GitHub's Devin Competitor, Sam Altman Talks GPT-5 and AGI, Amazon Q, Rabbit R1 Hacked (AI News)
Summary
TLDRThe video script discusses the latest advancements in AI coding assistance, highlighting GitHub Copilot Workspace and Amazon Q as examples of AI's growing capabilities in software development. GitHub Copilot Workspace is an AI coding assistant that can generate entire methods or pages of code, while Amazon Q is a generative AI assistant for businesses and developers, offering code generation, testing, debugging, and more. The script also touches on concerns about code quality due to AI-generated code reuse and the potential for AI to democratize software development. Additionally, it covers the Rabbit R1 AI box, Sam Altman's insights on building large-scale AI infrastructure, the challenges of productizing advanced AI, and the subtle dangers of AI. The script concludes with the first full music video generated by Sora, an AI text-to-video product, and a mention of Open Voice V2, an open-source voice cloning project.
Takeaways
- 🚀 **GitHub Co-pilot Workspace**: An evolution of the original GitHub Co-pilot, offering a more comprehensive tool that not only auto-completes code but also helps to define tasks, create plans, and generate code based on user specifications.
- 🔍 **Code Quality Concerns**: There's a critique that GitHub Co-pilot may lead to suboptimal code reuse and a potential degradation in the median baseline of code quality due to the model being trained on reused code.
- 🤖 **GitHub Co-pilot Chat**: A less impressive feature compared to the auto-complete tool, described as similar to Chat GPT but for code, which didn't seem to offer significant advantages.
- 📈 **Developer Productivity**: GitHub Co-pilot is reported to have boosted developer productivity by up to 55%, highlighting the potential impact of AI on software development.
- 🔧 **Control Over Process**: GitHub Co-pilot Workspace gives developers full control over the development process, from brainstorming to testing, while assisting with natural language inputs.
- 📱 **Mobile Compatibility**: GitHub Co-pilot Workspace is mobile compatible, allowing developers to contribute to code bases from their mobile devices, offering unprecedented flexibility.
- 🛒 **Amazon Q**: Amazon's generative AI assistant aimed at businesses and developers, capable of generating code, testing, debugging, and providing multi-step planning and reasoning for implementing new code.
- 📊 **Amazon QuickSight**: A business intelligence tool that can analyze business data, with Amazon Q's ability to dynamically generate reports and metrics based on user descriptions.
- 📈 **AI in Business**: Amazon Q positions itself as a business product, enabling employees to use natural language to build their own generative AI applications from company data.
- 🧱 **Rabbit R1 AI Box**: The Rabbit R1 has improved significantly since its release, particularly in terms of battery life, and it has been revealed to be running an Android app.
- 🌟 **GPT Models and AGI**: Discussion around the current state of GPT models, with GPT-4 considered a significant step forward, and the challenges of productizing PhD-level intelligence.
- 🎥 **First Fully Generated Music Video by Sora**: A milestone in AI where a full music video was created using Sora, OpenAI's text-to-video product, showcasing the potential of generative AI in creative fields.
Q & A
What is GitHub Copilot Workspace?
-GitHub Copilot Workspace is an evolution of the GitHub Copilot project, which is an AI coding assistant. It allows developers to define a task, such as solving a GitHub issue or defining a new feature, and then it builds the entire solution for the developer, including code generation and specification detailing.
What is a concern with AI coding assistants like GitHub Copilot?
-One critique is that developers might reuse code without thoroughly reviewing it, which could be suboptimal or contain bugs. This repeated use of unreviewed code could potentially degrade the overall quality of code in the model's training data.
What is Amazon Q?
-Amazon Q is a generative AI-powered assistant for businesses and developers. It is designed to assist with tasks such as coding, testing, and upgrading applications, as well as troubleshooting, performing security scanning, and optimizing AWS resources.
How does Amazon Q Developer assist with code transformation?
-Amazon Q Developer can dynamically generate interfaces for code upgrades, such as converting code into Java 8, providing a tool for developers to transform and upgrade their codebases.
What is the purpose of Amazon QuickSight and Amazon Q?
-Amazon QuickSight is a business intelligence tool that allows users to analyze business data easily. Combined with Amazon Q, it can generate reports with metrics and graphs based on abstract descriptions provided by the user.
What is the Rabbit R1 AI box, and what has been revealed about it?
-The Rabbit R1 AI box is a device that has improved significantly since its release, particularly in terms of battery life. It has been revealed to be running an Android app, and the Rabbit app has been made functional on Android phones.
What are some concerns raised by Sam Altman about AGI?
-Sam Altman, the CEO of OpenAI, expresses concerns about the subtle dangers of AGI, such as its potential to cause pervasive but less noticeable changes in society, like increased attention disorders. He also discusses the challenge of productizing PhD-level intelligence and the importance of iterative deployment of AI technologies.
What does Sam Altman think about the current state of models like GPT-4?
-Sam Altman considers models like GPT-4 to be 'embarrassing at best,' suggesting that there are more advanced models within OpenAI that have not been publicly disclosed.
What is the significance of the first full music video generated by Sora?
-The first full music video generated by Sora, a text-to-video product from OpenAI, signifies a major advancement in AI-generated multimedia content. It demonstrates the potential for AI to create complex, creative works.
What is Open Voice V2 and how does it work?
-Open Voice V2 is an open-source voice cloning project similar to 11 Labs. It allows users to create voice clones that can replicate any voice in any style and language, raising ethical concerns about the use of AI in voice replication.
What is the ethical concern surrounding AI and societal impact?
-The ethical concerns surrounding AI and its societal impact include issues related to privacy, consent, the potential for misuse, and the broader implications of AI on employment, social interaction, and the nature of human intelligence and creativity.
Outlines
🚀 GitHub Co-Pilot Workspace: AI-Powered Coding Assistant
GitHub Co-Pilot Workspace is an advanced AI coding assistant that builds upon the original GitHub Co-Pilot project. It allows developers to define a task, such as solving a GitHub issue or creating a new feature, and then generates a comprehensive plan and code for the task. The tool claims to boost developer productivity by up to 55%. It also addresses concerns about code reuse and quality by allowing developers to review and edit the AI-generated code. The workspace offers a natural language interface for planning, building, testing, and running code, with full control over each step of the process. It is designed to augment, not replace, developer creativity and is mobile compatible, enabling coding from anywhere.
🤖 Amazon Q: Generative AI for Business and Development
Amazon Q is a generative AI assistant aimed at businesses and developers, offering capabilities in code generation, testing, debugging, and planning. It comes in four different use cases: Amazon Q Developer, which assists with coding, testing, and application upgrades; Amazon Q Business, which uses a large language model for tasks like generating job postings; Amazon Quick Site, a business intelligence tool that analyzes business data; and Amazon Q Apps, which allows employees to build simple AI applications using natural language. The tool is positioned as a business product that can transform and implement new code from developer requests and make it easier for employees to access business data.
📱 Rabbit R1 AI Box and Android App Integration
The Rabbit R1 AI box has been revealed to be based on an Android operating system, and it has been demonstrated that the Rabbit App can run on an Android phone. This suggests that the company's hardware could potentially be replicated on other Android devices. Despite this, the form factor and hardware of the Rabbit R1 are appreciated, and there is a suggestion that an app version could be developed without cannibalizing the hardware market. The device's battery life has seen significant improvement with updates, making it more usable.
🧠 GPT's Future, AGI, and Societal Impact
Sam Altman, CEO of OpenAI, discusses the future of AI, including the challenges of building very large computers and the commoditization of AI models. He emphasizes the importance of iterative deployment of AI technology, allowing society to adapt and co-evolve with the technology. Altman also expresses concerns about the rate at which society can adapt to new AI technologies and the potential for subtle, overlooked dangers. He mentions that while GPT-4 is considered 'embarrassing' in comparison to future models, it is still important to release and improve upon such models. Additionally, the first full music video generated by Sora, an OpenAI text-to-video product, is highlighted, showcasing the potential of AI in creative fields.
Mindmap
Keywords
💡AI coding assistant
💡GitHub Co-pilot workspace
💡Code quality
💡Amazon Q
💡Natural language processing (NLP)
💡Developer productivity
💡Large language models (LLMs)
💡AGI (Artificial General Intelligence)
💡Ethical concerns
💡Sora
💡Open Voice V2
Highlights
GitHub Co-pilot Workspace is an evolution of the AI coding assistant that can define tasks and build entire code structures.
GitHub Co-pilot has been reported to boost developer productivity by up to 55%.
Critiques of GitHub Co-pilot include concerns over code quality due to the reuse of potentially suboptimal code.
GitHub Co-pilot Chat, a code-based version of Chat GPT, was released in 2023 but is not as powerful as the autocomplete feature.
Developers can now use natural language to brainstorm, plan, build, test, and run code with GitHub Co-pilot Workspace.
GitHub Co-pilot is designed to augment, not replace, developers, requiring human review of generated code and specifications.
Amazon Q is a generative AI assistant aimed at businesses and developers, offering code generation, testing, and debugging.
Amazon Q comes in four different use cases, including developer assistance, business intelligence, and secure AI application building.
Amazon QuickSight, combined with Amazon Q, enables the creation of comprehensive business reports with ease.
Rabbit R1 AI box was found to be based on Android, with the Rabbit App successfully run on an Android phone.
Sam Altman, CEO of OpenAI, discusses the challenges of building supercomputers and the commoditization of AI models.
Altman expresses concerns about the pace of societal adaptation to advanced AI and the development of a new social contract.
OpenAI's GPT-4 is considered a significant step forward, though described by Altman as 'embarrassing' in comparison to future models.
The first full music video completely generated by Sora, OpenAI's text-to-video product, has been released.
MyShell AI released Open Voice V2, an open-source voice cloning project that can replicate voices in various styles and languages.
Ethical concerns and societal impacts of AI are discussed, emphasizing the importance of gradual AI deployment and public input.
The potential dangers of AGI are considered, with a focus on subtle, overlooked risks rather than dramatic, obvious threats.
Transcripts
so it seems like now the major tech
companies are rolling out their AI
coding assistance and they are extremely
comprehensive and very impressive so we
have two examples of that we have one
from GitHub which is Microsoft and they
call it GitHub co-pilot workspace and
then we have Amazon's version which is
Amazon Q which they just rolled out plus
we have a few other news stories that
we're going to get to today so let's get
into it first this is GitHub co-pilot
workspace and this is the evolution of
the GitHub co-pilot project which was
really the first AI coding assistant and
it was incredible you just start typing
some code and it fills out the entire
method or even entire pages of code for
you and now GitHub co-pilot workspace
takes it a step further you start from
the task you start by defining what you
want to accomplish whether that's
solving a GitHub issue or defining a new
feature and it builds the entire thing
for you it's really the next generation
of AI coding assistants so this is the
blog post about it right here they say
in 2022 we launched GitHub co-pilot as
an autocomplete pair programmer in the
editor boosting developer productivity
by up to 55% now one critique of GitHub
co-pilot is that you are reusing code
that you're not really even looking at
and it's potentially suboptimal code or
even code that might have bugs in it and
so many people are reusing the same code
over and over again and all of that is
going back into the model to train it
maybe we're actually degrading the
median Baseline of code code quality
which is something interesting to think
about uh then in 2023 we released GitHub
co-pilot chat which is essentially like
chat GPT but with code honestly it's not
super impressive I never used it it's
kind of just like taking your code based
putting it into chat GPT and then asking
questions about it and it's not even
that good it's certainly not nearly as
powerful as GitHub co-pilot autocomplete
now we have GitHub co-pilot workspace
developers can now brainstorm plan build
test and run code in natural language
this new task Centric experience
leverages different co-pilot powered
Agents from start to finish while giving
developers full control over every step
of the process this is essentially
Microsoft's version of Devin all right
so we have an example of how it works
what we're seeing here is an issue a
GitHub issue create an AI player option
and then we have a description of what
it should be so then we have that we can
open it in workspace then the AI
actually fills out a much more detailed
specification for this issue and then
what we can do is click this generate
plan button we can edit any of the
details along the way as it says here we
can add parts to the spec it's now
generating a plan and then we can
actually just click Implement and it's
going to show us the diff right here so
all we had to do was describe what we
want to build and then it built it with
the diff in a really nice interface and
it's going to go step by step and
accomplish every one of the
specifications in the issue or in the
plan then we can actually open it in a
live preview so you can test it out
before merging the code there it is so
all within this one environment and then
we can actually create the poll request
and merge the code so very very cool and
I think what's interesting about GitHub
co-pilot is they're not claiming to
replace developers they are claiming to
augment developers and I really actually
believe that with this purpose you still
need to review the code you still need
to review the specifications but I think
this is going to give many more people
the ability to contribute to code bases
and right here it says and is expressly
designed to deliver not replace
developer creativity faster and easier
than ever before so again it all starts
with a task then we build a full plan
and it actually builds it for us and we
can edit it then we can create the code
and again completely editable then we
test out the code we actually see it
running and then we can create a pull
request and the code so let me show you
a video of it working end to endend and
this is from the GitHub co-pilot team so
let's watch this video together it's
about 2 minutes getting started with
your work usually takes place looking at
a project board and navigating to GitHub
issues co-pilot workspace brings your
favorite AI assistant into a native Dev
environment designed for everyday tasks
for example it can use the information
in your GitHub issue along with
references from your repository to build
out a specification based on the current
State and proposed state and you can
tailor the spec as you need whether
that's adding editing or removing items
once ready you can progress from spec to
plan and the process feels familiar with
the ability to adjust the plan as you
need by creating modifying or removing
files and adjusting the expected tasks
for each step this leaves you in control
free to solve the higher level problems
and build out your plan before getting
into the finer details of writing code
co-pilot workspace then streams the
suggested changes to our environment
notice that we have a diff view to
easily digest the changes and can easily
make updates within the editor but
that's not all at our fingertips we have
access to an integrated terminal so we
can run the test in our workspace before
committing our changes and creating a
pull request and what if you want to
make use of advanced features like step
through debugging no problem create a
code space and pick up where you left
off when you raise your pull request
with co-pilot workspace it generates a
description for you and automatically
adds a link to your workspace adding a
little bit more context for the reviewer
and supporting their code review
workflow and as it's a pull request our
usual checks trigger including GitHub
action workflows and code scanning
co-pilot workspace leaves you in control
solving the higher level problems and
iterating quickly over the solution and
and it is mobile compatible so you're
going to be able to do all of this from
your mobile phone which is kind of
insane to think about you can be coding
and actually contributing real code to a
project from your phone from anywhere in
the world next we have Amazon q and
Amazon Q is a generative AI powered
assistant for businesses and developers
and is now generally available now I
haven't played with it yet but what's
interesting is this is Amazon's attempt
at their own large language model and I
think they rolled their own but they
don't really give any specifications
about it and it comes in four flavors
and I'm going to talk about that in a
minute so a little bit about it Amazon Q
not only generates highly accurate code
it also tests debugs and have multi-step
planning and reasoning capabilities that
can transform and Implement new code
generated from developer requests Amazon
Q also makes it easier for employees to
get answers to questions across business
data such as company policies Etc so
again four different use cases and we're
going to take a look at each so first is
Amazon Q developer and it's very similar
to what we just looked at Amazon Q
assists developers and it professionals
with all of their tasks from coding
testing and upgrading applications to
troubleshooting performing security
scanning and fixes and optimizing AWS
resources so let's take a look at a
quick demo video and I'll walk you
through what we're seeing so first is
Amazon QBE business and really what this
is is just a large language model so
write a job posting this is essentially
a prompt you can put into any large
language model and it generates a job
posting not super impressive now what
I'm really interested in is Amazon Q
developer so you can ask it questions
and what we're seeing here is
transforming code so it's actually
converting it into Java 8 for example it
doesn't seem quite as impressive as
GitHub copilot workspace but that's
pretty cool it dynamically generated or
I believe it dynamically generated that
interface to upgrade and here we go so
it's doing that upgrade now now we have
Amazon q and Amazon quick site and quick
site by the way is just a business
intelligence tool that just means you
dump a bunch of your business data in
there and you can analyze it really
easily and I think this is a really
underappreciated use case especially as
a business you need data analysts data
scientists to do this work but now you
can essentially just describe the types
of metrics that you want to see and
Amazon quick site with Amazon Q is going
to put it all together for you so here
we go build a story explaining
profitability Trends and again you can
be very abstract like that and it puts
together an entire report with graphs
and everything that's super super
impressive and look at all these
suggestions of different metrics you can
run all generated by AI very very cool
then they have Amazon Q apps which says
it enables employees to use natural
language to securely build their own
generative AI applications and it's all
from the company's data so Amazon Q is
really positioned to be the business
product so employees simply describe the
type of app they want in natural
language and Q apps will quickly
generate an app that accomplish is their
desired task so let's look at this quick
example build an app that takes a ro
title and onboarding plan structure
weekly 6090 day and optionally a new
hire's name it should output a summary
of the role guidelines for the given
role so it's essentially using AI to
build really simple applications to be
used within the work environment and so
you generate these applications and then
they can be used over and over again
kind of cool I've not really seen this
elsewhere uh it's kind of neat and so
that's all for Amazon Q I haven't tested
it myself it looks pretty cool though so
I might go and test it next rabbit R1 so
I have my rabbit R1 right here it's
actually gotten much better since I've
gotten it one of my biggest complaints
was the fact that the battery drained
really quickly and then with one update
it improved probably about 10x for me so
where previously I could literally stare
at the device and watch the battery
drain percent by% now it lasts for 2
hours and only drains about 5% of
battery so a vast Improvement and really
it actually makes it usable now but what
now RS Technica has broke is that the
rabbit R1 AI box is revealed to be just
an Android app however it's not really
breaking anything we kind of knew that
they announced that the underlying
operating system they announced it a
while ago is Android and so yeah of
course it's just kind of an Android app
and so what somebody was actually able
to do is get the rabbit App working on
an Android phone which is pretty
interesting and so here we can actually
see the rabbit App working on a phone
that is the rabbit app and so the
company posted on X that they are aware
there are some unofficial rabbit OS app
website emulators out there but look of
course it can be an app I like the form
factor I like the hardware it's gorgeous
to me it feels nice I know I'm a sucker
for this kind of stuff but I really
appreciate it and of course I don't know
why they're not just also building an
app I I guess that would cannibalize
their Hardware Market but for $200 it
seems worth it to me and of course if
you don't want to buy it just don't buy
it and if you want to load it up on your
own device in a kind of hacked way
you're welcome to do that of course next
Sam Alman said some very interesting
things about GPT 5 and GPT 4 so he talks
about a lot of stuff at this Stanford
talk so let's go through a few of them
one he is asked like what he thinks
about right now and his answer is how to
build really big computers and we
already know he was trying to raise 78
trillion dollar we already know that
Microsoft is building the biggest
supercomputer ever made on behalf of
really open AI so he is thinking about
this deeply I've also said multiple
times models are becoming commoditized
that is not where the value is going to
be what questions then are you wrestling
with that no one else is talking about
how to build really big computers I mean
I think other people are talking about
that but we're probably like looking at
it through a lens that
no one else is quite imagining yeah and
can we continue on that thread then of
how to build really big computers if
that's really what's on your mind can
you share I know there's been a lot of
speculation and probably a lot of here
say too about the semiconductor Foundry
Endeavor that you are reportedly
embarking on um can you share what would
make what what's the vision what would
make this different than others that
just foundies although that that's part
of it it's like if if you believe which
we increasingly do at this point that AI
infrastructure is going to be one of the
most important inputs to the Future this
commodity that everybody's going to want
and that is energy data centers chips
chip design new kinds of networks it's
it's how we look at that entire
ecosystem um and how we make a lot more
of that and I don't think it'll work to
just look at one piece or another but we
we got to do the whole thing okay so
there's multiple big
problems yeah um I think like just this
is the Arc of
human technological history as we build
bigger and more complex systems another
thing he talks about and I'll show you
the clip in a second is the fact that
they're not sure how to productize PhD
level intelligence and how to actually
deliver the most value to the world
which is kind of interesting they're
kind of building the plane in the air
while flying it which makes me a little
bit nervous but I tend to be an optimist
so I have some good outlook on what the
future of AI will be I mean we're we're
definitely
wrestling with how we when we make not
just like grade schooler or middle
schooler level intelligence but like PhD
level intelligence and Beyond the best
way to put that into a product the best
way to have a positive impact with that
on society and people's lives we don't
know the answer to that yet so I think
that's like a pretty important thing to
figure out and he also talks about AGI
the AGI timeline how gp4 is embarrassing
at best which is interesting it kind of
leads me to believe he's seen something
much better internal at open AI let's
watch what he has to say about that open
ey is phenomenal chat gbt is phenomenal
um everything else all the other models
are
phenomenal it burned you've earned $520
million of cash last year that doesn't
concern you in terms of thinking about
the economic model of how do you
actually where's going to be the
monetization source well first of all
that's nice of you to say but Chachi PT
is not phenomenal like Chachi PT is like
mildly embarrassing at best um gp4 is
the dumbest model any of you will ever
ever have to use again by a lot um but
you know it's like important to ship
early and often and we believe in
iterative deployment like if we go build
AGI in a basement and then you know the
world is like kind
of blissfully walking blindfolded along
um I don't think that's like I don't
think that makes us like very good
neighbors um so I think it's important
given what we believe is going to happen
to express our view about what we
believe is going to happen um but more
than that the weight to do it is to put
the product in people's hands um and let
Society co-evolve with the technology
let Society tell us what it collectively
and people individually want from the
technology how to productize this in a
way that's going to be useful um where
the model works really well where it
doesn't work really well um give our
leaders and institutions time to react
um give people time to figure out how to
integrate this into their lives to learn
how to use the tool um sure some of you
all like cheat on your homework with
with it but some of you all probably do
like very amazing wonderful things with
it too um and as each generation goes on
uh I think that will expand and that
means that we ship imperfect products um
but we we have a very tight feedback
loop and we learn and we get better and
it does kind of suck to ship a product
that you're embarrassed about but it's
much better than the alternative um and
in this case in particular where I think
we really owe it to society to deploy
iteratively one thing we've learned is
that Ai and surprise don't go well
together people don't want to be
surprised people want a gradual roll out
and the ability to influence these
systems um that's how we're going to do
it there could totally be things in the
future that would change where we think
iterative deployment isn't such a good
strategy but it does feel like the
current best approach that we have and I
think we've gained a lot um from from
doing this and you know hopefully s the
larger world has gained something too
now here's a clip where he talks about
some of the dangers of AGI and I'll play
that quickly do you think the biggest
Danger from AI is going to come from a
cataclysmic event which you know makes
all the papers or is it going to be more
subtle and pernicious sort of like you
know like how everybody has ADD right
now from you know using Tik Tok um is it
are you more concerned about the subtle
dangers or the cataclysmic dangers um or
neither I'm more concerned about the
subtle dangers because I think we're
more likely to overlook those the
cataclysmic dangers uh a lot of people
talk about and a lot of people think
about and I don't want to minimize those
I think they're really serious and a
real thing but I think we at least know
to look out for that and spend a lot of
effort um the example you gave of
everybody getting addd from Tik Tok or
whatever I don't think we knew to look
out for and the unknown unknowns are
really hard and so I'd worry more about
those although I worry about both and
are they unknown unknowns are there any
that you can name that you're
particularly worried about well then I
would kind of they'd be unknown unknown
um well you can I am worried just about
so so even though I think in the short
term things change less than we think as
with other major Technologies in the
long term I think they change more than
we think and I am worried about what
rate Society can adapt to something so
new and how long it'll take us to figure
out the new social contract versus how
long we get to do it um I'm worried
about that so he actually has an entire
talk it's really interesting I'll drop
the link to that in the description
below I might actually make a full video
just on the talk because he talks about
a lot of interesting stuff let me know
if you want to see that all right next
an article from Venture beat but really
the gist is we have our first full music
video completely generated by Sora and
if you haven't heard of Sora it is the
text to video product that open AI kind
of previewed a few months back really
mind-blowing stuff let me show you some
brief Clips I'm not sure if I'm going to
get copyrighted for the music so I'm
just going to replace it for some
different music so it might seem a
little off but let me just show you the
Sora part cuz that's the interesting
part
Karma a think for me we hold hands make
plans keep seats Karma she's my best
friend One Step Closer here it ends get
a thing for me you see you be digging up
6et Karm never let me down my when I cut
[Music]
you and The Last Story just a quick one
my shell AI released open Voice V2 which
is an open Voice cloning project kind of
like 11 Labs but open source and
apparently it works really well let's
look at the video demo open Voice
instantly call any boys through generous
speech in any style at any
langage we are conflating a lot of
things with the word
intelligence ethical concerns surround
AI societal impact 3 2 1 ethical
concerns surround AI societal impact
wanders and watches with eager ears the
aroma of freshly baked bread filled the
kitchen the aroma of freshly baked bread
filled the kitchen the aroma of freshly
baked bread filled the kitchen we were
conflating a lot of things with the word
intelligence
restly so that works really well if you
want to see a tutorial for how to get
that installed and how to use it let me
know in the comments if you liked this
video please consider giving a like And
subscribe and I'll see you in the next
one
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