10 #Bitcoin ETFs inflows 7,066 $BTC(+$703.6M) and 9 #Ethereum ETFs inflows 14,425 $ETH(+$48.32M) yesterday.

According to Lookonchain's monitoring, the Binance attacker made an operational error while selling altcoins, dumping 908,793 PROM tokens (valued at around $5 million) into a nearly depleted liquidity pool on Uniswap V2. The attacker ultimately received only 0.0316 ETH, worth approximately $71, meaning the single operation resulted in a loss of roughly $5 million for the attacker.

The Binance hacker made a $5M mistake while dumping altcoins! The hacker sold 908,793 $PROM (worth ~$5M) into a nearly empty Uniswap V2 liquidity pool and received just 0.0316 $ETH ($71).

Binance has issued an update on its security incident recovery, announcing that Phase 1 withdrawal services will resume from 14:00 to 17:00 Beijing Time (06:00 to 09:00 UTC) on November 1. The first batch of supported networks and assets include BTC, ETH, BNB, TRX, SOL, XRP, ZEC, DOGE, TON, POL, AVAX, ARB, BASE, OP, and SUI. Deposit services remain fully open and unaffected by the incident. The exchange noted that withdrawal resumption will be phased, with specific assets and networks prioritized based on user demand data from the past week, and will be gradually rolled out after completing security and stability checks. Other networks and assets will be restored sequentially once ready. Due to high initial traffic, some users may encounter withdrawal delays or failures and are advised to retry later.

Security firm Blockaid has detected that Premia Labs' protocol on Arbitrum is facing a sustained attack. Attackers created empty option pools, utilized flash loans to purchase options, locked vault collateral in the relevant pools, and subsequently withdrew assets as liquidity. As of Blockaid's announcement, attackers have transferred approximately $400,500 in assets from the vault via around two transactions, and the attack remains ongoing.

Beating AI Flash News: Elon Musk disclosed that Memphis-based supercomputing cluster Colossus 2 plans to deploy around 1.2 million NVIDIA Blackwell GPUs by the end of the year. Two additional facilities will launch soon: Gun Range is set to roll out 220,000 GB300 GPUs by the end of November for model training; Spam, converted from a warehouse originally used to store goods like luncheon meat, will deploy around 200,000 GB300 GPUs exclusively for AI inference. Currently, Macrohard is equipped with 110,000 GB200 GPUs and 220,000 GB300 GPUs, while Macroharder and Minihard each have 220,000 GB300 GPUs. Adding the planned 420,000 new GPUs, the five clusters will total around 1.19 million GPUs. Training and inference workloads have distinct network requirements: Macroharder, Minihard, and Gun Range all use 800Gbps network cards, while Spam’s inference tasks do not need the same level of high-speed interconnection. Musk noted that its network configuration is simpler, requiring less than half the fiber optic cable of training facilities.

Beating AI News: Meta partners with Shanghai-based Fourier Intelligence to develop humanoid robot prototype Max in just three months. Built on Fourier’s hardware and technical accumulations from its first three generations of humanoid robots, Max saw Meta primarily adjust its body proportions, head design, and cameras, plus add components like both hands. Meta’s Vice President of Robotics Products spent nearly two months at Fourier’s Shanghai factory, completing an internal demonstration at the end of August. When Meta established its robotics team last year, it aimed to create an "Android of the robot world": developing its own AI software to enable robots from various manufacturers to use it. CTO Bosworth noted at the time that running and jumping robots are not the biggest challenge; the real bottleneck lies in fine manipulation—for example, picking up a cup of water without crushing it or spilling it, which requires AI to understand the physical world and master precise control over force and movement. The partnership with Fourier lets Meta avoid building the robot body from scratch, speeding up such experiments. Max stands about 1.5 meters tall, is equipped with NVIDIA Jetson Thor chips, and its five-fingered hands can grasp small bottles and toys. The two sides launched Max 2 in September, focusing on improving bilateral hand operation and stair-climbing capabilities. Meta’s long-term goal is to integrate its Muse AI agent with a physical form to enter homes and perform practical tasks.