一口气搞清楚ChatGPT

Summary

The video discusses ChatGPT, a new AI chatbot that has taken the world by storm. It provides background on the history of chatbots, explaining how they evolved from using pattern matching to machine learning models like GPT (Generative Pre-trained Transformer). The key points are: - ChatGPT was created by OpenAI and is built on GPT-3.5, the latest iteration of their natural language processing model. It has over 175 billion parameters, allowing it to generate human-like text. - ChatGPT has subverted most people's perception of chatbots. It can understand questions across different fields and provide coherent answers. This is a major breakthrough in communication between humans and AI. - Microsoft invested $10 billion in OpenAI and integrated ChatGPT into its Bing search engine. This sparked an AI war with Google, who hastily introduced their own chatbot called Bard. But Google made mistakes in their rushed response, causing their stock price to drop. - ChatGPT doesn't actually understand meaning, it just calculates probabilities to predict the next best word/sentence. But it is so good at imitation that it can pass the Turing test. The breakthrough is in the interface, allowing seamless communication. - ChatGPT could disrupt many industries like search engines and education. It can do routine creative work like basic writing and coding very efficiently. People need to avoid repetitive tasks that can be automated. - There are still limitations with fabricated answers and outdated data. But the pace of progress is extremely rapid. The social impacts and future development remain uncertain. We are witnessing a pivotal moment in AI history.

Takeaways

• Chatbots have evolved over decades from using pattern matching to machine learning models like GPT.
• OpenAI developed the GPT language models and ChatGPT using transformer architecture and reinforcement learning.
• ChatGPT's conversational ability has sparked excitement but it has limitations like lack of understanding.
• Microsoft invested in OpenAI and integrated ChatGPT into Bing search engine.
• Google has its own conversational AI but didn't focus on search until ChatGPT's popularity.
• The AI chatbot space has seen surging investments and valuations lately.
• Generative AI like ChatGPT can take over routine and repetitive work.
• These technologies are having a disruptive impact on sectors like education.
• There are open questions around copyright and ethics with AI content creation.
• The future societal impact of increasingly capable AI remains uncertain.

Q & A

What are some key milestones in the evolution of chatbots over time?

Some key milestones are ELIZA in 1966 using pattern matching, SmarterChild in 2001 using machine learning, and GPT models like ChatGPT using transformer architecture and reinforcement learning.

How did OpenAI develop ChatGPT?

OpenAI developed ChatGPT using the GPT family of transformer-based language models and training them with reinforcement learning from human feedback.

What are some limitations of ChatGPT currently?

Current limitations are that ChatGPT doesn't truly understand content and lacks common sense. It can make up fanciful responses and has biases from its training data.

Why did Microsoft invest in OpenAI and integrate ChatGPT with Bing?

Microsoft invested in OpenAI to gain access to large language models like GPT. It integrated ChatGPT into Bing to enhance search results with conversational AI.

How is Google responding to the popularity of ChatGPT?

Google has its own conversational AI models but didn't focus them on search. After ChatGPT's popularity, Google hastily announced its Bard model to compete.

How much activity is there around AI chatbots among tech companies?

There has been surging investment and valuations around generative AI startups and acquisitions by tech giants, especially after ChatGPT.

What kinds of jobs are susceptible to being automated by AI like ChatGPT?

Repetitive, routine tasks with predictable patterns are more susceptible to automation by generative AI models.

How is ChatGPT affecting education?

ChatGPT is being used by many students for homework help, raising concerns about cheating and the need to reform education systems.

What are some open questions around AI like ChatGPT?

Issues around copyright over AI-generated content, ethical biases, and future societal impact remain open concerns.

What is the outlook on advanced AI like ChatGPT going forward?

The capabilities of AI models like ChatGPT will keep improving rapidly, leading to uncertain future impact on jobs, education, ethics, etc.

Outlines

00:00

Introduction and Overview

The first paragraph introduces the video script, mentioning that the narrator asked ChatGPT to provide an outline for the video and it generated a numbered list outline. It then previews that the video will bring together all the information about ChatGPT - what it is, how it works, the problems it solves and causes, and who it impacts.

05:01

History of Chatbots and AI

The second paragraph provides background on the history of chatbots and AI, mentioning key milestones like Eliza, Alice, pattern matching, machine learning and neural networks. It explains how capabilities have advanced over time to handle natural conversations but still face challenges in truly demonstrating intelligence.

10:01

The Creation of OpenAI and GPT

The third paragraph discusses the founding of OpenAI in 2015 by tech leaders to advance AI research. It traces the development of the GPT language models, with each version trained on more data and parameters to power ChatGPT's abilities. The shift to a capped-profit model enabled further investment from Microsoft.

15:02

How ChatGPT Works

The fourth paragraph explains ChatGPT's underlying approach - it uses probability to predict the next word/sentence that should follow, based on all the text data it has analyzed. This allows it to generate human-like responses on most topics, though it doesn't truly comprehend meaning.

20:03

Microsoft Partnership and Impact

The fifth paragraph covers Microsoft's multibillion investment in OpenAI and integration of ChatGPT with Bing search, posing a threat to Google. It compares strengths of ChatGPT versus Google's chatbots and explains why Microsoft was better positioned to push this technology.

25:04

Google's Response and the AI Wars

The sixth paragraph details Google's rushed response announcing the Bard chatbot and botched launch. It analyzes the AI wars between tech giants and the wider impacts as more companies fight for dominance in this space.

Keywords

💡Chatbot

A chatbot is a software program designed to simulate human conversation through text or voice interactions. Chatbots like Eliza, Alice, and Smarter Child were early attempts at conversational AI that used pattern matching to provide pre-defined responses based on keywords. ChatGPT represents a major evolution in chatbot capabilities, using deep learning rather than rules to have more natural conversations.

💡Machine Learning

Machine learning is a type of artificial intelligence where systems are trained on large datasets rather than given explicit programming instructions. Instead of coding rules and logic, machine learning models like neural networks discern patterns from examples to make predictions or decisions. The massive datasets used to train ChatGPT allowed it to have more human-like conversations.

💡Language Model

A language model in AI refers to a system that can predict sequences of words and generate coherent text. ChatGPT uses a language model called GPT-3.5 that has been trained on vast amounts of text data from the internet, books, and other sources. This allows it to continue sentences, answer questions, and write texts in a remarkably human manner by modeling statistical patterns in language.

💡Transformer

The Transformer is a novel neural network architecture published by Google in 2017 that marked a major advance in language modeling. Unlike previous models that processed words sequentially, Transformer processes an entire sequence at once using an attention mechanism. This breakthrough enabled training models on much more data and was foundational to GPT-3 and ChatGPT's abilities.

💡Reinforcement Learning

Reinforcement learning refers to goal-oriented algorithms that learn by receiving positive or negative feedback signals. The ChatGPT model was trained using reinforcement learning from human feedback, so that it could learn to provide better and more helpful responses through billions of conversations with human trainers. This helped it have more natural, friendly dialog.

💡Generative AI

Generative AI refers to machine learning techniques that can create novel content like text, images, video, and more rather than just classify or analyze data. ChatGPT is an example of generative AI because of its ability to generate human-like text responses to questions and prompts rather than just search an existing database.

💡Turing Test

The Turing test proposed by Alan Turing in 1950 is an evaluation of a machine's ability to exhibit intelligent behavior equivalent to that of a human. ChatGPT's impressive language capabilities lead some to claim it has passed the Turing test, though its factual inaccuracies suggest it does not completely understand the semantics of human conversation.

💡Bing

Bing is Microsoft's search engine. Microsoft announced it is integrating ChatGPT into Bing search to combine ChatGPT's conversational abilities with Bing's up-to-date information. This poses a major threat to Google's search dominance and was a catalyst for Google rushing its Bard launch.

💡LaMDA

Language Model for Dialogue Applications (LaMDA) is Google's conversational AI system using Transformer architecture. LaMDA served as the foundation for Bard, Google's ChatGPT competitor. But Bard's premature launch with factual errors proved embarrassing compared to the more polished ChatGPT.

💡Algorithmic Bias

Algorithmic bias refers to unfair biases encoded in AI systems' algorithms based on limitations or lack of diversity in the training data. ChatGPT sometimes exhibits gender, racial, or ethical biases learned from texts on the internet, demonstrating a broader issue with AI responsibility.

Highlights

Chatbots evolved from using pattern matching to machine learning models that can have more natural conversations.

Key innovations like Google's Transformer and artificial neural networks enabled breakthroughs in natural language processing.

OpenAI developed the GPT language models using deep learning, with innovations like reinforcement learning from human feedback.

Microsoft invested $1 billion in OpenAI and built them a supercomputer, obtaining exclusive access to key AI advancements.

ChatGPT subverts perceptions of chatbots with its ability to have human-like conversations on any topic.

ChatGPT calculates the next most probable words based on contextual patterns from vast data.

ChatGPT excels at communication between humans and machines by translating natural language.

Microsoft strategically integrated ChatGPT into Bing search, posing a threat to Google's dominance.

Google rushed its AI response with Bard, but made embarrassing mistakes in its rollout.

Capital floodgates opened into generative AI as Microsoft and Google battle for dominance.

AI innovations like ChatGPT could automate routine and repetitive work, displacing some jobs.

Education systems are disrupted by AI's ability to help with homework and assignments.

Legal and ethical issues arise on AI original content's copyrights and ownership.

The rapid pace of AI advancement opens up possibilities but has unknown societal impacts.

Google still leads in foundational AI research but was caught off guard by ChatGPT's capabilities.

The AI war has begun between tech titans Google, Microsoft, Tencent, Alibaba etc.

Transcripts

is what you all want me to talk about

I’m getting all kind of private messages

so let’s talk about it today

To save myself the trouble

I asked ChatGPT

if it could write me an outline for a video

Here you go

1234567, all listed out

Can you list in detail

Can you list in detail

Can you list in detail

Can you write a script for me?

I don’t even have to write a draft

You certainly can’t delve into the manuscript

If I follow the script

If I follow the script

However

If I follow the script

just look at its ability to write

just look at its ability to write

just look at its ability to write

and decently

I was shocked

American medical license

bar exam

with the ability to write novel, code and look up information

It’s like

anything that can be conveyed in words

It can do it

This thing

how did it suddenly appear out of nowhere?

Before this, there were also chatbots

but why is this one turning the world upside down

and excites

the capital market

And what are its problems

and how are those tech giants counter it

Who will be put out of work because of it

Although I’m not

Although I’m not

but today, let’s

put all the pieces together

and talk about

ChatGPT

All that you need to know about

Talking about chat bot

we’ll have to go back in time to 1950

Known as the Father of Computer Science

Father of Artificial Intelligence, Alan Turing

published an

epoch-making paper

He came up with a very philosophical

imitation game

The famous

Turing test

It means that if you are not in a face-to-face

text conversation

can you accurately determine whether the person you are talking to

is an actual person

or a robot

If it’s hard to tell

then to a certain extent

the machine is intelligent

Turing exam

is easy and simple to understand

and quite interesting

Hence it attracted

Hence it attracted

to attack it

In the beginning

are very simple commands

It uses some language technique

and trick

to make you feel that

you are talking to a person

For example in 1966

in MIT lab

they invented a chat bot

called Eliza

The developer is very clever

He set Eliza up as a psychotherapist

You see for these kind of therapist

normally they listen more and talk less

So it can ask

Do you have any thought?

And people can reply

and it ask again

How was your rest yesterday

and people reply

The less it talks, the less mistake it makes

It really makes people believed that

it’s listening and communicating with you

In fact, behind it is some

very simple code of if….

then….

For example if it sees the word

“mother”

It’ll tell you

Tell me about your family

Keywords like this

are about 200 words

30 years later

in 1995

Eliza came out with a junior named ALICE

It has evolved to be very powerful

Although still incomparable to ChatGPT

but it can handle

everyday conversation

But in essential

Regardless it’s Alice or Eliza

The principle

is based on Pattern Matching

Pattern Matching

When it sees a keyword

it’ll pick up one

pre-planned answer

For example if it hears Hi How are you

Have you eaten

If it hears Mother

it’ll reply tell me about your family

Something like this

In fact, even now

on some e-commerce site

or banking site’s chat bot

they are still

based on this model

If you are chatting with it

and mention refund

it’ll send you the procedure for refund

or if you say ATM

it’ll send you the map of nearest ATM

This pattern matching

although not very intelligent

did reduce a lot of that

mechanical repetitive answer from human

From the perspective of intelligence

These rule-based robot

no matter how complicated the rules are

or more preplanned answers

there won’t be infinite answer

nor can it create new answer

So

if you are trying to use the Turing test

to become real intelligent

it’s impossible to realise

with pattern matching

And so a new school of

language learning emerged.

This is also the most important part

in artificial intelligent

Machine learning

As the name implies, the basic principle

is to let the machine learn

Meaning, I wont be setting some

rules and answers

I’ll just dump lots of ready-made example

for you to learn and find the pattern

Sounds more impressive now right

it also complies to

our understanding on the logic of learning

Based on this principle

In 2001

There is Smarter Child

Smarter Child

That's when the robot went viral

Why did it go viral?

First, it used some of the more advanced models

of machine learning at the time

to make conversation more natural

Moreover in 2000

A large number of chat apps had sprung up

like AOL Windows Yahoo

So Smart Child

swept up all these chatting platforms

and let billions of people all over the world

to have a conversation with it

No matter what you ask

doesn’t matter the quality of answer

it’ll chat with you at least for a sentence or two

It can be said as the predecessor of ChatGPT

Something fun like this

immediately became popular all over the world

Attracted more than 30 million users

to have conversation with it

It receives more than 1 billion pieces of

information every day

information every day

it was bought by a giant company

Guess who

Microsoft

Microsoft has been coveting

this sector since that early

Although this Smarter Child

is already good in chatting

but it is still far from

passing the Turing test

In two sentences you’ll know

that’s a machine

Let's keep making progress

In 2010

There’s one area of machine learning

is starting to shine

Artificial neural network

Artificial neural network

Our brain

depends on

more than 10 billion neurons

through network connection

to judge and convey information

Although each of these neurons is very simple

but when combine

can judge very complex information

So this artificial neural network

is to simulate the model

of human brain

After entering information

It will go through the judgment of

several hidden neural nodes

like neuron

and give you an output

In fact, the idea of this neural network

has long been existed

We can trace it

back to 1960s

But it needs two things for support

A large amount of data and powerful computing power

which were not available before

So this neural network thing

is only a talk on paper

Later in the 2010s

The era of internet

Data is certainly available

the computing power

continues to improve exponentially

This is what makes neural networks

finally working

People realised that

This mode is really good for solving

those that people know by just looking

intuitive thing

For example when you look at a face

you can immediately know who the face belongs to

Except for Liu Qiangdong

I’m face blind

I don’t know if she is pretty or not

Before this, it’s very difficult

for computer to figure out

who the face belongs to

But with neural link

Machine learning can slowly figure out the pattern

It is now widely used

not just face recognition

voice recognition, automated driving

including few years ago

AlphaGo that beats professional Go player Ke Jie

are learning in this way

So this neural network

can make great achievements in those fields

we mentioned just now.

But back in the realm of writing

it didn’t go so well

it didn’t go so well

Because usually machine learning

Because usually machine learning

Recurrent Neural Network

RNN to process text

The way it works is

to look at word by word in order

then process it word by word

The problem with that is

It can't do a lot of learning at the same time

and the sentence can’t be too long either

Otherwise, when it learns the latter

it forgets the former

Until 2017

Google published a paper

and proposed a new learning framework

called Transformer

The exact mechanism is more complicated

It’s not something I can figure out

but the result is that it can let the machine

but the result is that it can let the machine

Before this you have to learn word by word

like a series circuit

Now you can learn at the same time

like parallel circuit

In this way, the speed and efficiency of training

has greatly improved

With the Transformer

the machine can now learn words

very easily

Many of today's natural language processing models

are actually built on

its infrastructure

The T in Google’s BERT

including the T in ChatGPT

including the T in ChatGPT

Alright now

there have been very strong breakthroughs

in technology

Everything is ready

all that’s needed now is people and money

It's time for ChatGPT to debut

In 2015

few tech giants like

Elon Musk, Peter Thiel

Elon Musk, Peter Thiel

Founded a non-profit organization called OpenAI

the parent company of ChatGPT

to conduct research on AI

Its an non profit organisation

not for earning money

Simply for the sake of

pushing the technology forward

Because of this, the research including patents

are made public

Look at the investor list

we can hear

the familiar name, Elon Musk

he gradually discovered that

his Tesla also needed to invest a lot of

research in AI

for automated driving

In order to avoid

conflict of interest between Tesla and OpenAI

In 2018

3 years after OpenAI was founded

he stepped down from the board

So now OpenAI

actually has no relation to Musk

Bye~

The OpenAI guys

are indeed incredible

In 2017

Google introduced Transformer

and they quickly conduct research and learning

based on this foundation

and published a paper in 2018

to introduce a new language learning model

Previous models of language learning

basically required human supervision

artificially set some labels for it.

but for GPT

it doesn’t need all that

You just need to put in data

and it’ll learn till it gets

That's about it

In June 2018, OpenAI

introduced 1st Gen of GPT

In November 2019

they increased the amount of training data

and introduced GPT-2

Actually for machine learning

they require two things

One is model, another is parameter

The model determine how the machine learns

With the same data

I can learn faster and better than anyone

then you’re great

As for parameter

It needs large volume of computation

To put it bluntly, you need to dump in lots of money

No matter how good the model is

you still need to put in lots of money to train and verify

You cannot have one without the other

OpenAI team

is very confidence with the model

but the next step requires money

For every single step forward

it needs

another level of magnitude of data to support

and all these

need money to support

For example DeepMind by Google

the company that came out with AlphaGo

their annual expenditure goes up to 400 or 500 million dollars

In the beginning at OpenAI

they received $1 billion investment

but it’s not enough

but it’s not enough

at this time it is still a non-profit organisation

When Musk stepped down

and the $1 billion sentiment is no longer sufficient

where am I going to find more people with the same sentiment

due to capital pressure

In 2019 OpenAI transformed from

non-profit organisation

but it didn’t change completely to profit-making organisation

they still needed the sentiment

and transformed the organisation to

Capped-profit company

What does it mean?

What does it mean?

cannot exceed 100 times

Once exceed 100, the amount beyond that

will not be retrievable by investors

and will belong to OpenAI

I’m curious

If my

investment return is close to 100

I'd get the money out and invest again

then won’t I get the 100?

Regardless,

OpenAI became capped-profit company

it means if you invest in it

you can get a return

Here comes Microsoft

with investment of $1 billion

Then the investment must be

a win-win for both sides

At the OpenAI side, first they got the money

second, Microsoft built them

the world’s fifth super computer

which greatly improved its training efficiency

Meanwhile Microsoft

also obtained OpenAI’s team and technology

And of course

the research from OpenAI

will no longer be public

Microsoft is definitely not investing on sentiment

Once OpenAI got the support of super computation

they were starting to prepare on a miracle

The first generation

has only 120 million parameter

GPT-2 has 1.5 billion parameter

6 months later

they came up with GPT-3

and the parameter rose by 100 times

became 175 billion

The effect was really good

so close

to the current ChatGPT

Just ask whatever

and it’ll give you answer

At that time, there was already

a wave of sensation in the industry.

However this pure machine trained GPT-3

has a problem

and that is sometimes it gives really good answer

but sometimes it’s a little bit off

Another problem is that

no matter how much you increase the parameter

the improvement made is very limited

This is because during training

it didn’t have a very good respond mechanism

Meaning, there’s no one to tell it

which answer is correct

or which kind of answer is not good

For example if I'm playing chest

I want to win right

Winning is good

so I train myself to win

But for chatting

it’s hard to make the judgement

How do I know if the answer is good

or not

Can only learn

So in order to solve this problem

During training, OpenAI

added human feedback mechanism

You can chat with me and I’ll tell you

if you are doing good or bad

The professional term is

Reinforcement Learning from Human Feedback

That’s why when using ChatGPT

you can feel that

it can be very lean and talkative

This is because the people training it

likes it that way

If the person training it

is very humorous

then the ChatGPT

would probably be telling you jokes all the time

After adding

Reinforcement Learning from Human Feedback

It has greatly improved both the

efficiency and the effect of training.

In March 2022

the introduced GPT-3.5

where the conversation was optimised

In November 2022, they introduced

It's actually a very, very simple

chat interface

No matter what you ask

it could give you

all the answer

that sound reasonable

Of course there’ll be some problems

we’ll talk about it later

But if you look at it roughly

It really could talk about anything

And the language expression

is really like talking

After half a century

This time ChatGPT

This time ChatGPT

Turing test easily

Impressive right

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Lately ChatGPT is going viral

If you’d like to see

which concept stocks is getting viral because of ChatGPT

you just need to search ChatGPT

then you can see

US, Hong Kong stocks

Not only famous tech giants

like Microsoft and Google

you’ll also find

some unheard

potential stocks

For example

if I want to know which stock has potential

like TSMC

you can see the rating from Wall Street analyst

Target Price Forecast

And which stocks give

positive or negative signaks

Moomoo has it all

All those people are usually concern about

like Financial aspect, Technical aspect, Fundamental aspect

are all available

Not only they sort out

these information for free

the graphic visualisation

is quite intuitive too

including real-time updates

on global AI news

are even translated for you

Apart from ChatGPT

they have a Concept Segment

where you can see other concept stocks

like robotic science,IOT

Even if you’re not into buying stocks

it’s good to get an understanding

They also have millisecond quotes

and support 0.0037 seconds

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they are making miracle in technology

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Alright, let’s get back to ChatGPT

Anyway it

has subverted

most people's perception of chatbots

including me

So in just two short months

ChatGPT's monthly active users exceeded 100 million

The rate of expansion must be the fastest in history

The rate of expansion must be the fastest in history

But honestly

with ChatGPT being so subversive

The shock that the product itself

brings to people

has far surpassed those data

Until now

when I look at its answer

It didn’t all come out

in one go

it came out bit by bit

just like how a person is talking to you

Sometimes it really does give me goosebumps

But I guess a year from now

It shouldn't be surprising

for everyone to see this again.

Alright now let’s see

how does ChatGPT able to

chat on questions

of any fields

To put it simply

A large language model like GPT

it essentially calculates the

next word, next sentence

what should appear next

it’s a matter of probability

For example when it says I’m very

and the continuation to that

so many words in the database

it could be I’m very happy, I’m very healthy

I’m very anxious, I’m very hungry, etc

but you need to have a context

For example if the text above says the weather is nice today

then it could compute

that it’s I’m very happy

Actually every answers, every words

are just simple

It's calculated based on the correlation of previous text

when it learns enough

Hundreds of billions of parameters and words

After finding patterns through these complex models

It forms a

very large neural network

You don't need to tell it

What is programming and what is video scripting

It’ll know from learning more and more

It’ll know from learning more and more

This is what a video script should look like

So I asked it to write one

ChatGPT video script for me

From the conclusion of the correlation

it gives out answer word by word

It is still a language model

imitating how human talks

But does it know

the meaning of what it says?

At least the current ChatGPT version

doesn’t completely understand

It's like a kid who has a really good memory

but doesn't really know anything

and imitating adult

But make us think

it knows everything

This is why

This is why

it’s almost close to perfection

very much like human

But there are often

some logical mistakes

for us it’s like stupid mistake

of addition, subtraction, multiplication and division

This is because

it is actually a language model

For now

actually

GPT also often

has a lot of fabricated answers

Meaning to say

it doesn’t know what it’s talking about

but it was just not making sense

Including a lot of moral and ethical problems

For example if you ask what does it think about human

It’ll say

Human beings are inferior and selfish

It's the worst kind of creature

and should be wiped out

Then it must not know

what it is talking about

don't know where it learned this from

but all these nonsense problems

are all problems with the current version of ChatGPT

Although now

it’s just simply imitating

But as it get better and better

at imitating

and that in 99.99% of the cases

it can answer correctly

So whether it really understands

or just imitating

it doesn't really matter much

This was a question which

Alan Turing had already discussed in his paper

on the Turing Test

Rather than us asking

Can machines think like humans

might as well ask

Can machines do what humans do

It’s deep

Actually, I think

One of ChatGPT's major breakthroughs was

to greatly improve the efficiency of communication

between humans and machines

Human beings communicate information

primarily with words

The computer uses code

Humans have always accommodated computers

You’ll have to learn programming first

And figure out

program it to a

language that computer could understand

and let it execute

including search

We also change our questions

into few keywords

and then search

It changes

Computers can slowly understand people now

I can talk to it directly

then it’ll translate itself

and execute

Everyone thought ChatGPT was amazing

It knows everything that you ask

But the amazing thing about it

isnt’t that it

can do these tasks

It is mainly

it could accurately understand your question

And then contextualize

from its vast database

and come out with the most appropriate information

and tell you in human words

This communication link

is actually the most amazing part

It has such a powerful interface

Then we can more easily

hand over a lot of things

to the machine

Wouldn't that make things

much more efficient

Can you imagine

if we connect it

to a speech recognition system

like Siri

and let it talk to you freely

and if you could connect it to

professional analysis interface

like analysing AI stocks

and connect it to

programming and computing machine

as well as visual generation

then everyone of us

could be like in the movie

Iron Man and his assistant

For example if you ask it to compute

Mobius ring

and it’ll start computing

and then you say

Superb

You see how ChatGPT

opens up so many possibilities at once

and it is the hottest thing in the market now

the major shareholder behind it, Microsoft

must be really happy

So they started to invest more money

and in January they announced

to invest $10 billion

It was valued at $29 billion

This time the deal

between Microsoft and OpenAI

is quite interesting

For Microsoft

after they invested $10 billion

the revenue that OpenAI received

they have to give Microsoft 75%

until they get the $10 billion back

Meaning to say Microsoft is making sure

that the money they invested will get a return

Also, Microsoft hold

49% of OpenAI stake

And there’s a

100 fold upper limit of return on investment

A rather peculiar deal

When this deal is done

on February 7th

Microsoft held a press conference

They announced to incorporate ChatGPT into

their own search engine Bing

Microsoft called it “Copilot for the Web”

it’s like a web assistant

Actually there’s another problem with ChatGPT

the problem is that the training data

is only up till 2021

Meaning to say

it doesn’t know the recent events

When Microsoft combines it with Bing

the logical side they use ChatGPT

while news and information

can be searched with Bing

Isn’t it a strong alliance

ChatGPT For example if I ask ChatGPT

do you know Lin's channel?

it would say no

If I ask Bing

it’ll say Lin's channel

is a fun and useful

content creator

It's a good example for many people

who want to pursue their dreams

I'm a little embarrassed by that

So it’s viral for a reason

And Microsoft is sneaky

the chat function

can only be used on their own

Edge web browser

I have to say

their marketing

I give full mark

So in the face of all this publicity

the most anxious is Google

Why?

Because ChatGPT is likely to shake up

their biggest piece of the pie

Search engine

Imagine if I ask ChatGPT

and it can organize the language to tell me

So when I want to search for something

I don't have to go through

them myself

I can just ask ChatGPT

then no one will use search engine anymore

Can Google not panic

It now occupies 93% of the

93% global search engine market

That's a solid monopoly

Although Microsoft’s Bing is in second place

but it’s only 3%

Advertising revenue brought by the search business

can account for 60% of Google's total revenue

everyone was doing fine

and suddenly there’s GPT

Actually

Google has been leading

in AI sector

The Transformer

is created by Google

They have actually been testing

a robot named BERT

It’s similar to ChatGPT

but they didn’t spend a lot of energy

to train it

They also have another robot

which is more impressive, called LaMDA

It's based entirely on normal human conversation

So it can even make jokes

Or express emotions

It’s not at all like you ask

and it answers

Because it does speak so naturally

It even fooled

a test developer who was

working inside Google

I believe that LaMDA already has consciousness

Almost like a seven or eight year old

So

Google has actually

been very strong on chatbots

But its position is

quite different from Microsoft's

Google

is already the top in search engine sector

then they had to build a robot

and cut down their cash cow

Surely not unless it's a last resort

So that’s why

I think

the LaMDA

is more focus on conversation and chat

and not like ChatGPT

can answer any question

And they haven’t released these AI robots

is also because

they are worried about their reputation

After all their focus is on search engine

which needs to be strict and accurate

If they introduced

an untrained

speak nonsense robot

then that’s outrageous

On the other hand, training on such a large scale

requires a lot of computing power and burns money

Each question consumes roughly

10 to 100 times as much energy

as a Google search today

For example ChatGPT

now has to spent

$10 million per day to operate

So you can see

Microsoft's first-mover advantage

is indeed very reasonable

Not only they invested in the right company

but they also

have the ruthless hand to spend all these money

In the face of strong public opinion pressure from Microsoft

Coupled with overwhelming media coverage

Google can’t hold on longer

Just after ChatGPT was launched

Google initiated

Code Red

This is the moment

of our life or death

We need to focus the entire company

on the AI circuit

Because the key to this thing is that you have to be fast

How fast?

So fast that Google was about to twist its ankle

We mentioned earlier that Microsoft’s press conference

was on February 7th

where they announced to integrate ChatGPT

into their search engine

Google in a hurry

organised a press conference on February 8th

and introduced a conversational AI called Bard

This is developed based on their

Chatbot LaMDA

Just look at the stock prices of

Microsoft and Google after Google's announcement

You’d know how bad it is

for Google

You can't blame anyone in this business

You don't have to read any professional analysis

You just need to stay calm

watch their press conference

from beginning till the end

then you’ll know why

Everyone knows that

people are focusing on

AI chat

But during Google's 40 minutes press conference

they talked about their previous achievements

and later picture search

In the middle of this, the speaker

couldn't find the mobile phone for presentation

So have to skip this part

Later, when they finally got to the point

and begin to introduce Bard

they only talked for a few minutes

During the press conference

they also showed a video

introducing Bard

The terrible thing is that there are

factual mistakes in Bard's answer in the video

Actually to be honest

everyone can understand

if this type of chatbot

makes some factual error

However

the answer in the commercial video is incorrect

and even forgot to bring mobile phone

it was nothing but great cry and little wool

It’s obvious that

Google was doing it hastily

this is what the market is worrying about

Although ChatGPT is great

but everyone knows that

Google is the power house in AI sector

So even though you didn’t

make much noise

the outsiders would know you not to be messed with

and that you are holding back something big

They initiated the red alert

because it is to let

outsiders know that they take this matter seriously

Don’t sell out your stock first

Before the press conference

Google’s stock price is not worse than Microsoft

But they had to hastily

do something that

make a fool of themselves

So Google's market value evaporated

$100 billion

But in comparison, Microsoft is much more stable

Microsoft’s CEO

OpenAI’s CEO all came out

and personally explain

The nearly one-hour press conference

focused on the AI chat function

Plus various demos

Obviously well prepared

The AI war just started

Google was first caught off guard

by ChatGPT

And then out of panic

they did stupid mistake

The first battle was a disastrous defeat.

However this is only the first battle

Google is still Google after all

What’s gonna happen next

we’ll just wait and see

Of course this AI war

is not limited to these two companies

Meta, Baidu, Tencent, Ali

are all fighting to get in

Stocks that had anything to do with generative AI

started to soar

Nvidia, AMD

hardware manufacturer that provides computing power foundation

profited from this

Actually for AI chatting, AI painting

AI programming

all these generative AI

have been under development spurt

since two years ago

The amount raised over the past few years

From 2021, 2022

It's already taking off

It's over a billion dollars a year

As the year 2023 begins

Microsoft started with $10 billion

Capital has done all it can

to get into this track

This thing is developing so fast

will it cause many people to lose their jobs?

Who will lose their jobs?

Will it cost you your job?

technological innovation

It's always a double edged sword

it may create more jobs

Unemployment rate does not necessarily fall

The overall GDP will probably rise

But in the short term

It will certainly cause some people to lose their jobs

I was thinking how do you think we could

try to not lose our job

and even use this AI tool

to increase our productivity

My personal opinion

is that we have to avoid

repetitive routine work

When computers first came out

It might solve some

repetitive human tasks

Everyday doing the

same thing over and over again

You can fix it with a computer for loop

But now

it’s not just the repetitive works

Even routine work

as long as you have routine

even though every day you think you are creating content

but in actuality it doesn’t require much brain power

then this kind of task the computer

can quickly get it in the matter of minutes

What is routine work?

Let me give you an example

For example I let ChatGPT

write a fairy tales on Xiao Lin

It’ll come up with Xiao lin has a cat that can speak

it defeated dragon

saved the princess and became a hero

And I tell it, no it’s wrong

Xiao Lin is a woman, rewrite it

It’ll say Xiao lin is a woman

who has a cat that can speak

It defeated bad witch and became a hero

You see

this is the routine of a fairy tale

There’s an animal that can speak

defeated something and became a hero

Although the speaking cat

is basically useless in the story

but it is the standard of fairy tales

Similarly

There are some exceptionally skilled engineers

who can write codes

with their eyes shut

Writers who could

write 20 chapters of online novel in a day

Or some very basic

financial report of the company

basic design

basic legal advice, etc

For these tasks

once you get familiar you can do it with eyes shut

Because it has a routine

So now AI is learning these routine

so you don’t even have to do it anymore

AI will do it all

Attention, I’m not saying that

programmer, accountant or writer

or analyst will be replaced

It’s just that the routine part of

their work can be

easily learned by machine

So if you think there are some

routine tasks in your job

you need to be careful

Or at least

don’t put these routine work online

Else AI will learn it

Actually not just on unemployment

Because it is so

subversive

we can already see

the huge impact

on society

For example in education sector

it's only been online for a few months

Among the students

over the age of 18 in the United States

90% of them have used ChatGPT to help them with homework

Apart from sports

can it really help in any subject

How would I know

if you are doing the homework yourself

Of course it doesn't mean that

we can't use it to help

It's just that our current education system

is not ready for ChatGPT

It's as if we've spent hundreds of years

building a better

transportation system

but suddenly one day

all the cars could fly

From technical view point, flying car

is good in long-term

but right now when we don’t have a

complete new system

while everyone is flying their car

then it’ll be chaotic

The social order

would be greatly disrupted

So for companies and schools

they haven’t figure out how to integrate ChatGPT

into their existing system

For now they can only

ban it first

The content that AI created

the painting it created

who will own the copyright

These are really tough questions

So this generative AI

no one can say for sure

how it will develop in the future.

The ChatGPT team

did not have any special purpose

at the very beginning

Just put the data in

and let the machine learns

It was later that they discovered

how powerful it is

and could even connect to search engine

Everyone is basically tapping in the dark

You don’t know when one day

the AI is suddenly become enlightened in one field

Sometimes I feel that

It is actually quite exciting

to witness such a miraculous development of AI.

Pandora's box is

being opened bit by bit