WEBVTT

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Welcome to staff.

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Hi.

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I'm Artichiro Seda from NTT.

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Today, I want to talk about the update in Deamer Project 2.0.

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And in this series, we are expanding the project focus to cover

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protecting AI, as well as Israeli running continuous on laptops.

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So, by the Deamer Rema stands for Phoenix Virtual Machine,

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it's optimized for running containers and AI agents,

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but early candidates for other workloads as well.

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And Deamer features automatic host-of-fire system sharing

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that means the host-of-fire system can be easily shared

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to the guest operating system.

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And it also supports automatic port routing.

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That means you can access to the TCP IP ports of the guest office,

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just as the local host on the host operating system.

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So, you can just access the guest IP, just as the local host on the web

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roles that run on the host operating system.

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And Deamer comes with built-in integration for several

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container-owned times, including continuity, which is a default.

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And it also supports Joker, Potsumer, Kubernetes, and Aptiner.

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And Deamer supports several host operating systems,

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but in the case of Mac OS, you can just use BooRue to install Deamer,

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BooRue install Deamer, and you can use Deamer CityRs

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to stretch our virtual machine.

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And you can just prefix as a Deamer command in the disk commands,

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such as not a cityR, not a cityR means continuity,

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cityR uses the whole controlling or continuity.

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Basically, it's similar to Joker.

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So, this is Mac OS, and you can just prefix Deamer to unin,

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and it's not Linux.

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And inside Deamer share, the host directory is visible.

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This is mounted on the Mac OS host operating system.

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And you can run continuous using another cityR commands.

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This run is another cityR container, who running nzx.

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And you can just access to the test port as a Joker host.

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So, this is conducting through the disk as a Joker host.

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So, basically, it just looks like a process,

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running on the host operating system directly.

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But actually, it's wrapped inside the virtual machine.

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So, share is this, the project similar to Deamer.

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One example is WSC2.

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So, with WSC2, the Windows host file system is visible to the Linux disk.

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And the disk disk ports are just accessible as a Joker host on the Windows host.

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So, it's a very similar to Deamer.

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But WSC2, of course, only supports Windows host.

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And Deamer is also similar to big runs in some sense.

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But big runs is not property.

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And big runs also missing some features, such as automatic port running.

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So, you can just configure big runs to who are the ports.

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But it doesn't automatically scan ports used in the test operating system.

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So, it's quite different from Deamer in the sense.

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And also, Deamer is a very similar to the Kamasin,

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but it's only made for Joker.

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And it's now abandoned a few years ago.

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And Deamer is also similar to the Catastop, but without GUI.

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But the Catastop is just made for Joker.

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Of course, and it's property.

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And let me talk about origin of the project in the current status.

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So, I launched the project five years ago,

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for the sake of promoting Continuity,

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including Neurosyti, to Macintosh users.

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So, this project was originally designed as Continuity in Macintosh.

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But through the growth of the community,

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the scope has expanded, that's just for a Continuity.

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So, it's the Linux Macintosh Continuity in Macintosh.

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So, we support several Continular engines, including Joker,

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Pokémon, Kubernetes, and Optiner.

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And we also support Neon Continular workloads.

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For example, it's also used for Santa Boxing AI Coding Agents.

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So, you know, if you run AI Coding Agents like Cloud,

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it's Accentary rooms, everything under your home directory,

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or maybe it's installs some run-down properties from Internet.

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So, it's really scary to run AI Coding Agents

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or you are up directly.

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So, you can use Dima to send up such AI Coding Agents.

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And Dima is also used for when you want to run a No Ubuntu OS,

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such as Hydra on GitHub Actions.

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There was a GitHub Actions on this support.

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Ubuntu has a Linux list,

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but you can just run Dima inside GitHub Actions.

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So, you can run any distribution, such as Hydra,

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or Apprentices, or Work Linux, or Analytics, or Apprentices,

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or Alpine, and other distributions.

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And there's GitHub Actions.

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And Dima is originally made for Macintosh,

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but we now support several HOST operating systems,

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including Linux, Windows, KBC, and Dregal, Privacy.

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We don't support privacy, because our client doesn't really work well on privacy HOST,

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but I think we can see a real support privacy as well.

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And we have lots of separate free software projects based on Dima.

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The most of the famous one is Coding Mer.

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This is an alternative CRI for Dima,

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with Dregal at the default engine.

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So, Coding Mer is very famous.

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Maybe it's more famous than Dima itself.

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It has a very huge number of GitHub stores.

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So, with Coding Mer, you can just run Dregal on Mac OS, very easily.

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And it doesn't need a proprietary Dregal,

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just to write this.

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And also, there's a run chat desktop by Susie.

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It's a combination of Dima and K3S and GUI.

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So, this is a screenshot of run chat desktop.

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And with this GUI dashboard,

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you can check near the status of the Dima run chat desktop.

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If running Q3S, this is also free software.

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And the next one is a print.

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It's AWS product.

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And it's made for local development with AWS services,

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such as AWS server,

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application model, AWS some.

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They recently announced this support.

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And which is also free software as well.

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And there are projects that Dima and GUI,

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which provides GUI based on Q2 framework, like this.

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And also, potman desktop supports managing Dima instances,

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as well as native potman machine instances.

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And we have more supported projects.

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So, let's talk about how it works.

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So, this is a texture of the Dima.

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So, there is a Dima set here.

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CRI, quanti interface.

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This is used by Shuman or GUI or MCP programming.

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And this CRI can be used for managing the Dima host agent processes.

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And host agent process is a medium driver

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to support a server or partner machine implementations.

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And this Dima branches BM and also connects to the network driver.

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And instead of BM, we have a Dima agent process,

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which handles fire system sharing and port routing,

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and thinking real-time cook,

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or other jobs.

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And Dima is designed to be compatible

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to support different implementations of hyperbysers,

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such as QEMU or Apple's port rotation framework,

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and then was busy or macOS.

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We also support WSR2 or Windows hosts.

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And in budget 2.0 of Dima,

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we added support for care on kit,

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which supports GPU acceleration on macOS.

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And in Dima budget 2, we also support

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GRPC programming to support your favorite hyperbysers implementation.

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And we also have the concept of interon urm binary effectors.

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So the default is a two-emil user mode.

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So you can just run interbysers on the urm instances of QEMU.

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And on macOS hosts, you can also use Ruse 2,

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which is more fast faster than QEMU.

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And for fire system sharing, we support bar value FS

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and bar value 90.

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And we also support reverse SSH FS.

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When the guest operating system doesn't support bar value FS

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and bar value 90.

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And for networking, the default is user mode,

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network based on G-byser.

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So this company works in the user space,

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so it doesn't need any root privilege on the host.

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But when you want to access the virtual machine by IP,

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not just by the Ruka host address,

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you can use a solid BM8 driver.

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This needs root privilege,

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so you have to run it with SIDO.

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And for busy driver, you can automatically use

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a busy network driver to access the BM by IP.

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This one only works with busy,

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but this doesn't need SIDO command.

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And for port routing, we watch EVP events.

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It's a net link, SOC diagnosis events.

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And we use EVP to watch this port routing events.

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But this information doesn't work for keyboard service ports.

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Because keyboard service ports are quite different from regular ports,

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because it uses IP tables.

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So we also have a custom logic for what's in keyboard service ports.

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And it's a default,

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this row of the keys to waste is Ubuntu,

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but you can also choose other distributions,

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such as R-marinux,

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by R-Prinux, Center of Stream,

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DBN, Open Source, Oracle Linux,

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and Rukinux.

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And default contenting is contenting,

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but you can also use Apptina,

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or Pottina, in Rukinux mode by default,

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or in Rukinux mode,

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when you need privileged operations.

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And you can also use several functional testimonials,

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such as Kubernetes.

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And you can just choose your template using this

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and set your stats command.

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And let me talk about recent updates.

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So we recently got promoted to sensitive,

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incorporating projects.

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CNCF stands for CRAT Native Computing Foundation,

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which is hosting several projects,

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such as Kubernetes.

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And CNCF has three strategies,

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sandbox incubating and graduated.

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We joined CNCF as a sandbox in 2022,

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and we got promoted to interpreting that year.

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And we anticipate that we can promote it

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to the graduate level in the next couple of years.

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And the number of Retopsters is growing.

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So we now have more than 20,000 upstairs,

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and we have more than 170 contributors,

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so thanks to all the contributors and all the users.

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And in November, we released a remote version to 0,

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and this is the product infrastructure

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to other implementing new features

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without modifying remote.

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So we have the concept of VM driver programs

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to support additional hyperbysers,

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and we also support CRAT programs

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to add more subcommands to the DMACTS CLI.

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And we also have programs for URL schema

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for affecting templates from custom remote addresses.

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And we support GP Accertation using

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Clarity to VM driver.

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And we also added MCP server,

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model.pl.pl server for protecting AI agents.

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So in this case, we are extending things

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to cover AI as well as consumers.

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So the original goal in 2021 was to facilitate

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running continuity on Mac OS,

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but the project turned out to be ready to use

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for securing AI agents too,

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so as to prevent them from accessing the host of files

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and the commands.

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So you know, AI agents may make

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hallucination to remember files under the home directly.

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So this example is from Reddit,

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but this example quote,

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I tempted to clean up some packages and unused files

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and quote,

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launched RMR commands to test,

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test, test, press, press.

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And the program is that it even limits

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the home directly to the source.

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So it removes everything in the home directly.

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So it's very scary to run AI on your laptop directly.

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So it reminds useful for securing such AI agents.

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And I also have to note that AI may also make hallucination

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to install fake packages with possible names

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by running PPM install or MPM install

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or go install or whatever else.

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And AI agents now have a web search tool

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and AI agents are sometimes deceived

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by fake websites,

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once they're internet appears the web search tool

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to install some malicious purchases.

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So AI agents often come with a built-in sandboxing

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who is an example, they use a dandroque

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or the car container or Linux,

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but it's not as strong as virtual machines.

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And some AI agents use a sandbox exec,

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which is similar to dandroque or macOS,

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but this sandbox exec command has been

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deprecate almost a decade ago.

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And Apple recommends using up sandbox,

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but it's not direct refreshment

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through sandbox exec commands.

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So AI agent products are still

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relying on sandbox exec commands.

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So we can use Dima as a reversal sandbox

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for any AI agent.

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And it's also, it can coexist

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with the built-in sandboxing

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provided by AI agents.

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And we're running AI with Dima

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there are two scenarios.

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AI inside Dima and AI outside Dima.

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So AI inside Dima is running

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code x, compile, or code, or Gemini

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or maybe open code inside Dima.

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And you can also do an inference inside Dima

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using GPU acceleration.

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And AI outside Dima means

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AI agent running on the host

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can connect to Dima.

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And Dima provides MCP servers

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for protecting five system course

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and command execution course.

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And you can also use PIS code and remote SSH

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and compile routes with Dima.

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And we have an example of running AI inside Dima.

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For example, you can use this Dima city

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or start command to own the monster

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directly in mid-right mode.

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And we can install open code.

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So I don't have time to show the demo.

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But inside the website, we have example

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for continuous.

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And we also have examples for AI agents.

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So you can choose a credit code or code x

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or Gemini or GitHub compile route.

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And you can just run its inside Dima.

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And we also have GPU acceleration.

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So Dima CPP running inside Dima uses

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a parking to talk to a partner or GPU.

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And the partner or GPU talks to multi and brick

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which translates a parking right-body call

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to make a library course, which is used by Apple.

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I think I can show a quick demo.

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So this is using a parking GPU,

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a partner or GPU binas, a point for max.

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And I can talk to AI running inside Dima.

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Yeah, so the performance is not so much.

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And for running AI outside Dima,

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Dima exposes several MCP tools,

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such as district free,

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the right-body run share command.

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These are a similar to Gemini CLIs commands,

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but it's a strong risk on the box using BM.

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And we plan to raise the budget to a point

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to run in March.

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And in this race, we have sync modes.

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Unlike months, sync devices are written

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but only after user information.

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So this prevents AI from the situation

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where a story, I regrouped everything including

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AI.

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So this should be highly useful running AI

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in the inside Dima.

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And I don't have time to cover our future ideas,

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but we've come contributions in this field.

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And we have a huge community,

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and we have website, GitHub, and Slack, and Twitter,

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and must-do.

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And thank you.

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Thank you.

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Any questions?

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Sorry.

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Can you have multiple instances of Dima

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on different posts and talking to each other?

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They have to run on the same post.

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So, yeah.

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Yes.

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On one system.

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So you can use a bridge device

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to directly connect virtual machine

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to the host network.

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So you can just connect multiple instances

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running on several posts.

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What have you received, too?

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Actually, I don't use WC2 by myself,

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so I'm not sure about WC2 implementation.

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These are a lot of the big questions.

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That's it.

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Thank you.