Welcome to staff.
Hi.
I'm Artichiro Seda from NTT.
Today, I want to talk about the update in Deamer Project 2.0.
And in this series, we are expanding the project focus to cover
protecting AI, as well as Israeli running continuous on laptops.
So, by the Deamer Rema stands for Phoenix Virtual Machine,
it's optimized for running containers and AI agents,
but early candidates for other workloads as well.
And Deamer features automatic host-of-fire system sharing
that means the host-of-fire system can be easily shared
to the guest operating system.
And it also supports automatic port routing.
That means you can access to the TCP IP ports of the guest office,
just as the local host on the host operating system.
So, you can just access the guest IP, just as the local host on the web
roles that run on the host operating system.
And Deamer comes with built-in integration for several
container-owned times, including continuity, which is a default.
And it also supports Joker, Potsumer, Kubernetes, and Aptiner.
And Deamer supports several host operating systems,
but in the case of Mac OS, you can just use BooRue to install Deamer,
BooRue install Deamer, and you can use Deamer CityRs
to stretch our virtual machine.
And you can just prefix as a Deamer command in the disk commands,
such as not a cityR, not a cityR means continuity,
cityR uses the whole controlling or continuity.
Basically, it's similar to Joker.
So, this is Mac OS, and you can just prefix Deamer to unin,
and it's not Linux.
And inside Deamer share, the host directory is visible.
This is mounted on the Mac OS host operating system.
And you can run continuous using another cityR commands.
This run is another cityR container, who running nzx.
And you can just access to the test port as a Joker host.
So, this is conducting through the disk as a Joker host.
So, basically, it just looks like a process,
running on the host operating system directly.
But actually, it's wrapped inside the virtual machine.
So, share is this, the project similar to Deamer.
One example is WSC2.
So, with WSC2, the Windows host file system is visible to the Linux disk.
And the disk disk ports are just accessible as a Joker host on the Windows host.
So, it's a very similar to Deamer.
But WSC2, of course, only supports Windows host.
And Deamer is also similar to big runs in some sense.
But big runs is not property.
And big runs also missing some features, such as automatic port running.
So, you can just configure big runs to who are the ports.
But it doesn't automatically scan ports used in the test operating system.
So, it's quite different from Deamer in the sense.
And also, Deamer is a very similar to the Kamasin,
but it's only made for Joker.
And it's now abandoned a few years ago.
And Deamer is also similar to the Catastop, but without GUI.
But the Catastop is just made for Joker.
Of course, and it's property.
And let me talk about origin of the project in the current status.
So, I launched the project five years ago,
for the sake of promoting Continuity,
including Neurosyti, to Macintosh users.
So, this project was originally designed as Continuity in Macintosh.
But through the growth of the community,
the scope has expanded, that's just for a Continuity.
So, it's the Linux Macintosh Continuity in Macintosh.
So, we support several Continular engines, including Joker,
Pokémon, Kubernetes, and Optiner.
And we also support Neon Continular workloads.
For example, it's also used for Santa Boxing AI Coding Agents.
So, you know, if you run AI Coding Agents like Cloud,
it's Accentary rooms, everything under your home directory,
or maybe it's installs some run-down properties from Internet.
So, it's really scary to run AI Coding Agents
or you are up directly.
So, you can use Dima to send up such AI Coding Agents.
And Dima is also used for when you want to run a No Ubuntu OS,
such as Hydra on GitHub Actions.
There was a GitHub Actions on this support.
Ubuntu has a Linux list,
but you can just run Dima inside GitHub Actions.
So, you can run any distribution, such as Hydra,
or Apprentices, or Work Linux, or Analytics, or Apprentices,
or Alpine, and other distributions.
And there's GitHub Actions.
And Dima is originally made for Macintosh,
but we now support several HOST operating systems,
including Linux, Windows, KBC, and Dregal, Privacy.
We don't support privacy, because our client doesn't really work well on privacy HOST,
but I think we can see a real support privacy as well.
And we have lots of separate free software projects based on Dima.
The most of the famous one is Coding Mer.
This is an alternative CRI for Dima,
with Dregal at the default engine.
So, Coding Mer is very famous.
Maybe it's more famous than Dima itself.
It has a very huge number of GitHub stores.
So, with Coding Mer, you can just run Dregal on Mac OS, very easily.
And it doesn't need a proprietary Dregal,
just to write this.
And also, there's a run chat desktop by Susie.
It's a combination of Dima and K3S and GUI.
So, this is a screenshot of run chat desktop.
And with this GUI dashboard,
you can check near the status of the Dima run chat desktop.
If running Q3S, this is also free software.
And the next one is a print.
It's AWS product.
And it's made for local development with AWS services,
such as AWS server,
application model, AWS some.
They recently announced this support.
And which is also free software as well.
And there are projects that Dima and GUI,
which provides GUI based on Q2 framework, like this.
And also, potman desktop supports managing Dima instances,
as well as native potman machine instances.
And we have more supported projects.
So, let's talk about how it works.
So, this is a texture of the Dima.
So, there is a Dima set here.
CRI, quanti interface.
This is used by Shuman or GUI or MCP programming.
And this CRI can be used for managing the Dima host agent processes.
And host agent process is a medium driver
to support a server or partner machine implementations.
And this Dima branches BM and also connects to the network driver.
And instead of BM, we have a Dima agent process,
which handles fire system sharing and port routing,
and thinking real-time cook,
or other jobs.
And Dima is designed to be compatible
to support different implementations of hyperbysers,
such as QEMU or Apple's port rotation framework,
and then was busy or macOS.
We also support WSR2 or Windows hosts.
And in budget 2.0 of Dima,
we added support for care on kit,
which supports GPU acceleration on macOS.
And in Dima budget 2, we also support
GRPC programming to support your favorite hyperbysers implementation.
And we also have the concept of interon urm binary effectors.
So the default is a two-emil user mode.
So you can just run interbysers on the urm instances of QEMU.
And on macOS hosts, you can also use Ruse 2,
which is more fast faster than QEMU.
And for fire system sharing, we support bar value FS
and bar value 90.
And we also support reverse SSH FS.
When the guest operating system doesn't support bar value FS
and bar value 90.
And for networking, the default is user mode,
network based on G-byser.
So this company works in the user space,
so it doesn't need any root privilege on the host.
But when you want to access the virtual machine by IP,
not just by the Ruka host address,
you can use a solid BM8 driver.
This needs root privilege,
so you have to run it with SIDO.
And for busy driver, you can automatically use
a busy network driver to access the BM by IP.
This one only works with busy,
but this doesn't need SIDO command.
And for port routing, we watch EVP events.
It's a net link, SOC diagnosis events.
And we use EVP to watch this port routing events.
But this information doesn't work for keyboard service ports.
Because keyboard service ports are quite different from regular ports,
because it uses IP tables.
So we also have a custom logic for what's in keyboard service ports.
And it's a default,
this row of the keys to waste is Ubuntu,
but you can also choose other distributions,
such as R-marinux,
by R-Prinux, Center of Stream,
DBN, Open Source, Oracle Linux,
and Rukinux.
And default contenting is contenting,
but you can also use Apptina,
or Pottina, in Rukinux mode by default,
or in Rukinux mode,
when you need privileged operations.
And you can also use several functional testimonials,
such as Kubernetes.
And you can just choose your template using this
and set your stats command.
And let me talk about recent updates.
So we recently got promoted to sensitive,
incorporating projects.
CNCF stands for CRAT Native Computing Foundation,
which is hosting several projects,
such as Kubernetes.
And CNCF has three strategies,
sandbox incubating and graduated.
We joined CNCF as a sandbox in 2022,
and we got promoted to interpreting that year.
And we anticipate that we can promote it
to the graduate level in the next couple of years.
And the number of Retopsters is growing.
So we now have more than 20,000 upstairs,
and we have more than 170 contributors,
so thanks to all the contributors and all the users.
And in November, we released a remote version to 0,
and this is the product infrastructure
to other implementing new features
without modifying remote.
So we have the concept of VM driver programs
to support additional hyperbysers,
and we also support CRAT programs
to add more subcommands to the DMACTS CLI.
And we also have programs for URL schema
for affecting templates from custom remote addresses.
And we support GP Accertation using
Clarity to VM driver.
And we also added MCP server,
model.pl.pl server for protecting AI agents.
So in this case, we are extending things
to cover AI as well as consumers.
So the original goal in 2021 was to facilitate
running continuity on Mac OS,
but the project turned out to be ready to use
for securing AI agents too,
so as to prevent them from accessing the host of files
and the commands.
So you know, AI agents may make
hallucination to remember files under the home directly.
So this example is from Reddit,
but this example quote,
I tempted to clean up some packages and unused files
and quote,
launched RMR commands to test,
test, test, press, press.
And the program is that it even limits
the home directly to the source.
So it removes everything in the home directly.
So it's very scary to run AI on your laptop directly.
So it reminds useful for securing such AI agents.
And I also have to note that AI may also make hallucination
to install fake packages with possible names
by running PPM install or MPM install
or go install or whatever else.
And AI agents now have a web search tool
and AI agents are sometimes deceived
by fake websites,
once they're internet appears the web search tool
to install some malicious purchases.
So AI agents often come with a built-in sandboxing
who is an example, they use a dandroque
or the car container or Linux,
but it's not as strong as virtual machines.
And some AI agents use a sandbox exec,
which is similar to dandroque or macOS,
but this sandbox exec command has been
deprecate almost a decade ago.
And Apple recommends using up sandbox,
but it's not direct refreshment
through sandbox exec commands.
So AI agent products are still
relying on sandbox exec commands.
So we can use Dima as a reversal sandbox
for any AI agent.
And it's also, it can coexist
with the built-in sandboxing
provided by AI agents.
And we're running AI with Dima
there are two scenarios.
AI inside Dima and AI outside Dima.
So AI inside Dima is running
code x, compile, or code, or Gemini
or maybe open code inside Dima.
And you can also do an inference inside Dima
using GPU acceleration.
And AI outside Dima means
AI agent running on the host
can connect to Dima.
And Dima provides MCP servers
for protecting five system course
and command execution course.
And you can also use PIS code and remote SSH
and compile routes with Dima.
And we have an example of running AI inside Dima.
For example, you can use this Dima city
or start command to own the monster
directly in mid-right mode.
And we can install open code.
So I don't have time to show the demo.
But inside the website, we have example
for continuous.
And we also have examples for AI agents.
So you can choose a credit code or code x
or Gemini or GitHub compile route.
And you can just run its inside Dima.
And we also have GPU acceleration.
So Dima CPP running inside Dima uses
a parking to talk to a partner or GPU.
And the partner or GPU talks to multi and brick
which translates a parking right-body call
to make a library course, which is used by Apple.
I think I can show a quick demo.
So this is using a parking GPU,
a partner or GPU binas, a point for max.
And I can talk to AI running inside Dima.
Yeah, so the performance is not so much.
And for running AI outside Dima,
Dima exposes several MCP tools,
such as district free,
the right-body run share command.
These are a similar to Gemini CLIs commands,
but it's a strong risk on the box using BM.
And we plan to raise the budget to a point
to run in March.
And in this race, we have sync modes.
Unlike months, sync devices are written
but only after user information.
So this prevents AI from the situation
where a story, I regrouped everything including
AI.
So this should be highly useful running AI
in the inside Dima.
And I don't have time to cover our future ideas,
but we've come contributions in this field.
And we have a huge community,
and we have website, GitHub, and Slack, and Twitter,
and must-do.
And thank you.
Thank you.
Any questions?
Sorry.
Can you have multiple instances of Dima
on different posts and talking to each other?
They have to run on the same post.
So, yeah.
Yes.
On one system.
So you can use a bridge device
to directly connect virtual machine
to the host network.
So you can just connect multiple instances
running on several posts.
What have you received, too?
Actually, I don't use WC2 by myself,
so I'm not sure about WC2 implementation.
These are a lot of the big questions.
That's it.
Thank you.