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Mount Archil's elastic POSIX file system in your E2B sandbox for high-performance, shared access to S3, R2, and GCS. One use case is spinning up large fleets of parallel agents on large datasets without bottlenecks. See how to get started below.

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Vasek Mlejnsky

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10,572 просмотров • 1 месяц назад •via X (Twitter)

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Here is a KEY experiment, which may determine whether we truly understand the physics of "UFO levitation"? In movie 1, we can see that lowering a spinning wheel will make a large base-wheel turn anti-clockwise. Or if we raise the same spinning wheel, that will make a large base-wheel turn clockwise. Now let's turn the experiment around! Instead of lowering or raising an upper spinning wheel, we can apply an external force, that makes the large base-wheel turn anti-clockwise, or else clockwise. What happens then to the upper spinning wheel? Will it still go up or down as before? 🥳🛸 In slide 2, we can see one of many examples drawn in crops (by friendly aliens), to suggest that "spinning one wheel" (say a large base-wheel) will cause another spinning wheel (say a small upper wheel) to "lift up". Such a novel "lifting motion" will not cause any downward Newtonian action-reaction, because all of the force is applied as a horizontal spin-torque to the large base-wheel. It seems like "magic", but that may be how Nature works! I will do this critical experiment in a few weeks, once some needed parts arrive. Meanwhile if other inventors would like to have a go, please feel free, and communicate your new results here. 🛸

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Dennon Lewis 🏃‍♂️💨 To produce high volumes of sprinting you have to train for it; you cannot hope to turn up on a Saturday and just repeatedly output sprint after sprint without conditioning yourself for it. Dennon records the highest sprint for a large percentage of Dorking’s game, this is down to his position and style of play but as mentioned above, his training has to replicate that. If you’d like to find out more about how your training should be tailored to complement your game, reach out and let’s get a plan in place 💪

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How do you deploy AI agents for financial institutions without compromising on security, isolation, or scale? Rogo powers complex research, analysis, and deal workflows for leading financial firms, supporting complex tasks across tens of thousands of concurrent users. To meet the diverse needs of financial teams, Rogo relies on both specialist and general-purpose agents that can adapt to a wide range of workflows. With Claude Managed Agents and self-hosted sandboxes, Rogo gets the orchestration and post-training capabilities needed to design these agent systems, while E2B provides the execution layer underneath. Every piece of code generated by an agent runs inside its own E2B sandbox with full auditability and traceability. Each sandbox is powered by an isolated microVM, providing the kernel-level isolation critical for Rogo's customers. The result is a seamless agent experience backed by the security, reliability, and compliance requirements that financial institutions demand.

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