News linked to both this project and an event.
According to the official announcement, HTX recently officially launched the first "Quant Master Trading Competition", aiming to build a stage for real competition and strategy verification for professional quantitative teams and API strategy traders. From now until September 14, 00:00 (UTC+8), API quantitative trading users who register for the competition and meet the specified asset and trading volume requirements will be ranked in three major leaderboards and share the prize pool based on the trading volume, profit amount, and profit rate generated by their spot and contract API trading. The total prize pool will be unlocked tier by tier according to the cumulative trading volume of all participants, up to a maximum of 1,000,000 USDT. In addition, the Quant Master Trading Competition also features bi-weekly phase rewards, and the Top 3 strategies on each leaderboard can win $HTX reward funds. New users who register for the competition can also enjoy 4 exclusive benefits, including Prime 11 exclusive low fees, early bird rewards, broker activation rewards, and interest-free loans up to 50,000 USDT.
According to official announcements, Tencent Cloud has officially launched Agent Bucket, providing independent cloud space for a massive number of Agents to uniformly store user-uploaded materials and files such as reports, images, and code generated by Agents. The product introduces independent Space units under the Bucket to achieve fine-grained isolation and management at the single Agent or user level for access credentials, capacity quotas, read/write rate limiting, and more.
Apollo Chief Economist Torsten Slok issued a risk warning, stating that major AI companies are heavily borrowing for industrial expansion, with the total scale of related bond issuance estimated to reach $700 billion. This massive new supply is diverting market funds, creating a significant crowding-out effect on U.S. Treasuries and other credit products.Torsten Slok stated that if the scale of debt financing for AI infrastructure continues to expand, the overall capital allocation logic in the bond market will undergo a restructuring, persistently suppressing demand for U.S. Treasuries while exerting medium- to long-term pressure on the liquidity of the entire credit market.
Elon Musk posted on X, stating that the latest completed training run of Grok V9 (1.5T parameters) has "performed very well," and this result has not yet incorporated the supplementary training portion from Cursor data. The base model currently under internal development is V9, with approximately 1.5 trillion parameters. Compared to V8, it features significant improvements in data cleaning, training methods, model scale, and has been optimized for the Blackwell architecture to enhance computational efficiency.Musk emphasized that, in contrast, the current public-facing version v4.2, built on the V8 base model with approximately 0.5T parameters and running on the Hopper architecture, still has certain limitations in training data quality and coverage. The performance gap between Grok V8 and V9 is massive, with the new-generation model achieving a leapfrog upgrade in overall capabilities.