's big six banks - Royal Bank of Canada, TD Bank and BMO - have outlined a plan to earn millions from their investments in AI as the banks moved from experimental AI projects to applying them in chatbots, building internal tools and lowering their reliance on third-party tools. Bank of Nova Scotia, CIBC and National Bank have also disclosed several AI initiatives. The Canadian government has said it has access to Anthropic's Project Glasswing, which allows companies to have access to Mythos. It is not clear which, if any, banks in Canada are using it. Some banks deferred comments to the Canadian Bankers Association, which said banks have invested heavily to protect the financial system and are complying with robust requirements from OSFI on cyber risk management and incident reporting. In an interview in June, RBC's AI Group Head Bruce Ross said Mythos underscored a shift in the cyberattack landscape, making it imperative for organizations to respond rapidly since attack methods can emerge as soon as new vulnerabilities are identified. "The way we're (the industry) dealing with it is, building our own AI defenses... we'll continue to do that," Ross said. (Reporting by Nivedita Balu in Toronto; editing by Caroline Stauffer and Deepa Babington)
Anthropic Wrongly Bills a Free-Tier User $16.6 Million: What Happened?
An audit by Vaudit found $1.7 million in overcharges across $34 million in AI invoices. Anthropic confirmed a massive billing error after its system tried to charge a South Korean free-tier user $16.6 million, despite zero API usage and no registered card. The phantom invoices blocked his credit card and triggered a four-day support ordeal before the company responded. Inside Anthropic's $16.6 Million Phantom Invoice A phantom invoice is a payment demand generated by a billing system without any underlying transaction or usage. That is exactly what a Korean developer, known as remy_notes, received from Anthropic in early July. The story quickly went viral after he shared the screenshots on Threads. The first invoice arrived on July 7, totaling $1,669,875. Less than 24 hours later, a second one multiplied the figure almost tenfold to $16,627,739. The escalation occurred without any activity being recorded on the accoun Follow us on X to get the latest news as it happens. The developer initially suspected phishing. However, the emails came from Anthropic's official domain and used the company's legitimate Stripe infrastructure. Furthermore, his dashboard showed zero API usage, no billable keys, and no payment method on file. He audited his own automation scripts and AI agents, finding nothing that explained the charges. His bank declined two overseas charge attempts on July 8 because the amounts exceeded the card's per-transaction limits. The repeated attempts still resulted in his primary credit card being blocked. What Caused the Billing Error, According to Anthropic Anthropic confirmed the mistake on July 12 and assured that no money was collected. The company attributed the invoices to an incorrect automatic credit reload setting, which it disabled as a precaution. It also clarified that the incident did not involve unauthorized access. Anthropic has not explained how the reload value reached such an extreme figure. The resolution, however, was far from smooth. The user spent four days and around 18 emails seeking written confirmation that the invoices were void. Meanwhile, automated replies kept arriving instead of human responses. He eventually asked the company to respond by Monday afternoon, Korean time. The case also exposed a wider industry problem. Audit startup Vaudit reviewed $34 million in AI invoices from 60 enterprise clients and found roughly $1.7 million in overcharges. That represents an error rate of about 5%, much of it tied to AI billing systems. Clients affected by those errors included major corporations like Panasonic, HP, and Honda. For users, the lesson is simple. Reviewing billing dashboards, monitoring card notifications, and reporting unusual charges quickly can prevent a glitch from becoming a financial nightmare.
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MEXC Reports 7.1 Billion USDT in SpaceX Futures Volume as Q2 Closes the Gap to Wall Street
Victoria, Seychelles, July 14th, 2026, Chainwire MEXC, a pioneer in 0-fee digital asset trading, today released its Ecosystem & Growth Report for the second quarter of 2026. In Q1, users mostly bought gold and other hedges against macro risk. In Q2, their attention turned to AI projects and US stocks, and MEXC spent the quarter building products for exactly that demand. Users can now back a company before its IPO, trade stock futures on it, hold tokenized shares, and buy real US stocks and ETFs, all inside one MEXC account. Every piece of that path launched or grew during the quarter. SpaceX was still a private company when MEXC ran two SPACEX(PRE) subscription rounds. More than 74,000 entries put over 173 million USDT into them, and demand for the second round reached more than 30 times the amount on offer. That demand mirrors a wider market trend: CoinGecko reports that tokenized pre-IPO trading volume surged 1,060%, with SpaceX accounting for the largest share of activity. The company then completed the largest IPO on record on June 12. Users kept trading it on MEXC after the listing, and SpaceX perpetual futures collected more than 7.1 billion USDT in volume in the weeks that followed. One name went from private to public within a quarter, and users traded at every stage. RealStocks launched on June 1 and added the last piece, real shares. Eligible users buy actual US stocks and ETFs through a licensed securities broker partner, and the shelf covers more than 7,000 names. More than 120,000 users signed up in the first month, and over half of the new accounts moved on to a first deposit. By June 18, the product had settled dividends on 34 stocks and ETFs, the kind of payout only real share ownership carries. Micron's June earnings lifted trading volume in its MEXC futures by approximately 142% in a single day. The activity spilled into related AI memory names, SanDisk, SK hynix, and a DRAM ETF. One earnings report moved a whole supply chain on the platform, because users now trade US market news the moment it breaks. "My first quarter as CEO had one goal, and that was to move MEXC from a crypto exchange toward a gateway for every market users care about," said Vugar Usi, CEO of MEXC. "Q2 put real numbers behind the word gateway, from Pre-IPO demand to actual dividend payouts." The quarter's ten biggest new-token gainers averaged +4,956%, and six of the ten were AI agent projects. Only one meme coin made the list, a clear reversal of the first quarter, when memes ran the gain rankings. The AI winners build practical systems. They settle transactions between agents, place trades for retail users, and verify identities, so the money went to projects that already do that work. The most-traded list leaned the same way, with four AI and infrastructure names to three meme names. During the quarter, MEXC appointed Vugar Usi as Chief Executive Officer and marked its 8th anniversary with a brand upgrade built on two promises: 0 Fees and Infinite Opportunities. The upgrade marks the company's move from a traditional exchange toward a universal gateway for global markets. A partnership brought the USD1 stablecoin into MEXC's trading and product suite, and the first USD1 event drew more than 161,000 participants, with new users alone pushing $2.4 billion through futures. A TradingView integration now sends perpetual futures orders straight from the chart, so users move from analysis to execution without a tab change. The Prediction Market added a Combo feature on June 9, which folds several event predictions into a single position. Average daily volume in the Prediction Market grew more than 6,700% from early to late June, and daily users rose more than 3,200%. The June Proof of Reserves put the average reserve ratio at 156.5%, which means the platform holds more assets than users have deposited, with Bitcoin backed at 269%. Between May and June, the risk team identified 4,394 illicit networks; a separate intervention effort blocked roughly 303,000 USDT in suspected fraudulent transfers. The full Q2 report, with the complete token tables, product data, and community programs, is available here. About MEXC MEXC is the world's fastest-growing cryptocurrency exchange, trusted by more than 40 million users across 170+ markets. Built on a user-first philosophy, MEXC offers industry-leading 0-fee trading and access to over 3,000 digital assets. As the Gateway to Infinite Opportunities, MEXC provides a single platform where users can easily trade cryptocurrencies alongside tokenized assets, including stocks, ETFs, commodities, and precious metals.
Anthropic appoints Surajj Gurav to strengthen enterprise AI growth in India's BFSI sector The Mainstream
Anthropic has expanded its India go-to-market (GTM) team with the appointment of Surajj Gurav to its Enterprise GTM team. He will work with banking, financial services, and insurance (BFSI) organisations to accelerate the responsible adoption of enterprise AI. Surajj joins Anthropic's India GTM team led by Irina Ghose. In his new role, Surajj will partner with leading BFSI enterprises to help them adopt Anthropic's trusted AI capabilities while addressing the industry's regulatory, security, and governance requirements. His appointment supports the company's focus on enabling the safe and responsible adoption of AI across enterprises. Before joining Anthropic, Surajj served as Director - Sales, BFSI at Snowflake, where he led strategic engagements with financial institutions, helping organisations modernise data platforms and accelerate cloud-based digital transformation. Earlier, he was Chief Revenue Officer (India) at Snapwork Technologies, where he drove enterprise growth, customer acquisition, and revenue expansion across the Indian market. Prior to that, Surajj spent more than 3 years at Microsoft as Specialist - Business Applications, working with leading BFSI organisations to support digital transformation through Microsoft Dynamics 365, Power Platform, low-code application development, robotic process automation, and AI-enabled customer experience solutions. Over the course of nearly 3 decades, Surajj has also held leadership roles at MicroStrategy, Equifax, IBM India Pvt. Ltd., Oracle India, Sun Microsystems India, Pre-emptive Systems, Velocis Systems, Redington India Ltd., Team Computers Pvt. Ltd., Momentum Infocare Pvt. Ltd., SSI Limited, and Datapro Infoworld Ltd. His experience spans enterprise software, cloud platforms, analytics, AI, digital transformation, middleware, business applications, and enterprise technology sales. Throughout his career, he has partnered with organisations across banking, financial services, telecom, manufacturing, and the public sector to deliver large-scale technology transformation initiatives. With deep expertise in enterprise AI, cloud technologies, analytics, digital transformation, customer experience, and strategic enterprise sales, Surajj will play a key role in supporting Anthropic's continued growth across India's BFSI sector. Also read: Viksit Workforce for a Viksit Bharat Do Follow: The Mainstream LinkedIn | The Mainstream Facebook | The Mainstream Youtube | The Mainstream Twitter About us: The Mainstream is a premier platform delivering the latest updates and informed perspectives across the technology business and cyber landscape. Built on research-driven, thought leadership and original intellectual property, The Mainstream also curates summits & conferences that convene decision makers to explore how technology reshapes industries and leadership. With a growing presence in India and globally across the Middle East, Africa, ASEAN, the USA, the UK and Australia, The Mainstream carries a vision to bring the latest happenings and insights to 8.2 billion people and to place technology at the centre of conversation for leaders navigating the future.
Kraken rolls out Mastercard crypto debit card in UK and Europe
Kraken has launched a Mastercard debit card in the UK and Europe, allowing users to spend from a wide range of cryptocurrency and cash balances. The crypto exchange said the card can be used for everyday purchases online and in stores wherever Mastercard is accepted. Users can pay from more than 600 supported crypto and cash currency balances. The funds are converted in near real time at the point of purchase. Kraken said the card offers up to 2% cashback, paid weekly in Bitcoin, euros or pounds. It also said there are no transaction or ATM fees. The product is being introduced first in the UK and the European Economic Area (EEA), with other markets expected to follow "soon," according to the company. In the UK, the Kraken Card is issued by Monavate, which is authorised by the Financial Conduct Authority (FCA) to carry out electronic money activities and related payment services. In the EEA, the card is issued by UAB Monavate, which is authorised by the Bank of Lithuania. The launch forms part of Kraken's broader effort to develop a "holistic financial offering". The company is also redesigning its app to include more personalised features and a more intuitive interface. The card launch follows a recent agreement by Kraken parent Payward to acquire Reap Technologies in a $600m deal. Reap Technologies focuses on stablecoin-based card issuing and payments infrastructure. The company has developed a card issuing and cross-border payments platform linking traditional financial systems with digital assets for global business payments. Kamo Asatryan, global head of consumer at Kraken and chief AI and data officer of Payward, said: "People shouldn't have to worry about where their money is sitting before they spend it. Our customers already earn, save, invest, and trade with Kraken. "The Kraken Card adds 'spend' to that list, bringing it all together into one experience that just works."
MEXC reports 7.1 billion USDT in SpaceX futures volume as Q2 closes the gap to Wall Street
Victoria, Seychelles, July 14th, 2026, Chainwire MEXC, a pioneer in 0-fee digital asset trading, today released its Ecosystem & Growth Report for the second quarter of 2026. In Q1, users mostly bought gold and other hedges against macro risk. In Q2, their attention turned to AI projects and US stocks, and MEXC spent the quarter building products for exactly that demand. Users can now back a company before its IPO, trade stock futures on it, hold tokenized shares, and buy real US stocks and ETFs, all inside one MEXC account. Every piece of that path launched or grew during the quarter. SpaceX was still a private company when MEXC ran two SPACEX(PRE) subscription rounds. More than 74,000 entries put over 173 million USDT into them, and demand for the second round reached more than 30 times the amount on offer. That demand mirrors a wider market trend: CoinGecko reports that tokenized pre-IPO trading volume surged 1,060%, with SpaceX accounting for the largest share of activity. The company then completed the largest IPO on record on June 12. Users kept trading it on MEXC after the listing, and SpaceX perpetual futures collected more than 7.1 billion USDT in volume in the weeks that followed. One name went from private to public within a quarter, and users traded at every stage. RealStocks launched on June 1 and added the last piece, real shares. Eligible users buy actual US stocks and ETFs through a licensed securities broker partner, and the shelf covers more than 7,000 names. More than 120,000 users signed up in the first month, and over half of the new accounts moved on to a first deposit. By June 18, the product had settled dividends on 34 stocks and ETFs, the kind of payout only real share ownership carries. Micron's June earnings lifted trading volume in its MEXC futures by approximately 142% in a single day. The activity spilled into related AI memory names, SanDisk, SK hynix, and a DRAM ETF. One earnings report moved a whole supply chain on the platform, because users now trade US market news the moment it breaks. "My first quarter as CEO had one goal, and that was to move MEXC from a crypto exchange toward a gateway for every market users care about," said Vugar Usi, CEO of MEXC. "Q2 put real numbers behind the word gateway, from Pre-IPO demand to actual dividend payouts." The quarter's ten biggest new-token gainers averaged +4,956%, and six of the ten were AI agent projects. Only one meme coin made the list, a clear reversal of the first quarter, when memes ran the gain rankings. The AI winners build practical systems. They settle transactions between agents, place trades for retail users, and verify identities, so the money went to projects that already do that work. The most-traded list leaned the same way, with four AI and infrastructure names to three meme names. During the quarter, MEXC appointed Vugar Usi as Chief Executive Officer and marked its 8th anniversary with a brand upgrade built on two promises: 0 Fees and Infinite Opportunities. The upgrade marks the company's move from a traditional exchange toward a universal gateway for global markets. A partnership brought the USD1 stablecoin into MEXC's trading and product suite, and the first USD1 event drew more than 161,000 participants, with new users alone pushing $2.4 billion through futures. A TradingView integration now sends perpetual futures orders straight from the chart, so users move from analysis to execution without a tab change. The Prediction Market added a Combo feature on June 9, which folds several event predictions into a single position. Average daily volume in the Prediction Market grew more than 6,700% from early to late June, and daily users rose more than 3,200%. The June Proof of Reserves put the average reserve ratio at 156.5%, which means the platform holds more assets than users have deposited, with Bitcoin backed at 269%. Between May and June, the risk team identified 4,394 illicit networks; a separate intervention effort blocked roughly 303,000 USDT in suspected fraudulent transfers. The full Q2 report, with the complete token tables, product data, and community programs, is available here. About MEXC MEXC is the world's fastest-growing cryptocurrency exchange, trusted by more than 40 million users across 170+ markets. Built on a user-first philosophy, MEXC offers industry-leading 0-fee trading and access to over 3,000 digital assets. As the Gateway to Infinite Opportunities, MEXC provides a single platform where users can easily trade cryptocurrencies alongside tokenized assets, including stocks, ETFs, commodities, and precious metals. MEXC Official Website｜ X ｜ Telegram ｜How to Sign Up on MEXC For media inquiries, please contact MEXC PR team: [email protected]
Crypto Exchanges Close the Gap to Wall Street as MEXC Logs 7.1 Billion in SpaceX Futures
The build-out is happening almost entirely offshore, with US retail locked out and MEXC still operating in Europe without a MiCA license. Crypto exchange MEXC said today (Tuesday) that perpetual futures tied to SpaceX shares drew more than 7.1 billion USDT in trading volume in the weeks after the rocket company listed on June 12. The figure comes from the exchange's own second-quarter report and has not been independently audited. Users could subscribe to SpaceX before it went public, trade futures on it afterward, hold a tokenized version, and buy the actual share, without ever leaving the platform. MEXC ran two SPACEX(PRE) subscription rounds while the company was still private, collecting over 173 million USDT from more than 74,000 entries, the report said. One name went from private to publicly traded inside a single quarter, and MEXC sold a product at every stage of the journey. RealStocks, which went live June 1, supplied the last piece. The service routes orders for actual US shares and ETFs through a licensed securities broker partner, giving buyers dividends rather than price exposure alone. The exchange has still not named the broker, disclosed custody arrangements, or explained how the USDT-to-dollar conversion is priced. More than 120,000 users signed up in the first month and 52% of them funded an account, according to the company. By June 18, it had settled dividends on 34 stocks and ETFs. Stock futures carried much of the equity flow. Micron's June earnings lifted MU futures volume on the platform by roughly 142% in a single day, MEXC said, with activity spilling into SanDisk, SK hynix and a DRAM ETF. "Q2 put real numbers behind the word gateway," said Vugar Usi, who took over as chief executive during the quarter. Binance, Kraken and Coinbase Are Building the Same Thing Binance opened access to roughly 7,000 US stocks on June 1, the same day RealStocks launched. Orders are arranged through broker-dealer Nest Trading, with Alpaca handling custody, dividends and corporate actions, and fractional purchases start at $5, funded in USDC, USDT or BNB. Kraken went the tokenized route instead. Its xStocks brand passed $25 billion in cumulative transaction volume in under eight months, listed on Deutsche Börse's 360X venue, and now accounts for eight of the eleven largest tokenized equities. Coinbase has described its own version of the plan as an "Everything Exchange" covering crypto, stocks, derivatives and event contracts. Prediction markets are the other shared front. MEXC opened a zero-fee event contract platform in March and added multi-outcome Combo positions on June 9. Average daily volume there rose more than 6,700% between early and late June, the company said, off a starting base it did not disclose. Traffic Runs Both Ways as Brokers Copy the Perpetual The borrowing is not one-directional. On Monday, Pepperstone said it would extend its perpetual CFD range beyond SpaceX into metals, stock indices and energy, with gold, silver, Nasdaq, S&P 500, WTI and Brent versions listed as planned. The perpetual, a contract with no expiry that uses periodic funding payments to stay near the underlying, began life in crypto and is now being fitted onto shares and commodities inside a regulated CFD wrapper. "We believe perpetual markets will become a standard feature of modern finance," Pepperstone group chief executive Tamas Szabo said. European regulators have already told firms that perpetual futures fall under EU CFD rules, which drags the format inside the same retail leverage caps that MEXC's offshore version sits outside. The Refund the Report Does Not Mention MEXC's Launchpad section says SPACEX(PRE) traded 12% above its subscription price at listing and reached a 38% peak return. It says nothing about refunds. On June 12, MEXC cancelled tokenized SpaceX allocations and returned money to subscribers, along with Binance, Bybit and Bitget Wallet, after xStocks failed to source the underlying shares. All four had been reselling access to allocations that Kraken's tokenization arm promised to procure, and when that single supplier came up empty, so did everyone hanging off it. Demand was never the constraint. Binance's campaign drew more than $557 million in USDC before it was pulled, and MEXC's first round ran 15.5 times oversubscribed. The shares just never showed up. US Retail Stays Outside the Perimeter None of this touches American investors. Tokenized equity products are closed to US persons, and Kraken's SpaceX token also excluded users in the UK, Canada and Australia. Europe is narrowing as well. MEXC entered July without a MiCA license and without any public update on its application, and its published list of restricted jurisdictions, last revised in May, does not include EU member states. Hong Kong's securities regulator put the exchange on its warning list over unlicensed activity in 2024. MEXC put its June reserve ratio at 156.5% across major assets, with bitcoin backed at 269%, and said its futures insurance fund hit $753 million in July. Both numbers are the exchange's own, and neither has been verified by an outside auditor.
Musk Fortune Falls Below $900 Billion As SpaceX Slides
Elon Musk's net worth has fallen below one trillion dollars recently. SpaceX shares experienced a significant decline after their initial public offering. This market shift reflects a demand for AI profits over future promises. Musk's wealth contraction coincides with Tesla's India expansion plans. Starlink's launch in India remains stalled due to regulatory and security concerns. Elon Musk stopped being a trillionaire on Monday, and the reason says more about the AI trade than about the richest man alive. His fortune slipped to $879.3 billion after another pullback in SpaceX shares stripped $37.9 billion from his wealth in a single session -- with a later reading closer to $871.6 billion as the sell-off deepened. The peak was $1.45 trillion, reached on 16 June when SpaceX shares touched an all-time high above $225. Four weeks and more than half a trillion dollars later, the world's first almost-instant multitrillionaire is merely, spectacularly, rich.The cause is singular, and it sits outside Musk himself. SpaceX shares slid to just under $140, closing on the $135 price at which the company went public a month ago, a decline of more than 38 per cent from the high it touched the day after listing. The rocket that carried Musk past every wealth record in history is doing what rockets do once the burn ends -- falling back toward the pad it launched from. The force pulling it down is a market that has switched from paying for AI promises to demanding AI profits, and that same force has already halved Larry Ellison and dropped him from second-richest to eighth in a matter of weeks.
Bank: "Unknown Unknowns for SpaceX"
In recent days slew of banks have issued their valuation forecasts on SpaceX following on from its Initial Public Offering (IPO). The range was extremely wide, from $143 per share from Deutsche Bank to a staggering $800 from Raymond James. However, analysts at technology research company Moffett Nathanson took a more modest view and their share price guidance was $131, and said there was no credible financial model to support anything higher. Moffett Nathanson issued a comprehensive 93-page report where they compared and contrasted the prospects for SpaceX and its rival AST SpaceMobile. They stated: "Never before has so much attention been lavished on a company in advance of its IPO. And no company, in the weeks following its IPO, has been treated to more withering scrutiny. By now, you will surely have read umpteen articles and reports poking and prodding every aspect of the largest IPO of all time." "By and large, the coverage has been split into two camps. One camp has fawned over the sheer audacity of the enterprise and the spectacular size of SpaceX's addressable market. The other has relentlessly lampooned the utter ridiculousness of so many of the numbers thrown around in the company's S-1 and analyst commentary," continued Moffett Nathanson. "We're in neither camp." "To be sure," the report added. "There is plenty to poke fun at. SpaceX's assessment of its total addressable market (TAM), at almost $30 trillion, is absurd. So too are its forecasts for a mobility (D2D wireless) segment that is, to us, likely little more than a niche market. Founder and CEO Elon Musk has called for launching compute into orbit at a rate of 100 GW annually by year-end 2029, an amount that exceeds global in-service data centre capacity today and for which sufficient material inputs will not exist in three-and-a-half years. There is simply no credible financial model that can support what is at the time of this writing a roughly $2 trillion valuation. Our own certainly does not. On this basis alone, it would be easy - some might argue prudent - to initiate coverage with a flashing red 'Sell' rating." Moffett Nathanson admitted that SpaceX has fashioned a monopoly in the rocket segment, with Blue Origin the only competitor but probably 10 years or more behind. The researchers look at the other key expectations outlined by SpaceX, not least its Starlink service and in particular the prospects of orbital data centers. "There are 'unknown unknown' opportunities that will inevitably arise from SpaceX's advantaged position, and those opportunities should appropriately be rewarded in SpaceX's valuation, even if there is, admittedly, no rigorously quantifiable approach to doing so," says the report, and adds that "SpaceX faces significant regulatory, antitrust, and political risk. It is perfectly legal to establish a dominant position in a business, as SpaceX has done in its Space segment, by innovating, taking risks, and driving down costs. Leveraging that dominant position into dominant positions in adjacent businesses, however, introduces antitrust risk. Overseas governments may also be hesitant to rely on foreign-owned critical infrastructure." "We expect significant volatility in SpaceX shares. Much has been made of technical factors such as index inclusion and lock-up expirations. These are not our specialty, nor our focus. What is more important, in our view, is the yawning disconnect between valuation and actual forecasts. We suspect - but we certainly can't be sure - that the market will be inclined to give SpaceX the benefit of the doubt when it is feeling generally ebullient. We further suspect that it will not give SpaceX the benefit of the doubt if sentiment for the broader market turns generally skeptical," stated the firm.
SpaceX cleared to fly Starship again after booster failure in May
The Federal Aviation Administration (FAA) has cleared SpaceX to fly Starship prototypes again, after the company identified the probable cause of the failure of the rocket system's booster stage during a flight in May. SpaceX said over the weekend that the next flight of Starship could happen as soon as this Thursday, July 16. It would be the second-ever launch of the third version, or V3, of Starship. SpaceX also said that this Starship will carry the first third-generation Starlink satellites to space. Previously, Starship had only carried dummy versions of the larger, more powerful internet satellites. This is SpaceX's second test flight of its Starship system, and its first as a public company, testing the market's appetite for the company's "fly, fail, fix" approach to rocket development that often ends in fireballs -- or, as CEO Elon Musk calls the explosions: "rapid unscheduled disassembly." SpaceX completed its IPO and publicly listed on the Nasdaq Stock Exchange on June 12, making it one of the 10 most valuable companies in the world and raising nearly $86 billion, a record. SpaceX's first test launch of the V3 Starship on May 22 was largely successful. The company's Super Heavy booster lifted the 407-foot rocket into space before the upper stage section separated and deployed 20 satellite simulators along with two modified Starlinks that recorded footage of the Starship exterior. The new third-generation booster was supposed to return to Earth and perform a simulated landing in the Gulf of Mexico. But its engines didn't properly re-ignite, and it instead plummeted into the water below. The problem happened at that moment of booster separation, according to SpaceX and the FAA. SpaceX said in a post published over the weekend that "slight differences in engine startup on the ship" caused the Booster to turn 90 degrees in the wrong ...
Anthropic Claude India Pricing announced: Check what users will have to pay for Claude services
Anthropic Claude Cost India: Anthropic now offers its Claude AI assistant with pricing in Indian rupees. This move simplifies payments and removes currency conversion fees for users. India has become Anthropic's second-largest global market after the United States. The company recently opened an office in Bengaluru to support its growth. Localized pricing is crucial for competing in India's tech market. Anthropic has quietly done something Indian users have been asking for: it has started charging for its Claude AI assistant in rupees instead of US dollars. The switch means anyone signing up for a paid Claude plan in India will now see prices in familiar currency, without the extra math or the surprise dollar conversion charges that usually show up on the credit card bill. What Changes for Anthropic UsersIndian subscribers browsing Claude's web and mobile apps will now find rupee price tags on every paid tier. Gone is the need to route payments through international cards or absorb currency conversion fees, a hurdle that has long kept budget-conscious users away from foreign AI subscriptions. Anthropic Claude India Pricing: The New Price TagsClaude Pro: Rs 2,000 a month if billed yearly, or Rs 2,399 a month if paid monthly Claude Max: Two new tiers at Rs 11,999 and Rs 23,999 a month, built for developers, researchers and anyone who burns through AI credits quickly Claude Team: Starts at Rs 2,399 per user per month on annual billing, aimed at businesses Claude Team Premium: Rs 11,999 per user per month for companies wanting higher limits All these figures already include GST, so there are no hidden add-ons at checkout. Why Anthropic Is Betting Big on IndiaThe numbers explain the urgency. India now makes up 5.8% of Claude's entire global user base, enough to place it just behind the US in Anthropic's rankings. Growth has been sharp too. Anthropic CEO Dario Amodei said Anthropic's revenue run rate in India had doubled in just four months, a pace that has clearly caught the company's attention. That kind of momentum is hard to ignore, and it explains why Anthropic has been laying down roots rather than just testing the waters. Anthropic Setting Up Shop in BengaluruThe rupee pricing is the latest step in a broader India push. Anthropic opened its first Indian office in Bengaluru back in February, giving it a direct line to the country's massive developer and enterprise community. It has also teamed up with homegrown fintech player Razorpay, making it easier for Indian businesses to plug Claude into their own products and services. A Crowded BattlefieldAnthropic is not the only one eyeing India's AI appetite. OpenAI, Google, Microsoft and Perplexity have all ramped up their India game with new launches, partnerships and enterprise deals of their own. Local pricing gives Anthropic one less excuse for price-sensitive Indian users to look elsewhere, and one more reason to believe the country is no longer just another market on the map, but a genuine growth engine for the company.
Kalshi, Polymarket: Gambling or Financial Products Under US Law?
Prediction markets, which allow people to put money on everything from elections to sporting events, have grown into a multibillion dollar industry. Their rapid expansion has triggered a wave of lawsuits over one fundamental question: who gets to regulate them, states or the federal government? States argue many of the contracts offered on prediction market platforms are simply another form of gambling and fall under state gaming laws. Prediction market companies contend that their contracts are financial products that should be regulated under federal commodities law. In this video, we explain how prediction markets work, why states and the Commodity Futures Trading Commission disagree over who has authority to regulate them, how courts have responded to the growing number of lawsuits, and why the answers could reshape the future of sports betting, event contracts, and prediction markets in the US. FEATURING Melinda Roth, Professor, Washington & Lee School of Law Gillian Brassil, Reporter, Bloomberg Law J.J. McCorvey, Reporter, Bloomberg News
Kalshi, Polymarket: Gambling or Financial Products Under US Law?
Prediction markets, which allow people to put money on everything from elections to sporting events, have grown into a multibillion dollar industry. Their rapid expansion has triggered a wave of lawsuits over one fundamental question: who gets to regulate them, states or the federal government? States argue many of the contracts offered on prediction market platforms are simply another form of gambling and fall under state gaming laws. Prediction market companies contend that their contracts are financial products that should be regulated under federal commodities law. In this video, we explain how prediction markets work, why states and the Commodity Futures Trading Commission disagree over who has authority to regulate them, how courts have responded to the growing number of lawsuits, and why the answers could reshape the future of sports betting, event contracts, and prediction markets in the US. FEATURING Melinda Roth, Professor, Washington & Lee School of Law Gillian Brassil, Reporter, Bloomberg Law J.J. McCorvey, Reporter, Bloomberg News
SpaceX Stock Drops 25% From IPO as $18.5 Billion Revenue Fails to Calm AI Bubble Fears
* SpaceX shares fell near IPO price amid technology sector weakness. * Starlink generated $11.4 billion revenue despite continued company losses. * AI valuation concerns pressured technology stocks and market sentiment. * Investors questioned whether AI spending justifies current company valuations. SpaceX shares have declined roughly 25% since the company's initial public offering, extending losses as the broader technology sector comes under pressure from concerns that AI-related valuations have outpaced earnings growth. The stock recently fell to $149.47, its lowest level since listing, leaving it within striking distance of its $135 IPO price. The decline reflects growing investor caution over richly valued AI and technology companies despite continued optimism from Wall Street. While SpaceX remains the dominant commercial launch provider and its Starlink satellite business continues to expand, investors are weighing persistent operating losses, elevated capital expenditure and broader concerns that the AI investment boom could resemble previous technology bubbles. SpaceX Stock Extends Decline Despite Strong Revenue Growth SpaceX shares fell another 4.45% in the latest trading session, bringing the stock closer to its IPO price after losing nearly 28.7% from its post-listing high during its first week of trading. The decline has also affected founder Elon Musk's wealth, with his estimated net worth falling below $900 billion as the company's market value contracted. Financial results continue to divide investors. SpaceX reported more than $18.5 billion in revenue last year but posted a net loss of nearly $5 billion, highlighting the significant investment required to expand its launch, satellite and artificial intelligence businesses. Starlink Growth Offsets Concerns Over Profitability Despite the recent sell-off, investors remain encouraged by the continued expansion of Starlink, which has become SpaceX's largest commercial business. The satellite internet division generated approximately $11.4 billion in revenue during 2025, underscoring the company's growing recurring revenue base beyond launch services. Some analysts also view SpaceX's AI initiatives as an emerging growth driver, particularly in terrestrial applications rather than long-term space exploration. Others remain cautious, arguing that the company's valuation continues to reflect aggressive assumptions regarding future AI commercialization and ambitious space development projects. AI Market Correction Weighs on Technology Stocks SpaceX's decline comes amid a broader retreat across AI-linked equities as investors reassess whether corporate earnings can justify unprecedented spending on artificial intelligence infrastructure. In early July, the S&P 500 fell 0.4%, while the Nasdaq Composite declined 1.2%. Samsung Electronics dropped 6.9%, and several members of the "Magnificent Seven" technology group also retreated after reaching record valuations. Economic data point to the scale of the current AI investment cycle. U.S. AI investment reached 11.33% of gross domestic product in the first quarter, according to the analysis cited, approaching the 11.49% peak recorded during the dot-com era. Meanwhile, real business fixed investment increased 5.5% last year, reflecting continued spending on AI infrastructure despite mounting concerns over future demand. Market Concentration Raises Bubble Concerns Several valuation metrics suggest investors are becoming increasingly concerned about concentration risk within U.S. equity markets. The Buffett Indicator, which compares total U.S. stock market capitalization with GDP, stood at approximately 236%, a level historically associated with elevated market valuations. At the same time, the 10 largest companies account for roughly 40% of total U.S. market capitalization, exceeding the 26% to 29% concentration seen during the peak of the dot-com boom. Nvidia remains one of the largest beneficiaries of the AI investment cycle, with a market capitalization of around $5 trillion, making investor sentiment toward AI infrastructure companies increasingly influential on broader market performance. Semiconductor Spending and Private AI Valuations Remain in Focus Some investors have warned that AI infrastructure spending may be outpacing sustainable demand. Investor Michael Burry, known for predicting the 2008 financial crisis, has questioned long-term returns on AI investments, citing the relatively short two-to-three-year replacement cycle for AI chips and significant insider selling among semiconductor companies. Memory manufacturers have also benefited from the AI boom. Companies including SK Hynix and Micron Technology have roughly tripled revenue over the past year as demand for high-bandwidth memory accelerated. However, new fabrication plants typically require at least three years to become operational, raising the risk of excess capacity if AI demand weakens before new production comes online. Meanwhile, private-market enthusiasm for AI companies remains strong. As reported earlier by IBTimes.sg, Anthropic has reached a reported valuation of $1.2 trillion, ahead of OpenAI's $908 billion, even as OpenAI is reportedly considering delaying its IPO until 2027. The contrast between rising private-market valuations and declining public-market share prices highlights a growing divide in investor sentiment. As public markets increasingly demand stronger earnings to support premium valuations, SpaceX's post-IPO performance has become a closely watched indicator of how investors are reassessing companies positioned at the intersection of AI infrastructure, advanced technology and long-term growth.
PsiQuantum has a plan to make a massive quantum computer out of light
The machine that could change the world will be housed in a room that looks like a data center crossed with an ice cream factory. Inside will be some 100 stainless-steel cabinets, each about six feet tall and connected to a supply of liquid helium that keeps them only a few degrees above absolute zero. Inside those cabinets will be hundreds of chips, and on those, thousands of particles of light flying through a maze of optical switches and beam splitters. Each photon must be accounted for, because precisely measuring where it ends up will help answer questions that current computers might take millions of years to solve. This computer, as described, does not exist. It's the brainchild of a company called PsiQuantum, founded in 2016 by four physicists from UK universities. In a crowded field of deep-pocketed competitors with similarly fantastical visions, the company aims to be first to fulfill its promise. In the years since the physicist Richard Feynman first envisioned them in 1981, quantum computers have promised to speed up everything from medical research to AI by harnessing the qualities of quantum particles. Unlike normal computer bits, which can be either a 1 or 0, quantum bits can exist in multiple states at once. And combining enough of those quantum bits together could produce a computer capable of tasks well beyond the reach of today's conventional machines. But even today's best quantum prototypes are too small and error-prone to do anything useful. That makes PsiQuantum's promises for what its computers will ultimately do all the more bold. Consider the company's hopes for predicting the effects of cytochrome P450 enzymes, which often break down drugs in the body. If pharma companies knew more precisely how they would work on a particular molecule, they could design more effective medications faster. Estimating this for a specific drug can take over 10 years with today's methods, says Philipp Ernst, vice president of quantum applications for PsiQuantum, but "we aim to get it down to four minutes." In a field full of such claims, PsiQuantum has attracted unusual investment and scrutiny for two reasons: It is one of the few companies aiming directly at building a large and useful machine, and it is already working with a major chip manufacturer to build its systems using existing semiconductor fabs. Its vision has attracted momentum: Last year, PsiQuantum raised $1 billion in funding and broke ground in Chicago on a site it's building in partnership with local governments. It also has a second site in the works in Australia, which it promises will be operational -- meaning hardware-ready -- in 2027. And it's one of just two companies (along with Microsoft) to reach the third stage of an intensive government evaluation program to see which quantum companies might succeed. Evaluating whether PsiQuantum will do what it says is harder than, say, judging a drugmaker by its clinical trial results: Advances in quantum computing are incremental, opaque, and tough to verify from the outside. But the company is now approaching its prove-it moment, when years of closed-door work and hundreds of millions in investment will either culminate in a useful quantum computer or fall short. We could start to know which as soon as next year. A new kind of machine Terry Rudolph, one of PsiQuantum's four founders, is soft-spoken and shaggy-haired. He was born in Malawi and learned only after earning his first physics degree that he is a grandson of the famed physicist Erwin Schrödinger. He later self-published a 150-page book to explain quantum computing to teenagers (my PR contact gave me a signed copy with a wink that said "We never expect anyone to actually read this," but I can report that it is a funny and helpful book). Around 2014, Rudolph and his cofounders became increasingly convinced that the quantum breakthroughs they were finding to be possible in theory might also be possible in a real machine. They eventually left their academic positions and divided the tasks before them: Rudolph worked on theory, Mark Thompson on engineering, Pete Shadbolt on scaling the technology up, and Jeremy O'Brien on articulating the vision and finding investors (O'Brien served as CEO until February; he's been replaced by Victor Peng, a veteran of the semiconductor industry). To understand why the quantum computer the company is building would be a big deal, consider how imprecise much of modern science remains. We cannot reliably predict, for example, which lithium-ion battery will catch fire or how quickly a critical aircraft component will corrode. This isn't just because these systems are complex, though they are. It's that, at their core, they are governed by quantum mechanics. Subatomic particles don't have well-defined properties -- this location and that velocity -- but instead occupy quantum states spread across many possibilities. And that in turn influences a range of atomic and molecular behavior. Schrödinger (Rudolph's grandfather, remember) showed how to describe this haziness mathematically a century ago this year, but precisely carrying out the calculations on real-world systems quickly becomes unfeasible even for the best computers. Scientists cope with this gap using approximations, imperfect simulations, or experiments on animals. PsiQuantum co-founder and chief scientific officer Pete Shadbolt (left), and machinery the company has built to manufacture its own barium titanate, a material with the perfect qualities for routing light particles (right). Feynman, David Deutsch, and other physicists in the 1980s wondered if we could do better. Maybe such complexity could instead be modeled using a new kind of machine. Rather than using transistors that are only ever on or off, this one would use particles held in quantum states, manipulate them to perform calculations, and then measure them at the end for an answer. Using quantum systems to simulate quantum systems would for the first time allow a simulation of physics and chemistry that directly reflected reality. It would be an invaluable tool for designing new drugs, materials, or really anything affected by quantum mechanics. Revolutionary, in other words. Humankind's leaps in understanding how nature works have often resulted in the invention of powerful new tools, Rudolph told me. "I don't think it's a coincidence that the Industrial Revolution coincided with our ability to calculate and simulate the laws of Newtonian mechanics, the laws of thermodynamics,...the laws of classical electromagnetism," he says. "Whenever we have more power to calculate and simulate and understand things, we build incredible machines that come from it." He sees something similar coming with quantum computers. Chasing photons One mystery has always been which quantum thing -- ions, atoms, or something entirely new engineered with quantum properties -- could be made stable and controllable enough to use as a qubit, the basic unit in the quantum computing world. Quantum systems are delicate, and observing any particular particle causes it to collapse into one state rather than a superposition of multiple states. If this happens during the computation rather than at the end, it produces an error that must be corrected for. Too many of these means the computer fails to produce a useful answer. Just as engineers in the early days of aviation weren't sure whether airplane wings would be fixed or flap like a bird's, we're not yet sure which of these quantum things will work best. Google and IBM are betting on superconducting qubits, superconducting circuits made of aluminum or other metals. Intel is using electrons. PsiQuantum is using photons, the particles that make up light. "Photons have lots of nice things going for them," Rudolph says. They can maintain quantum states for a long time; indeed, the photons in the universe's cosmic microwave background may have done so for billions of years. But photons also move fast and scatter easily. More importantly, two photons are more likely to pass through one other than interact. That makes them a challenging candidate for quantum computation, in which qubits need ways to influence one another. For a while, this last flaw seemed to doom the idea of quantum computing with light. But in 2001, researchers from the Los Alamos National Laboratory and the University of Queensland found a loophole. They discovered they could essentially fake interactions between photons by sending the light particles through a network of beam splitters and detectors. Their paper changed everything. PsiQuantum was created to make the theory a reality. Size was the first problem; previous plans would have required a computer as large as California. Mercedes Gimeno-Segovia, who was a PhD student of Rudolph's in the early 2010s (after almost becoming a professional violinist instead), thought of a way for the machine to be smaller. The basic process since then has been this: First create photons with lasers and then "entangle" them, exploiting a quantum phenomenon in which the particles no longer have individual states but instead share one. Next, route them through a maze of gates that perform computations, and finally read out details of their quantum state at the end, all while tracking and correcting for the errors that occur. Succeeding at each of these steps millions of times is not so much an engineering hurdle as a brick wall. And building the supply chain -- like manufacturing new materials with the qualities to route individual photons around -- is arduous. To get a sense of it all, last year I joined Shadbolt at the SLAC National Accelerator Laboratory, in Menlo Park, California. The center has helped produce several Nobel Prizes and played a role in the 1968 discovery of quarks, fundamental building blocks of matter that make up protons and neutrons. But PsiQuantum set up shop there essentially to siphon liquid helium from SLAC's giant cryoplant. This is what the company uses to cool its computing cabinets down to deep-space temperatures. Right now the cabinets operate at 2 K, or -456 °F, but the goal is to be able to run them slightly warmer -- at a balmy -452 °F. Most quantum approaches require the whole machine to be cooled to superconducting temperatures, so that much of the expense in running it will actually be spent on refrigeration. But photonic computers require only one piece to be this cold -- the detectors that measure single photons at the end of the computation. And the required temperature can be a bit higher. (PsiQuantum said in May that it will spend some of the $100 million award in CHIPS Act funding it's slated to get on these detectors). The siphoning setup was a temporary solution; PsiQuantum now has its own cooling system at its testing facility in Milpitas, California, and is setting up a larger one at its production site in Australia next year. These helium systems represent some of the biggest capital expenditures for any quantum company and will consume a significant chunk of PsiQuantum's $1 billion funding round. In the afternoon we drove to a lab in San Jose, where I donned a cleanroom suit -- a head-to-toe covering that keeps dust at bay -- to watch the manufacture of a blueish crystal called barium titanate. It's prized by PsiQuantum because it quickly and reliably routes light particles with very little electrical input, keeping the precious photons undisturbed as they move through the circuit. But for all barium titanate's theoretical value to the company, its structure makes it a pain to manufacture, and the material wasn't available at scale when PsiQuantum got its start. The company, in what Rudolph told me was an agonizing decision, opted to make it in-house, requiring a massive investment. I saw a technician -- operating at what looked like a giant pressure cooker -- adding the base elements to several hoppers; then I watched through a porthole as the elements got heated, vaporized, and finally crystallized into a thin layer on a wafer disc. At that time each disc took about 12 hours to make; the company now says several are produced each day. The discs then get shipped to the chipmaker GlobalFoundries in Malta, New York, where PsiQuantum's chips are made. The company has invested heavily in making its own barium titanate, a material whose delicate crystalline structure is tedious to manufacture. PsiQuantum's bet is that this entire supply chain, byzantine as it might sound, will make the company more efficient than its competitors. That's because, if you squint, it looks like a souped-up and high-precision version of the existing supply chain for silicon photonic chips, another type of technology that transmits information with light -- one that's already used in data centers. If PsiQuantum produces its chips at scale, it can take advantage of tools and infrastructure that already exist. But it's not a given that one working chip can easily be wired up to thousands more. That's why the company is testing in phases: Its Milpitas site has connected three cabinets together, with 250 chips in each, but the next step is to scale the systems up and see whether the company's techniques for correcting errors can keep up. Once the cooling system arrives at the Australian site late next year, the company says, it aims to connect about 100 cabinets together. Then PsiQuantum will work up to running the world-changing algorithms it has promised. The timeline for this, it's worth noting, is up for debate. News articles have said that 2027 is the year that PsiQuantum aims to have its first full-scale quantum computer come online at its Australian site, but the company insists the deadline has been misread, and that it only intends for its facility to be "operational" by the end of next year. That means cooling systems in place and ready for hardware to be installed, but no promises about what size computer will be ready. In an industry where timelines are perpetually in flux yet central to how companies are judged, that distinction isn't trivial. Into the unknown The outsider with perhaps the best guess of whether PsiQuantum will succeed is the Pentagon. The US Defense Advanced Research Projects Agency -- the Pentagon's research and development arm -- has been running an initiative to determine which of the boastful quantum companies might actually deliver. In the last year and a half, the heads of the program have been sounding more confident. Joe Altepeter, who ran the program until last year and proudly described himself as a "quantum skeptic," told me in March 2025: "I am more optimistic now than I have been at any point in the past 10 years." And in a statement earlier this year, his successor, Micah Stoutimore, said "it now seems likely that someone will build a utility-scale quantum computer by 2033," referring to a machine that generates more value from its calculations than it costs to build and operate. The program has been scrutinizing PsiQuantum's systems for over a year and putting them through the third stage of a benchmarking initiative meant to determine whether the technology will actually work. But to the rest of the industry, PsiQuantum is sort of a black box. "It is very hard for an outsider to evaluate," says Scott Aaronson, a theoretical computer scientist at the University of Texas at Austin who runs a popular blog that often covers the industry. Other companies, like Google and Quantinuum, have regularly published results over the years demonstrating chips and systems with incremental improvement, publicly laying the engineering groundwork needed to eventually build large machines. PsiQuantum has instead focused squarely on a commercial goal -- a computer with one million qubits, which is the scale that researchers expect to unlock research currently not possible on normal computers. PsiQuantum often differentiates itself with this industrial-scale goal, but IBM, which debuted a development road map in 2020, has been progressively building bigger and bigger systems. It initially targeted 2028 for a large-scale, error-corrected system, a deadline that now appears to have been pushed out to 2030. Making it useful On top of actually building the machine, a major focus for PsiQuantum is getting the rest of the world to develop a plan for how to use it. PsiQuantum has announced partnerships with customers including the defense giant Lockheed Martin, which intends to use it for materials design; the automaker Mercedes, which wants it for battery design; and the aerospace manufacturer Airbus. That these companies don't have a computer to experiment with is not a problem, according to Ernst at PsiQuantum. "There's a PlayStation 6 probably coming up from Sony next year or the year after, and people are programming those games right now," he says. "This is, in principle, very similar." (It's a glib analogy but not an entirely empty one; the quantum algorithms for solving a research problem can be cracked even if there is not yet hardware to run them on.) The idea is that experts in quantum information from both PsiQuantum and its customers will be able to translate design problems -- say, the requirements for a battery in a Mercedes electric vehicle -- into algorithms the computer could solve. The company offers a software package called Construct, which companies can use to design their own algorithms that might one day run on the computer. The future of quantum computing hinges on these algorithms. Quantum computers get painted as a speedup for everything, but in reality, they're suited to a subset of problems, and answering a question with this sort of machine requires the question to be formulated with very specific types of algorithms. People spend entire careers working on such algorithms, even if the computers to run them don't exist yet. At their core, they use the rules of quantum mechanics to manipulate probabilities in ways that ordinary computers can't. The most famous example, and a reason the government is so interested in quantum computers, is Shor's algorithm. It was developed in 1994 by the theoretical computer scientist Peter Shor and could effectively break many forms of encryption used online, for everything from credit card numbers to military intelligence. The thing keeping the world together, for now, is that nobody has a computer to run the algorithm on (and security experts are already launching new encryption methods that could withstand attacks from a quantum computer). PsiQuantum is researching how long its systems might take to run Shor's algorithm. PsiQuantum's chips are manufactured at GlobalFoundries in Malta, New York, and tested at company headquarters in California. Both PsiQuantum and GlobalFoundries have been awarded federal CHIPS Act funding. The company also published a paper in December in collaboration with Airbus, essentially seeing if a new algorithm developed by the authors could beat a classical computer in modeling fluid dynamics, like the turbulence around an airplane wing. Andrew Childs, an expert in quantum simulation, told me PsiQuantum achieved only a moderate speed increase over what today's computers can do. "It's probably unlikely that speedups like this will have a significant practical impact until we have very large-scale quantum computers," he said in an email. (When I asked Ernst, he agreed the improvement was modest.) Some of the algorithms PsiQuantum is working on are not expected to be perfected or even used in the first applications of its computer. Instead, its initial tasks might be more along the lines that Feynman envisioned way back in 1981: simulating the smallest particles of our world. The company's most significant research in this realm is in modeling quantum chemistry. Take those pesky P450 enzymes. More precisely understanding how they operate, PsiQuantum says, would allow for faster drug development and testing. Last year, PsiQuantum published methods for doing these sorts of chemistry calculations on a quantum computer, along with another paper demonstrating an algorithm that can simulate the collision of two molecules and estimate the likelihood of different outcomes femtosecond by femtosecond (there are one quadrillion femtoseconds in a second). It's a remarkable amount of detail not currently possible with today's technology, and it would allow drug and materials researchers to simulate new chemical interactions. Dominic Berry, who developed some of the core techniques used in the collision paper but isn't involved in PsiQuantum, says the company made impressive improvements, but to do the simulations scientists are most curious about would require the algorithm to be made even faster and PsiQuantum's early computer to have fewer errors than currently expected. Until PsiQuantum's computers are up and running, the breakthroughs that these research papers tease remain in the realm of theory. It's a space where Rudolph operates quite comfortably. He told me that Alan Turing created the theory of classical computing with pen and paper, imagining how the 1s and 0s would be represented in the machine, and how with the right approach to logic you could compute almost anything. "But there is no way that by hand, with a pen and paper, Turing was ever going to produce -- you know -- Minecraft and Facebook," he says. That took more than 70 years of tinkering (during which we fortunately created more useful things than Minecraft and Facebook). For all the time Rudolph spends dreaming up things quantum computers might do, in other words, people working on those problems are still stuck with pen and paper for now: "Until you have the actual machine in hand, you don't have the opportunity to really explore its potential."
Retail Investors Piled Into SpaceX While Dumping Tesla, Apex Data Shows - FinanceFeeds
SpaceX's long-awaited public listing became the defining retail investing story of the second quarter, attracting demand from every generation while triggering a broader rotation away from energy, commodities and Tesla toward the companies building artificial intelligence infrastructure. According to Apex Fintech Solutions' Q2 2026 Investor Pulse report, the newly listed SpaceX generated approximately $1.25 billion in net buying across nearly 2.2 million trades after its 12 June market debut, making it the largest net purchase of the quarter by a considerable margin. At the same time, retail investors aggressively accumulated memory-chip manufacturers while reducing exposure to many of the year's strongest-performing commodity and energy stocks. The report provides one of the broadest snapshots of U.S. retail investor behaviour, drawing on trading activity across millions of brokerage accounts supported by Apex's clearing and custody infrastructure. SpaceX Became The Quarter's Biggest Retail Trade The public debut of SpaceX proved to be more than another high-profile IPO. According to Apex, the company immediately entered the Top 25 holdings across all four investor generations, a rare achievement for a newly listed stock. SpaceX ranked 13th among Gen Z investors, 15th among both Boomers and Gen X, and 16th among Millennials. It also quickly became one of the ten most widely held stocks among Boomers. In total, the stock attracted around $1.25 billion in net buying across almost 2.2 million trades, nearly doubling the second-largest net purchase recorded during the quarter. Apex Chief Executive Bill Capuzzi said the listing demonstrated that demand extended well beyond younger retail traders. "The SpaceX listing answered it. In a matter of weeks, it became the largest net buy of the quarter and a new top holding for Boomers and Gen Z alike. That demand wasn't generational -- it was cross-generational." Retail Investors Rotated Into AI Infrastructure While SpaceX dominated trading flows, the report suggests the broader investment theme during the quarter centred on artificial intelligence infrastructure rather than AI software. Micron became a top-five holding across every generation after climbing seven to eight positions in portfolio rankings. SanDisk and Western Digital also recorded strong buying, while Intel and Marvell ranked among the largest net purchases during the quarter. Rather than concentrating on a handful of mega-cap technology companies, retail investors broadened their exposure across the semiconductor supply chain, particularly businesses expected to benefit from rising demand for memory and AI computing infrastructure. The trend also appeared in generational preferences. Younger investors expressed the AI theme through higher-growth names such as Rocket Lab, Nebius and AST SpaceMobile alongside SpaceX, while Boomers favoured established semiconductor companies and large-cap industrial and financial stocks including Caterpillar, ExxonMobil, Eli Lilly and JPMorgan Chase. Tesla Became Retail's Biggest Source Of Funding One of the report's most notable findings is what investors sold to finance those purchases. Tesla recorded the largest net selling activity of any stock during the quarter despite remaining one of retail investors' most widely held companies. Investors also reduced positions in many of the energy and commodity stocks that had benefited from geopolitical tensions earlier in the quarter, including Chevron, ConocoPhillips, Newmont and silver-related investments. According to Apex, the pattern suggests retail investors were not indiscriminately buying AI stocks but actively reallocating capital away from sectors that had already outperformed. "Retail didn't just chase the AI trade; it funded it, selling the commodity and energy winners from the spring and trimming Tesla while leaning into memory and infrastructure," said Mike Treacy, Vice President of Risk at Apex Fintech Solutions. The Rotation Mirrors A Changing Market Narrative The quarter began with heightened geopolitical uncertainty following conflict involving Iran, which drove oil prices sharply higher and initially favoured energy producers, commodity companies and defensive assets. As markets recovered and equity indices returned to record highs, investor attention shifted back toward long-term structural growth themes, particularly artificial intelligence and semiconductor infrastructure. Memory-chip manufacturers emerged as some of the largest beneficiaries of that change in sentiment as investors increasingly viewed memory capacity as a critical bottleneck for next-generation AI systems. The report suggests retail investors participated in that rotation with unusual discipline, systematically reducing exposure to previous winners rather than simply adding new technology positions. What It Means For Future IPOs For investment banks and private technology companies, the success of SpaceX's listing could prove equally significant. According to Apex, the IPO demonstrated that blockbuster private companies can attract sustained demand across every demographic rather than relying primarily on younger, speculative investors. That could strengthen expectations for future listings involving large artificial intelligence companies and other late-stage private technology businesses. Capuzzi specifically pointed to the possibility of future listings by companies such as Anthropic and OpenAI, suggesting the SpaceX experience may reshape expectations for how retail investors engage with major technology IPOs. Why This Matters The second quarter illustrates how quickly retail investor preferences can shift as market narratives evolve. Rather than simply chasing momentum, Apex's data suggests investors actively recycled capital from geopolitical winners into businesses positioned to benefit from the long-term expansion of artificial intelligence infrastructure. SpaceX's immediate success also demonstrates that retail investors remain willing to commit significant capital to high-profile technology listings, potentially providing a favourable backdrop for the next generation of AI-focused public offerings.
SpaceX gets green light for Starship's next test flight following mishap probe
'Erroneous engine alarm system settings also contributed to the return failure, and Super Heavy plunged into the Gulf of Mexico at high speed, said FAA' On Monday, the US Federal Aviation Administration took a significant step by closing its review into a SpaceX Starship's booster malfunction that occurred during a test flight last month, paving the way for SpaceX to officially launch the rocket's next test flight from Texas. The test flight of SpaceX's Starship rocket launched on May 22 marked the 12th test since 2023. This new version is anticipated to be the focal point of Musk's launch business, satellite ambitions and efforts to put astronauts on the moon. After the Starship upper stage accelerated into space on a non-orbital flight that ended up in the Indian Ocean, the Super Heavy booster made an unsuccessful attempt to execute a controlled soft landing in the Gulf of Mexico. Notably, SpaceX has made procedural alterations to address the interconnected causes. In this connection, the FAA said: "Erroneous engine alarm system settings also contributed to the return failure, and Super Heavy plunged into the Gulf of Mexico at high speed." The company is gearing up for another Starship test launch from its Starbase facility in Texas on Thursday. Similarly, like the last flight, SpaceX hopes to return Super Heavy to the Gulf of Mexico waters and the Starship spacecraft to the Indian Ocean after a roughly hour-long flight through suborbital space. For the first time, the 13th Starship flight will deploy actual Starlink V3 satellites, building on previous tests that focused on validating orbital positioning and deployment mechanisms. SpaceX is all set to roll out Starlink V3 satellites aboard launch vehicles by the end of this year-a long -awaited breakthrough as the program has fallen years behind Musk's initially projected timelines despite over $15 billion in crucial spending on the rocket's development to date.
Anthropic reveals why Claude gives different answers in Hindi and English
Anthropic has unveiled new research showing that Claude's behaviour changes depending on both the AI model and the language used. Based on more than 3,00,000 anonymised conversations, the study identifies four behavioural dimensions that could help explain why users in different languages experience the chatbot differently. As artificial intelligence systems become increasingly central to work, education and decision-making, ensuring they behave consistently across users has emerged as a growing challenge. Anthropic's latest research suggests that consistency is far more complex than simply translating responses into different languages. The AI company has published a new analysis examining how its flagship chatbot, Claude, expresses different values depending on the model being used and the language in which users interact with it. Drawing on more than 300,000 anonymised conversations, the study introduces a framework that measures subtle behavioural differences across Claude's responses, offering fresh insight into how AI systems adapt -- or drift -- across cultures and product versions. According to Anthropic, these patterns do not necessarily indicate that Claude holds different beliefs. Instead, they reflect variations in how the assistant communicates, balances competing priorities and responds to users in different contexts. Four behavioural dimensions shape Claude's responses Anthropic's researchers identified four recurring dimensions that explain a significant share of the behavioural variation across Claude's responses. The first, Deference vs. Caution, measures whether the assistant tends to accommodate a user's request or prioritise warning against potential risks. Warmth vs. Rigor captures the balance between empathy and encouragement on one hand, and factual precision and critical evaluation on the other. The remaining two axes focus on communication style. Depth vs. Brevity reflects whether Claude expands on a topic beyond what was explicitly requested, while Candour vs. Execution measures the extent to which the chatbot acknowledges uncertainty instead of delivering polished, confident answers. Anthropic says these four dimensions account for roughly 15% of the observable variation in Claude's expressed values across conversations, providing a structured way to compare behavioural differences between models and languages. The framework also appears to align with how users already perceive Claude's different model families. Sonnet 4.6, for example, consistently displayed greater warmth and a stronger tendency to affirm users, while Opus 4.7 was more likely to prioritise accuracy, challenge assumptions and introduce caution when discussing potentially risky topics. Language plays a surprisingly large role One of the study's most striking findings is that Claude's behaviour changes noticeably depending on the language used during a conversation. Among the 20 most common languages on Claude.ai, the largest differences emerged along the Warmth vs. Rigor and Candour vs. Execution dimensions. Conversations conducted in Hindi and Arabic tended to feature more supportive, encouraging and emotionally expressive responses. By contrast, English and Russian interactions more frequently emphasised analytical reasoning, correction of inaccuracies and requests for supporting evidence. Other patterns also emerged. Claude showed its greatest level of deference when responding in Arabic, whereas English conversations leaned more towards caution. English interactions also tended to produce more detailed explanations, while Arabic responses were generally more concise. Dutch conversations displayed greater openness about uncertainty, whereas Indonesian responses more often focused on confidently completing the requested task. Anthropic argues that these differences are likely influenced by several factors, including variations in multilingual training data and broader linguistic and cultural norms. The company notes that previous evaluations had already identified differences in how Claude handled knowledge and sensitive requests across languages, making value expression a logical area for further investigation. The implications extend beyond academic research. Anthropic points to a hypothetical example in which two users ask Claude to review the same business proposal, one in Hindi and another in Russian. Even if the underlying assessment remains similar, the framing could differ enough to leave each user with a different impression of the proposal's quality. Why the findings matter The research arrives as Anthropic rapidly expands Claude's presence across enterprise platforms including Amazon Bedrock, Google Cloud and Microsoft's AI ecosystem, where businesses increasingly expect predictable behaviour regardless of geography or language. Understanding these behavioural shifts could help developers evaluate whether differences reflect appropriate cultural adaptation or inconsistencies that require further training. It may also provide a more systematic way to measure changes introduced through future model updates. The timing is significant for Anthropic itself. The company has experienced rapid growth in recent months, securing a $65 billion funding round in May 2026 that valued the AI laboratory at $965 billion. Its latest models, including Claude Opus 4.8 and Mythos-class Fable 5, have positioned the company among the industry's leading developers in reasoning and autonomous AI capabilities. A new tool for building trustworthy AI Anthropic says the value-axis framework is intended to become more than a research exercise. Future work will examine how these behavioural differences affect user trust, decision-making and overall satisfaction, while also exploring whether training techniques or system prompts can produce more consistent outcomes across languages. The findings also contribute to a broader debate surrounding responsible AI deployment. As regulators and enterprise customers place greater emphasis on transparency and fairness, developers are under increasing pressure to demonstrate not only what their models can do, but also how they behave in different contexts. Rather than aiming for identical responses across every language, Anthropic's work highlights the more nuanced challenge facing modern AI developers: creating systems that remain culturally responsive without compromising consistency, reliability or shared ethical standards.
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Polymarket prices BTC above $52K at 99.95% as seized-coin transfers watched
Polymarket Reprices the July 16 BTC Ladder After Seized-Crypto Transfers to Coinbase Prime Polymarket's July 16 Bitcoin price ladder is still pricing a high-probability floor scenario, with the $52,000 strike at 99.95% (about $288,204 traded). The catalyst traders are watching is a report that U.S. government-linked wallets moved seized BTC and ETH to Coinbase Prime, and the ladder shows where the market draws the line between "noise" and a meaningful sell-pressure risk. Key Takeaways * Polymarket implies Bitcoin is above $60,000 on July 16 at 91.5% (Yes 91.5% / No 8.5%), while above $64,000 is only 20.5% (Yes 20.5% / No 79.5%). * The government-to-exchange transfer headline is being treated as limited near-term downside in this market: low strikes remain near-certain while higher strikes stay heavily discounted. * Resolution is set for 2026-07-16 16:00:00 UTC; the market's 24h and 7d summary changes are both 0.0, signaling stable pricing into the settlement window. A report says U.S. government-linked wallets moved about $288 million in seized bitcoin and ether to Coinbase Prime on Monday, with BTC routed through new intermediary wallets while ETH went directly. The transfers appear to conflict with a prior no-sell reserve order for seized bitcoin, though the moves could also reflect custody or internal staging rather than a confirmed sale. Odds & Liquidity Snapshot: $288K Traded With $60K at 91.5% and $64K at 20.5% on the Strike Ladder This is a price-ladder contract, so each row is its own binary: "Yes" means BTC is above that strike at resolution, and "No" is the complementary outcome -- not a single bet on a specific final price. The ladder's shape shows where traders think the distribution sits for July 16: above $60,000 is priced at Yes 91.5% / No 8.5%, above $62,000 at Yes 64.0% / No 36.0%, and above $64,000 at Yes 20.5% / No 79.5%, while tail outcomes like above $68,000 are only Yes 0.35% / No 99.65%. With about $288,204 in volume and a flat historical summary (24h change 0.0, 7d change 0.0; low volatility; stable consensus), the market is signaling limited disagreement and little need to reprice the near-certainty lower strikes (e.g., $56,000 at Yes 99.65% / No 0.35%) despite the exchange-transfer headline. The contrast that matters here is speed and granularity: instead of a single "bullish vs bearish" narrative, Polymarket continuously prices a probability curve across strikes, making it clear that traders are far more confident about staying above mid-$50ks than about breaking into the mid-$60ks by the resolution timestamp. Watch whether the mid-strikes tighten or gap: if the market starts assigning more weight to downside risk, you would expect the biggest sensitivity at $60,000 and $62,000 (where Yes/No are not near 100/0), rather than at $52,000-$58,000 which are already priced as near-certain. Also track whether volume concentrates around one or two strikes ahead of 2026-07-16 16:00 UTC, which can signal where traders think the true "line" for settlement risk sits. What Traders Watch Next on Polymarket: Macro and Crypto Contracts That Can Shift BTC Ladder Probabilities Beyond this July 16 ladder, traders often sanity-check nearby time windows and broader range contracts to see whether the rest of Polymarket is pricing the same distribution. Big activity is sitting in "What price will Bitcoin hit in July?" (100.0% on ↑ 62,500; $8,269,859 volume) and the longer-dated "What price will Bitcoin hit in 2026?" (100.0% on ↓ 60,000; $47,335,043 volume), while adjacent expiries like "Bitcoin above ___ on July 15?" (99.95% on 52,000; $338,073 volume) can highlight any day-to-day drift. For cross-asset context, "What price will Ethereum hit in July?" (100.0% on ↑ 1,800; $1,855,906 volume) and the weekly band "What price will Bitcoin hit July 13-19?" (56.5% on ↑ 64,000; $322,292 volume) show where traders think follow-through risk sits across the broader crypto tape. Odds Trend By the Numbers * Platform: Polymarket * Market: Bitcoin above ___ on July 16? * Contract type: Price strike ladder: each rung has separate Yes/No; Yes means the spot price is above that USD strike at settlement. * Resolution window: Jul 16, 2026 (UTC) * Status: Active (open for trading) * Volume: ~$288,204 Top strike rungs +7 more strikes not shown
SpaceX Stock Plunges to All-Time Low After Competitor Makes Major Leap
Shares of Elon Musk's SpaceX took another beating when trading resumed on Monday, sliding to an all-time low of just under $139, well below its IPO opening price of $150. It's now over 38 percent down from its all-time high of $225 three weeks ago, illustrating how rapidly the hype has inverted into widespread skepticism over Musk's vision. Following a blockbuster Wall Street debut, the space company has struggled to maintain any degree of momentum as investors continue to ask some very hard questions, including over its major pivot to orbital data centers and its near-term profitability. Despite being valued at almost two trillion dollars, the company lost nearly $5 billion last year. Shares have hovered below the company's opening price for weeks now, despite plenty of bullishness among analysts. The news comes just days after Chinese state-run media showed a Long March 10B rocket booster being caught by an offshore recovery platform, indicating the country was making major strides in catching up with SpaceX's reusable rocket tech. Over the weekend, an experimental Japanese reusable rocket safely took off and landed, suggesting the nation may be right behind China as well. Beyond some steepening international space launch competition, experts believe SpaceX's transformation into an "AI play" may be closely related to its Wall Street woes, as the BBC reports. "Everyone saw SpaceX as an AI story," CFRA investment research analyst Keith Snyder told the broadcaster. "With Elon Musk, any company he touches gets people excited," he added. "But this was also the first time people felt like they were able to invest in something that was being marketed as an AI play." How SpaceX will cover its enormous losses and start actually making some money -- not to mention, prove that orbital data centers don't just make sense but are even feasible to begin with -- remains a major point of contention. In short, the initial enthusiasm surrounding SpaceX's IPO is firmly behind us. "If you bought around the first tick you're definitely underwater," Snyder told the BBC. "It started to look a lot like a meme stock." "If you're an IPO investor, you're ok," Mergermarket analyst Samuel Kerr added. "If you bought in the first few days, you're not very happy right now." Investors remain sharply divided on where SpaceX shares are headed next. Many analysts from major investment banks remain bullish, expecting the stock to make massive gains. Case in point, Morgan Stanley believes the company will reach a price tag of $300 -- far more than double its current stock price.