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Ethereum co-founder Vitalik Buterin shared that the cost of Bitcoin mining is roughly half derived from capital expenditures on computing power equipment and the other half from electricity consumption; in contrast, the cost of AI inference is almost entirely dominated by capital expenditures on computing power. This difference reflects the distinct cost structures of the two computing businesses. Bitcoin miners need to continuously pay for electricity and determine their profit margins based on mining machine efficiency, coin prices, and network difficulty changes; AI inference, on the other hand, relies more on investments in expensive hardware like GPUs, as well as equipment utilization and computing efficiency.The industrial boundaries of both are also changing. As the demand for AI computing power grows, some Bitcoin mining companies are beginning to shift their existing electricity resources and data center facilities towards AI and high-performance computing businesses, hoping to transition from pure mining to computing infrastructure services. Some mining companies are leveraging previously allocated electricity capacity for mining to enter the AI data center market. However, transformation does not mean that cost pressures disappear: mining operations are more directly exposed to fluctuations in electricity prices and Bitcoin prices, while AI computing businesses must bear risks related to GPU procurement, depreciation, and underutilization. Both types of businesses compete for electricity and computing resources, but ultimately, profitability depends on how these resources are converted into revenue.

According to Bitcoin.com, Bitcoin mining service provider Sazmining has announced the launch of a personal purchase plan, allowing customers to directly own immersion hash boards developed by Block's Bitcoin mining division Proto, which is owned by Jack Dorsey.Sazmining is responsible for the installation, operation, and maintenance of the mining facilities in the United States, and the mined Bitcoin will be sent directly to the customers' personal wallets. Each hash board is priced at $4,187, with a down payment of $1,397, and the remaining amount can be paid in 18 months with zero interest.The equipment is expected to start operating between November and December 2026, with a single hash power of about 200 TH/s and an energy efficiency of about 15 J/TH. Sazmining will charge a uniform rate for electricity and maintenance fees and provide hash board operation services to customers. The company was founded in 2018 and operates mining facilities in the United States, Paraguay, and Norway, serving both individual and institutional clients.

According to Xinhua News Agency, General Secretary of the Communist Party of China and President Xi Jinping emphasized during his inspection in Ulanqab, Inner Mongolia on the 16th that it is necessary to coordinate high-quality development and high-level protection, and to unswervingly follow the path of ecological priority and green development. Xi Jinping learned about the "East Data West Calculation" hub node and the green computing power industry in the Chahar High-tech Zone, and required that completed projects operate efficiently and subsequent construction be completed on schedule.He stated that the computing power network is one of the "six networks" planned and constructed by the country, and the computing power industry is in a stage of accelerated development, emphasizing the importance of "computing power and electricity coordination" and "computing power and water coordination." Xi Jinping also inspected the Huangqi Sea Nature Reserve and required the comprehensive implementation of the Wetland Protection Law.

Analyst Jukan published a discussion on the storage industry's cycle, believing that computing power and storage will tighten or loosen in sync, and that there will not be a situation where computing power is continuously in short supply while storage alone turns to surplus. He also stated that the logic of shorting storage while going long on hard drives does not hold, as hard drives are tied to the storage cycle; if this cycle declines, hard drives will struggle to remain secure on their own.Jukan noted that the market lacks a clear judgment on trends after 2027. Historically, prices often peak one to two quarters before supply increases, followed by an expansion in shipments and a contraction in profit pools. He believes that this cycle is different from those of personal computers, smartphones, and general-purpose servers, as the products used are not standardized, and the triggering factors are also different. Some investors who still view storage through the lens of past experiences of profits during upswings and losses during downswings dominate pricing, leading to a low valuation of storage. He stated that a sharp collapse similar to previous ones is unlikely to reoccur, but a gradual decline is possible; even if Samsung and SK Hynix's profit margins are halved from current levels, the price-to-earnings ratio may still be in the teens, about half of the valuation of hard drive companies.He also believes that when storage prices decline, other demands will absorb supply at various price levels, with local AI-driven personal AI demand expected to emerge. If the storage prices pushed up by hyperscale cloud providers cannot be controlled, local AI will struggle to spread. Referring to the transition from mainframes to personal computers and from cloud to smartphones, he anticipates that this AI cycle will shift from cutting-edge laboratories to local open-source AI, with the latter absorbing storage demand. He simultaneously stated that storage prices will not remain high for over ten years; prices will eventually decline, but new consumer demands driven by local AI and open-source initiatives may provide bottom support.

According to Catcher Predict monitoring, in the market prediction on Polymarket for the event "Dota 2: Power Rangers vs Kalmychata - DreamLeague Eastern Europe Closed Qualifiers Playoffs," the "Yes" option in the sub-market "Ends During the Day" has experienced significant fluctuations in winning probability, soaring from 50% an hour ago to the current 91% (a fluctuation of 41%). Please note the impact of related breaking news.

Box CEO Aaron Levie stated that the significant increase in AI tokens and computing power consumption will come from large-scale autonomous agent clusters operating internally within enterprises, rather than personal assistants. He anticipates that the related tokens and computing power consumption could see an increase of about 100 times.Aaron Levie mentioned that the usage of personal agents will generally be capped per person. Knowledge work is currently limited by the ability of humans to generate, transmit, and produce information; at this stage, most agents are still tasked by humans, compressing about 3 to 5 hours of work into approximately 10 minutes, still constrained by the speed at which humans initiate tasks.He further stated that true significant growth will occur when backend agents are deployed in clusters to execute tasks that are completely decoupled from human initiation. The above remarks were quoted by @MTSlive.

On October 13, Ruantong Power was reported to have received 8,000 NVIDIA GPU cards, specifically the NVIDIA 6000D (domestic "special edition" of the Blackwell architecture), which will be used for the production of related servers.

Multiple venture capital firms in Silicon Valley are competing to secure GPU computing power to provide exclusive resources for their AI startups. a16z established a computing power pool of about 20,000 GPUs as early as 2024 and is negotiating expansion with data center companies Switch and Volta. General Catalyst plans to build a data center for its portfolio companies and has brought in the former head of NVIDIA DGX Cloud in May this year to oversee AI infrastructure operations.Even if AI startups complete their financing, they may not be able to rent GPUs in a timely manner. In April this year, major cloud providers like Microsoft were reported to prioritize allocating computing power to internal teams and large clients, leaving some startups facing months of waiting. a16z previously disclosed that during times of computing power shortages, prices that could originally be secured with a six-month contract might require a three-year commitment. Model training requires a large amount of GPU usage in a short period, while inference demand is difficult to predict, making it easy to waste funds by locking in computing power for several years in advance.a16z is concentrating on purchasing and leasing computing power through the Oxygen project, redistributing it to its portfolio companies, allowing them to access prices and contract terms typically reserved for large clients. In August this year, a16z co-led a $300 million financing round for Volta, which is valued at $2.4 billion, with investments covering both AI startups and data center companies providing computing power. The small venture capital firm Crucible Capital has built a cluster with 576 NVIDIA B300 GPUs for its portfolio companies to test, while also selling some computing power to a cutting-edge AI laboratory. This model allows venture capital firms to take on investments that were previously mainly borne by cloud providers and data center operators.

The computing power and inference cost trading platform Itô co-founder Affaan announced that the Itô team has joined the trading company Jump Trading, responsible for its computing power trading business. Affaan and co-founder Alejandro stated that the team will lead the newly established internal computing power trading desk at Jump Trading and has begun trading in this emerging market.According to their introduction, Itô initially hoped to leverage the new contract market to help enterprises address the centralized AI supply chain risks that the existing system struggles to cover. After communicating with over a thousand funds, enterprises, venture capital institutions, and related practitioners, the team focused on the intermediate market for computing power and inference costs. They noted that the common contract duration for capacity is 3 to 5 years, with about 30% requiring prepayment, while the revenue for late seed round to Series C companies is mostly settled monthly and based on usage, and the secondary market prices for popular chips are also quite volatile.Affaan also mentioned that the total contract value for related medium market clusters sometimes ranges from hundreds of millions to several hundred million dollars. Itô previously built a platform as an end buyer, with team members' backgrounds including Goldman Sachs' credit basket business, open-source engineering tools, and supercomputing cluster research. They stated that Jump Trading's conditions in credit, risk control, trading experience, and hardware led them to choose to advance this business through an internal trading desk.

Navitas Semiconductor announced a collaboration with NVIDIA (NVDA.O) to develop an 800V to 12V power conversion board for next-generation AI infrastructure.

AI computing power operator KONST has completed a $30 million Series B financing round, led by ADATA Technology, with strategic investments from M Mobility and other venture capital firms.The new funds will be used to expand the construction of its AI data centers and accelerate the Token factory strategy.

SWI Group has raised 800 million euros (approximately 895 million dollars) from institutional investors to expand its artificial intelligence data center and computing power infrastructure layout in the United States and Europe.The company also plans to transform eligible old Bitcoin mining sites into artificial intelligence infrastructure and is actively seeking to reach cooperation agreements with hyperscale cloud service providers.

Grayscale's Research Director Zach Pandl stated in his column The Stack on October 8 that the rising demand for AI is due to decreasing usage costs and technology's ability to perform tasks more autonomously, thereby increasing the demand for computing power and the physical infrastructure that supports AI. Lower costs can unleash more AI activities, and the low-cost competition of open-source weight models is driving down token prices, making cheaper intelligence economically viable for more applications and automated workflows.The article cites that Anthropic's latest Sonnet model claims to reduce the cost of each task by up to 30%; OpenAI's always-on agent dots, launched on September 29, can work towards user goals around the clock, potentially significantly increasing the demand for computing power. Pandl compares that chatbots primarily answer questions, while agents execute multi-step processes to achieve goals, with tasks like preparing for client meetings potentially consuming 5 to 50 times the tokens of a single chat interaction, and always-on agents may extend processing beyond a single conversation.Pandl cites Goldman Sachs' prediction that by 2030, token consumption could increase 24 times, primarily driven by agents; even with improved efficiency, if usage grows faster, the total demand for computing power may still rise. He points out that digital activities still rely on physical infrastructure that requires time to deliver, such as electricity, data centers, and GPUs, and cheaper AI can coexist with tight computing power supply, mentioning that CoreWeave recently signed new contracts at higher computing power prices. His conclusion is that cheaper intelligence and stronger agents may expand use cases and usage enough to offset efficiency gains, thereby supporting the demand for scarce computing power and benefiting its owners.

According to Bits media, the Russian Ministry of Energy stated that cryptocurrency miners apply for grid access under the fourth category of power supply reliability. Such users can be directly cut off by the authorities at any time without prior negotiation.This category was established by the government in February this year, allowing technical access in areas where energy shortages have been declared and mining has been prohibited. The Ministry of Energy stated that this move can effectively utilize existing energy infrastructure while not threatening the reliability of power supply to residents.

Jan van Eck stated that allowing more nuclear power projects can simultaneously boost AI and Bitcoin: on one hand, it raises the value of AI, and on the other hand, it alleviates the selling pressure on Bitcoin by providing cheaper energy for miners. There is strong bipartisan support for nuclear energy in the United States, with the goal of increasing nuclear power output to four times the current level within 25 years, as evidenced by the accelerated restart of the Three Mile Island nuclear reactor.Matthew Sigel, Head of Digital Asset Research at VanEck, stated that miners holding long-term power contracts and infrastructure have undervalued option value; if miners shift to AI contract revenue, the pressure to sell Bitcoin will consequently decrease.

According to CoinDesk, Bitcoin is facing selling pressure, marking the third time since September 23 that it has been blocked near $87,000. FxPro analyst Alex Kuptsikevich stated that since the beginning of last week, BTC has formed a trend of "gradually higher local lows," but bulls have not yet gained sufficient upward momentum.The current price is approaching the apex of a triangle formed by horizontal resistance and an ascending support line. If this pattern is broken, the market may experience greater volatility. The total market capitalization of the cryptocurrency market has fallen back to about $2.93 trillion. Meanwhile, U.S. stocks have performed strongly, with the Nasdaq 100 index reaching a new closing high and the S&P 500 index less than 0.5% away from its historical peak. However, U.S. Treasury yields continue to rise, with the 10-year Treasury yield climbing to 5.32%, close to its highest level since 2002.Market observers believe that for BTC to break through $87,000, sufficient buying pressure is needed to absorb the selling pressure that continues to appear around this price level. Once it stabilizes at this level, it may further open up space for movement towards an 8-month high.

According to Catcher Predict monitoring, the event "Power Balance: 2026 Midterm Elections" is currently among the hottest trades on the prediction market Polymarket, with a cumulative pool size reaching 178 million dollars. The option with the highest market consensus is "Democratic Party Victory," corresponding to a winning probability of approximately 66.5%.

Cryptocurrency analyst Darkfost stated that over the past decade, the volatility of Bitcoin prices around the "Power Law" trend line is gradually decreasing, and market cycle fluctuations are converging. The oscillation indicator peak has dropped from +169 in 2018 to +102 in 2025, with its daily standard deviation decreasing from 4.81 to 2.47, a decline of about 49%.Darkfost added that as of the current model's oscillation indicator at +34.5, the Bitcoin price is approximately $84,700. According to the model parameters for that day, an oscillation indicator of +100 corresponds to a Bitcoin price of about $157,800, which is approximately 86% higher than the current price. He also pointed out that $157,800 is not a fixed target price but rather a reference level calculated based on the current regression parameters. If the Power Law trend line continues to rise in the future, this reference price will also increase accordingly.