A crypto whale shorted Ethereum (ETH) with 25x leverage, holding a position worth $12.43 million.

12:30 p.m. ET yesterday, Donald Trump hosted a lunch at the White House with executives from multiple artificial intelligence firms. Attendees included Jensen Huang, Elon Musk, Mark Zuckerberg, Alphabet CEO Sundar Pichai, and Anthropic co-founder and CEO Dario Amodei, among others. After the lunch, Trump and a group of U.S. AI giants took impromptu questions from reporters. When asked about "AI displacing jobs", Trump called on Musk to respond. Musk blurted out "AI" out of habit before quickly correcting to "SI"—a detail that caught Trump’s attention, prompting the president to thank him repeatedly. Musk then stated that robots and superintelligence can bring significant improvements to humanity in fields like healthcare, and while future job markets and work tasks will undergo major changes due to AI, "the overall demand for humans remains very high". Anthropic co-founder Dario Amodei revisited his earlier call for "slowing AI development"—a stance that conflicts with Trump’s views—saying AI has enormous benefits but carries real technological risks, and how to address them is still under discussion. He again emphasized: "We need to work together to ensure we win safely". During the interview, the broader tech community generally viewed Amodei as overly nervous compared to Musk’s calm response. When introducing Amodei to reporters, Trump remarked, "Dario is great, whatever he says is okay". Amodei responded with an exaggerated, forced laugh, then awkwardly dropped his smile, bowed his head and said nothing, creating an awkward moment.

Trader 0x4287 opened a 5x long on 1.38M aster-2:native($1.05M) on @Aster_DEX and is currently sitting on an unrealized profit of over $137K(+65.36%).

Trader 0x4287 opened a 5x long on 1.38M $ASTER($1.05M) on @Aster_DEX and is currently sitting on an unrealized profit of over $137K(+65.36%).

Insight Beating AI Flash News: Frontier edge AI R&D firm Liquid AI has launched its first self-developed decision-making model, d1. Like Jev, d1 does not generate long texts; instead, it directly performs selection, judgment, and scoring, enabling agents to select tools, handle routing, and conduct audits. Liquid re-ran evaluations using Hugging Face’s decision model comprehensive benchmark Decision Index 0.2.1. d1 scored an overall 58.9, outperforming Jev’s 57.9. Across five major categories, d1 leads in art judgment, language understanding, and retrieval classification; it trails Jev slightly in tool calling, and lags by 8 points in knowledge reasoning. Liquid notes that d1 is the first model to surpass Jev in this evaluation suite. d1 is compatible with Jev’s three decision-making modes: Choice (selecting one from multiple options), Noul (true/false judgment), and Score (scoring against standards). A single request can complete multiple judgments at once, returning probabilities and structured results directly—no intermediate text generation and parsing required. d1 is now available via Liquid’s API, with a free tier named `d1:free`. The model’s weights and parameter size have not been disclosed, and Liquid plans to integrate it into OpenRouter.

According to market data from BIT (bit.com), during Wednesday’s U.S. pre-market trading, SVRN, the treasury firm of NEAR, added another 10.98% in pre-market hours after surging 29.34% the prior day. Fueled by NEAR’s recent momentum, SVRN has rallied 669% over the past month. Separately, SDEV, the treasury firm of SKY, jumped 108.28% yesterday, but dropped 13.44% in today’s pre-market trading.

Insight Beating AI Flash News: The OpenClaw Foundation has launched OpenClaw Enterprise (OCE), a solution enabling enterprises to uniformly deploy and manage long-running AI Agents on their own infrastructure. The project was first initiated internally at OpenAI before being donated to the OpenClaw Foundation, with development contributions from Red Hat, NVIDIA, and other partners. Its code is licensed under the MIT License, allowing enterprises to deploy it independently, and the official states it will remain permanently free. OCE primarily addresses management challenges after enterprises deploy Agents: administrators can centrally create multiple Agents, restrict access permissions for different users and Agents, and integrate isolation, auditing, and lifecycle management capabilities. The underlying models, Agent harness, and sandbox are all replaceable, with no mandatory dependency on OpenAI. OpenAI and Red Hat have already conducted internal trials. OpenAI’s internal Agent "Androidclaw" can read codebases, GitHub, and logs. When builds fail, it locates relevant pull requests (PRs) and attempts fixes; upon identifying product issues, it can trace faults, submit PRs with video evidence, and even merge them directly. However, OCE is not yet at the formal production stage. The official only recommends it for internal pilots, with version 1.0 scheduled to launch later this year.