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Samsung SDS stated in its earnings call that its strategic investment in the South Korean cryptocurrency exchange Dunamu is a "strategic layout for entering the digital asset infrastructure business." Both parties are discussing cooperation on stablecoin infrastructure, next-generation AI payments, and virtual asset financial system integration (SI). Samsung SDS President Lee Joon-hee mentioned that they will combine Dunamu's blockchain operation experience with Samsung SDS's capabilities in IT services, AI, cloud computing, and security to strengthen the digital financial infrastructure business.The earnings report disclosed on the same day showed that Samsung SDS's revenue for the second quarter was 3.7178 trillion won (approximately 2.6 billion USD), a year-on-year increase of 5.9%; operating profit was 231.8 billion won (approximately 160 million USD), a year-on-year increase of 0.7%. Among them, the cloud computing business revenue was 779.4 billion won, a year-on-year increase of 17%, with external cloud computing business revenue surging 75% year-on-year. The company plans to expand its AI infrastructure from the current 110MW to 230MW by 2029, and further expand to over 800MW by 2031. Samsung SDS previously announced an investment of approximately 20 billion won in Dunamu in May 2024.

According to Jinshi reports, Meta Platforms CFO stated that the overall computing power in the industry will remain tight in the foreseeable future.

Ethereum co-founder Vitalik Buterin published a new article introducing a novel cryptographic obfuscation technology called Diamond iO. This technology aims to address the extremely low efficiency of traditional indistinguishable obfuscation schemes, allowing programs to run while hiding internal logic and critical data. Although traditional iO technology possesses strong privacy protection capabilities, its operational costs are prohibitively high, making it nearly impractical. Diamond iO, by adopting more aggressive new cryptographic assumptions, enhances computational efficiency from "universe-level time consumption" to "planet-level time consumption," bringing it closer to practical application.Diamond iO is built on technologies such as Attribute-Based Encryption (ABE) and Fully Homomorphic Encryption (FHE). By encrypting programs, it allows users to execute the encrypted programs and obtain correct outputs without being able to view the internal code or hidden keys. This solution introduces a new input encoding mechanism and conditional decryption method, reducing computational complexity while ensuring the program logic remains hidden. Its core application scenarios include protecting programs that contain private keys, enabling secure software licensing, constructing trustless cryptographic services, and supporting blockchain and artificial intelligence systems with stronger privacy protection.However, Diamond iO is still in the early research stage, and its security relies on new cryptographic assumptions, including All-Product LWE and Evasive LWE, which require further research validation. At the same time, the technology still faces efficiency challenges such as high computational overhead and circuit depth limitations. Researchers believe that by optimizing underlying hash functions, improving homomorphic encryption schemes, and reducing security parameter requirements, Diamond iO is expected to become an important direction for advancing practical program obfuscation technology in the future.

NVIDIA released the open-source AI model NVIDIA Ising Calibration 1.5, designed for the automatic analysis of quantum processor (QPU) diagnostic data, and to autonomously determine device calibration schemes, achieving automation of the quantum computer calibration process. NVIDIA stated that Ising Calibration 1.5 is a visual language model (VLM) specifically designed for quantum computing calibration scenarios, capable of understanding experimental data from quantum chips and performing "zero-shot" analysis in the absence of historical cases, while also enabling context learning (ICL) with relevant experimental samples to help continuously optimize the operational state of quantum devices.In the QCalEval quantum calibration benchmark test, Ising Calibration 1.5 averaged about 10% ahead of similarly sized open-source models in zero-shot inference capability, and when using relevant experimental cases for context learning, it showed an approximately 86.5% performance improvement over the previous generation model, surpassing multiple open-source models and approaching the level of top closed-source large models. The model has 31 billion parameters and supports operation on NVIDIA Grace Blackwell and Vera Rubin data center GPUs. It also launched an NVFP4 quantized version, which can be deployed on a single consumer-grade GPU or NVIDIA DGX Spark, significantly lowering the usage threshold for quantum laboratories.NVIDIA claims that the training data for Ising Calibration 1.5 comes from various qubit architectures, including superconducting qubits, quantum dots, ions, neutral atoms, and helium surface electrons, providing calibration capabilities for different types of quantum computing devices. Industry experts believe that automated calibration is one of the key bottlenecks in the scalable development of quantum computing. NVIDIA's launch of this AI-driven quantum calibration tool signifies that AI models are beginning to extend from traditional computing domains into the quantum hardware control layer, potentially becoming an important component of the future quantum computing industry infrastructure.

According to a report by the WSJ, Nvidia has invested in the AI laboratory Safe Superintelligence (SSI), founded by former OpenAI chief scientist Ilya Sutskever. The two parties have reached a long-term cooperation agreement aimed at expanding SSI's computing resources while helping Nvidia secure important clients in the AI field. Both companies stated that Nvidia made a "large-scale" investment after understanding some of SSI's research progress, but did not disclose the specific amount.As part of the collaboration, SSI will receive a significant amount of Nvidia's flagship GPU resources, with its computing power expected to increase by an order of magnitude. Previously, SSI primarily relied on TPU chips provided by Google for AI research and development. This collaboration indicates that Nvidia is further expanding its AI chip ecosystem and binding future computing power demands through investments in top AI laboratories.SSI was established in 2024 by Ilya Sutskever, with the goal of developing "Safe Superintelligence." The company has previously raised about $2 billion in funding, with investors including Andreessen Horowitz and Sequoia Capital, and reached a valuation of approximately $30 billion last year. This is not Nvidia's first investment in an AI company founded by former core members of OpenAI. In March of this year, Nvidia also invested in Thinking Machines Lab, founded by former OpenAI chief technology officer Mira Murati, whose first AI model is trained on Nvidia hardware.Ilya Sutskever is one of the important researchers in the field of modern artificial intelligence, having co-founded OpenAI and promoted the development of large model technologies such as ChatGPT. However, after leaving OpenAI, he began to question the approach of solely relying on expanding data and computing power to drive AI progress, turning instead to explore new directions in superintelligence research.

Recently, global growth sectors have remained active in trading, with the semiconductor, quantum computing, and technology-themed ETF sectors performing well. Market funds continue to focus on high-growth assets. According to data from the Gate platform, AXTIG/USDT (AXT Semiconductor) is currently priced at $49.04, up 4.38% in 24 hours; QNTG/USDT (Quantinuum) is currently priced at $55.55, up 3.46% in 24 hours; SNXXG/USDT (SanDisk 2x Long ETF) is currently priced at $15.169, up 3.13% in 24 hours.Gate gStocks adopts a 1:1 fully-backed native stock reserve mechanism, where each tokenized security corresponds to an equal number of native stocks as underlying asset support, and supports 24/7 trading, unified account management, and a minimum investment of 1 USDT with fractional share trading.Users can participate more flexibly in global popular stock investments, achieving a one-stop allocation of digital assets and traditional securities. As the ecosystem of tokenized securities continues to enrich, Gate gStocks will continue to expand more quality stocks and ETF targets, providing users with a more diverse choice of global asset allocation.

Spanish AI company Multiverse Computing announced the completion of a €500 million ($570 million) Series C funding round, with a pre-money valuation of €1.5 billion ($1.7 billion), a 5-fold increase from its Series B valuation.The company focuses on sovereign and efficient AI, and this round of financing was co-led by Forgepoint Capital International, BNPP SIVF, and Bullhound Capital.

On July 24, according to WEEX TradFi market data, the computing power sector continues to strengthen, with funds repricing around AI security, network connectivity, and advanced packaging. Among them, NETON rose over 32.12% in 24 hours, MXLON rose over 16.69%, and AMKRON rose over 8.42%, with related targets also strengthening.WEEX Labs believes that Cloudflare is laying out AI content control and security products, and MXL and AMKR benefit from the demand for high-speed connectivity and advanced packaging, leading to a short-term increase in the heat of related assets. Attention should be paid to the performance of financial reports and market volatility risks at the beginning of next month. Currently, the WEEX coin stock 0 fee rate activity is ongoing.

According to BBX data, yesterday and in recent days, global companies listed on the US stock market have disclosed the latest real announcements regarding digital asset transformation and ecological strategic investments. The core dynamics are as follows:Canton sells traditional business to fully transition to blockchain clearing: Canton Strategic Holdings, Inc. (NASDAQ: $ CNTN) officially announced that it has sold its biotechnology R&D department Gravitas Life Sciences, LLC to Gravitas Collective Corp. The transaction was completed on July 17, 2026. The company clearly stated that this divestiture is an important milestone in its transformation into an operating company, and in the future, it will support the Canton Network through Canton Coin and promote the on-chain digital transformation of traditional financial markets as a strategic investor.Empery Digital invests $20 million in cross-industry computing power electricity park: The US-listed company Empery Digital Inc. (NASDAQ: $ EMPD), which adopts a Bitcoin fund management strategy, announced that it has completed a $20 million preferred stock investment (holding approximately 8%) in Cardinal Data Power, Inc. (CDP) on July 20, 2026. CDP focuses on building electricity-driven data center parks, and this round of financing will support its construction of the first gigawatt-level data center park covering over 3,000 acres in West Texas (Phase I is planned to be operational in 2027, with a long-term plan exceeding 5GW) to meet the next generation of AI and computing power energy demands.

Bloomberg New Energy Finance (BNEF) latest forecast shows that by 2035, electricity consumption by data centers in the United States will account for about 20% of the nation's total electricity consumption, a significant increase from the current level of about 5.9%. The agency has raised its forecast for data center electricity demand in 2035 to 106 GW, which is 36% higher than the 78 GW predicted in April this year. Currently, the operating capacity of data centers in the U.S. is about 40 GW, accounting for approximately 3.5%-4% of the national electricity demand, while under BNEF's baseline scenario, this proportion is expected to reach 8.6% by 2035. The high-growth model from the Electric Power Research Institute (EPRI) indicates that if the combined effects of cryptocurrency mining and AI computing power are taken into account, the upper limit of this proportion also points to 20%.In response to the explosive growth in AI computing power demand, Bitcoin mining companies are actively transforming. Companies like Core Scientific and Riot Platforms have partnered with tech giants such as AWS and Google to convert their existing mining sites into AI data centers. Currently, Bitcoin mining companies have secured about 6 GW of electricity capacity, which is expected to expand to 12 GW by 2027, with some analysts estimating that about 20% of mining companies' computing power capacity will shift towards AI workloads by then. Data from the Electric Reliability Council of Texas (ERCOT) shows that data centers now account for about 90% of local large load applications, with many sites originally used for cryptocurrency mining being repurposed as AI computing facilities. This trend is also directly reflected in the capital markets, as Core Scientific has seen a significant rebound in its stock price after emerging from bankruptcy and partnering with AI cloud service provider CoreWeave.

According to Jinshi reports, Microsoft has agreed to invest billions of dollars in Mistral's European computing infrastructure to expand artificial intelligence infrastructure in Europe.

According to Cointelegraph, the State Duma of Russia has passed the bill No. 1194918-8 "Digital Currency and Digital Rights" in its second and third readings on Tuesday, setting rules for the operation of crypto assets and cross-border trade within the country.The bill establishes a regulatory framework for market participants such as cryptocurrency exchanges, brokers, asset management companies, and custodians, and sets operational requirements for industry companies. The bill allows crypto assets to be used for foreign trade activities, while payments for goods and services within Russia remain prohibited. The main provisions are expected to take effect on September 1, 2026, with a transition period until July 1, 2027, and the bill still needs to be signed by President Vladimir Putin to become law.

Fluidstack, a cloud computing startup focused on AI computing power leasing Neocloud, announced that it completed an $830 million Series A funding round in January, with a valuation of $7.5 billion. The round was led by the Situational Awareness fund of former OpenAI researcher Leopold Aschenbrenner, with participation from multiple investors.According to reports, Fluidstack builds infrastructure for AI laboratories, aiming to become the company that can deploy hundreds of gigawatts of computing power the fastest in the world.

According to market news, Goldman Sachs reported on July 18 that the Dark Side of the Moon released the Kimi K3 model, with 28 trillion parameters, surpassing Claude Fable 5 and GPT-5.6 Sol on the Arena.ai programming leaderboard, reaching a new high for Chinese models with an API pricing of $2.3 per million tokens. Two days after the release, Zhiyu fell by 28%, MiniMax dropped by 16%, the Nasdaq 100 index futures fell by more than 1.8%, and the Philadelphia Semiconductor Index has cumulatively dropped by more than 18% from its peak.Goldman Sachs believes that Kimi K3 marks a turning point: a Chinese laboratory that cannot match the largest pre-trained computing power in the West has rapidly narrowed the gap with top American models through architectural innovation and reinforcement learning, proving that "scaling" is no longer the only winning path. Goldman Sachs warns that the "era of computing power expansion" may be coming to an end, and the investment logic for AI infrastructure built around "the more computing power, the better" needs to be rewritten. Goldman Sachs maintains a buy rating on MiniMax and a neutral rating on Zhiyu. Future attention will focus on the intensive release of 20-50 trillion parameter models such as Zhiyu GLM, Alibaba Qwen, and MiniMax M3 Pro.

According to The Block, Bernstein pointed out in its latest research report that the perpetual contract structure originating from the cryptocurrency market has first entered the AI computing power market. The Architect AX exchange, registered in Bermuda and not regulated by the CFTC, has launched GPU computing power perpetual contracts, which are anchored to spot prices through funding rates, a mechanism that directly originates from the cryptocurrency market. The cash-settled computing power futures from CME and ICE are still awaiting CFTC review, with a launch expected by the end of 2026.In addition, the CFTC-regulated prediction market platform Kalshi has previously launched prediction contracts linked to GPU rental prices and introduced the computing power pricing curves for B200, H200, and A100 chips on July 14, with the B200 quoted at $5.41 and a historical peak of $7.39.Bernstein noted that unused GPU computing power cannot be stored, and hedging is the only way to bear price risk. However, the current market liquidity is still dominated by speculative funds, and the difficulty in constructing computing power benchmark indices is also a major bottleneck in market development.

According to "AI Technology Review," China's leading large model company Zhipu has invested hundreds of millions of yuan to acquire the AI heterogeneous computing power software infrastructure company Zhongke Jiahe. This move aims to completely address Zhipu's shortcomings in the underlying engineering and compiler capabilities of large models, in response to the structural shortage of computing power and high-concurrency inference challenges caused by a surge in user numbers.Zhongke Jiahe's technology originates from the Compiler Laboratory of the Institute of Computing Technology, Chinese Academy of Sciences, founded by Dr. Cui Huimin. Its core team has been deeply involved in the development of compilers for several domestic chips, including Loongson, Sunway, Cambricon, and Huawei Ascend. Zhongke Jiahe's core advantage lies in its virtual instruction set technology, which can unify different brands and models of chip ecosystems through middleware software, assembling scattered domestic chips into a unified ultra-large-scale cluster, thereby significantly improving overall computing power utilization; its SigInfer inference engine is claimed by the official source to reduce the inference latency of large models by up to 74 times.Recently, Zhipu's Coding Agent business has experienced explosive growth. The newly released GLM-5.2 large model saw a 27-fold increase in daily Token call volume during its first week on the aggregation platform, leading to the exposure of systemic engineering bottlenecks in its inference infrastructure under high concurrency and long context scenarios. After being placed on the U.S. Entity List, Zhipu has actively promoted domestic alternatives and has now completed inference adaptation for eight major domestic computing power platforms, including Huawei Ascend, PingTouGe, and Moore Threads. The acquisition of Zhongke Jiahe will not only directly improve Zhipu's unit Token inference cost and output quality but also provide core underlying compiler technology support for its previously rumored self-developed custom AI inference chip plan.

According to PR Newswire, AI computing power energy infrastructure Bloom Energy announced a massive project investment of $1.7 billion, with participation from Industrial Development Funding (IDF) and asset management giant Oaktree.It is reported that Bloom Energy will provide exclusive "behind-the-meter power" capabilities for AI cloud computing company Nebius to meet the growing demand for AI computing power.

According to Bloomberg, cloud computing service provider Nebius Group announced that it has reached an agreement with artificial intelligence model development company Reflection AI to sell computing power worth over $1 billion.According to statements from both parties, the agreement is valid until 2029, and Reflection AI will gain access to computing resources using NVIDIA GB300 AI chips to support its artificial intelligence model research and development.