News linked to both this project and an event.
According to Chaoxiang Research, UBS released a SemiBytes Flash Note on July 20, 2026, judging that the semiconductor sector is transitioning from a broad-based rally to a phase of severe divergence, while the AI-themed crowded trade continues. The report covers five core topics. The release of Kimi K3 drives another upgrade in open-source model scale; longer context windows boost demand for HBM and storage, with NVIDIA being the biggest beneficiary. Micron's cumulative free cash flow over the next few years is expected to exceed $400 billion; after the buyback ban is lifted, the theoretical buyback ratio could exceed 40%, which is not yet fully priced in by the market. Divergence within the analog chip sector is intensifying; stocks with higher AI exposure have gained a 42x P/E premium, while valuations for stocks with automotive and industrial exposure remain near historical averages. Position crowding data shows that Lam Research, Broadcom, Seagate, Micron, and AMD remain in a state of extreme long positioning crowding.
According to Bloomberg, UK startup CuspAI, founded just two years ago, has raised nearly $500 million, with its core bet being the use of artificial intelligence to improve semiconductor production processes. On Monday, CuspAI announced the establishment of the "AI Materials Foundry," an alliance that brings together more than 48 tech companies, industrial companies, and research institutions, with members including NVIDIA, Meta, and Hyundai Motor Group.
According to TechFlow Research, Goldman Sachs' July 16 energy storage report pointed out that electricity demand from data centers is surging, traditional grid expansion requires four to eight years, and energy storage has become the fastest solution with a 12 to 18-month deployment cycle. Goldman Sachs estimates that by 2030, behind-the-meter energy storage opportunities in the US will bring about 50GWh of increment, plus 11GWh from 800V DC data centers, total US energy storage deployment will reach 172GWh, significantly upwardly revised from the previous 112GWh. Globally, annual energy storage installations are expected to reach 2100GWh by 2040. Goldman Sachs believes energy storage is transitioning from renewable energy supporting equipment to a necessity for AI infrastructure, which will change the industry valuation logic. In terms of targets, FLNC (Buy) secured exclusive battery partner qualification for Nvidia DSX Vera Rubin, data center pipeline projects reached 12GW, up 30% sequentially; CATL (Buy) has about 30% global energy storage market share, already used in Shanghai SenseTime data center; Tesla (Neutral) 2025 energy storage deployment 46.7GWh, energy business 2028 estimated revenue 29 billion USD; Energy Vault (Neutral) received 6x EV/EBITDA valuation; LGES (Buy) North America ESS capacity expected to reach 50GWh by end of 2026. Canadian Solar, Ford, Samsung SDI, Shoals, Sungrow are also worth watching. Goldman Sachs emphasizes the need to distinguish those with real order support
AI infrastructure startup Fireworks AI has announced the completion of a $1.5 billion financing round, valuing the company at $17.5 billion. The company, previously backed by NVIDIA, primarily provides developers with cloud-based services for running open-source AI models, helping enterprises deploy AI applications at lower costs. This funding round was led by Atreides Management, Index Ventures, and TCV, with participation from NVIDIA, Evantic, and Lightspeed Venture Partners, among others. Currently, Fireworks processes approximately 40 trillion AI tokens daily. Its clients include companies such as Elastic, GitLab, and MongoDB. Previously, over half of its revenue came from the AI coding tool Cursor, but its client base has since become more diversified. (CNBC)
Odaily reports, as the value of the artificial intelligence industry rapidly increases, political and tech circles in the United States have begun discussing how to share the immense wealth generated by AI with the public. A series of proposals all point in the same direction: having the government or public institutions hold equity in AI companies.Recently, Sam Altman discussed the possibility of granting the U.S. government or other public entities partial ownership in OpenAI. Meanwhile, the U.S. government already holds approximately 10% of Intel's shares, and it has indicated it may receive a certain percentage of revenue from NVIDIA's chip sales to China.U.S. Senator Bernie Sanders proposed that major AI laboratories contribute half of their shares to a new sovereign wealth fund, allowing the public to share in the growth dividends of the AI industry.Observers suggest that these plans essentially aim to redistribute some of the economic benefits from AI development back to society. However, critics point out that most current proposals boil down to one model: having the government hold equity in AI companies.Supporters argue that AI could become the most significant productivity transformation in the coming decades, and involving the government in revenue distribution could alleviate wealth concentration. Opponents, however, worry that direct government ownership of stakes in tech companies could impact market competition, corporate governance, and innovation incentives.As the valuation of the AI industry continues to rise, how to distribute the economic benefits generated by artificial intelligence is becoming a core topic of debate among U.S. policymakers and the tech industry. (The Information)
According to TechFlow Research, Morgan Stanley's July 13 roadshow feedback report points out that Nvidia's current biggest problem is not fundamentals, but the market capitalization size leading to a lack of incremental capital. Quarterly growth is 95% and management believes growth will accelerate; next year's free cash flow yield will exceed 5%, with over half potentially returned to shareholders, so value investors may become the new buying force. Morgan Stanley also focuses on Nvidia's NeoCloud financing support model, providing credit endorsement for cloud service providers in exchange for revenue sharing, creating a recurring revenue stream with 100% gross margin beyond hardware. Morgan Stanley maintains an Overweight rating on Nvidia with a target price of $288.
Gradium, a Paris-based real-time voice AI startup, has announced the completion of a $100 million seed funding round, with NVIDIA participating as an investor.The company has recently rapidly launched multiple voice AI products, covering tools such as real-time speech-to-text (STT), text-to-speech (TTS), real-time translation (Gradium Translate), and the Phonon audio model. The funding will be used to establish a new office in San Francisco, deeply integrate with the North American AI industry ecosystem, and accelerate the recruitment of global technical talent. Gradium specializes in ultra-low-latency real-time voice interaction models, spun out of the French AI lab Kyutai, with its founding team hailing from top AI institutions such as Google Brain, DeepMind, and Meta.
According to TechFlow Research, Bank of America reaffirmed its Buy rating for NVIDIA in a July 7 research report, with a price target of $350 versus the current $195.55, implying 79% upside. NVIDIA is currently trading at 15.7x expected 2027 P/E ratio, the lowest in seven years, representing a 30-35% discount to tech peers. BofA believes the market has overestimated risks such as HBM cost pressure and custom ASIC competition. Vera Rubin inference performance per watt is 10x higher than Blackwell, and gross margin is expected to remain at 75%. NVIDIA's sales to hyperscale customers increased 115% year-over-year, nearly twice the growth rate of cloud capex. Crowded positioning and $65 billion in ecosystem investment are risks but have been priced into the valuation.
According to official news, Prime Intellect announced the completion of a $130 million Series A financing round, led by Radical Ventures with participation from NVIDIA, Intel Capital, Dell Capital, and existing investors. The company stated that it will utilize the funds to continue building its "Open Superintelligence Stack" to support users in training, deploying, and continuously optimizing their own models.
According to Reuters, Chinese AI startup DeepSeek is developing its own AI chips, three informed sources revealed. The chip is designed specifically for inference scenarios, rather than for model training. The project was launched approximately one year ago and remains in the early stages. The company has engaged with chip design, wafer foundry, and storage enterprises, and has quietly increased recruitment of chip design engineers without publicly posting job listings. If successfully developed, DeepSeek will reduce its reliance on Nvidia and Huawei Ascend chips, following the trend of global AI giants such as OpenAI and Anthropic developing their own hardware. Affected by U.S. export controls, DeepSeek previously shifted from Nvidia H800 to Huawei chips. This self-developed chip is regarded as a significant strategic transformation. Meanwhile, DeepSeek also plans to complete its first round of external financing, with a fundraising scale of approximately $7 billion, and a valuation reaching $52 billion to $59 billion.
Serenity has released an exclusive analysis of the AI ASIC market on the X platform, presenting the core thesis that "NVIDIA is the kingmaker of the ASIC market." It proposes a set of industry reasoning logic, arguing that NVIDIA CEO Jensen Huang is not pleased with Broadcom monopolizing the custom ASIC track. With implicit support from the NVIDIA ecosystem, companies such as Marvell, MediaTek, AlChip, and GUC are steadily capturing market share originally held by Broadcom, taking on more custom chip projects for hyperscale cloud vendors. This landscape is comparable to the rise of emerging cloud service providers last year, serving as an important means for NVIDIA to hedge against the moat created by leading cloud vendors developing their own ASICs.Serenity suggests this could represent a two-year trading opportunity but does not constitute investment advice. It also predicts that after 2030, major companies like Google will internalize a significant amount of chip design work. It added that NVIDIA has the ability to reshape the valuation of the industry chain, and there have already been market expectations that Marvell could potentially reach a trillion-dollar market cap.
Odaily reports: AI chip startup Etched has completed a roughly $800 million funding round, with investors including quantitative trading giant Jane Street and a venture capital firm affiliated with Taiwan Semiconductor Manufacturing Company (TSMC). The company is currently testing its AI inference chip product and plans to begin shipping to select customers this summer. It has also signed sales contracts totaling approximately $1 billion, though specific customers were not disclosed.Founded in 2022, the company positions itself as a potential competitor to NVIDIA in the field of AI computing chips, focusing on designing customized chip architectures for large model inference scenarios. It is collaborating with TSMC to develop "low-voltage inference" technology aimed at reducing energy consumption and heat dissipation pressure.This funding round, previously reported to have a valuation of around $500 million, includes participation from Stripes, funds associated with Peter Thiel, and several quantitative firms. Jane Street is said to have invested over $100 million in total, with subsequent additional contributions. (Bloomberg)
according to on-chain analyst Ai Yi's monitoring, on June 29, SHAZ announced the completion of a $1.6 billion financing to support a six-year strategic partnership with NVIDIA; 11 hours ago, Leopold Aschenbrenner's fund disclosed a new 19.9% stake in SHAZ. The former saw a gain of 1.45%, while the latter climbed 14% after-hours. The SEC requires funds to submit public reports when their holdings exceed 5%.
cloud computing startup Runpod has announced the completion of a $100 million funding round and stated it has rejected multiple acquisition offers. Specific investor information has not yet been disclosed. The company focuses on providing GPU computing power rental services for developers, supporting open-source models and AI application deployment. Currently, this sector generally relies on NVIDIA GPU servers for computing resources. As AI applications expand, market demand for low-cost, highly flexible computing infrastructure continues to rise, driving up both the valuations and funding activity of cloud service providers like Runpod. (The Information)
According to CNBC, after listing on the Nasdaq at an approximate valuation of $2.6 trillion, SpaceX quickly became the world’s fifth-largest publicly traded company and entered a market-cap ranking race with Amazon. However, pricing in the options market suggests it may take considerable time for SpaceX to climb into the global top three—or even claim the No. 1 spot. Currently, SpaceX’s market capitalization remains significantly below that of third-place Alphabet and second-place Apple—both valued above $4.4 trillion. To overtake them and become the world’s second-largest company by market cap (just behind NVIDIA), SpaceX’s stock price would need to rise roughly 70% to $340 per share. Based on implied probability models derived from options-market pricing, the likelihood that SpaceX reaches this target price before July 2028 stands at approximately 50%. If the goal is to become the world’s largest company by market cap—surpassing NVIDIA—the options market assigns a roughly 38% probability of achieving this by June 2028, rising to about 41% by year-end 2028. Analysts note that options prices reflect the collective market expectation regarding future trajectories. Higher-strike options carry an elevated uncertainty premium, indicating that—even though SpaceX possesses a compelling long-term growth narrative—reaching the pinnacle of market capitalization is still viewed as a high-difficulty, long-duration endeavor.
Sharon AI has announced the issuance of convertible senior notes to raise $700 million, with the proceeds intended to support its computing agreement with NVIDIA.
Sharon AI Holdings, a Nasdaq-listed company, announced a six-year strategic computing cooperation agreement with NVIDIA to jointly expand AI infrastructure capabilities in Australia.Under the agreement, the two parties will collaborate to build approximately 72MW of data center computing capacity and deploy infrastructure based on the NVIDIA DSX AI Factory architecture. The plan is to gradually scale up to 40,000 Grace Blackwell GB300 GPUs to meet the computing needs of AI startups, enterprise clients, and research institutions.The cooperation model adopts a structure combining revenue generation with credit support: Sharon AI will be responsible for selling cloud services based on NVIDIA's computing power, while NVIDIA, upon receiving hardware and basic product revenue, will also participate in a share of cloud service revenue, forming a sustainable "usage-driven revenue model."Sharon AI stated that this collaboration will significantly enhance its capital efficiency, enabling it to expand AI infrastructure capabilities without relying on traditional heavy-asset financing and accelerate the deployment of "sovereign AI computing power" in Australia. With this partnership, Sharon AI's total AI factory capacity will increase to 132MW, of which approximately 102MW is already contracted by clients. The company expects to deploy over 55,000 NVIDIA GPUs by mid-2027. (Businesswire)
OpenRouter, an AI model aggregation platform founded by OpenSea co-founder Alex Atallah, has announced the completion of a $113 million Series B funding round, led by CapitalG, the growth fund under Alphabet, Google's parent company.Other participants in this funding round include a16z, Menlo Ventures, NVentures (affiliated with NVIDIA), as well as ServiceNow, MongoDB, Snowflake, and Databricks. The company's valuation has now exceeded $1 billion.
AI hardware startup Hark announced the completion of a $700 million funding round, reaching a post-investment valuation of $6 billion. This Series A round was led by Parkway Venture Capital, with participation from NVIDIA, AMD Ventures, ARK Invest, Brookfield, Greycroft, Intel Capital, Qualcomm Ventures, Salesforce Ventures, and others. The new funds will be used to expand GPU infrastructure and accelerate large model research and development. (Bloomberg)
AI startup Hark announced it has raised $700 million in funding, achieving a post-money valuation of $6 billion. This Series A round was led by Parkway Venture Capital, with participation from NVIDIA, AMD Ventures, ARK Invest, Brookfield, Greycroft, Intel Capital, Qualcomm Ventures, and Salesforce Ventures.