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Flash

first_img MegaETH ecosystem MNX launched, introducing futures for private AI companies such as OpenAI

According to CoinDesk, the cryptocurrency exchange MNX, developed by the prediction market platform Manifold Markets, officially launched on Tuesday, offering futures contracts linked to the valuations of private AI companies such as OpenAI, Anthropic, DeepSeek, and Moonshot. The platform is built on the MegaETH blockchain and completed a $6.4 million funding round in June, led by Village Global.Compared to existing products from OKX and Bitget, MNX's contracts expire at the end of 2027 and do not charge periodic funding rates; the perpetual contracts offered by Bitget and OKX have no expiration date. Max Killberg from Village Global stated that AI is driving one of the largest investment cycles in history, but the financial infrastructure surrounding it remains quite underdeveloped. The organization hopes to build financial markets around AI rather than just betting on another prediction market.Stephen Gruggett, co-founder of Manifold Markets, indicated that MNX's model is better suited for private companies like OpenAI and Anthropic, which have infrequent equity trades and are difficult to price. Traders can use up to three times leverage, with prices determined by trading activity on the MNX platform rather than external price sources.If the company is still not publicly listed when the contracts expire, the exchange will use public valuations from funding rounds, investment funds, or secondary markets; MNX currently does not serve U.S. customers but plans to obtain the necessary licenses and intends to launch markets covering a broader range of the AI economy, including company revenue, employment, housing, AI supply chains, and computing power.

The success rate of the Zhipu legal model is nearly three times higher, and the testing cost is about one-seventieth of that of its competitors

The artificial intelligence company Zhipu released a legal-specific model GLM-Legal, which is further trained based on GLM-5.3-Flash. In the Harvey LAB evaluation covering 24 categories of legal services, the task pass rate increased from 6.7% to 19.2%, nearly tripling the original version, surpassing models like Kimi K3 and Claude Fable 5, and ranking seventh on the Vals AI leaderboard.When reviewing software service contracts, GLM-Legal suggested shortening the termination notice period from 60 days to 30 days and required service providers to offer up to 90 days of handover support. In another software project dispute involving 40 documents, it found that the company reported to the client that the project was 60% complete, while internal records indicated only about 41%. It also identified emails from the CEO requesting to conceal risks and continue charging, and analyzed potential legal liabilities in conjunction with contract terms.According to independent evaluations by Vals AI, the cost for GLM-Legal to complete a test is $0.15, while the closely performing Gemini 4 Argon costs $10.55, a cost difference of about 70 times. GLM-Legal took an average of 72 minutes, while the latter took 44 minutes. Zhipu stated that the model was trained specifically on legal data and conducted reinforcement learning in tens of thousands of simulated legal environments. Currently, GLM-Legal requires an API trial application.

first_img The funding gap for Bitcoin mining companies is about 50 billion USD, and the borrowing costs for IREN and others are diverging

According to the Miner Weekly briefing published by BlocksBridge Consulting, Bitcoin mining companies expanding into the fields of artificial intelligence and high-performance computing are facing significantly different borrowing costs, with lenders increasingly scrutinizing large data center projects. The briefing points out that securing large AI clients is only part of the challenge; mining companies also need to raise billions of dollars to purchase computing power equipment, build data centers, and ensure the power infrastructure required for contract fulfillment. BlocksBridge indicates that large lending institutions have become more selective about data center loans, with decisions increasingly depending on client qualifications, contract terms, and project completion paths.The transition from Bitcoin mining to AI infrastructure by IREN reflects the differences in financing costs: the company secured $3.65 billion in GPU financing in June at a blended interest rate of 6%; in August, it completed another $2.4 billion financing with a fixed interest rate of 9%. The two agreements correspond to different projects and are not directly comparable, but they show that even within the same company, borrowing costs can vary significantly. Financing arrangements may also incur costs beyond interest; in another transaction involving Cipher Digital, Google guaranteed a $1.4 billion lease obligation in exchange for warrants representing a 5.4% equity stake in Cipher, with exercising the warrants potentially diluting existing shareholder equity.The rise in financing demand highlights the overall challenges mining companies face in entering the AI market. Data from VanEck shows that during the peak of the Bitcoin bull market in October last year, mining company debt surged by approximately 500% compared to the second quarter of 2024.
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