一口气搞清楚ChatGPT
Summary
TLDRThe 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 - There are still limitations with fabricated answers and outdated data.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
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.
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.
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.
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.
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.
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.
Mindmap
Keywords
💡Chatbot
💡Machine Learning
💡Language Model
💡Transformer
💡Reinforcement Learning
💡Generative AI
💡Turing Test
💡Bing
💡LaMDA
💡Algorithmic Bias
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
This reminds me of
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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
and support 0.0037 seconds
So you can really see
they are making miracle in technology
Recently in Japan, Moomoo open up
functional experience of the platform
The users
If you are interested
click on the link down below
and experience it for yourself
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
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
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