🚨BREAKING: LLaMA 3 Is HERE and SMASHES Benchmarks (Open-Source)
Summary
TLDRThe video script discusses the launch of Llama 3, the latest model in the Llama series by Meta AI. The host expresses excitement about the new release, noting its significance in the world of AI and its potential to attract more people to artificial intelligence. Llama 3 is available in both 8 billion and 70 billion parameter versions, with the middle size version expected to follow. The model is positioned as a competitor to Chat GPT and is showcased for its impressive coding capabilities, including the quick creation of a Python snake game. The host also highlights the model's enhanced performance, ability to handle complex tasks, and its focus on agents as first-class citizens in AI. Additionally, the script touches on Meta AI's commitment to trust and safety with the release of Llama Guard 2 and other safety tools. The video concludes with the host's anticipation for further testing and integration of Llama 3 into various applications.
Takeaways
- 🚀 **Llama 3 Launch**: Meta AI has launched Llama 3, the third version of the Llama series, continuing the trend of open-source, locally run AI models.
- 🎨 **Tie-Dye for the Launch**: The speaker is excited about the launch, even wearing a tie-dye hoodie to celebrate the event.
- 📈 **Performance Enhancements**: Llama 3 offers enhanced performance with both 8 billion and 70 billion parameter versions, designed for a wide range of applications.
- 🔍 **Missing Middle Size**: There's an observation that the middle size version around 34 billion parameters is missing, implying potential future releases.
- 🤖 **AI Agents Emphasis**: Llama 3 positions AI agents as first-class citizens, highlighting their importance beyond simple prompts.
- 🐍 **Coding Test**: The speaker tests Llama 3's coding capabilities by asking it to write a Snake game in Python, which it does successfully and quickly.
- 📊 **Benchmarks and Scalability**: Llama 3 shows excellent performance in benchmarks, outperforming other models like Gemma 7B and MISTL 7B, especially in coding tasks.
- 🧩 **Multi-Step Task Capability**: The model's ability to handle multi-step tasks effortlessly is a significant improvement, beneficial for AI agents.
- 🔒 **Trust and Safety Updates**: Meta AI has updated its responsible use guide and trust and safety tools, including Llama Guard 2, to ensure responsible development and use of LLMs.
- 🌐 **Global Availability**: Meta AI is expanding its availability, rolling out in multiple countries and integrating into various platforms like Facebook, Instagram, and WhatsApp.
- 📱 **Mobile Integration**: Users can access Meta AI features through their mobile devices, making AI capabilities more accessible and convenient.
- 📸 **Image Generation**: Meta AI's image generation feature is now faster, allowing users to create images on the fly, with the option to animate them.
Q & A
What is the significance of the launch of Llama 3?
-Llama 3 is the third version of the Llama series of models developed by Meta AI. It is significant because it continues the trend of open-source, locally run models that have helped a new generation of people get into artificial intelligence. It offers enhanced performance, scalability, and is capable of handling complex tasks like translation and dialogue generation with improved efficiency.
What are the different versions of Llama 3 that have been released?
-Llama 3 has been released in both 8 billion and 70 billion pre-trained and instruction-tuned versions to support a wide range of applications. However, the middle size version around 34 billion parameters is missing, which is expected to be released in the future.
How does Llama 3 perform in coding tasks?
-Llama 3 has shown significant improvements in coding tasks. It was able to generate a complete snake game in Python on the first try, which is a complex task. It also scored triple the math score of its competitors, indicating a strong capability for reasoning, code generation, and instruction following.
What are the trust and safety measures that Meta AI has implemented with Llama 3?
-Meta AI has updated the Responsible Use Guide (RUG) and introduced Llama Guard 2, which includes tools like Code Shield and Cybersec SEC Eval 2. These tools are designed to ensure the models are used responsibly, looking for insecure code practices, susceptibility to prompt injection, and other potential issues.
How does Llama 3 compare to other models in terms of benchmarks?
-Llama 3 outperforms its predecessor, Llama 2, across the board in benchmarks. When compared to other models like Gemma 7B and Mistil 7B Instruct, Llama 3's 8 billion parameter version showed superior results in MLU, GP QA, and human eval. The 70 billion parameter version also performed well against larger models like Gemini Pro 1.5 and CLA 3 Sonnet.
What is the context length supported by Llama 3?
-Llama 3 supports an 8K context length, which doubles the capacity of Llama 2. While this is an improvement, it is still considered small compared to other models like GPT 4, which supports 128k, and Gemini Pro 1.5, which supports a million tokens.
How does Meta AI plan to integrate Llama 3 into their ecosystem?
-Meta AI plans to integrate Llama 3 into their ecosystem through various applications and platforms like Facebook, Instagram, WhatsApp, and Messenger. It will be used for tasks such as recommending restaurants, finding events, and providing real-time information without leaving the app.
What are the potential use cases for Llama 3 in the AI stack?
-Llama 3 can be used in various layers of the AI stack. At the infrastructure layer, it can be used for agent orchestration, evaluation, and deployment. At the app layer, it can be integrated into existing apps to add AI features or be the foundation for new AI-driven apps. It is expected to be particularly useful for developing agents and other AI-powered applications.
How does the release of Llama 3 impact the AI market?
-The release of Llama 3 puts competitive pressure on closed models like GP4, Claude, and Gemini, potentially pushing down prices and commoditizing models. It signals a shift towards open-source models, which can democratize AI technology and make it more accessible to developers and users.
What are the trust and safety tools included in Llama Guard 2?
-Llama Guard 2 includes tools like Code Shield, which protects against insecure code practices, and Cybersec SEC Eval 2, which evaluates the model for various security issues including susceptibility to prompt injection and offensive cybersecurity capabilities.
How can developers access Llama 3 models?
-Developers can access Llama 3 models by visiting the Meta AI website and downloading the models. The models are available in both 8 billion and 70 billion parameter versions, and the code is open-sourced on GitHub, allowing developers to fine-tune the models as needed.
What is the significance of the 15 trillion tokens of data used to train Llama 3?
-The 15 trillion tokens of data represent a significant increase in the training dataset size compared to Llama 2, which is seven times larger. This larger dataset, including four times more code, contributes to the enhanced capabilities and performance of Llama 3, making it one of the most capable models available.
Outlines
🚀 Introduction to Llama 3 and Meta AI's New Developments
The video script begins with excitement for the launch of Llama 3, the third version of the Llama series of models from Meta AI. The host talks about the impact of the original Llama leak on the open-source AI community and how it has influenced the field. The script introduces the new features of Llama 3, including its availability in both 8 billion and 70 billion pre-trained and instruction-tuned versions. The host also mentions the absence of a middle size version and highlights the model's capabilities for a wide range of applications. The script discusses the model's performance, particularly in multi-step tasks and complex scenarios like translation and dialogue generation. It also touches on the model's training on a vast dataset and its enhanced scalability and performance.
📊 Llama 3's Benchmarks and Trust & Safety Features
The second paragraph delves into the benchmarks of Llama 3, comparing its performance with other models like Google's Gemini Pro 1.5 and Mistil 7B. The host highlights Llama 3's significant lead in benchmarks, especially in math scores and code generation. The script also discusses Meta AI's focus on trust and safety, introducing the Responsible Use Guide (RUG) and the Llama Guard 2, which are designed to ensure the responsible development and use of the model. The host expresses enthusiasm for the model's potential in agents and AI-powered applications and anticipates further developments in this area.
🌐 Meta AI's Integration and Expansion of Llama 3
The third paragraph discusses the integration of Llama 3 into various applications and platforms, emphasizing its potential use in chat, search, and more across Meta's apps. The host suggests that Meta AI should integrate user context into Llama 3 to enhance its functionality. The script also mentions the improvements in Meta AI's image generation capabilities and its global rollout in several countries. The host describes the practical examples of how Meta AI can be used in everyday scenarios, such as planning a night out or a weekend getaway, and its incorporation into social media feeds and messenger apps.
📈 Llama 3's Performance and Future Testing
The final paragraph focuses on the performance of Llama 3, showcasing its improvements over Llama 2 across various benchmarks. The host expresses eagerness to test Llama 3 thoroughly using their evaluation rubric. The script also mentions the availability of Llama 3's code on GitHub, indicating that while the code is open-source, the original weights may not be. The host invites viewers to like, subscribe, and look forward to upcoming videos that will further explore Llama 3's capabilities.
Mindmap
Keywords
💡Llama 3
💡Meta AI
💡Pre-trained and Instruction Tune Versions
💡Multi-step Tasks
💡Code Generation
💡Benchmarks
💡Trust and Safety
💡Llama Guard
💡Open Source
💡Image Generation
💡AI Stack
Highlights
Llama 3, the third version of Meta AI's Llama series, has been launched.
Llama 3 is available in both 8 billion and 70 billion pre-trained and instruction-tuned versions.
The middle size version around 34 billion parameters is expected but not yet released.
Llama 3 is positioned as a competitor to Chat GPT with enhanced capabilities for agents.
Meta AI's new chat interface for Llama 3 allows users to test its capabilities directly.
Llama 3 demonstrated impressive performance by quickly generating a working Snake game in Python.
The model has been trained on a dataset seven times larger than Llama 2, including four times more code.
Llama 3 supports 8K context length, doubling the capacity of Llama 2.
Benchmarks show Llama 3 outperforming other models like Gemma 7B and Mistil 7B in various tasks.
Meta AI has released Llama Guard 2, enhancing trust and safety tools for responsible AI development.
Llama 3 integrates with Meta's apps for tasks like recommending restaurants and finding events.
Meta AI's image generation feature now produces images as you type, offering real-time creation.
The Llama 3 model is open source, allowing users to download and fine-tune the model.
Meta AI is expanding its availability globally, with support in over a dozen countries outside the US.
Llama 3 is being integrated into Meta's search and recommendation systems for a more personalized user experience.
The GitHub page for Llama 3 provides access to the model's code and benchmarks for developers.
Llama 3's training on 15 trillion tokens represents a significant advancement in AI model capabilities.
The speaker plans to conduct a full suite of tests on Llama 3 and integrate it into Crew AI.
Transcripts
llama 3 day is here what an exciting day
I even broke out the tie-dye hoodie just
for this launch today we are going to be
talking all about llama 3 we're going to
review the announcement I'm going to
show you what's new about it what's
different about it and I have a bunch of
videos planned for llama 3 including
testing and coding and fine-tuning
everything so very exciting times if
you're not already subscribed be sure to
subscribe to continue getting awesome AI
content so let's dig into it so just a
few minutes ago we had the launch of
llama 3 this is the third version of the
Llama series of models out of meta Ai
and taking a step back the original
llama leak which was about a year ago
was really what set off the entire
open-source locally run model craze and
I am so thankful to meta and whoever
leaked it because it got an entire new
generation of people into AR icial
intelligence and then we had llama 2
which was a huge upgrade from llama 1
and now today we have llama 3 so let me
show you what it's all about this is the
blog post build the future of AI with
meta llama 3 you can find this you can
download the models and everything from
here l.a. comom lama3 now available with
both 8 billion and 70 billion
pre-trained and instruction tune
versions to support a wide range of
applications now if you're a keen
Observer you're probably noticing
they're missing that middle size version
around 34 billion parameters I'm sure
it's coming and it looks like meta AI
has released or maybe they hadn't at I
didn't know about it essentially a chat
GPT UI competitor right here so we can
actually test it out and I'll run a
quick couple tests on it just to show
you but the full battery of tests I'm
going to save for another video and it's
interesting that they say right here
whether you're developing agents or
other AI powered applications these
models offer the capabilities and
flexibility you need to develop your
ideas and basically agents are now first
class citizens in the world of AI there
were a lot of people who doubted that
agents are actually a thing because they
said well it's just a prompt right it's
so much more than that and I'm glad that
meta is seeing that and also knows that
and here it is meta AI meta aai this is
their new chat interface for llama 3
Let's just test something really quickly
and I bet you know what I'm going to
test write the Game snake in Python all
right here we go it is lightning fast
look at this and I'm not actually sure
if it's using the 8 billion or 70
billion parameter version but it is
super fast so we're going to copy the
code and it is using the curses Library
so I think that means it's going to be
terminal based all right pasted the code
in here doesn't look like we have any
immediate errors let's push play all
right we have a working snake game in
fact this is one of the more complete
games that I've seen amazing it even
gives me the score it has a window and
this time the snake snake can go through
which is cool and let's see what happens
if the snake goes into itself if I can
actually do that yep and it crashes
Flawless this would be an absolute pass
for llama 3 so again be sure to check
out my coming videos where I'm going to
do the full Suite of tests and if you
want to try it yourself just go to meta
and now they have their own inference
front end which is amazing all right
let's keep reading so we have enhanced
performance enhanced stated thee art
performance of llama 3 and openly
accessible model that excels at language
nuances contextual understanding and
complex tasks like translation and
dialogue generation with enhanced
scalability and performance llama 3 can
handle multi-step tasks effortlessly
while our refined posttraining processes
significantly lowers false refusal rates
improve response alignment and boost
diversity and model answers so this is
all good I'm especially interested in
multi-step tasks being handled
effortlessly because that in my mind
screams a agents and you know I'm going
to be plugging this into crew AI
additionally it drastically elevates
capabilities like reasoning code
generation and instruction following and
they have the download model link right
here if we click it you request access
put in your information why would we
ever want to get llama 2 anymore meta
code llama I can't wait for meta code
llama to be based on llama 3 and then
you download it and here are the
benchmarks so llama 3 models take data
and scale to new heights it's been
trained on our two recently announced
custombuilt 24,000 GPU clusters on over
15 trillion tokens of data a training
data set seven times larger than that
used for llama 2 including four times
more code I love the coding use case I'm
so glad that they're using a lot more
code obviously it's really good I just
tested it with snake and it got it on
the first try this results in the most
capable llama model yet which supports
8K context length and that doubles the
capacity of llama 2 8K is still pretty
small GPT 4 is 128k and even that's
small nowadays Gemini Pro 1.5 is a
million tokens so we're getting a bit
jaded with our token limits now uh AK is
small but fine-tuned versions will
increase that drastically and hopefully
it still maintains the quality looking
at the benchmarks they are comparing the
8 billion parameter version to Gemma 7B
which is Google's small open model and
mistl 7B instruct which is always one of
my favorites if not my favorite but now
metal Lama 38b the clear winner the
clear winner for these smaller models
for the mlu five shot 78.4 compared to
53 and 58 GP QA zero shot 34 compared to
21 and 26 basically across the board
human eval GSM AK math I mean look at
the math score for llama 3 the math
score is triple what Gemma 7B and mistl
7B instruct are so I should probably add
more comp complex math questions at this
point to my llm rubric if you have any
that you suggest drop it in the comments
below I'll add it then we have the large
model and here's the interesting thing
meta decided to compare their large 70b
model against Gemini Pro 1.5 which is
Clos source that is Google's
top-of-the-line model the million token
context window model and CLA 3 Sonet but
not Cloud 3 Opus and Cloud 3 Opus is
pretty much regarded as the best model
out there Clos open doesn't matter it is
the best so it's interesting that they
only compared it against clae 3 Sonet
because the Sonet model is the middle
model of all three of the Claude models
so again MML five shot it won but just
barely GPT QA it lost but just barely
human eval it is much better and as a
reminder human eval is code generation
so look at this llama 38b code
generation double that of Gemma 7B and
mistl 7B and for llama 370b human eval
is 81 nearly 82 Gemini Pro 71 and CLA 3
Sonic 73 so they really went all out on
the coding aspect of this model and
that's my favorite use case so I could
not be more excited that probably also
means it's really good at function
calling and so again I think agents GSM
8K at one and then for the math
benchmark it got a 50 which is actually
a bit less than Gemini Pro 1.5 and quite
a bit bit more than Cloud 3 Sonet and
we're going to talk a little bit about
trust and safety because that is a big
theme for meta especially because
they're open sourcing all of this they
really want to make sure that people are
using it responsibly whatever that
actually means and so let's take a look
at some of their new Innovations for the
trust and safety category so with the
release of llama 3 we've updated the
responsible use guide rug to provide the
most comprehensive information on
responsible development with llms our
system Centric approach includes updates
to our trust and safety tools with llard
2 so I've not actually heard of lard
surprisingly optimized to support the
newly announced taxonomy published by ml
Commons expanding its coverage to a more
comprehensive set of safety categories
code shield and cyers SEC eval 2 so what
is llama guard making safety tools
accessible to everybody so enabling
developers advanced Safety and building
an open ecosystem so llama guard is
their kind of architecture for making
sure that the models are being used
appropriately and here's what it looks
like we have the responsible llm product
development stages determine the use
case we have the model level so you're
actually creating the model we have the
system level where llama guard 2 and
llama code Shield are being implemented
and then building transparency here is
an evaluation meet llama cyber secc eval
and basically what it does is looks for
insecure code practices cyber attacker
helpfulness code interpreter abuse
offensive cyber security capabilities
and susceptibility to prompt injection
so it'll be interesting for this last
one because there have been a number of
jailbreaking techniques that have just
worked and completely shattered The
Cutting Edge closed source and open
source models and they have an entire
paper for this but I'm not going to go
over that now if you want to see that
let me know in the comments below and
yeah meta AI is brand new that's meta
doai that is their front end to their
inference engine they are basically
competing with chat GPT but it is free
at least for now so a better assistant
thanks to our latest advanced with metal
Lama 3 We Believe meta AI is now the
most intelligent AI system you can use
for free boy their continued releases
into the open source Community is such a
great defensive competitive play I
really believe that and the more they
release for free the more pressure they
put on closed models like gp4 like
Claude like Gemini and they will
continue to push down the price which is
good for everybody else for us
developers and users of these systems
and I've also been saying that models
are becoming commoditized very quickly
and we talked in a previous video a lot
about the AI stack and where the value
is going to be right so at the bottom we
have the hardware layer that's the
Invidia and the grocs of the world and
there's going to be a lot of value
created there but that you know probably
had to be started many years ago above
that we have the infrastructure layer
and that's agent orchestration tools and
evaluation tools and observability
deployment everything like that there's
going to be a ton of value there we have
the model layer which I don't think
there's going to be a lot of value in
the long run there and then at the very
top we have the app layer so apps built
with or apps completely built on top of
AI or existing apps that are now having
AI features and I do think that there's
going to be a lot of value there
although we haven't seen that yet so you
can use meta AI in feed chats search and
more across our apps to get things done
and access real-time information without
having to leave the app now what I think
they need to do and I don't think
they've done it yet but I bet they will
is start to integrate all the context
that you already have as a user of all
their systems into llama 3 so it
shouldn't just be a stateless engine all
the time we should be able to ask
questions about whatever's on the page
about my chat history about things that
I've done in the past that's really what
I'm excited about and now meta ai's
image generation is now faster producing
images as you type so you can create
album artwork for your band Decor
inspiration great I didn't actually know
you can create images with meta AI so
let me just give that a try real quick
create me an image of a robotic llama
all right yep there it is very cool
let's see what it looks like if it's any
good so I typically use Dolly and I'm
really happy with it it's fine wow okay
this is really good it's definitely not
as high quality as Dolly but it's good
and if you look right here we have an
imagined Watermark so they do Watermark
all all of their AI images so yep you
can use meta AI it's already on your
phone in your pocket for free starting
to go Global with more features you can
use it on Facebook Instagram WhatsApp
and messenger boy they are going hard to
get things done learn create and connect
with the things that matter for you they
are rolling out meta AI in English in
more than a dozen countries outside of
the US now people have access to meta AI
in Australia Canada Ghana Jamaica Malawi
New Zealand Nigeria Pakistan Singapore
South Africa Uganda Zambia and Zimbabwe
and we just getting started so this is
an example planning a night out with
friends ask meta AI to recommend a
restaurant with sunset views and vegan
options so it looks like it already does
have external context oh my God this is
so exciting organizing a weekend getaway
ask meta AI to find concerts for
Saturday night and we can just watch the
example happening right here so this is
within the messenger app you ask it a
question and boom pops it up right there
the information you need so you just at
meta AI it and then you can ask it
questions very very cool and they're
also including llama 3 meta AI in search
as well this is a huge launch for meta
so show me a video of the recipe great
these are really cool examples oh wow
they're even putting it in your feed so
I'm not a big Facebook user in fact I
don't really use Facebook at all but now
meta AI is available directly in your
feed that is their bread and butter
product that is how they make so much
money so it's interesting to see how
completely invested in Ai and
specifically llama 3 meta is so it's a
really good signal that if you're a
developer and you're thinking about
where to build your AI app llama 3 is
probably a pretty good option and here's
another example so you can simply say
imagine a bird and it'll give you an
image of a bird and then you say animate
and it will actually animate it so
that's very very cool now I still think
that the quality of the images is not
quite at the dolly or the mid journey
level but that's okay it's completely
fre which is nice and then yeah meta
just saying animate turns it into a gift
that you can share now here is the meta
llama GitHub page so they do actually
have the code and here it is here's the
code for llama 3 you could download the
models so I don't believe this is open
weight at least not yet now maybe I'm
getting that wrong but I don't see
anywhere where it says open weight so
this is open source because they are
open sourcing the code and you can
download the model and do with it what
you like you can fine-tune it but I
don't think the original weights are
released so if you want to check out the
GitHub repository it's github.com sleta
l/ lama3 and here's the model card for
it and this will likely be available on
hugging face if it's not already and
there's that 15 trillion token count
which is just insane that is an insane
amount of tokens and then they boiled it
all down to effectively the same size
model as lamao so it's 8B instead of 7B
and 70 billion parameter models and here
are a bunch of benchmarks here's llama 2
7B llama 2 13B and a bunch of benchmarks
and then llama 38b and across the board
100% of their scores are beating llama 2
and then here's the llama 370b and you
can see it is a market improvement from
the Llama 270b model again across the
board so I'm super excited to test this
out as soon as I'm done with this video
I'm going to start recording another
video testing it putting it through its
Paces in my llm rubric so if you enjoyed
this video please consider giving a like
And subscribe and I'll see you in the
next one
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