Bitcoin Drops Below $109,000

Arbitrum released data showing that its overall network revenue in September surpassed $5 million, hitting $5.45 million, a new all-time record. The majority of this revenue came from Orbit licensing fees, amounting to $4.75 million, a sum likely tied to the robust trading activity on the Robinhood Chain during the month.

According to blockchain intelligence platform Arkham, it has marked Robinhood’s wallets across 12 blockchains, covering the Bitcoin network and Robinhood Chain, with total related crypto assets valued at approximately $24.96 billion. Robinhood holds 185,185 BTC worth around $15.59 billion, while its Dogecoin (DOGE) holdings are valued at roughly $2.88 billion.

Per PeckShield’s monitoring, the attacker behind the NEAR Intents exploit has transferred the stolen funds to KuCoin and bridged them to BTC. The attacker’s address has interacted with an address labeled as the North Korean Lazarus Group (0x098B7...E2f96).

Stacks co-founder Muneeb Ali announced in a post on X that he will serve as the new CEO of Stacks Labs. Last year, Stacks underwent an ecosystem restructuring, with Stacks Labs becoming its protocol operations hub. For the past year, Alex Miller held the interim CEO role at Stacks Labs. Ali stated, "I am more bullish on STX than ever before. Now that Bitcoin staking has been successfully launched, it’s time to double down on developing Bitcoin capital markets." Driven by this news, STX’s price surged 10.9% over the past 24 hours.

According to market data from BIT (bit.com), during U.S. stock trading hours, SVRN, a NEAR treasury-linked company, dropped more than 20% to trade at $39.49. Among AI stocks, optical communication concept stocks rallied strongly: LITE and COHR rose nearly 10%, AAOI gained 5.79%, while neocloud-related concept stocks saw broad declines, with SHAZ leading the fall, down 7.7% at present.

Insight Beating AI News Flash: Runway has released the robot model Praxis-1, applying the expertise from training AI video models to real-world robots. It first learns how objects move and how humans perform tasks from a large number of regular videos, then translates that knowledge into robot movements. Runway conducted an object placement test: after pre-training with internet videos, the robot’s average error was 16.1 cm; when using custom-collected teleoperation videos of robots, the error was 16.0 cm. The test covered 93 evaluation sets, with results nearly identical across the two training approaches. If this line of work can be scaled, the data gap plaguing robot training could expand by several orders of magnitude. Collecting data via human-operated robot teleoperation requires specialized equipment, space, and labor, while regular videos are already abundant online. Runway aims to repurpose these videos—originally not intended for robot control—into training materials for robots to master movements. Praxis-1 has been tested on multiple robot models from Noble Machines, Standard Bots, and Ultra, including robotic arms, dual-arm robots, and mobile robots. Runway also showcased that the same strategy can adapt from a studio setting to a kitchen to complete tasks. The model is currently only accepting early test applications; its weights are set to be released in the coming months, with parameter size and more comprehensive independent evaluations still undisclosed.