Bitcoin ETFs see $10.49M inflow, but Ethereum ETFs suffer $64.22M outflow in latest trading

According to market data from BIT (Bit.com), US crypto-related stocks have turned from losses to gains, with the following performance: MSTR up 2.04%, COIN up 2.08%, CRCL up 0.91%, SBET up 0.93%, BMNR up 1.01%, HOOD up 0.34%, and ABTC up 6.73%.

According to market data from BIT (Bit.com), U.S. AI software stocks remain active. Palantir (PLTR.US) rose over 1% to hit a new high, while ServiceNow (NOW.US), Shopify (SHOP.US), and Salesforce (CRM.US) gained more than 3%. SAP SE (SAP.US), Snap (SNAP.US), and Workday (WDAY.US) each climbed over 1%. On the news front, Bank of America Securities upgraded Salesforce’s rating from Underperform to Buy, sharply lifting its target price from $160 to $285. In its report, BofA noted that although revenue directly tied to AI still accounts for a small share, it is optimistic about the long-term prospects of the company’s enterprise AI. Additionally, Ben Schneider, chief U.S. equity strategist at Goldman Sachs, and TMT expert Pete Callahan pointed out that the AI investment narrative is shifting from semiconductor capital expenditure to application-layer areas such as the "inference economy" and personal agents. Callahan bluntly stated that "programming AI is no longer a market secret", adding that the market is urgently searching for the next major AI story.

Beating AI News (from Dongcha) – AMD today announced the launch of the AMD Helion Agent AI Rack Solution. Built on an open infrastructure design compliant with Open Compute Project (OCP) specifications, the solution is engineered to meet the computing power demands of large-scale AI agent tasks, supporting flexible combinations of CPUs and GPUs. It offers two primary configurations: The first is a CPU-only rack powered by 6th Gen AMD EPYC processors, supporting up to 32,768 CPU cores, designed for hyperscale deployments, providing dedicated computing power for agent tasks and connecting to separate model inference infrastructure. The second is an integrated rack combining AMD EPYC CPUs, AMD Instinct MI350P GPUs, and general-purpose compute nodes, targeted at enterprise-grade agent AI applications. AMD states that Helion supports both liquid and air cooling configurations, allowing customers to adjust CPU and GPU resources based on their workload, performance, power consumption, and cost needs. The solution also integrates open-source software and hardware plus a built-in token router, enabling the distribution of agent model calls to both frontier and open-source models. AMD plans to submit the Helion specifications to the OCP for further community development and adoption. Currently, the solution is being developed in collaboration with ecosystem partners, with a launch scheduled for November 2026.

Beating AI News: Nicolas Bustamante, head of Microsoft’s proactive AI Agent team, predicts AI streams will become the mainstream interaction method by 2027. Chat-based models leave too much work to users—requiring them to figure out AI’s capabilities, write prompts, provide context, and repeatedly direct agents. For billions to use agents daily, not everyone can be expected to master these tasks. Bustamante’s envisioned AI stream works like an auto-updated to-do list: AI drafts emails needing responses; when sales data refreshes, team reports are prepped. Users browse it like social media, approving, editing, or ignoring items, only turning to chat for complex issues. Meta’s Muse already proactively suggests and executes tasks. The model also has commercial logic: as users open the stream daily, AI recommends restaurants, goods or services based on their plans, with clearly labeled ads covering the agent’s operational costs.

According to monitoring by AI Aunt, a crypto whale address swapped its UBTC holdings for 16,704.47 ETH over the past 22 hours, worth approximately $42.46 million, at an average purchase price of around $2,541.89.

According to BIT (Bit.com) market data, Microsoft’s stock price hit a near one-year high, rising 0.8% intraday. On the news front, Microsoft plans to gradually increase the use of its self-developed AI chips in data centers to reduce reliance on NVIDIA GPUs. Microsoft stated that it will mainly rely on its self-developed Maia chip architecture to handle AI model requests in the future, and plans to deploy several gigawatts of computing power on the Maia series chips. Microsoft unveiled its third-generation AI accelerator chip, the Maia 300, on Monday, which is expected to enter production in 2027. Each data center rack can hold 96 Maia 300 chips, double the number of the previous-generation Maia 200; compared with GPUs, its AI token processing capacity per rack can reach up to 7 times higher, and the number of tokens processed per megawatt increases by approximately 40%. Microsoft said the Maia 300 is expected to boost AI service performance and lower data center operating costs. Evercore ISI analysts forecast that by the first quarter of 2027, Maia chips will account for around 10% of Microsoft’s AI chip spending.