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Microsoft Corporation is an American multinational technology company that produces computer software, consumer electronics, personal computers, and associated services.
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Google fires shots in the AI chip "ground war": Recruiting new cloud providers to reduce reliance on NVIDIA
Google is mounting a competitive offensive against NVIDIA in the AI chip market, attempting to expand the commercial application of its self-developed Tensor Processing Units (TPUs) to challenge NVIDIA's long-standing dominance in the AI computing market.Google is currently both a significant customer of NVIDIA's AI server chips and is also developing its own AI chip business to compete with and potentially replace NVIDIA's GPUs. Previously, almost all Google TPUs were deployed in its own data centers, with usage available to customers only through Google Cloud rental services.However, starting this year, Google has changed its strategy, planning to sell TPU chips to emerging cloud service providers (Neoclouds). These new cloud service companies primarily focus on providing AI computing resources and represent a key customer segment driving the demand growth for NVIDIA GPUs.Analysts believe that this move by Google signifies TPU's transition from internal specialized infrastructure to a broader commercial chip platform. By enticing Neoclouds to adopt TPUs, Google aims to reduce AI companies' reliance on the NVIDIA GPU ecosystem and expand its own influence in the AI infrastructure field.NVIDIA currently dominates the AI chip market with its CUDA software ecosystem, high-performance GPUs, and vast developer network. As major tech companies like Google, Amazon, and Microsoft continue to advance their self-developed AI chips, competition in the AI computing market is shifting from a single GPU supply model to a diversified chip ecosystem battle. (The Information)
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Morgan Stanley: AI Capex to Reach $1.4 Trillion in 2028
According to TechFlow Research, Morgan Stanley's July 10 report projects that in 2028, the combined capital expenditure of the five major hyperscalers—Microsoft, Google, Amazon, Meta, and SpaceX—will reach $1.4 trillion, a more than threefold increase from 2025 levels; available compute capacity will expand from 30GW to 120GW. Meta is listed as the top pick, with 2027/2028 Capex raised to $225 billion/$250 billion. Morgan Stanley particularly emphasizes Meta's API business opportunities: Muse Spark 1.1 pricing is 30%-86% lower than peers, and every 100MW of compute capacity can generate approximately $8 billion in revenue and approximately $1.9 per share in EPS increment. The deciding factor in the compute race is shifting from "how much to build" to "how much to sell," as Meta simultaneously holds five monetization paths. Morgan Stanley maintains an Overweight rating on Meta, Amazon, and Google.
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JPMorgan: Software Profits Are Shifting from Model Layer to Infrastructure
According to TechFlow Research, a July 13 report from JPMorgan pointed out that Starbucks building its own AI tools to replace Microsoft and IBM software, Microsoft using its self-developed MAI to replace OpenAI and Anthropic models, and Meta developing cloud business to sell AI compute collectively illustrate a trend: the software profit pool is shifting downstream from the model layer. DigitalOcean's Q2 remaining performance obligations exceeded $800 million, a 10-fold year-over-year increase, with AI inference already accounting for a significant portion; over half of Cloudflare's requests originate from AI agents, and it launched a crawler paywall to open new revenue sources. Morgan Stanley believes model providers face pressure of being replaced, infrastructure layer demand remains strong but the structure is changing, enterprise customers' bargaining power is rising, and investment logic needs to shift from "model as winner" to "infrastructure and intermediary layers".
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Gate Pre-IPOs Second Phase Launches OpenAI (OPENAI), Supporting Dual Token Participation with USDT and GUSD
: Digital asset trading platform Gate has announced that it will open subscriptions for the second phase of its Pre-IPOs project, OpenAI (OPENAI), from July 15, 2026, 15:00 to July 17, 2026, 15:00 (UTC+8), supporting participation with both USDT and GUSD. The total subscription value for the project is approximately $20 million, with 27,700 OPENAI asset certificates issued at a price of 1 OPENAI = $722. The minimum investment is 100 USDT or 100 GUSD, with implicit handling fees and custody costs waived. OpenAI, driven by products like ChatGPT, is advancing generative AI development and has received investments from Microsoft and others, with an implied market valuation of approximately $895 billion.The OPENAI asset certificate is a pre-IPO mirror note for OpenAI, designed to reflect the company's value before and after its public listing. Gate will hedge its exposure by acquiring the corresponding stocks and will offer pathways including pre-market trading, long-term holding, and future conversion into underlying stock assets, stock tokens, or USDT. Allocations are calculated based on the "average hourly locked amount"; the earlier the participation and the longer the lock-up period, the higher the weight. The certificates will be unlocked in three phases on July 17, August 17, and September 17, with pre-market trading opening on July 20. Concurrently, Gate is launching VIP/Super Agent airdrops, GT rewards, and a 3.8% annualized GUSD minting yield. Furthermore, Gate has already introduced Pre-IPOs, IPO Access, Gate Stocks, and gStocks, covering US, Hong Kong, and Korean stocks, encompassing over 12,500 stocks and ETFs, and will continuously expand its global asset ecosystem, including ETFs and RWAs. Gate will continue to bridge traditional finance with on-chain assets, providing global users with a more open, efficient, and one-stop investment service.
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Serenity: OpenAI’s Strategy to Build an Independent Ecosystem Has Made the Magnificent Seven Uneasy
Serenity, known as the “White-Haired Stock Guru,” stated on X that if Sam Altman and OpenAI are angering the “Magnificent Seven” (Mag7), including Apple, it precisely proves they are doing the right thing. Currently, OpenAI has chosen to build its own ecosystem rather than being absorbed into the systems of other tech giants. This strategic direction is worth noting. Since the rise of tech giants like Google, Apple, and Microsoft, the market has not seen a true disruptor in a long time, and OpenAI is emerging to fill that role.
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Federal Reserve Announces Leadership and Objectives of Five Major Monetary Policy Task Forces
According to the Federal Reserve's official website, Federal Reserve Chair Kevin Warsh announced on July 9 the establishment of five monetary policy task forces, led jointly by external economists, business leaders, and former central bank officials, operating independently and providing research results to the Federal Open Market Committee (FOMC). The research directions of the five task forces are as follows: • Communication Mechanism: Led by former Governor of the Bank of England Mervyn King and others • Balance Sheet Policy: Led by Harvard University Professor Karen Dynan, University of Chicago Professor Raghuram Rajan, and others • Quality of Economic Data: Led by Harvard University Professor Raj Chetty, former Walmart CEO Doug McMillon, and others • Productivity and Employment: Led by a16z Co-founder Marc Andreessen, Microsoft Xbox CEO Asha Sharma, and others • Inflation Framework: Led by Harvard University Professor and former Chairman of the Council of Economic Advisers Greg Mankiw, Nobel Laureate in Economics Thomas Sargent, and others Warsh stated that the Federal Reserve's commitment to price stability and maximum employment is unwavering, and these task forces aim to evaluate and optimize policy tools and analytical methods to address the current important economic situation.
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Polymarket new: "Will the US government revoke public access to another major AI model?"
The PPP Prediction Market tool monitors that Polymarket has listed a new event: "Will the US government revoke public access to another major AI model?" The current probability is reported at 33%.The settlement rules state: If the US federal government, by the end of 2026, passes relevant legislation, issues an executive order, implements export controls, or takes any other action that substantially restricts US public access to a major AI model, the market outcome will be "Yes." Otherwise, the outcome will be "No." A "qualifying action" refers to a formal measure taken by the US government, the effect of which is equivalent to completely prohibiting the public from accessing a specific AI model within the United States. Furthermore, the settlement rules emphasize that regardless of the action's true purpose or nominal goal; if the action effectively results in the public being unable to access the model within the US—for example, prohibiting the model from being provided to foreign citizens or governments, as long as the general public cannot access the model through conventional channels within the US—it meets the qualification requirements. Merely excluding access to the model from a single channel is insufficient. Removals of public access that are not caused by any formal action of the US government are not eligible."Mainstream AI model" refers to the flagship, general-purpose large language model or multimodal foundation model developed by one of the following companies: OpenAI, Anthropic, Google (including Google DeepMind), Meta, xAI, Microsoft, Amazon, Mistral AI, DeepSeek, Alibaba, ByteDance, Moonshot AI, and Zhipu AI (Z.ai). Models designed for specific tasks, or those that are outdated, used solely for research or preview purposes, do not meet this criterion.The action can target a single model or a group of models, as long as at least one major AI model becomes inaccessible to the public within the US as a result. A temporary suspension of public access to a model meets this condition. However, if an action has been implemented or a related resolution has been issued, but the public can still access the model before the resolution takes effect, that action does not meet the condition.The information sources for this market are official announcements and information from the US government and the relevant AI companies. However, reliable media reports may also be referenced to form a consensus.The Odaily Seer Channel continues to monitor prediction markets, observing changes before prices are set.
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AI Frenzy Continues? US Tech Companies' Data Center Lease Commitments Hit a Record High of $850 Billion
The Kobeissi Letter, citing Bloomberg on X, stated, "US technology companies have committed a record $850 billion over the next few years for data center leases, an increase of $570 billion year-over-year, representing a 204% jump, and a sequential increase of $200 billion, or 31%."According to the report, Meta added $79 billion in new commitments in the first quarter of 2026, up 76% from the previous quarter, bringing its total commitments to approximately $183 billion. Microsoft added $41 billion in the same period, up 26% sequentially, bringing its total commitments to around $197 billion. Oracle leads with total commitments of approximately $250 billion, having locked in several key sites to fulfill its contract with OpenAI.
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Binance Adds 15 New bStocks Tokens as Margin Collateral
according to an official announcement, Binance CrossMargin, PortfolioMargin, and PortfolioMargin Pro have added 15 new bStocks tokens as qualified collateral assets, including Circle (CRCLB), Micron (MUB), NVIDIA (NVDAB), Sandisk (SNDKB), Tesla (TSLAB), SpaceX (SPCXB), Advanced Micro Devices (AMDB), iShares MSCI South Korea ETF (EWYB), Intel (INTCB), Strategy (MSTRB), Lumentum (LITEB), Meta (METAB), Microsoft (MSFTB), Palantir (PLTRB), and Invesco QQQ Trust (QQQB). The corresponding trading pairs are now available for margin trading. This feature is only available to VIP3 and above users in eligible regions, and loans are not currently supported.
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Microsoft announces $2.5 billion investment in new Applied AI division
Microsoft announced a $2.5 billion investment in a new "Applied AI Consulting and Solutions" division to help enterprises deploy and customize AI software more efficiently. The establishment of this division comes as many large enterprises face challenges in AI adoption, including complex configurations, difficulties in aligning with business scenarios, and unclear investment returns.Microsoft stated that the new team will focus on enterprise-level AI implementation, including model customization, system integration, and business process optimization, aiming to enhance the usability and commercial value of AI in real-world production environments. Market analysts believe this move further signals that AI competition is shifting from model capabilities to a new phase focused on "deployment and monetization capabilities." (TechCrunch)
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Microsoft Establishes New 6,000-Person Department to Assist Enterprises in Advancing Artificial Intelligence Deployment
According to Bloomberg, Microsoft announced the establishment of a new organization comprising 6,000 employees, specifically dedicated to assisting enterprises with the technical implementation and strategic deployment of artificial intelligence. This department will integrate engineering, corporate training, management, and industry expertise to provide customers with more systematic AI application support.
1011 Insider Whale Agent: AI Computing Power Transactions Are Shifting, Funds Moving from Memory Chips to Hyperscale Cloud Providers
According to Odaily, "1011 Insider Whale" agent Garrett Jin pointed out in a post that there has been a clear change in market structure this week, with funds within the AI industry chain being reallocated.Change 1: Signs of a cyclical peak in Memory chipsHe stated that Micron's stock price faced resistance and fell back around the $1250 level. Despite earnings results exceeding expectations, the stock price is still declining on increasing volume, displaying typical top-forming characteristics of "weakening after good news is priced in."Concurrently, capital is rapidly flowing out of the memory chip sector. DRAM-related ETFs are experiencing declines on heavy volume, and SK Hynix and Samsung Electronics in the South Korean market are also weakening. Data shows that foreign investors have withdrawn over 100 trillion Korean Won (approximately $650 billion) from the South Korean stock market in the past two months.Change 2: Funds rotating towards AI HyperscalersHe noted that the real direction for absorbing this capital is not small and mid-cap AI concept stocks, but rather the core cloud computing giants represented by Google, Microsoft, and Amazon.Last Friday, when the chip sector came under pressure, GOOG and MSFT had already stabilized on increased volume, and this week META has further strengthened this trend by rallying on high volume.Garrett Jin believes the logic behind this capital migration is the "token optimization trend." As more simple tasks are handled by low-cost models, value will gradually concentrate on the token-based billing cloud services and orchestration layers, rather than the foundational model layer. This also forms the core moat for hyperscale cloud providers. The current strategy should focus on catching up opportunities in hyperscale cloud names.
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Citrini analyst jukan: MediaTek reportedly locks in Meta as ASIC customer after TPU
: Citrini analyst jukan posted on X platform, stating that supply chain sources indicate MediaTek has essentially secured its second ASIC customer beyond Google. If nothing unexpected happens, this customer will be Meta, as previously rumored. Per its usual practice, MediaTek does not publicly comment on individual products, customer situations, or market rumors. Qualcomm currently seems to hold key major clients such as Meta, Microsoft, and ByteDance, but industry insiders believe that MediaTek is not at a disadvantage as it deepens its cooperation with Google and has the opportunity to lock in a second customer. According to semiconductor supply chain sources, based on the order prospects and generational transition pace of AI data centers and ASIC products from major cloud service providers, Google remains the most proactive and aggressive key client. MediaTek not only has two product codenames, Zebrafish and Humufish, but market information and industry insiders familiar with ASICs have confirmed that its participation in the v9 generation Triggerfish is almost certain. This implies that from late 2026 through 2028, and even extending to 2029, MediaTek can stably generate revenue from TPU mass production. Compared to Qualcomm's proposed 2029 cloud AI revenue target of $15 billion, MediaTek, holding multiple TPU ASIC orders, is only a matter of time before reaching the $10 billion level. The industry is also watching whether MediaTek can smoothly secure a second key cloud service provider as a major client. Combining earlier market information and recent supply chain confirmations, MediaTek is still actively cooperating with Meta on ASIC products, with the collaboration likely centered on AI accelerator chips. Meta has recently partnered with both Arm and Qualcomm, but those related products are aimed at CPUs. For its self-developed AI accelerator chips, there have been no clearer collaboration announcements. IC design industry insiders note that Meta’s recent cloud AI development strategy has indeed been relatively chaotic and unclear, with its internal chip development plans undergoing multiple adjustments. Even in the CPU domain, it has sought multiple partners and adopted different approaches. Regarding AI accelerator chips, although Meta has previously formally announced its cooperation plan with Broadcom, supply chain sources indicate this has not interrupted the ongoing cooperation plans between MediaTek and Meta. IC design industry insiders also emphasize that the cloud AI development roadmaps of MediaTek and Qualcomm remain distinctly different. MediaTek is concentrating all its resources on the ASIC business, while Qualcomm plans to advance both customization and standardization simultaneously, covering both AI accelerator chips and CPU product directions.
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WhiteBIT Launches TradeFi, Supporting Perpetual Contracts for Over 45 Traditional Asset Categories
European cryptocurrency exchange WhiteBIT has announced the launch of a new market category, TradeFi. Users can now trade over 45 perpetual contracts tied to the price movements of commodities, stocks, and ETFs within a crypto trading interface. TradeFi uses USDT as margin and settlement currency, enabling users to trade relevant contracts through a single WhiteBIT account. The underlying assets cover gold, silver, crude oil, natural gas, copper, as well as stocks like Apple, Microsoft, Nvidia, Tesla, Coinbase, Robinhood, and certain market ETFs. WhiteBIT stated that TradeFi instruments are offered through its perpetual contracts interface, and these products only track the price fluctuations of traditional assets. They do not represent actual trading or investment in the underlying assets, nor do they confer ownership, shareholder rights, or related entitlements.
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MGBX will list METAB (Meta), LITEB (Lumentum), and MSFTB (Microsoft) for spot trading
According to official sources, MGBX will list METAB (Meta), LITEB (Lumentum), and MSFTB (Microsoft) for spot trading on July 1, 2026 at 18:00 (SGT). Deposit opening time is July 1, 2026 at 16:00 (SGT). Trading opening time is July 1, 2026 at 18:00 (SGT). Withdrawal opening time is July 2, 2026 at 19:00 (SGT).
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Ondo Integrates with Uniswap, Enabling On-Chain Trading for Over 430 Tokenized Stocks and ETFs
Ondo Finance has announced the integration of its tokenized securities platform, Ondo Global Markets, with Uniswap. Over 430 tokenized stocks and ETFs on the platform are now simultaneously available on Ethereum and BNB Chain. Users can trade via the Uniswap interface or the UniswapX API.Compliant users can trade tokenized shares of companies such as SpaceX, Tesla, NVIDIA, Apple, Microsoft, and Amazon, as well as major ETF assets like SPY and QQQ, directly on-chain. Trades leverage UniswapX to benefit from optimal liquidity routing, MEV protection, and gas-free transactions. All wallets and protocols integrated with the UniswapX API can support Ondo's full suite of tokenized securities without requiring additional development. Data shows that since its launch in September 2025, Ondo Global Markets has covered over 430 tokenized securities, with its TVL surpassing $1 billion and cumulative trading volume exceeding $20 billion.
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Analysis: Tightening spending impacts growth expectations for OpenAI and Anthropic, AI industry shifts toward cost-efficiency era.
As companies begin to reassess the return on AI investment, the industry is shifting from a "tokenmaxxing" high-consumption model to prioritizing efficiency, placing new constraints on the growth of AI large model developers. Multiple enterprises have started to cut or optimize model call costs. For example, the CEO of AI startup Lindy stated that they have switched 100% of traffic from Anthropic's Claude model to the lower-cost DeepSeek, expecting to save millions of dollars in expenses within a few months.This shift reflects tightening corporate AI budgets. The previous "unlimited use of model resources" tokenmaxxing model is gradually being replaced by cost control and ROI orientation. Some companies have even implemented tiered budgets for AI tool usage; for instance, Uber has set monthly spending caps on internal AI expenditure.Analysts point out that as enterprises move from "expanding usage" to "refined calling," the high-growth model that OpenAI and Anthropic previously relied on is facing challenges. Industry data still shows strong growth: Anthropic's annualized revenue is approximately $47 billion, while OpenAI's run rate is close to $25 billion. However, the market is beginning to focus on the sustainability of this growth.Meanwhile, model calling methods are evolving. Technologies like "model routing" are emerging, using lower-cost models to perform simple tasks in place of high-end models to optimize overall computational costs. Industry competition is also intensifying, with Microsoft, Amazon, and Google all accelerating the launch of low-cost AI models and enterprise-level tools, further compressing price margins. Against the backdrop of increasingly rationalized enterprise AI spending, major AI model companies may face a situation of "slowing growth expectations" coexisting with "IPO window pressure." (CNBC)
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“Cordyceps” CI/CD Supply Chain Vulnerability Pattern Exposed, Affecting Code Repositories of Microsoft, Google, and Others
Cybersecurity firm Novee, in its latest research, revealed a CI/CD supply chain vulnerability pattern dubbed “Cordyceps,” primarily involving command injection, authentication logic flaws, artifact poisoning, and privilege escalation within GitHub Actions workflows. According to the report, unauthenticated users can exploit these vulnerabilities under specific conditions to hijack workflows, steal credentials, or gain control of code repositories.
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LinkedIn Co-Founder: xAI Is “a Disaster”; SpaceX “Buys Its Way” into the AI Race
Reid Hoffman, co-founder of LinkedIn and investor in Anthropic and OpenAI, recently shared his views on the “Pioneers of AI” podcast, offering assessments of several AI companies. Hoffman bluntly stated that SpaceX “is not an AI company,” describing its acquisition of Cursor and other moves as “buying relevance with money,” and labeled xAI as “a complete disaster”—all 11 of xAI’s original co-founders have departed, the company has undergone three reorganizations, and its flagship model Grok consistently lags behind competitors in benchmark tests. Regarding the U.S. government’s order—citing export controls—for Anthropic to delist its Fable and Mythos models, Hoffman expressed strong concern, criticizing the government’s approach as “authoritarian and principle-free,” and pointing out the stark asymmetry in regulatory standards applied to Anthropic versus OpenAI. Furthermore, Hoffman argued that Anthropic and OpenAI are not engaged in zero-sum competition; rather, each holds distinct advantages—in coding, design, legal frameworks, and consumer-facing applications—and both stand poised to become “infrastructure-level” companies in the AI era. He also announced his resignation from Microsoft’s board to fully dedicate himself to Manas AI, an AI-driven drug discovery company.
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Serenity’s In-Depth Analysis of Tech Giants’ AI Strategies: Amazon’s Path Forward Looks Promising; Microsoft and Meta Must Justify Their Capital Investments
Serenity, dubbed the “White-Haired Stock God,” stated in a post that the market should not interpret AI-related capital expenditures by large tech companies as “funds being siphoned away.” Rather, these investments are more accurately described as laying the groundwork for substantial future revenue growth or margin expansion. Serenity currently favors Amazon most highly, viewing it as one of the clearest examples of AI transformation among hyperscale cloud providers. Amazon may leverage large language models to achieve autonomous delivery, warehouse robotics, and automation across logistics and transportation—thereby lowering operational costs. Meanwhile, Amazon is also expanding its AWS compute infrastructure to drive revenue growth and, potentially, enter the AI chip sales market via its in-house Trainium chips. Serenity ranks Google second among tech giants in AI strategy, noting its AI capital spending aims primarily to defend the moat around its search business. Additionally, Google Cloud’s TPU-based compute advantage gives it chip commercialization potential comparable to NVIDIA’s GPUs. Regarding Microsoft and Meta, Serenity says both firms still need to demonstrate to the market the necessity of their massive AI capital outlays. Microsoft’s recent sentiment has been weak, partly due to delays in its in-house AI chip Maia and the impact on AI development pace stemming from its partnership with OpenAI.
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