CLAUDE 3 Just SHOCKED The ENTIRE INDUSTRY! (GPT-4 +Gemini BEATEN) AI AGENTS + FULL Breakdown

Summary

Anthropic's release of Claude 3, a new generation AI model, has taken the tech world by surprise. The model, including its variants - Claude 3 Hi, Cou, and Opus, outperforms existing AI models across various benchmarks, showcasing near-human comprehension and advanced capabilities in analysis, forecasting, and multimodal tasks. With its sophisticated vision capabilities and reduced refusals, Claude 3 is set to redefine the standards for AI intelligence and user interaction, offering a range of applications from complex problem-solving to language learning and content creation.

Takeaways

• 🚀 Anthropic released the next generation AI model, Claude 3, which outperforms all other models on benchmarks.
• 🌟 Claude 3 includes three models: Hi, Cou, and Opus, with Opus being the most intelligent and capable of near-human comprehension.
• 📈 Claude 3 models show increased capabilities in analysis, forecasting, content creation, and conversing in non-English languages.
• 📊 Claude 3 Opus surpasses GPT 4 and Gemini Ultra 1.0 in benchmarks, nearing 100% accuracy in some categories.
• 💡 The qualitative aspect of AI performance is highlighted, emphasizing user experience and satisfaction with the model.
• 👀 Claude 3 models possess new vision capabilities, allowing them to process various visual formats and assist enterprise customers.
• 🔍 A demonstration shows Claude 3 Opus performing complex, multimodal analysis and generating sub-agents for parallel task processing.
• 📝 Claude 3 models have improved accuracy and reduced refusals, offering more nuanced understanding and better user interaction.
• 🔥 The release of Claude 3 signifies a rapid evolution in AI, with new models quickly surpassing previous state-of-the-art systems.
• 📚 The potential use cases for Claude 3 models are vast, including task automation, interactive coding, data processing, and language learning support.

Q & A

What is the name of the new AI model released by Anthropic?

The new AI model released by Anthropic is called Claude 3.

How many new models were released as part of the Claude 3 family?

Three new models were released as part of the Claude 3 family: Claude 3 Hi, Claude 3 Coup, and Claude 3 Opus.

What sets Claude 3 Opus apart from other AI models?

Claude 3 Opus is considered the most intelligent model, outperforming its peers on various evaluation benchmarks for AI systems, including undergraduate and graduate level expert knowledge and reasoning.

What are some of the capabilities of the Claude 3 models?

The Claude 3 models show increased capabilities in analysis and forecasting, nuanced content creation, and conversing in non-English languages such as Spanish, Japanese, and French.

How does Claude 3 Opus perform on benchmarks compared to GPT 4 and Gemini's 1.0 Ultra?

Claude 3 Opus surpasses both GPT 4 and Gemini's 1.0 Ultra on benchmarks, showing higher percentages in categories like common knowledge, SWAG, and other tasks.

What is the significance of the multimodal capabilities of the Claude 3 models?

The multimodal capabilities allow the Claude 3 models to process a wide range of visual formats, including photos, charts, graphs, and technical diagrams, making them effective at tasks beyond just text.

How does Claude 3 Opus handle complex tasks like analyzing the world economy?

Claude 3 Opus can use tools like web view and Python interpreter to analyze data, create plots, perform statistical analysis, and even dispatch sub-agents to complete complex tasks in parallel.

What improvements have been made in the Claude 3 models regarding refusals?

The Claude 3 models show a more nuanced understanding of requests and refuse to answer harmless prompts much less often than previous generations, reducing unnecessary refusals.

What are the potential use cases for the different Claude 3 models?

Opus is for task automation and complex actions, Sonet is for data processing and sales recommendations, and Haiku is for customer interactions, quick support, and content moderation.

How does the recall accuracy of Claude 3 Opus compare to other models?

Claude 3 Opus has near-perfect recall accuracy, surpassing 99%, and can identify limitations in the evaluation process itself.

What is the context window offered by the Claude 3 models at launch?

The Claude 3 models initially offer a 200k context window, but they are capable of accepting inputs exceeding 1 million tokens for enhanced processing power.

Outlines

00:00

🚀 Introduction to Claude 3 AI Models

The script introduces the release of the next generation AI model, Claude 3, which has surprised the AI community by outperforming other models on benchmarks. It highlights three new models within the Claude 3 family: Claude 3 Hi, Claude 3 C爪, and Claude 3 Opus, with increasing intelligence and cost. The Opus model is particularly noted for its state-of-the-art intelligence, surpassing other AI models in various evaluations, including expert knowledge and reasoning, mathematics, and non-English language capabilities.

05:01

🌟 Claude 3's Multimodal and Vision Capabilities

The script discusses the multimodal capabilities of the Claude 3 models, which include sophisticated vision capabilities. It emphasizes the excitement for enterprise customers, as the models can process various visual formats and have been trained on tool use. A demonstration is provided where Claude 3 Opus analyzes the US GDP trends, creating a markdown table and a plot of the data with high accuracy. The model also performs statistical analysis and Monte Carlo simulations, showcasing its advanced capabilities.

10:02

🤖 Sub-Agents and Complex Analysis

The script explores the concept of sub-agents in the Claude 3 models, which allows the model to break down complex tasks into sub-problems and delegate them to other versions of itself. This feature is demonstrated through an analysis of the world economy, where the model generates a prompt for other models to follow, leading to a comprehensive analysis and prediction of GDP changes across major economies. The script also touches on the potential for AI models to learn from their predictions as they come true.

15:02

📚 Haiku Model and Document Processing

The script introduces the Haiku model, which is highlighted for its speed and affordability. It demonstrates the model's ability to process thousands of scanned documents from the Library of Congress Federal Writers Project, transcribing and understanding the content. The model can also generate structured JSON output with metadata, offering potential applications for organizations with extensive archives of scanned documents.

20:03

🗣️ Sonnet as a Language Learning Partner

The script showcases the Sonnet model's ability to act as a language learning partner. It describes a scenario where the model helps improve Spanish language skills by correcting messages, providing ideal learner messages, and engaging in conversation. The model can also create quizzes based on the discussion, aiding in language learning. The script also mentions improvements in the new generation of models, such as reduced refusals and improved accuracy.

📈 Claude 3 Model Comparison and Potential Use Cases

The script compares the three Claude 3 models, highlighting their unique features and potential use cases. Opus is noted for its highest intelligence, Sonet for its balance between intelligence and cost, and Haiku for its speed and low cost. The script emphasizes the state-of-the-art nature of the Claude 3 models and their potential to surpass other AI systems, inviting users to test and explore the capabilities of these new models.

Keywords

💡Anthropic

Anthropic is the company responsible for the release of the AI models discussed in the video. They have surprised the AI community with the release of their next-generation AI model, Claude 3. The company's focus on AI development is evident in their ability to create state-of-the-art models that outperform others in benchmarks and evaluations.

💡Claude 3

Claude 3 is the latest AI model from Anthropic, which includes three new models: Claude 3 Hi, Claude 3 Cou, and Claude 3 Opus. These models are designed to offer varying levels of intelligence and capabilities, with the Opus model being the most advanced and capable of near-human levels of comprehension and fluency on complex tasks.

💡Benchmarks

Benchmarks are standardized tests or criteria used to evaluate the performance of AI models. In the context of the video, benchmarks are used to compare the capabilities of different AI models, such as Claude 3 and GPT 4. The script highlights that Claude 3 models surpass other state-of-the-art models in various benchmarks, indicating their superior performance.

💡Multimodal

Multimodal refers to the ability of an AI model to process and understand multiple types of data inputs, such as text, images, and diagrams. The Claude 3 models are described as having sophisticated vision capabilities, allowing them to process a wide range of visual formats, which is a significant advancement in AI technology.

💡Sub-agents

Sub-agents are smaller, specialized versions of an AI model that can be dispatched to perform specific tasks as part of a larger, complex problem-solving process. This capability allows the main model to break down complex tasks into smaller, more manageable sub-problems, enhancing the efficiency and effectiveness of the AI's problem-solving.

💡API

API, or Application Programming Interface, is a set of rules and protocols that allows different software applications to communicate with each other. In the context of the video, the mention of APIs suggests that the Claude 3 models will be integrated into various applications, enabling users to leverage their advanced capabilities in diverse contexts.

💡General Intelligence

General intelligence, or artificial general intelligence (AGI), refers to the ability of an AI system to understand, learn, and apply knowledge across a wide range of tasks, similar to human intelligence. The Claude 3 models are described as leading the frontier of general intelligence, indicating their advanced cognitive capabilities.

💡Context Window

The context window refers to the amount of previous data or conversation an AI model can reference when generating a response. A larger context window allows for more nuanced and contextually relevant responses. The Claude 3 models are capable of accepting inputs exceeding 1 million tokens, which is a significant increase from previous models.

💡Recall Accuracy

Recall accuracy is a measure of an AI model's ability to correctly remember and retrieve information from a large dataset. High recall accuracy is crucial for tasks that require precise information retrieval. The Claude 3 models demonstrate near-perfect recall accuracy, surpassing 99%, which is a testament to their advanced memory capabilities.

💡Vision Capabilities

Vision capabilities in AI refer to the model's ability to process and understand visual information, such as images, charts, and graphs. The Claude 3 models are described as having sophisticated vision capabilities, which enable them to analyze visual data and provide insights, a significant advancement in AI's multimodal understanding.

💡Latency

Latency in AI refers to the delay between a user's input and the AI's response. Low latency is desirable for real-time interactions, such as live chats or automated customer support. The Claude 3 models, particularly Haiku, are noted for their near-instant response times, which are crucial for applications requiring immediate feedback.

Highlights

Anthropic released the next generation of AI models, Claude 3, which outperforms all other AI models on benchmarks.

Claude 3 family includes three models: Claude 3 Hi, Cou, Law, and Opus, with increasing intelligence and cost.

Claude 3 Opus is the most intelligent model, exhibiting near-human levels of comprehension and fluency on complex tasks.

Claude 3 models show increased capabilities in analysis, forecasting, content creation, and conversing in non-English languages.

Claude 3 Opus surpasses GPT 4 and Gemini's 1.0 Ultra on benchmarks, setting a new standard for AI intelligence.

Claude 3 models have sophisticated vision capabilities, processing various visual formats like photos, charts, and diagrams.

Claude 3 Opus can perform complex, multi-step, multimodal analysis, including creating sub-agents to handle complex tasks.

Claude 3 models have improved accuracy and reduced refusals, showing a more nuanced understanding of requests.

Claude 3 Opus has near-perfect recall accuracy, surpassing 99% in certain cases.

Claude 3 models can accept inputs exceeding 1 million tokens, offering enhanced processing power for long context prompts.

Claude 3 Sonet is designed for high endurance in large-scale AI deployments, offering strong performance at a lower cost.

Claude 3 Haiku is the fastest and most cost-effective vision-capable model, ideal for quick responses and seamless AI experiences.

Claude 3 models are expected to enable citations, allowing them to point to precise sentences and reference material for verification.

The release of Claude 3 signifies rapid evolution in the AI space, with new models quickly surpassing previous benchmarks.

Anthropic's team has developed a state-of-the-art AI system that is expected to have significant implications for various industries.

Transcripts

so something actually shocking did

happen in AI today and that was

anthropic release of the next generation

of Claude Claude 3 now this was a model

that took Everyone by surprise because

it beats every other AI model across the

board on the main Benchmark so without

wasting any more time let's get into the

meat of this release so you can see here

that they actually released three new

models and in the clae 3 Model family

there is Claude 3 hi coup claw 3 Sonet

and Claude 3 Opus and essentially you

can see as the models increase in

intelligence the cost does go up quite

slightly but these three different

models are very very fascinating and

later on in the video I'll show you how

they all differ and how Claude 3's Opus

the one right here how this model is

smarter than any other AI currently

available making it state-ofthe-art you

can see that they said a new standard

for intelligence Opus are most

intelligent model model outperforms its

peers on most of the common evaluation

benchmarks for AI systems including

undergraduate level expert knowledge

graduate level expert reasoning basic

mathematics and more it exhibits near

human levels of comprehension and

fluency on complex tasks leading the

frontier of general intelligence all

Claude 3 models show increased

capabilities in analysis and forecasting

nuanced content creation C generation

and conversing in non-english languages

like Spanish Japan Japanese and French

and now this is where we actually get to

the crazy benchmarks because you're

about to see something that surprised me

and caught me off guard these benchmarks

are actually quite shocking you can see

that clae 3 their most powerful model

Opus actually surpasses the other

state-of-the-art models you can see that

GPT 4 and Gemini's recently released 1.0

Ultra actually I wouldn't say pale in

comparison to the new model but they

actually do get surpassed on these bench

marks clearly you can see here that the

undergraduate level knowledge the MML U

is at

86.8% compared to the other models it is

beaten and what's crazy is that we can

see that on the left across the board

this is excelling at every single tasks

and this goes to show how crazy things

are because it was only recently that we

did just get Gemini Ultra which

surpassed GPT 4 on every single

benchmarks but now we literally just get

clothed three only around 2 to 3 months

later that surpasses Gemini 1.0 Ultra on

every single benchmarks you can see that

this is some really really impressive

stuff because if we take a look at the

percentages we are nearing 100% in some

categories you can see 95.4% on common

knowledge L swag and we can see on some

of these other ones that it's 96.4%

90.8% and 95% so this is something that

really did shock me because I didn't

expect a clae release for a little a

little bit more but not only did they

surprise me about the release date these

benchmarks surprisingly managed to take

on Google already which is a very

impressive feat and Dethrone GPT 4 now

something that I did see and this is of

course around the first hour of this

model being released was that there is a

qualitative aspect that you can't sort

of look at when you're looking at these

benchmarks essentially what I mean here

is that whilst it is good to yes look at

these benchmarks and think okay how does

the AI do on the these on these maths

problems on these coding problems and

reasoning over text but the actual

qualitative data that you can get from

your users is something that is very

important because at the end of the day

it's your users who's going to be using

this that determine whether or not your

product is actually good and so far

based on what I've seen the qualitative

data where people are actually talking

about how good the model actually is

shows us that this model isn't just good

at reasoning and doing well on some of

the benchmarks this is clearly a model

that people really do like you can see

here that this person says excited to

share what we've finally been working on

to me talking to Opus feels different

than talking to any other large language

model it seems just to get you this

can't be represented in any evaluation

metric or Benchmark you have to just go

experience it yourself and then this

person says evaluations aside Clause 3

Opus feels like the smartest model I've

talked so that is something that I feel

will be important and I would love to

see where this model ends up on the llms

chatbot Arena because that is something

that uses quality data to judge where

the models actually do lie and I think

it is a very important metric one of the

most surprising things that we did get

from the clae 3 release was of course

the vision capabilities Claude 3's

different models and I will get into

later how these models actually do

differ do possess New Vision

capabilities this is actually a model

that is multimodal it states that the

claw 3 models have sophisticated Vision

capabilities on par with other leading

models they can process a wide range of

visual formats incl including photos

charts graphs and Technical diagrams

we're particularly excited to provide

this new modality to our Enterprise

customers some of whom have up to 50% of

their knowledge bases encoded in various

formats such as PDFs flowcharts or

presentation slides so you can see that

clae 3 is finally becoming a model that

is very very effective at a wide range

of tasks not just text and something

that is important is they've actually

shown us a demonstration on how well

Claude 3 Opus combined with the Vision

model is going to be at doing in this

video we're going to see if Claude and a

couple of friends can help us analyze

the world economy in a matter of minutes

okay I've asked Claude 3 Opus which is

the largest model in anthropics new

Claude 3 family to look at the GDP

trends for the US and write down a

markdown table of what it sees we've

given Opus and all the other models in

the clae 3 family extensive training on

tool use and one of the major tools it's

using is this web view tool it goes to a

URL looks at what's on the page and

because it's multimodal it can use the

information on that page to solve

complex problems so here's the markdown

and it's important to note that CLA

doesn't have direct access to these

numbers it's literally looking at the

same browser you and I are seeing

looking at the trend line and trying to

estimate what the exact numbers are

let's see how accurate it was we've

asked the model to create a plot of the

data and it's used the second tool this

python interpreter to write out the code

and then render the image for us to

check and here's the image look it's

actually added helpful little tool tip

animations to explain some of the major

Peaks and troughs in the last decade or

two of the US economy and we can compare

that graph with the actual data and it

turns out it's pretty close it's

actually within 5% accuracy and by the

way Cloud's transcription here isn't

just coming from its pre-existing

knowledge of US GDP we tried it with a

large sample of madeup GDP graphs and

its transcription accuracy was within

11% on average next we asked the model

to do some statistical analysis

projecting out into the future

performing simulations to see where the

GDP of the US might head and we can see

that it's run this analysis using Python

and it's able to perform these Monte

Carlo simulations to see what the range

of GDP possibilities might look like for

the next decade or so but I wonder if we

can go further we're going to get the

model to analyze a more complicated

question that is how GDP might change

across all of the biggest world

economies and then to help it do that

we're going to give it one more tool

called dispatch sub agents this

basically allows the model to break down

the problem into lots of sub problems

and then write prompts for other

versions of itself to help pick up the

slack the models can then complete a

more complex task by all working

together here you can see it's written

this prompt and given very precise

instructions that it wants the other

models to follow including a format for

the data that it's hoping to return it's

dispatched matched a version of this

prompt to one model that's going to look

at the US one for China One for Germany

Japan and so on we can see in these

progress bars that the sub agent models

are now completing the set task for each

of the individual economies they're

going to the relevant web pages they're

getting the information they're running

the code to analyze it just like we saw

in the previous US example but all in

parallel let's just skip forward to see

what the model produced you can see it's

run the analysis it's produced a pre-

and post pie chart of how it expects the

world economy to look in 2030 versus

2020 and it's given us a written

analysis too where it makes variable

predictions that relate to the

statistical analysis that it ran it's

telling us that it thinks the GDP share

of particular economies will change and

which ones will be larger or smaller by

2030 so there we have it complex

multi-step multimodal analysis run by a

model that can create sub agents to get

get even more tasks running in parallel

we're excited to see what you our

customers can do with these Advanced

clae 3 capabilities so yeah that small

demo was rather impressive we actually

got to see Claude 3 act as not only

someone who is able to accurately take

data from an image that doesn't exactly

have the data just doing pure estimates

which is really really good and just

shows how well their visual system is

but also a very very interesting feature

that caught me off guard were two of

them the first one being this

simulations I think that this is really

really cool we can see it doing some

kind of you know kind of tree search

which looks absolutely amazing and is

going to be very very useful for data

analysis like they stated it's going to

be used for predicting things and I do

wonder how some of those predictions

will hold up in the future and you know

if we actually do use the future data

and then say look this actually was

correct cor maybe we could even get

models that are increasingly

increasingly smarter as their

predictions come true they decide to I

guess you could say reinforce that data

somehow so that is going to be a whole

new area that I really didn't see before

that I'm excited to explore with Claude

3 now I know most people are going to be

excited about this and so was I the sub

agents area was something that I found

to be absolutely astounding this is

where you can literally get an AI model

to automatically decide to dispatch sub

agents to do the rest of the task and I

just find that that is a concept that is

really really effective and you can see

here that it managed to complete the

task with much more efficiency than just

asking one model so I think that what we

have here on that demo was showing us

just how great this claw 3 Model is not

just in terms of its Common Sense

reasoning in terms of its Vision

capabilities but also in terms of its

ability to do complex step-by-step

reasoning with mult multiple different

tasks and that right there within the

API and Tool use which they state is

coming soon I'm guaranteeing you is

going to have some massive implications

for the industry because people are

going to be using this in very very

creative ways as we've seen with other

AI models next of course we do have

another short demo and this is by the

other model Haiku and this one is very

very fascinating too Claude Haiku is one

of the fastest and most affordable

Vision capable models in the world to

demonstrate this we're going to read

through thousands of scanned documents

in a matter of minutes the Library of

Congress Federal writers project is a

collection of thousands of scanned

transcripts from interviews during the

Great Depression this is a gold mine of

incredible narratives and real life

Heroes but it's locked away in hard to

access scans of transcripts imagine

you're a documentary filmmaker or

journalist how can you dig through these

thousands of messy documents to find the

best source material for your research

without reading them all yourself since

these documents are scanned images we

can't feed them into a text only llm and

these scans are messy enough that they

would be a challenge for most dedicated

OCR software but luckily Haiku is

natively Vision capable and can use

surrounding text to transcribe these

images and really understand what's

going on we can also go beyond simple

transcription for each interview and ask

Haiku to generate structured Json output

with metadata like title date keywords

but also use some creativity in judgment

to assess how compelling a documentary

the story and characters would be we can

process each document in parallel for

performance and with claude's high

availability API do that at massive

scale for hundreds or thousands of

documents let's take a look at some of

that structured output Hau is able to

not just transcribe but pull out

creative things like keywords we've

transformed this collection of many many

scans uh into Rich keyword structure

data imagine what any organization with

a knowledge base of scan documents like

a traditional publisher healthcare

provider or Law Firm can do Haiku can

parse their extensive archives and

bodies of work we'd love for you to try

it out and see what you build so once

again that was a very impressive demo on

how these Vision capabilities can be

used at scale for multiple Industries in

multiple applications and once again I

can't imagine what people are going to

do once they do get their access on the

apis now another thing that was actually

really cool was that they stated that

there is going to be immediate response

from one of the claw 3 models and that

is of course their most lightweight

model ha cou so it states that ha cou is

the fastest and most cost effective

model on the market for its intelligence

category and it can read an information

and data dense research paper on arxiv

which is around 10,000 tokens with

charts and graphs in less than 3 seconds

so following launch we expect to improve

performance even further and for the

vast majority of workloads Sonet is two

times faster than claw 2 and 2.1 these

are the previous models with higher

levels of intelligence and it excels at

tasks demanding rapid responses like

knowledge retrieval or sales Automation

and opus delers similar speeds to claw 2

and 2.1 but with much higher levels of

intelligence so you can see right there

these near instant results are going to

be able to provide some very very

interesting applications because as you

all know AI that is very latency Laden I

guess you could say isn't something that

is quite effective in certain responses

for example in live chats Auto

completions and in certain scenarios

where responses must be immediate and

real time IQ being the most cost

effective model and the fastest is going

to be interesting to see if it actually

does manage to Dethrone some of the

other ones who are very very quick but

considering the intelligence it might

just be haikou that takes the cake

there's also another very impressive

demo that I do want you all to see and

this is their model sonnet acting as a

language part this is just a simple

prompt to turn son it into a dialogue

agent that will talk with you in a

language that you're trying to learn so

I chose Spanish and I wanted it to

basically take my imperfect Spanish and

and help me improve it um so I decided I

wanted it to do a few things things I

wanted it to take my message which will

be in kind of imperfect Spanish um and

write out what it thinks I intended in

English I then ask it to write back the

ideal learner message which is just my

message as it kind of should have been

written in Spanish so I can see the kind

of Ideal form of this uh then I asked it

to write a teacher response which just a

response to me in Spanish uh so that I

can continue the conversation great so

this is basically just son it saying

that we're ready to start so I'll just

start with a simple first message and

here it's following the format that I

asked for so it's repeating the message

that I tried to send it back to me in

English it's telling me how I should

have said it so it's corrected some of

the grammar issues in my request um and

then it's responded to me in Spanish and

then it's asked me uh where I'm from so

okay now imagine I don't know a certain

word in Spanish but I still want to say

it I'm going to just include that word

in English in square brackets and

hopefully it will just translate it back

to me and suppose I hit a roadblock

because I just don't understand the

message that it's sent to me I can just

ask it to translate that message to me

into English and then I can read that

and I can respond to it again in Spanish

continuing the dialogue and as a final

step you could ask Sonet to create a

little quiz for you based on the things

that you've been discussing so hopefully

that is a useful prompt if you're

interested in using Sonet as a language

learning partner I hope you try out now

something in addition that I did also

want to mention was less refusals you

can see here that claw 3 actually

refuses things a lot less it states that

previous clawed models often made

unnecessary refusals that suggest Ed a

lack of contextual understanding we've

made meaningful progress in this area

Opus Sonet and highq are significantly

less likely to refuse answer prompts

that border on the system's guard rails

than previous generations of models as

shown below the claw 3 models show a

more nuanced understanding of requests

recognize real harm and refuse to answer

harmless prompts much less often this is

definitely something that I would say is

a win for Claude and anthropic because

one of the main problems with Claude 2.1

was that it really just didn't answer

many of your questions prob most of the

times it just refused to answer your

questions leading to user frustration

and I was someone who was actually in

that group because trying to use Claude

when it's very very good is very very

fun but when it doesn't want to respond

to what you're stating because it thinks

there's a real danger when there really

isn't is one of the most frustrating

things you could ever experience but you

can see they've now improved this

another thing was of course the improved

accuracy and they state that businesses

of all size rely on our models to serve

their customers making it imperative for

our model outputs to maintain high

accuracy at scale to assess this we use

a large set of complex factual questions

that Target known weaknesses in current

models and we categorize the responses

into correct answers incorrect or

hallucinations and admissions of

uncertainty where the model says it

doesn't know the answer instead of

providing incorrect information compared

to claw 2.1 Opus demonstrates a two-fold

Improvement in accuracy or correct

answers on these challenging op

open-ended questions while also

exhibiting reduced levels of incorrect

answers in addition to producing more

trustworthy responses we will soon

enable citations in our claw 3 models so

they can point to precise sentences and

reference material to verify their

answers now there was also something

that I really wanted to talk about which

is the perfect recoil Lord 3 Opus has

recoil accuracy that borders on 99% they

state that the Claude 3 family of models

will initially all offer a 200k context

window upon launch and however all three

models are capable of accepting inputs

exceeding 1 million tokens and we may

make this available to select customers

who need enhanced processing power to

process long context prompts effectively

models require robust recall

capabilities the needle in a haystack

evaluation measures a model's ability to

accurately recall information from a

vast Corpus of data and they state that

we enhance the robustness of this

Benchmark by using one of the 30 random

needle question pairs per prompt and

testing on a diverse crowdsource Corpus

of these documents Claude 3 Opus not

only achieved near perfect recall

surpassing 99% accuracy but in some

cases it even identified the limitations

of the evaluation Itself by recognizing

that the needle sentence appeared to be

artificially inserted into the original

text by a human so you can see here that

claw 3 is actually a very very effective

system that is able to completely

identify what's going wrong in it a

200,000 context window and they also

state that all of these models are

capable of 1 million token context input

which just goes to show the era of 1

million context window is upon us and

this is very very impressive stuff

because this now allows for a lot more

use case capabilities now one of the

main questions that I actually had when

looking at Claude was of course the

difference between the three models this

was something that was a little bit

confusing when looking at the blog post

initially but they've actually made made

it really simple to understand if you

want the cliff notes you can just

screenshot this and share it to whoever

might need it but essentially Opus is

just the highest intelligence available

it's the smartest model that you use if

you're trying to get the most factual

answer sonnet is strong performance at a

lower cost so it's a balance of the

intelligence and of course the cost and

Haiku is the near instant speed and a

very low cost so that is essentially the

difference between these three models if

you were wondering now we can dive into

a little bit more detail on these model

models you can see that clae 3 Opus and

then you can see at the bottom here it

does have the differentiator and the

differentiator is the main thing that

you do want to pay attention to this is

just higher intelligence than any other

model available you can see it costs the

costs do seem quite steep if I'm being

honest with you guys like that does seem

like a pretty expensive model but then

again this is a state-of-the-art AI

system that is leading the frontier of

AI intelligence so there's no surprise

that this model is that expensive now of

course it shows us the potential uses

for Opus and it does say task automation

plan and execute complex actions across

API and databases interactive coding

research and design research review

brainstorming and hypothesis generation

drug discovery of course we've

additionally got strategy Advanced

analysis of charts and graphs financials

and market trends forecasting and then

of course the highest intelligence of

any other model and this is Opus now

then of course we do have Sonet which is

where they State CLA 3 Sonet strikes the

ideal balance between intelligence and

speed particularly for Enterprise

workload it delivers strong performance

at a lower cost compared to its peers

and it's engineered for high endurance

in large scale AI deployments it says

that the potential use cases for this

are data processing it says rag or

search and retrieval over vast amounts

of knowledge sales product

recommendations forecasting targeted

marketing and time-saving tasks such as

code generation quality control and pass

text from images of course like I stated

before it's more affordable than other

models with similar intelligence and

it's better for for scale so if there is

a model with similar intelligence as

Sonet this model is just a bit cheaper

then of course we do have Hau and CLA 3

Hau is our fastest most compact model

for near instant responsiveness it

answers simple queries and requests with

unmatched speed users will be able to

build seamless air experiences that

mimic human interactions so of course

the potential use cases for this are

customer interactions quick and accurate

support in live interactions and

translations content moderation catch

risky Behavior or customer requests and

cost-saving tasks such as optimize

Logistics Inventory management extract

Knowledge from unstructured data and

essentially smarter faster and more

affordable than any other models in its

intelligence category so overall we can

see that this new state-of-the-art

system claw 3 by and thropic has really

surprised everyone and taken us back

because it is something that is now a

state-of-the-art model that surpasses

every other AI system so this is

something that is quite fascinating

because the AI space is always rapidly

evolving and it was only a couple of

months ago that we had a new AI system

literally surpassed GPT 4 and now that

system has been surpassed so it seems as

if the race is heating up and things are

accelerating but I leave you all with

this question what do you think about

claude's new model are you going to be

testing this out because of course right

now you can see that you can actually

use Claude if you want to if you want to

be able to just test out how good the

system is and I'm going to be doing

another video and actually testing out

the system showing you some of the best

use cases because I feel like that is

better saved for another video rather

than talking about this actual

announcement so hats off to the

anthropic team for an amazing product

and hopefully we can all have some fun

using this amazing new AI system