Coinbase Research: Bitcoin Breaks Key Support, Market Possibly in Early Stage of Long-term Downtrend

According to Token Terminal data, over the past week, the volume of ETH bridged from Ethereum mainnet (L1) to Robinhood Chain (L2) has surged roughly 10-fold, surpassing $100 million. Robinhood Chain uses ETH as its native gas token, as noted. Token Terminal stated that if adoption of the chain continues to grow, it could become a new, significant source of demand for ETH.

According to official announcements, Binance Wallet has integrated Robinhood Chain. Users can directly access and trade tokens on Robinhood Chain via the Binance Wallet App and browser extension, delivering a more convenient multi-chain operation experience.

DigiTimes reports that fueled by surging AI demand and structural production capacity bottlenecks, the price of next-generation HBM4 may jump from $2 per kilobit to $4–5 or higher in the second half of 2026. This is partly due to the extreme complexity of HBM4 manufacturing: its production cycle lasts four to six months, and initial yields are notably low. Additionally, HBM production consumes approximately three times the wafer capacity of standard DDR5 DRAM, severely restricting the total memory volume manufacturers can output at existing facilities. (Jinshi)

Bitcoin’s BIP-110 proposal is approaching its early August deadline, yet miner support for the measure remains below 1%, signaling significant resistance to the initiative. Officially titled “Temporary Soft Fork for Reducing Data”, BIP-110’s core controversy centers on restricting non-financial data on the Bitcoin blockchain. The proposal aims to cap OP_RETURN data capacity within a year, ban most arbitrary data exceeding 256 bytes from being written to the chain, and limit certain script formats primarily used for data storage. Supporters argue the plan would refocus the Bitcoin network on its payment function and reduce node operational burdens; opponents counter that it would escalate policy disputes over block space usage into consensus rule changes, effectively determining which transactions qualify as “acceptable”. Strategy founder Michael Saylor and Blockstream co-founder Adam Back have both publicly opposed BIP-110. Saylor remarked, “There are 110 things more dangerous than junk data”, adding that the proposal would “turn the junk data debate into a consensus change, invalidating some currently valid transactions that pay fees”. Back stated that if supporters cannot accept the status quo, they may choose to fork, but “Bitcoin will not join”. Data shows BIP-110 uses a user-activated soft fork mechanism with a 55% miner signaling threshold, though miner signaling rates have never topped roughly 1% to date, with the current cycle sitting at 0 and no major mining pools backing the measure. The share of nodes running BIP-110 software also remains in the single digits, primarily from Bitcoin Knots users. The proposal’s current signaling cycle will end around block height 959,615, with a voluntary lock-in period expected in early August and activation targeted for around September. If broad support is still absent by then, the initiative could result in a minority of nodes forming a separate chain.

Crypto analyst Ali Charts noted in a post that Bitcoin is currently at a critical juncture for its next major move, with the $64,700 level serving as the key threshold to watch. If Bitcoin fails to break above the channel’s top at $64,700, it could trigger a deeper pullback. Should sellers hold that level, Bitcoin may dip to the channel’s mid-support at $63,000 and could further test the channel’s bottom around $61,500. However, Ali Charts added that a Bitcoin hourly close above $64,700 would invalidate the bearish outlook. After breaking through this resistance, Bitcoin could next target $66,400, with its second target set at $68,000.

The Kobeissi Letter stated that the U.S. economy is growing increasingly dependent on AI investment. AI investment now accounts for over 25% of U.S. GDP growth contribution, marking an all-time high. Related investments cover software, IT equipment, R&D, data center construction, and other areas. In other words, for every $4 of U.S. economic growth, more than $1 is driven by AI investment. At the same time, AI-related spending has risen to approximately 8% of U.S. GDP, also a historical record. By contrast, during the 2000 dot-com bubble, spending on IT equipment, software, and R&D peaked at around 6.5% of GDP. Today, U.S. economic growth is increasingly centered on AI.