加密行业领导者再与白宫高层线上会议

cryptonewsPublicado em 2024-08-09Última atualização em 2024-08-09

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Podcast Notes: Hyperliquid Has Become the Top Interest Point for Traditional Hedge Funds

Empire Podcast hosts Jason Yanowitz and Santiago Santos discuss the surging institutional interest in Hyperliquid, a decentralized perpetual exchange, marking the highest level of engagement from traditional hedge fund managers since Paul Tudor Jones endorsed Bitcoin in 2020. The primary driver is the demand for weekend trading of commodities like oil, especially during geopolitical tensions such as the Iran conflict, as Hyperliquid provides the only active price discovery venue when traditional markets are closed. Trade XYZ, a front-end on Hyperliquid, has seen significant growth, with weekend oil price predictions having a median error of only 50 basis points. Santos predicts commodity trading volume on Hyperliquid will surpass Bitcoin within the year and that its market cap could rise from $25 billion to $100 billion. Other key points include Kraken raising $200 million at a reduced valuation of $13.3 billion, and the SEC clarifying that self-custodied DeFi frontends like MetaMask are not subject to broker-dealer rules, resolving a major regulatory uncertainty. The hosts also note the strong correlation between crypto and macro markets, with the S&P 500 posting one of its best 10-day rallies since 1950. They highlight MicroStrategy's continued Bitcoin acquisitions and the potential of real-world asset (RWA) tokenization as a key trend. The discussion concludes with skepticism towards many L2 projects, predicting a wave of protocols truly going to zero as capital concentrates in proven assets like Bitcoin and Hyperliquid.

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Podcast Notes: Hyperliquid Has Become the Top Interest Point for Traditional Hedge Funds

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a16z: The Next Frontier of AI, The Triple Flywheel of Robotics, Autonomous Science, and Brain-Computer Interfaces

a16z presents a comprehensive investment thesis for the next frontier of AI: Physical AI, centered on a synergistic flywheel of robotics, autonomous science, and novel human-computer interfaces (HCIs) like brain-computers. While the current AI paradigm scales on language and code, the most disruptive future capabilities will emerge from three adjacent fields leveraging five core technical primitives: 1) learned representations of physical dynamics (via models like VLA, WAM, and native embodied models), 2) embodied action architectures (e.g., dual-system designs, diffusion-based motion generation, and RL fine-tuning like RECAP), 3) simulation and synthetic data as scaling infrastructure, 4) expanded sensory channels (touch, neural signals, silent speech, olfaction), and 5) closed-loop agent systems for long-horizon tasks. These primitives converge to power three key domains: * **Robotics:** The literal embodiment of AI, requiring all primitives for real-world physical interaction and manipulation. * **Autonomous Science:** Self-driving labs that conduct hypothesis-experiment-analysis loops, generating structured, causally-grounded data to improve physical AI models. * **Novel HCIs:** Devices (AR glasses, EMG wearables, BCIs) that expand human-AI bandwidth and act as massive data-collection networks for real-world human experience. These domains form a mutually reinforcing flywheel: Robotics enable autonomous labs, which in turn generate valuable data for robotics and materials science. New interfaces provide rich human-physical interaction data to train better robots and scientists. Together, they represent a new scaling axis for AI, moving beyond the digital realm to interact with and learn from physical reality, promising significant emergent capabilities and value.

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a16z: The Next Frontier of AI, The Triple Flywheel of Robotics, Autonomous Science, and Brain-Computer Interfaces

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