Michael Saylor, MicroStrategy's executive chairman, says the company's new digital credit product "Stretch" strips away volatility and risk from Bitcoin. He tells Romaine Bostick and Katie Greifeld on The Close that MicroStrategy has launched four credit instruments this year worth $4 billion, with more to come. ...

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]

RT Michael Saylor (@saylor)Strategy is offering $STRC (“Stretch”), a new Perpetual Preferred Stock via IPO, to select investors. To view the press release, prospectus, and investor presentation, along with additional information about $MSTR, $STRK, $STRF, and $STRD, click here: https://t.co/hohIXoDc8z ...

Strategy debuts fourth preferred stock offering called 'Stretch' as bitcoin holdings top 600,000 BTC https://t.co/E93aQeXn3C ...