AI Expert Explains Future Programming Jobs… and Python
Summary
TLDRThe video discusses how AI is poised to transform industries beyond tech and consumer software. It explains how new low-code/no-code tools will enable small and mid-sized companies to deploy AI, creating a long tail of $5 million custom projects. The speaker envisions thousands of new firms providing specialized AI solutions, requiring developers skilled in python and cloud platforms. He encourages viewers to skill up in python which, unlike lower-level languages, enables rapid AI application development and deployment. A free blueprint is offered to guide complete beginners through learning python and achieving cloud certification.
Takeaways
- 😀 AI is creating opportunities in sectors beyond tech/consumer software that haven't been impacted yet
- 👨💻 Being a proficient developer with Python and ML knowledge will be advantageous
- 🍕 AI projects in other sectors may be smaller ($5M) but more numerous
- 🛠️ Low/no code tools are making custom AI solutions for niche sectors feasible
- 🏭 Specialized AI consulting firms will emerge to serve various industries
- 💻 Python leads in ML because it has easy to use libraries and caters to non-traditional developers
- 🔌 Python tools often use performant C/C++ in the background
- ☁️ Deploying trained models at scale requires cloud infrastructure knowledge
- 💡 Non-web dev pathway starting with Python & cloud certs is viable
- 🎓 Free blueprint provided for learning Python, tools, and getting certified
Q & A
What is the main argument made about AI and job opportunities in the video?
-The main argument is that while AI might be perceived as a threat to jobs, it actually opens up many new opportunities in sectors that have not yet been significantly impacted by AI. Proficiency in development and understanding of AI and machine learning, especially in languages like Python, positions individuals to capitalize on these emerging opportunities.
Who is mentioned as a globally recognized leader in AI in the video, and what is their contribution?
-Andrew Ng is mentioned as a globally recognized leader in AI. He's highlighted for giving a talk on the potential for AI across various sectors that haven't been heavily impacted by AI technology yet.
What examples of future AI projects are mentioned in the video?
-Examples include a pizza maker using AI to ensure even cheese distribution on pizzas, an agriculture company using AI to determine the optimal height to chop wheat for increased food production and environmental benefits, and projects related to materials grading like cloth and sheet metal.
Why does the traditional model of hiring many engineers for a single large-scale software project not apply to these future AI projects?
-The traditional model doesn't apply because these future AI projects are more specific and smaller in scale, making the high cost of customization for such projects unfeasible. These projects do not cater to massive user bases like internet consumer software, requiring a different approach.
How do low code and no code tools relate to future AI projects according to the video?
-Low code and no code tools are exciting developments that enable users to customize AI systems more easily for specific use cases. These tools allow for more niche AI solutions to be developed and maintained by smaller teams or even the end-users themselves, making AI more accessible to various sectors.
What is the significance of Python in AI development as discussed in the video?
-Python is highlighted as the language of choice for AI development due to its extensive libraries and frameworks that simplify machine learning and data analysis tasks. Its ease of use and the ability to run on top of performance-enhancing languages like C++ make it particularly valuable for AI research and application development.
What unique AI application examples are provided to illustrate the diverse potential of AI?
-Unique applications include Amore AI, a relationship coaching app, and Bear.a, an app designed to make ships more fuel-efficient by optimizing their routes. These examples demonstrate AI's potential beyond traditional tech and consumer software sectors.
What does the video suggest about the future landscape of AI in industries outside of tech and consumer software?
-The video suggests a vast and largely untapped potential for AI applications across a wide range of industries outside of the traditional tech and consumer software sectors. It implies that these sectors will experience significant transformation and benefit from AI technology in the future.
How does the video propose individuals prepare for the opportunities AI is creating?
-The video proposes that individuals prepare by becoming proficient developers, gaining a basic understanding of language models or machine learning, and becoming very proficient in a programming language like Python. It also suggests focusing on emerging AI tools and obtaining cloud certifications.
What free resource is offered at the end of the video, and what does it promise?
-At the end of the video, a free blueprint is offered that promises to take beginners from scratch through learning Python, other industry-level tools, and obtaining a legitimate cloud certification. This blueprint aims to prepare individuals for the job market with the necessary skills for the future AI-driven industry.
Outlines
🤖 Examples of Future AI Programming Jobs
The paragraph discusses how AI will create new opportunities and jobs that we can't foresee yet. It suggests that technical skills like development will still be valuable to build on. The speaker Andrew Ng provides examples of potential smaller-scale AI projects in diverse sectors, explaining how the old model of hiring many developers for one huge project doesn't apply anymore. Instead, he sees many $5 million niche industry projects enabled by new low/no code tools for customization.
🍕 Opportunities for Developers in Industry-Specific AI
The paragraph builds on the previous one by providing a specific example of a pizza company wanting to use AI for food inspection. Rather than a one-size-fits-all solution, this $5M project needs customized tools that internal IT teams could leverage. Many opportunities exist for developers to build these tailored solutions, either at the company itself, as an external contractor, or creating more generic tools that serve an entire sector. Python is poised to be very useful for machine learning and deployment over other languages.
Mindmap
Keywords
💡AI as a general purpose technology
💡Customization
💡Low code/no code tools
💡Python
💡Sector-specific AI applications
💡Cloud certification
💡AI Engineers
💡Machine learning
💡Ecosystem
💡Opportunities in AI
Highlights
AI's potential to create job opportunities in sectors previously untouched by technology, emphasizing the importance of being proficient in programming languages like Python.
Introduction to AI as a general-purpose technology and its diverse use cases emerging across various industries.
Discussion on how AI can transform smaller, niche industries beyond the tech and consumer software sectors.
Highlighting the shift from large-scale, one-size-fits-all software solutions to customized AI applications for specific industry needs.
Examples of AI projects like pizza quality control and agricultural optimization, showcasing the practical applications of AI in everyday industries.
The challenge of adapting AI solutions to small-scale projects due to high customization costs and how this is changing.
The role of no-code and low-code tools in democratizing AI, allowing non-experts to create and deploy AI systems.
A new trend in AI: Building tools for end-users to customize AI systems for their specific needs, enhancing operational efficiency.
The importance of Python in AI development, being the preferred language due to its simplicity and powerful libraries.
The shift towards using AI for unique applications in industries like dating and shipping, illustrating AI's vast potential.
Encouragement for developers to learn AI and machine learning fundamentals, positioning them for future job opportunities.
The strategic advantage of mastering Python for AI applications, given its role as the leading programming language in AI research.
The potential for AI to lead to the creation of thousands of new companies and job opportunities across diverse sectors.
A call to action for individuals to prepare for future opportunities by gaining a solid foundation in Python and cloud technologies.
Offering a free blueprint to guide learners from beginners to job-ready professionals in Python, AI, and cloud certifications.
Transcripts
so imagine AI blows into all these other
sectors where it's still relatively
small and thousands and thousands of
companies pop up and you happen to be a
proficient developer I think that's a
good thing and then imagine if you have
basic grounding in language models or
machine learning that's even better and
then add the fact that you're very
proficient in a programming language
like python what's up everybody it's
Travis here from travis. media today I'm
going to give some examples of what
future AI programming jobs might look
like now we're all thinking that AI is
going to take all the jobs but I think
it's going to create many opportunities
that we don't know about yet and yes I
think there will be jobs for devs like
us still being a technical person will
be a baseline requisite and you'll have
that skill to build on and today I want
to play two clips from a talk that I
really enjoyed from an expert on the
matter about the potential for AI and
all the other sectors that haven't
really been touched yet then I want to
discuss the implications how you may
want to start preparing early for these
opportunities and then I want to finish
the video on python why it's at the
Forefront of all this and then provide
you with a free blueprint that will take
you from a to Z let's get started so a
huge opportunity right now in this
industry is AI as a general purpose
technology in the very diverse use cases
that are starting to exist right now the
speaker here is a globally recognized
leader in AI by the name of Andrew in
I'm not going to try to pronounce it but
the whole talk is fascinating he's a
fascinating guy so there's this graph
here and on the left we have the big
leaders we have the ads the web search
e-commerce product recommendations the
big money and Spotlight right now is in
this Tech World in consumer software
world but not really yet into the rest
of the economy as you go down this curve
there presents the rest of all the
sectors that AI really hasn't impacted
yet which is way bigger than just Tech
and consumer software so I'm going to
play this first clip which gives some
examples of future projects on the
smaller scale and it turns out that
about 10 15 years ago you know vars my
friends and I we figured out a recipe
for how to hire say 100 Engineers to
write one piece of software to Surf more
relevant ads and apply that one piece of
software to bilon users and generate
massive Financial value so that works um
so real quick just for context what he's
saying is that previously with ad
Solutions and such you have a billion
users with which you can write one piece
of software for you can hire 100
developers that will write the software
and you're rich but once you go out into
smaller Industries you don't get this
model anymore it gets more specific and
smaller and the high cost of
customization no longer makes sense
that's where we head down this curve
into the other sectors but once you go
outside consumer software internet
hardly anyone has a 100 million or a
billion users they can write and apply
one piece of software to so once you go
to other Industries as we go from the
head of this curve on the left over to
the long tail these are some of the
projects I see and I'm excited about I
was working with a pizza maker that was
taking pictures of the pizza they were
making because they needed to do things
like make sure that the cheese is spread
evenly so this this is about a $5
million project um but that recipe of
hiring hund Engineers or dozens of
Engineers to work on a $5 million
project that doesn't make sense um or
another example working with an
agriculture company that um with them we
figured out that if we use cameras to
find out how tall is the wheat and wheat
is often bent over because of wind or
rain or something and we can chop off
the Wheats at the right height then that
results in more food for the farmer to
sell and is also bets of fund the
environment but this is another you know
$5 million project that that old recipe
of hiring a large group of highy school
Engineers to work on this one project
that doesn't make sense um and similarly
materials grading cloth grading sheet
metal grading many project like this so
whereas to the left in the head of this
curve there's a small number of let's
say multi-billion dollar projects and we
know how to execute those you know
delivering value in other Industries I'm
seeing a very long ter of tens of
thousands of let's call them $5 million
projects that until now have been very
difficult to excuse on because of the
high cost of customization what he's
getting at is that now based on all the
work that people have done in AI this is
possible the aggregate work that's been
done allows these smaller more Niche
solutions to be done with the creation
of no code or low code tooling the trend
that I think is exciting is that the AI
Community has been building better tools
that lets us aate these use cases and
make it easy for the end user to do the
customization so specifically I'm seeing
a lot of um exciting low code and no
code tools that enable the user to
customize the AI system what this means
is instead of me needing to worry that
much about pictures of pza um we have
tools we we're starting to see tools
that can enable the IT department of the
pizza making factory to train AI system
on their own pictures of pizza to
realize this $5 million worth of value
and by the way the pictures of piser you
know they don't exist on the internet so
Google and Bing don't have access to
these pictures uh we need tools that can
be used by really the pza factory
themselves to build and deploy and
maintain their own custom AI system that
works on their own pictures of pizza so
here's where I'm going with this and
where he's going with it you have this
pizza company that wants to use AI for
pizza food inspection it's a $5 million
project you don't take the same model
that you took with all the previous
stuff where you get billions of users
create this one major solution and sell
it to all the users this is a much
smaller case in Ai and the tools we have
now now allow for us to start moving
into these sectors for example he had
talked earlier about sentiment analysis
and how they used to put all that
together now with open AI you can just
say act as a sentiment analysis and
it'll do so so we have this basic AI
tooling available for these projects now
so this company this Pizza Company would
benefit from a low code or a no code
solution that they can use to do their
work so imagine a team of devs in the
pizza it Department who would write the
code they take the data they take the
images of the pizza from the company and
train a model and then build out a no
Code system for the company to use or
maybe they would maintain it for the
company or say you're a contractor or
you own an AI consulting firm that would
build out these solutions for the
companies in any companies who'd come
your way it will consist of AI Engineers
as well as application developers who
add in all the other functionality
enabling endusers or business
departments to send in human readable
prompts perhaps you'll be a Dev at that
company perhaps that tool will be more
generic and be pushed out to the entire
food industry or pizza industry and then
competitors will come so there's a lot
of opportunities to be realized in this
general purpose technology the tech and
consumer industry is small compared to
all the other sectors out there that
haven't really found benefit in AI yet
he also gets into the importance of
building many new companies that focus
on all these particular sectors
individually imagine the opportunities
then another example he gave is his team
is building out a new app called like
Amore AI or amori or something like that
where they're working working with the
CEO of Tinder the dating app to get
relationship data and his app will
provide relationship coaching or
something like that but it Bridges AI in
relationships that's a sector that
hadn't been explored yet another one he
mentions is bearing. a which is making
ships fuel efficient so it's like Google
Maps for ships to save like 10% on all
fuel costs so imagine AI blows into all
these other sectors where it's still
relatively small and thousands and
thousands of companies pop up and you
happen to be a proficient developer I
think that's a good thing and then
imagine if you have basic grounding in
language models or machine learning
that's even better and then add the fact
that you're very proficient in a
programming language like python now I
want to discuss briefly python all these
AI researchers are using python even in
this video he gives this example in
Python within a Jupiter notebook because
currently python is the choice language
for machine learning and data analysis
in all things in this broad field why is
that why not C or C++ well because
python has libraries and Frameworks that
make machine learning and data analysis
in the surrounding ecosystem easier
packages like numpy or Matt plot lib or
pandas are very very popular also
because many of the people doing AI
research they're not traditional
developers they need a tool to help them
in their AI research and python is an
easy one to pick up and run with and to
add to this most of the Python tools
like tensorflow actually use a C++ in
the background making it very performant
other packages use C so you could learn
C++ and be one of the real game changers
in the background this is a great
Pursuit but it's a hard one because you
could more quickly become really really
good at Python and just run with that
python is what you can use on top of c
and C++ without having to know these
more challenging languages now I'm not
saying that knowing python makes you an
AI engineer of course not but all of
these apps are being built with it or
around it knowing it well will go a long
way in the coming years in addition
where are all these trained models being
deployed when they're ready to go well
in the cloud somewhere Azure has a great
solution for this and here's a tip you
don't have to go down the traditional
webd route you don't have to learn HTML
CSS and JavaScript I think there's a
legitimate pathway from scratch to start
out with python and while becoming
proficient with it in other industry
standards like git become Cloud
certified so much so that I've created a
free completely free blueprint that will
take anyone starting out from scratch
through learning Python and other
industry level tools and getting a
legitimate Cloud certification along the
way from start to finish all the way to
job already and it's completely free
I'll put a link to it below so what do
you think about all the opportunities
what do you think about python let me
know down below let's have a discussion
if you found this video helpful give it
a thumbs up consider subscribing to the
channel and I'll see you in the next
[Music]
video
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