https://t.co/Uo0F8wjFNSflyingtulip.com (@flyingtulip_):A unified onchain exchange, engineered from first principles.Stablecoin, money market, spot, derivatives, insurance.Better yield, better UX.Thanks @PineAnalytics for the thoughtful breakdown. ...

(Reuters) -Crypto exchange Kraken is in advanced talks to secure fresh funding that could value the company at about $20 billion, Bloomberg News reported on Friday. The funding would include a commitment of $200 million to $300 million from a strategic investor, the report said, citing a person familiar with the discussions. A spokesperson for Kraken declined to comment on the report. The deal, which is subject to market conditions, would follow the company's $500 million fundraising round at a $15 bill ...

Core Viewpoint - Boston Dynamics' Spot robot has showcased impressive new capabilities, including performing backflips, which highlights its advanced engineering and potential applications in various industries [1][3][5]. Group 1: Technical Achievements - Spot can perform multiple backflips and other complex movements, demonstrating agility comparable to that of a gymnast [3][5]. - The engineering team, led by Arun Kumar, initially doubted the feasibility of Spot performing backflips, indicating the experimental nature of the project [5]. - The training for these movements is not merely for show; it aims to ensure Spot can recover quickly from falls while carrying heavy loads in industrial settings [8][10]. Group 2: Training and Development Process - The development process involves iterative testing in simulation environments before deploying successful movements to the physical robot [11]. - The team utilizes reinforcement learning to enhance Spot's performance, achieving speeds over 5.2 meters per second, which is more than three times the default controller's maximum speed [13]. Group 3: Practical Applications - Since its commercial launch in 2020, Spot has been utilized in various industrial applications, including surveying at Ford factories and conducting safety inspections at Kia [14][17]. - Spot has also been involved in radiation surveys for Dominion Energy and automated inspections at Chevron's facilities, showcasing its versatility in different environments [16][17]. Group 4: Public Perception and Engagement - Public performances, such as those on "America's Got Talent," aim to change perceptions of robots, presenting them as engaging and beneficial rather than threatening [20][22]. - The deployment of Spot for unique tasks, such as delivering pizza for Domino's, illustrates its adaptability and potential for diverse applications [18].

渤海证券表示，8月以来人形机器人催化频出，近期英伟达发布新一代机器人计算平台Jetson Thor，在 性能及能耗表现较前一代产品实现大幅提升。我们认为，行业正处于产业落地关键阶段，计算能力的明 显提升将赋能人形机器人实现更高自主水平和控制能力，建议持续关注产业链投资布局机会。 今日截至10点17，机器人ETF（562500）上涨0.20%，在有限区间内震荡盘整，盘中两度实现翻红。成 分股方面，海目星领涨7.49%，亚威股份、大华股份均上涨超2%，奥普特、汇川技术等跟涨。流动性方 面，盘中成交金额达6.81亿元，市场交投活跃，量能持续释放。 消息方面，波士顿动力公司近日宣布，其四足机器人Spot通过强化学习成功完成多次后空翻动作，展现 出更强的动态控制能力。这一动作虽非客户需求，但训练过程显著提升了Spot在跌倒或滑倒时的自我保 护能力。Spot的行走姿态也因训练变得更加自然，更接近真实动物。Spot甚至能在前腿加装滚轮的情况 下保持平衡，展现强大适应性。 机器人ETF（562500）是全市场唯一规模超百亿的机器人主题ETF，成分股覆盖人形机器人、工业机器 人、服务机器人等多个细分领域，帮助投资者一键布局机器 ...

Program Highlights - Introduces a new VIP Program offering ultra-low maker & taker fees [1] - The program spans across Spot, Futures & Options trading [1] Target Audience - Targets volume traders seeking a competitive edge [1]

Complete simple tasks under our key Bybit features.🔥 Spot, Futures, Earn, TradFi and Bybit Pay. ...

seems everyone is competing to have a super app combining stocks, spot, perps, and prediction marketspeople are imo distracted by AI and are underestimating how much of a role crypto plays in the next few years ...

Core Insights - The breakthrough success of Physical Intelligence's π VLA model marks a significant turning point in the robotics industry, revealing the complexity and fragmentation involved in building true robotic intelligence [1] - The future of robotics will not be about creating more human-like robots but rather about developing a more powerful and flexible technology stack [2] - The article emphasizes that the next wave of successful robotics will focus on diverse forms shaped by tasks, terrain, and environments rather than converging on a single humanoid form [6][14] Group 1: Robotics Evolution - The robotics technology stack is undergoing a major deconstruction, similar to the development of autonomous driving and VR industries, where specialized companies excel in specific areas rather than trying to dominate the entire industry [1] - The success of the π0.5 model raises the stakes for the entire industry, as robotics must prove itself in the real world filled with physical constraints [1] - The article draws parallels between the evolution of robotics and the concept of carcinization in biology, where different species evolve similar traits to adapt to their environments [5] Group 2: Human-like Robots vs. Functional Design - The assumption that robots must mimic human forms to be effective is termed the "humanoid fallacy," which overlooks the potential for innovation through non-human designs [8][9] - The efficiency of bipedal locomotion is questioned, with evidence showing that wheeled robots are significantly more efficient than humanoid robots [9][11] - Successful consumer robots, like vacuum cleaners, thrive not because they resemble humans but due to their unique designs that cater to specific tasks [10] Group 3: Practicality and Deployment - The article highlights that practical applications and deployment in real-world environments are crucial for generating valuable training data for robots [18] - Companies like Formic emphasize that the only way to achieve large-scale deployment is through useful robots that provide economic value from day one [18] - The focus should shift from creating humanoid robots to developing specialized robots that can perform tasks effectively in various environments [12][19] Group 4: Learning and Adaptation - The future of robotics lies in decoupling intelligence from specific forms, allowing for generalized learning across different embodiments [13][14] - Physical Intelligence's approach to cross-modal and cross-embodiment learning demonstrates that diverse data sources can enhance robotic learning and performance [17] - The article suggests that the next generation of robotics will benefit from a model that aggregates data from various physical forms and tasks, leading to improved generalization [16][17] Group 5: Robotics Stack - A clear hierarchical map of the robotics system is proposed, breaking down the components from data collection to intelligent control [20] - Each layer of the robotics stack supports the next, facilitating the flow of data from deployed robots into structured training for models like π0.5 [20]

Watch out for Spot!Boston Dynamics’ agile mobile robot has been on patrol at Cargill’s oilseed facility since mid-2024, helping out with routine inspections and visual safety checks.It’s all part of Cargill’s push toward more autonomous operations, where robots handle the rounds, and humans focus on bigger-picture tasks like predictive maintenance and long-term planning. ...

Watch out for Spot!Boston Dynamics’ agile mobile robot has been on patrol at Cargill’s oilseed facility since mid-2024, helping out with routine inspections and visual safety checks.It’s all part of Cargill’s push toward more autonomous operations, where robots handle the rounds, and humans focus on bigger-picture tasks like predictive maintenance and long-term planning. ...