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Article
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first_img Robinhood Chain saw over 17% of tokenized stocks locked in Meme coin trading pairs, with 31% of the trading volume coming from Meme coin pairs

DeFiprime founder Nick Sawinyh analyzed that the Meme coin issuance platform on the Robinhood Chain is massively using tokenized stocks as paired assets. As of September 1, approximately 17.2% of the on-chain supply of 19 high liquidity Robinhood stock tokens is locked in 432 pools that use stock tokens as quoted assets, contributing 31.3% of the DEX trading volume of related stock tokens in the past 24 hours. The four issuance platforms Long, Bankr, Flap, and PAIR have set stock-paired Meme coins as default products.Among them, the AI/NVDA pool holds 8,783 NVDA (accounting for 16.2% of the total on-chain tokenized NVDA), with a 24-hour trading volume of about $6.2 million; the BONER/HIMS pool holds 37,172 HIMS (accounting for 50.4% of the total HIMS on the chain), with a trading volume of about $12.5 million. This mechanism has led to significant premiums for some tokenized stocks over the weekend (when issuers cannot issue more), with HIMS once trading at a premium of 112% compared to the NYSE closing price. The TVL of the Robinhood Chain has nearly doubled since August 1 to $740 million, with on-chain DEX daily trading volume reaching $1.49 billion on August 31. The analysis points out that 9 stock tokens have an on-chain circulating market value of less than $1.5 million, and a single Meme coin pool can absorb a large proportion of the circulating supply. This analysis is based on specific block snapshot data, with prices and pool balances changing rapidly.

first_img Micron warns that AI storage walls are intensifying, with HBM accounting for about 17% of the interruptions in Meta Llama 3 training

According to TrendForce, at Hot Chips 2026, Micron emphasized that the progress of AI computing power is faster than storage improvements, and the challenge of the "storage wall" is becoming increasingly prominent. Micron Fellow Raghu Sriramaneni pointed out that the computing power of AI accelerators increases approximately threefold every two years, while the bandwidth of HBM increases by less than double during the same period, and the gap may further widen. The deepening reliance on HBM also brings reliability issues; Micron cited Meta Llama 3 data indicating that HBM failures account for about 17% of unexpected training interruptions. New designs that blur the boundaries between computing and storage may help break through the bottleneck.The expansion of HBM also brings area and supply pressures: the latest generation of packaging integrates two GPUs with eight 12-layer HBM4 stacks, with storage accounting for about 90% of the semiconductor area, more than eight times the area occupied by GPUs; achieving equivalent capacity with HBM requires about three times the wafers of standard DDR5 DRAM. Thermal management has also become a key constraint, with solutions such as liquid cooling and ultra-thin chips being explored.Micron is advancing innovations in interconnect, packaging, and cooling, including SerDes and die-to-die PHY optimized for storage, larger size SiP and advanced packaging with glass substrates, as well as liquid cooling and hybrid bonding, and is developing fusion bonding to reduce thermal resistance and enhance data throughput.
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