CASHCAT drops 30% following its listing on Robinhood, with one trader holding on despite an unrealized loss of $412,000 and has not sold yet.

Google has agreed to acquire certain corporate data from bankrupt airline Spirit Airlines for $10 million to improve its products and AI models. The data includes internal emails, Microsoft Teams chat logs, calendars, spreadsheets, booking and frequent flyer records, as well as marketing, productivity, operations and employee human resources data. Spirit stated that the data delivered to Google will be anonymized to remove personally identifiable information. The deal faces competition: AI data firm Mercor previously bid $7.5 million for the same set of data. The transaction still requires approval from a U.S. bankruptcy court, with U.S. bankruptcy judge Sean Lane scheduled to review it on Wednesday local time. Spirit Airlines ceased operations in May this year and is selling its remaining assets through bankruptcy proceedings. As AI companies ramp up demand for high-quality training data, internal corporate business data is emerging as a new type of data asset for AI model training and product optimization.

Bitcoin’s recent volatility has dropped to multi-year lows, with its 30-day realized volatility standing at around 42%, compared to the S&P 500’s roughly 18% — marking the narrowest gap in volatility between the two assets on record. The market is stuck in a stalemate between buyers and sellers: sell-offs by corporates and mining firms cap upside gains, while deleveraging and ongoing accumulation by long-term holders limit downside declines. As Bitcoin’s volatility eases, some short-term traders have shifted their risk appetite to assets like AI stocks, tokenized equities, stock perpetuals, and prediction markets. A NYDIG study notes that short-term traders tend to chase volatility, narrative momentum, and upside potential, with “traders targeting 5x or 10x returns” now having options including Bitcoin, Nvidia, gold, stock perpetuals, 0DTE options, and sports event contracts. Data shows that monthly trading volume of traditional asset perpetuals on crypto platforms has surged more than fivefold from $52 billion in January to $268 billion in June. Meanwhile, South Korean retail traders have clearly shifted from cryptocurrencies to AI-related stocks, with trading volumes on major South Korean crypto exchanges falling by up to around 80% year-over-year. CoinDesk points out that the Bitcoin market is currently more like in a “dormant” state, with falling trading participation, shrinking market depth, and regulatory uncertainty combining to suppress volatility. If U.S. crypto regulation makes substantial progress, the macro environment shifts, or a new market narrative emerges, the current low-volatility regime could be broken, and thinner liquidity may further amplify price swings.

NVIDIA has released a technical blog announcing that its cuML and cuVS libraries now support multi-GPU UMAP functionality, enabling distributed execution of dimensionality reduction for large-scale vector data across multiple GPUs—significantly cutting runtime while preserving embedding quality. NVIDIA noted that during tests on the MIRACL dataset (containing 106 million vectors, totaling ~870GB) run on a DGX system equipped with 8 H100 GPUs, cuML’s multi-GPU UMAP completed end-to-end processing in just 8 minutes, delivering up to 74x speedups over projected CPU-based implementations. Prior CPU-based solutions failed to process the full dataset even with 2TB of memory. The approach works by partitioning data into multiple clusters, building local k-nearest neighbor (kNN) graphs in parallel across different GPUs, then merging these into a global graph, thereby overcoming the memory constraints of a single GPU. NVIDIA added that this technology can reduce hundreds-of-GB UMAP tasks that previously took hours or even days to process down to just minutes.

Market sources say Anthropic is asking lead banks to provide around $1.25 billion each in loans, while other major participating banks are expected to contribute roughly $1 billion apiece. Separately, reports indicate the credit line Anthropic aims to raise ahead of its IPO could exceed its $10 billion target.

According to Axios reporter Alex Isenstadt, the White House plans to co-host an event with President Trump tomorrow, with several tech industry leaders in attendance. White House sources noted that prediction market firms have not been invited to the event and will not participate. BlockBeats previously reported that on August 15, insiders disclosed that U.S. President Trump is expected to attend a crypto industry innovation conference at the White House next week, where he will hold discussions with executives from multiple crypto firms, as well as heads of prediction market and AI companies. Attendees of the conference include leaders from firms such as Coinbase, Ripple, Gemini, Robinhood, Polymarket, and Kalshi. All these executives are members of the newly established Innovation Advisory Committee of the U.S. Commodity Futures Trading Commission (CFTC). Sources said the conference is scheduled to take place at the Eisenhower Executive Office Building adjacent to the White House, aiming to hold policy dialogues around innovative fields including U.S. fintech, crypto assets, prediction markets, and artificial intelligence. CFTC Chairman Mike Selig and other government advisors are also expected to attend, while Treasury Secretary Bessent and Commerce Secretary Lutnick may be present.

Tesla plans to publicly unveil its Cybercab, a driverless taxi, in Austin, Texas, U.S. as early as this month. The vehicle features a steering-wheel and pedal-free design, with Tesla employees already testing the fully driverless version on private roads within the company’s campus. Reports note that Cybercab runs on Tesla’s FSD (Full Self-Driving) software, though its autonomous driving capabilities and safety remain under scrutiny. The U.S. National Highway Traffic Safety Administration (NHTSA) is still investigating Tesla’s FSD for traffic rule compliance issues, while existing Robotaxi services in some markets still have human safety drivers on board. Cybercab is designed to operate without in-vehicle personnel intervention; Tesla plans to use remote operators to handle emergencies and has started integrating Starlink connectivity into the vehicles. Data scale is another concern. Tesla stated in July that it needs to accumulate dedicated driving data for Cybercab. To date, Tesla’s unsupervised Robotaxis have logged around 380,000 miles across six cities, while Waymo has completed over 220 million miles of fully autonomous driving on public roads since 2020. Additionally, Cybercab’s lack of traditional driving controls may face restrictions under U.S. federal vehicle safety regulations. It remains unclear whether Tesla is seeking regulatory exemptions, according to reports. The Verge points out that as Cybercab’s launch approaches, there remains significant uncertainty regarding the autonomous driving safety and regulatory approvals required for its commercial operation.