AMD发布全开源MoE大模型Instella-MoE,16B参数规模挑战主流开源模型
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Opinion: The widespread adoption of inexpensive open-source models has led to a decline in the spot rental price of H100 GPUs and a drop in the token price index.
According to Mars Finance, on June 27, research firm Silicon Data released data indicating that the widespread adoption of inexpensive open-source models has led to a decline in the spot rental price of H100 GPUs and a drop in the token price index. However, the firm believes that this does not represent a weakening of overall AI demand. It points out that the large-scale shift of users to inexpensive open-source models has actually increased overall computing consumption, maintaining the demand for high-end computing resources.
The ENS governance crisis has escalated, and the community plans to propose delegating 5 million ENS tokens to reform the allocation of voting rights.
According to Foresight News , AvsA, a core contributor to the ENS DAO, recently released a draft proposal on the forum, suggesting reforming the DAO governance structure by delegating (rather than distributing) 5 million ENS tokens. According to the draft, the 5 million ENS tokens will be transferred from the DAO treasury to a multi-delegation contract, with 1 million tokens allocated to each of five stakeholder groups (users, integrators, developers, traditional domain name system participants, and the governance community). A maximum of 10 candidates from each group will be selected based on criteria. The delegated parties will not receive any financial rights in the tokens, only voting rights. If a party does not participate in voting for more than 6 months, their voting rights will be redistributed. The proposal is based on the fact that ENS governance is in crisis, with a single proxy holding enough voting power to pass any proposal independently, and total delegated votes continuing to decline, resulting in significantly low participation in recent proposal voting. This proposal is currently in the feedback collection phase and has not yet entered the formal voting process.
More severe than the dot-com bubble: Token consumption plummeted by 20%, and the gap between AI investment and sales growth reached 46%.
According to Beating's monitoring, the Silicon Data LLM Token consumption index, which tracks users' actual computing power expenditure, has fallen nearly 20% from its May high. This sudden halt in high growth sends a crucial warning to investors: large model vendors may be losing pricing power with cost-sensitive clients, and it has also raised doubts about the ultimate return on investment for the hundreds of billions of dollars in AI capital expenditure. The divide between bulls and bears has intensified. Bears point out that Allianz Research data shows the growth gap between AI investment and sales has reached 46%, exceeding the 32% imbalance seen during the 2001 telecom bubble burst. Bulls counter that while the average token price has plummeted by 90% since 2023, total expenditure has still nearly doubled, meaning the index decline is merely a structural digestion after price cuts stimulated consumption, and the long-term return on investment in the inference phase is far more optimistic than in the training phase. Increased policy regulation is translating into hidden compliance costs for enterprise users. Washington has imposed stronger policy scrutiny on the distribution and cross-border access of cutting-edge models (such as the release review of OpenAI and geopolitical export controls on Anthropic models). Coupled with the EU's Artificial Intelligence Act's stringent compliance requirements for top-tier models, this has placed a heavy policy burden on leading platforms. To mitigate geopolitical and compliance risks, corporate CFOs have a more rational reason to proactively shift their workloads towards lightweight models that are less subject to regulatory constraints. Subtle changes are also emerging in the hardware chip sector. Although orders for top-tier GPUs and high-bandwidth memory (HBM) are booked until 2026, with substantial supply-demand easing not expected until 2028, the market's main procurement focus has shifted from training chips to inference optimization hardware, and the winners are being reshuffled.
JPMorgan Chase: Large-scale model usage and GPU leasing prices rise simultaneously, continuing to support AI infrastructure demand.
According to Mars Finance, JPMorgan Chase's latest "Data Center Watch" report shows that in June, large model usage, API spending, and non-cloud vendor GPU leasing prices all strengthened, indicating that demand for AI infrastructure is still expanding. Although model token prices continued to decline year-on-year, the increase in usage has significantly offset the impact of price reductions, and the overall unit economics of model providers are showing an improving trend. (Cailian Press)
US AI chip stocks fell across the board in pre-market trading, with AMD dropping nearly 3%.
According to data from Odaily Odaily, AI chip stocks in the US stock market fell collectively in pre-market trading. Intel, Lattice Semiconductor, and AMD fell nearly 3%, while NXP, Qualcomm, Broadcom, Nvidia, TSMC, and Tesla fell more than 1%. Microsoft rose 1%, Amazon rose 0.5%, and IBM rose 0.4%. MSX is a leading RWA trading platform that has listed hundreds of RWA tokens, including popular US stock and ETF tokens such as NVDA, GOOGL, MSFT, AMZN, META, TSM, and AMD.
Shinhan Asset Management partners with Plume on tokenized fund pilot
Shinhan Asset Management and Plume will test a tokenized fund using a Korean won-denominated ultra-short-term bond fund as its underlying asset.