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Famous trader Killa: Bitcoin may bottom out before the midterm elections, and the rise after the midterm elections needs to be approached with caution

Renowned trader Killa recently released a video predicting market trends before and after the U.S. midterm elections. His analysis summarizes the timing relationship between previous midterm elections and Bitcoin's bottoming out (2014: bottomed out about 70 days after the midterm elections. 2018: bottomed out about 40-44 days later. 2022: bottomed out almost during the midterm elections), suggesting that Bitcoin may form a weekly level bottom before the U.S. midterm elections on November 3.He also presented two main scenario hypotheses: Early bottom scenario: BTC forms a low point before (or around) the midterm elections (possibly sweeping the current low or maintaining above 80k), then starts to rebound, first testing the 80k area, and may eventually surge to 95k. This would lead to a bullish fourth quarter, contrary to the common expectation of "risk-off after the elections." Classic risk-off scenario: first rises sharply (possibly sweeping the high point or even reaching 94-95k), then experiences a historically common sell-off/risk-off decline after the midterm elections (similar in 3 out of the last 4 occurrences).Killa advises investors to closely observe the price structure leading up to the midterm elections and react accordingly. If an early bottom is reached, they may hold bullish positions after the elections; if a high is reached and then starts to weaken, consider risk-off. Overall, he emphasizes that the pattern is accelerating in change and cannot simply replicate the historical experience of "must drop after the elections." Killa, as a quantitative trader focused on BTC, predicted the peak of this bull market in May 2025 and has over 200,000 followers on platform X. In mid-April, he shorted Bitcoin at 74,688 USD and turned bullish during the market-wide decline on June 5.

Vitalik compared the mining costs of BTC and the inference costs of AI: the former has electricity costs accounting for nearly half, while the latter relies more on capital expenditures for computing power

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.

Deepsigma launches a DeFi perpetual contract platform covering 77 traditional financial markets

The decentralized perpetual contract exchange Deepsigma has launched a real-time simulation trading platform, covering 77 traditional financial markets, including U.S. stocks, stock indices, commodities, and U.S. Treasury yield rates. The platform is developed based on the Cypherium blockchain, driven by a team of alumni from Goldman Sachs, Citadel Securities, Google, and Uber, supporting long and short exposure trading of related assets.Deepsigma's perpetual contracts do not tokenize, custody, or physically deliver the underlying assets but instead track prices through external market data sources. The platform currently supports the S&P 500 Index, Dow Jones Industrial Average, Nasdaq Composite Index, Russell 2000 Index, Cboe Volatility Index, as well as contracts for crude oil, gold, silver, natural gas, and copper. The platform's risk engine employs multiple external price sources, mark prices, circuit breaker mechanisms, partial liquidation, and insurance funds, and uses a central limit order book and clearing layer to handle margin, collateral, and settlement.Deepsigma is also developing a decentralized identity framework based on zero-knowledge proofs and configuring off-chain AI analysis tools with no fund execution permissions; the underlying Cypherium utilizes a hybrid PoW and HotStuff Byzantine Fault Tolerance consensus mechanism, holding 4 U.S. patents.
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