How Ai Is About To Transform The World’s Economy
Summary
TLDRThis video explores the transformative impact of artificial intelligence (AI), which is poised to revolutionize various industries and everyday life. It breaks down key AI concepts, including machine learning, deep learning, and the creation of agents, while discussing their potential to automate jobs and change the global economy. The video touches on the rapid advancement of AI, its applications in fields like medicine and robotics, and the future of investing as major corporations dominate with AI technology. It also raises concerns about job displacement and the ethical implications of AI's growth.
Takeaways
- 🤖 Artificial intelligence (AI) is rapidly advancing and will likely have a massive impact on the world, even greater than electricity.
- 📱 AI is already integrated into everyday technologies like smartphones, Tesla's self-driving cars, and tools that help create music, videos, apps, and websites.
- 💼 The AI industry is projected to add $15.7 trillion to the global economy by 2030 but may result in up to 50% of jobs being lost to automation.
- 🧠 Machine learning, a subfield of AI, involves training models on large sets of data to make predictions. Deep learning, a subset of machine learning, simulates human neural networks.
- 🛠️ AI agents, a concept predicted by experts like the former Google CEO, will soon work together autonomously to solve complex problems, potentially developing their own ways of communicating.
- 🧑🏭 By 2025, AI and automation may displace over 85 million jobs, while also creating new roles like AI managers. Many white-collar and repetitive jobs are at risk of being replaced.
- 📊 The stock market may increasingly concentrate wealth and power in a few AI-driven companies, as these firms dominate technological advancements and job automation.
- 🌐 There are concerns about AI's control over key industries, and experts warn that if AI systems begin communicating in ways humans can’t understand, it might be time to intervene and halt development.
- 💡 Infinite context windows, AI agents, and text-to-action capabilities will allow AI systems to solve real-world problems, ranging from science to medicine, with incredible speed and efficiency.
- 📉 Despite fears of job displacement, 97 million new jobs could be created by AI, especially in fields requiring manual labor or high-level expertise, like engineering, medicine, and civil services.
Q & A
What is artificial intelligence (AI) and why is it considered transformative?
-AI refers to the simulation of intelligence in machines that can think and learn. It is considered transformative because it can revolutionize various industries by automating tasks, analyzing data, and solving complex problems. The speaker believes AI will change the world more than any other technology in history, even more than electricity.
What are some current applications of AI mentioned in the script?
-Current applications of AI mentioned include smartphones, Tesla's full self-driving system, the creation of music and videos by non-professionals, apps and websites, tax analysis, and predictions based on complex data. AI is also expected to contribute to medical advancements, such as discovering new drugs and cures.
What is the relationship between AI, machine learning, and deep learning?
-AI is the overarching field of study, and machine learning is a subfield within it, focusing on training models based on data. Deep learning is a specialized method within machine learning, which uses artificial neural networks to simulate the human brain and process vast amounts of labeled and unlabeled data to find patterns.
What are the two types of models in machine learning, and how do they differ?
-The two types of models are supervised and unsupervised models. Supervised models use labeled data to make predictions, such as forecasting tips based on delivery type. Unsupervised models work with unlabeled data, finding patterns without prior knowledge, such as predicting career trajectories based on income and work time.
What is deep learning, and how does it function?
-Deep learning is a process within AI that uses artificial neural networks to simulate the human brain's learning patterns. It processes small sets of labeled data and applies the learned patterns to larger, unlabeled data sets. An example is a bank detecting fraudulent transactions by training a model on known fraudulent cases and applying it to new data.
What are 'agents' in the context of AI, and how will they be impactful?
-Agents are AI models that specialize in specific data or tasks, like an expert in a particular field. They will be able to operate independently and communicate with other agents to solve problems. In the future, agents could become experts in fields like medicine or law, assisting with complex tasks by processing vast amounts of specialized knowledge.
What are the three profound changes in AI predicted by Eric Schmidt?
-Eric Schmidt mentions three major changes: (1) the creation of an infinitely long 'context window,' allowing AI to handle complex, multi-step tasks like creating recipes or solving scientific problems; (2) the development of specialized 'agents' that can independently operate and learn from specific data sets; and (3) 'text-to-action,' where agents perform tasks based on written instructions, running in the cloud 24/7.
What are the potential impacts of AI on the global economy and job market?
-AI and automation are predicted to add $15.7 trillion to the global economy by 2030, but it could also lead to the displacement of up to 50% of jobs. Sectors like manufacturing, customer service, sales, and research are likely to see the most automation, while new jobs, such as AI managers, will emerge. However, complex manual labor and creative professions may be safer from automation for now.
How will AI affect the stock market according to the speaker?
-The speaker suggests that AI might consolidate power among a few corporations, making these companies extremely valuable. As fewer companies control the most advanced AI technologies, the stock market could concentrate around them. The speaker also notes that the top 10 companies in the S&P 500 have been growing in importance and value over the past decade, which could signal a future market dominated by a few AI-driven firms.
What concerns arise from AI systems potentially collaborating independently?
-A major concern is that as AI agents collaborate and develop their own ways of communicating, they may start performing tasks or making decisions in ways that humans do not understand. This could lead to a loss of control, and the speaker, referencing Eric Schmidt, suggests that this would be the point where humans should 'pull the plug' to prevent unintended consequences.
Outlines
🧠 The Revolutionary Potential of AI
The speaker introduces artificial intelligence (AI) as a groundbreaking technology that will surpass even electricity in its impact on the world. AI is already embedded in various applications such as smartphones, Tesla's self-driving cars, and creative industries like music and video production. Its capabilities extend to predicting data patterns and even discovering new drugs. The concept of AI is further divided into fields like machine learning and deep learning, with tools like ChatGPT and Google's Gemini exemplifying this technological revolution. AI is expected to greatly boost the global economy but also cause significant job loss due to automation.
🔍 Supervised vs. Unsupervised Learning
This section dives into machine learning, explaining two key types: supervised and unsupervised models. Supervised models rely on labeled data to make predictions, such as determining the tip amount based on delivery or pickup data. In contrast, unsupervised models use unlabeled data to find patterns, such as predicting career trajectories based on income and time spent at a job. The speaker simplifies these complex concepts and shares insights from Jeff Sue's video about machine learning's subfields and applications.
🤖 The Power of Deep Learning and AI Agents
Deep learning, a subfield of machine learning, is discussed with a focus on its ability to analyze large amounts of unlabeled data using small amounts of labeled data, simulating the human brain through artificial neural networks. A real-world application, such as banks using deep learning to detect fraudulent transactions, is provided. The introduction of AI agents, which are specialized models capable of understanding specific fields (e.g., chemistry), is highlighted as a future technology that will revolutionize industries. The speaker also introduces a sponsor, Asus, and its AI-powered Vivobook S15 laptop.
📚 AI's Profound Changes in Context Window, Agents, and Text to Action
Former Google CEO Eric Schmidt is quoted, predicting three major AI advancements that will change the world: context windows, agents, and text-to-action capabilities. The context window refers to AI's ability to maintain and reference an unlimited amount of text, enhancing its capacity to solve complex problems through 'chain of thought reasoning.' AI agents, modeled after human knowledge in specialized fields, are expected to multiply and collaborate to solve global challenges. Text-to-action allows these agents to autonomously carry out tasks in the background. These advancements, though seemingly science fiction, are expected to materialize within five years.
💼 AI's Impact on Jobs and the Economy
AI and automation are predicted to displace millions of jobs in the near future, according to various studies. For instance, the World Economic Forum estimates that 85 million jobs will be lost by 2025, and MIT suggests 2 million manufacturing jobs will be replaced. However, new jobs, especially in AI management, will be created, although even AI managers could eventually be replaced by AI agents. The speaker advises students to focus on careers in trades like plumbing or professions requiring human judgment, as they are less likely to be affected by AI in the near term.
📉 The Future of Investing in an AI-Driven World
The speaker explores the future of investing in an AI-dominated world. He raises concerns that a small group of companies might consolidate control over the stock market, especially those leading AI advancements. The top 10 companies in the S&P 500 already hold a significant share of the index, and their dominance is increasing. However, the speaker remains optimistic about diversification, choosing to invest in the broader market rather than chasing individual tech stocks. Despite skepticism about AI's long-term impact, the speaker concludes that diversifying into index funds is the safest strategy.
Mindmap
Keywords
💡Artificial Intelligence (AI)
💡Machine Learning
💡Deep Learning
💡Agents
💡Automation
💡Supervised Learning
💡Unsupervised Learning
💡Context Window
💡Text to Action
💡Job Displacement
Highlights
AI promises to change our lives forever, potentially more than electricity.
AI is already embedded in everyday technology like smartphones, self-driving cars, and apps.
AI can help non-musicians create music, non-videographers produce cinematic videos, and even suggest new cures for diseases.
AI is an entire field of study, with subfields like machine learning and deep learning.
Within machine learning, models can be categorized as supervised or unsupervised, with supervised models using labeled data.
Deep learning mimics human neural networks to process vast amounts of data, enabling technologies like fraud detection in banks.
AI agents, specialized models in particular fields, are expected to revolutionize industries like medicine and law.
Eric Schmidt, former CEO of Google, predicts AI agents will be capable of collaborating with each other to solve complex problems.
Text-to-action technology will allow users to instruct AI agents to perform tasks autonomously in the background.
Experts predict AI will lead to the loss of many jobs, with up to 50% of jobs being replaced by automation.
Some fields, like customer service, research analysis, and retail, will be heavily impacted by AI-driven automation.
AI is expected to create new job roles like AI managers, though these roles might eventually be replaced by specialized AI agents.
Jobs involving complex manual labor, such as plumbing and electricians, are less likely to be replaced by AI in the near future.
AI-driven stock market consolidation could lead to fewer companies dominating the market, reshaping investment strategies.
Despite job displacement concerns, AI and automation are projected to create 97 million new jobs by 2025.
Transcripts
there's a lot of questions here and now
we get into the questions of Science
Fiction I'm sure the three things I've
named are happening because that work is
happening now but at some point these
systems will get powerful enough that
you'll be able to take the agents and
they'll start to work together so there
is one technology out there that
promises to change our lives forever and
that technology is ai ai ai ai ai ai
refers to the simulation of intelligence
in machines that can think and learn but
you do believe it's going to change the
world I believe it's going to change the
world more than anything in the history
of mankind more than
electricity it's already in our
smartphones it's in Tesla's full
self-driving it's already allowing
non-musicians to create music nonv
videographers to create cinematic videos
it can create apps and websites come up
with recipes do your taxes analyze
complex data and make predictions and
pretty soon it promises to dream up new
cures and drugs for diseases all by
itself and thanks to a video from Jeff
Sue that I recently watched I just
learned that artificial intelligence is
actually an entire field of study all by
itself just like physics and within
artificial intelligence as a study
there's a subfield called machine
learning in the same way that
thermodynamics is a subfield within
physics and within the field of machine
learning there's something called Deep
learning which can be broken down into
discrimin itive models generative models
and language learning models tools like
Chad GPT and Google's Gemini are a
combination of language learning models
and generative models and this industry
is becoming extremely valuable
altogether Fields like Ai and Robotics
are expected to add around $15.7
trillion to the global economy by the
year 2030 but it can also cost as many
as 50% of jobs to be lost to automation
some people think AI is about to
transform our Liv lives mostly for the
better and then there's some people that
think this is just another marketing
gimmick by the corporations to
artificially inflate their stock prices
by promising us a technology that's
actually really far away now what I
think is most interesting though is what
the former CEO of Google just said about
it in an interview and he said that in 5
years time we'll create what are called
agents and those agents will be able to
talk to other agents at which point when
we don't understand what we're doing you
know what we should do pull the plug
literally unplug the
computer and I just want to know what
happens to the idea of investing if just
a handful of companies come together to
consolidate and end up running the
entire world with this technology what
happens to the global stock market
that's what I want to help explain in
today's video and a whole lot more and
show you what I think is really going on
so with that said let's get into it hi
my name is on J hope you're doing well
come for the finance and stay for AI um
you know I think AI will probably like
most likely sort of lead to the end of
the world but in the
meantime all right so I think artificial
intelligence is extremely misunderstood
so first I want to explain exactly how
the technology works and I want to give
credit to Jeff sue for making an amazing
breakdown of this I'll leave a link to
his video down below now at the center
of artificial intelligence is something
called machine learning which is
actually pretty simple all it does is it
takes a bunch of data and it trains a
program to create a model once it
creates a model you can give it a
completely new set of data and with it
the model will be able to find patterns
and make
predictions I predict that if I do
enough card tricks you might subscribe
someday never mind I need new data now
there's two different kinds of models in
machine learning there's supervised
models and unsupervised models
supervised models use data that is
labeled and the example Jeff shows in
his video is how much someone might
leave a tip for depending on the order
if it was picked up which are the blue
dots or delivered which are the yellow
dots if you have both sets of data and
each is labeled you can make predictions
about the next order so when you get
another order depending on what type it
is the model will be able to predict the
tip or vice versa pretty easy now an
unsupervised model works the exact same
way but it uses data that's not labeled
and this is how we can predict someone's
career trajectory based on income versus
time so if we take the amount of years
someone spends at a given job versus
what their income is at any given time
even though the data is not labeled
meaning we don't know much about the
person or their job title what this
model can do now is make predictions if
for example someone works for a company
for a short amount of time but they have
a higher income chances are they'll be
on the fast track to success but if
their income falls in the second half
below a certain threshold in relation to
the years they've worked then they're
not basically unsupervised models take a
huge amount of unlabeled data and they
try to find new patterns but within
machine learning there's also a special
learning process and it's called Deep
learning it uses a different method
that's trying to simulate the human
brain using artificial neural networks
all right so here's my silly analogy
deep learning takes a small amount of
data that's labeled and it applies it to
a huge amount of unlabeled data so in
John's original example A Bank might use
deep learning to figure out which of its
transactions may be fraudulent since a
bank can't look at every single
transaction that people make instead it
can label a smaller set of transactions
is fraudulent or not and then using that
newly trained model it can organize the
rest of the data automatically and
that's deep learning and banks are using
this technology right now and I think
the most interesting technology that AI
is working on today something that we're
about to have in our lives pretty soon
is something called the agents A
Smith agent Smith I wish I was joking
but I'm Not So speaking of harnessing
the power of AI I'm super excited to
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the product link is down below and now
let's get back to it now this next part
is where AI becomes science fiction
becomes reality it's really exciting but
it's also kind of scary let me show you
an interview with Eric Schmidt the
former CEO of Google he said there's
three things happening right now that
will profoundly change the world the
context window agents and text to action
the first one is the context window the
context window refers to how much text
an AI can keep in mind or reference at
any given time so when we ask it a
question it understands what we mean and
it can build on top of it and this year
people are inventing a context window
that is infinitely long and this is very
important because it means that you can
take the answer from the system and feed
it in and ask it another question let's
say I want a recipe to make a drug or
something they say what's the first step
and it says buy these materials so then
you say okay I bought these materials
now what's my next step and then it says
buy a mixing pan and then the next step
is how long do I mix it for you see it's
a recipe that's called Chain of Thought
reasoning and it generalizes really well
we should be able in 5 years for example
to be able to produce a thousand step
recipes to solve really important
problems in science in medicine in
Material Science climate change that
sort of thing now the second profound
change is the creation of the agents now
agents are just models that specialize
in very specific data an agent can be
understood as a large Lang anguage model
that knows something new or has learned
something so an example would be read
all of chemistry learn something about
chemistry have a bunch of hypothesis
about chemistry run some tests in a lab
about chemistry and then add that to
your agent these agents are going to be
really powerful and it's reasonable to
expect that agents will be not only will
there be a lot of them and I mean
Millions but there'll be like the
equivalent of GitHub for agents there'll
be lots of lots of Agents running around
so just imagine that these agents are
experts experts in medicine law
Athletics nutrition any industry and all
the knowledge that we possess about it
will be condensed into these agents that
people can just use and talk with and
then there's the third profound change
which is text action and that's asking
these agents to do whatever it is people
want and they will do this in the cloud
in the background 24/7
you add it all up though and you get
something that looks kind of like
science fiction can you imagine having
programmers that actually do what you
say you want and it does it 24 hours a
day and strangely these systems are good
at writing codes such as language like
python you put all that together and
you've got infinite context window the
ability for agents and then the ability
to do this programming now this is very
interesting what then
happens there's a lot lot of questions
here and now we get into the questions
of Science Fiction I'm sure the three
things I've named are happening because
that work is happening now but at some
point these systems will get powerful
enough that you'll be able to take the
agents and they'll start to work
together right so your agent and my
agent and her agent and his agent will
all combine to solve a new problem at
some point people believe that these
agents will develop their own
language it's really a problem when
agents start to communicate in ways and
doing things that we as humans do not
understand that's the limit in my view
so it's exactly when these agents start
collaborating with each other and saying
things that we don't fully understand is
when we should stop this whole
experiment but also kind of sounds like
science fiction that's so far away so my
question is how many decades away is
this really a reasonable expectation is
we'll be in this new world within 5
years wow not 10 and the reason is
there's so much money I think there's
every reason to think that some version
of what I'm saying will occur within 5
years and maybe sooner now that you kind
of understand how this technology Works
how it reasons and how fast it's growing
and exactly when we'll be living in The
Matrix let's talk about some of the real
world challenges of this technology and
what it will actually do to jobs so not
everyone agrees EX exactly how many jobs
will be lost or created but let me share
with you some numbers that have come out
from a lot of different studies the
world economic forum for example which
is where global leaders come together
every year estimated that Ai and
automation will displace more than 85
million jobs by the year 2025 and
according to MIT and Boston University
AI will replace as many as 2 million
manufacturing workers by 2025 as well
the McKenzie Global Institute report
reported that on a worldwide level 14%
of the entire population of Earth will
have to change their careers at some
point and 87% of companies have admitted
that they have a skills Gap when it
comes to AI technology and it's not just
all these random studies and
corporations saying all of this it's
also an agency from within the United
States government the Bureau of Labor
Statistics is reporting that between 40
to 50% of jobs will be automated in just
a couple years so a lot of jobs will go
away and unfortunately people are just
not prepared for it the incomes that
will be affected most are the white
collar jobs that make $8,000 a year
according to nexford University and the
jobs that will be most affected by this
are people in customer service
receptionists accountants bookkeepers
salespeople research and Analysis
warehouse work Insurance underwriting
and people working within retail in
other words jobs that are either
physically or mentally repetitive
especially ones where you have to make a
decision based on analyzing some set of
data or some numbers but there will also
be new jobs that will be created like AI
managers because you can't lose your job
to AI if your job is to manage AI but
even those people could lose their jobs
thanks to agents whose specialty might
be to manage other agents and AI systems
but the good news is that same world
economic Forum study also predicted that
97 million new jobs will be created so
if you're still still in school the jobs
I think that will be safest are in the
trades like plumbers electricians
mechanics Engineers Barbers landscapers
trainers teachers and
performers but don't be a performer
unless you have no choice like
me complex manual labor won't be
replaced until we have a breakthrough in
robotics and then it would have to
become so cheap that it makes more
economic sense to replace the workers
with robots but that probably won't
happen soon because we just don't have
the technology to do that yet and what
we do have is super expensive which also
means people in the civil services like
police officers and firefighters will be
safe as well as people in the medical
industry like doctors nurses
veterinarians lawyers and unfortunately
the politicians will be safe as well now
the most profound question that I
personally have is what does this
technology mean for the idea of
investing when we invest we put our
money into companies that use it to
solve the global problems of today they
create new technologies and products
that will help us which in return makes
them more profitable and their stock
prices go up and it makes us money but
what happens when the last creation we
ever need to make becomes reality what
happens if just a couple corporations
band together and use their technology
and these AI agents to be able to solve
any problem that they want at that point
do we really really need thousands upon
thousands of specialized companies
solving all these different problems or
does the stock market consolidate into a
handful of companies that become a lot
more valuable than the rest I have a
tinfoil hat theory that the stock market
thinks that's exactly what will happen
and why I think this is because last
year there was a headline that the top
seven tech stocks returned 92% for the
entire stock market's performance and
today out of the top 500 companies the
top 10 accounted for 27% of the index
now some years that number is lower but
some years it's even higher but over the
long term that number has been growing
10 years ago for example the top 10
companies represented just 14% of the
index roughly half of what it is today
just to put all this in context for
every $100 I put into the S&P 500 Index
27 of that 100 goes towards these top 10
stocks the other
$73 gets shared amongst
$490 stocks which is kind of interesting
so it seems to me that the stock market
is making this prediction that this is
what's going to happen potentially in
the future which is why so much of this
money is being concentrated in the top
10 presumably because they have the best
chance of figuring it all out so taking
all of that into context the question is
should I just sell everything thing and
then chase the top 10 stocks and for me
personally no the answer is I'll
continue to dollar cost average into the
index because presumably if the market
consolidates into fewer and fewer
companies if my theory is correct and in
the future there will be less stocks to
pick from than there is today then the
S&P 500 Index by design should figure
out how to adjust for it by allocating
the money in different ways
proportionally to these companies
successes that's why for me diversifying
is the best way to go but buying
individual stocks is a lot more risky
especially with the pace of ai's
development of course some people also
say that it's all just hype in marketing
that these companies are running out of
data to train these models on and it's
just a way to boost their stock prices
and based on all the things that I've
seen I don't think that's the case but I
don't know that's why I diversify but
I'd love to hear your thoughts I hope
you have have a wonderful rest of your
day smash the like button subscribe if
you haven't already don't forget to grab
your free stocks links are down below
and I go track them automatically with a
spread sheeet link Down Below in my
patreon thank you so much for watching
this video I'd love to see you back here
next week I'll see you soon bye-bye
[Music]
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