AI Expert Explains Future Programming Jobs… and Python

Summary

The 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

00:00

🤖 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.

05:02

🍕 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.

Keywords

💡AI as a general purpose technology

AI as a general purpose technology refers to the wide-ranging applications of artificial intelligence across various sectors beyond traditional tech domains like advertising or web search. In the video, this concept illustrates the potential for AI to revolutionize industries by providing tailored solutions to unique problems, such as improving food inspection in pizza production or optimizing agricultural practices. The term underscores the versatility and transformative power of AI, which can extend to countless areas, including those not traditionally associated with high-tech.

💡Customization

Customization in the context of AI refers to the adaptation or tailoring of AI solutions to meet the specific needs of individual industries or companies. The video highlights the shift from one-size-fits-all software, used in large-scale applications like web search, to niche, customized projects that address unique challenges, such as ensuring even cheese distribution on pizzas. This shift indicates a move towards more specialized and bespoke AI applications, emphasizing the importance of AI systems that can be adapted to different scenarios and requirements.

💡Low code/no code tools

Low code/no code tools are platforms that allow users to create and manage applications without extensive programming knowledge. In the video, these tools are presented as a means to democratize AI, enabling non-experts, such as the IT department in a pizza factory, to develop and deploy AI solutions. This approach lowers the barrier to entry for AI application, making it accessible to a broader range of users and industries, thereby expanding the potential use cases for AI technology.

💡Python

Python is highlighted in the video as the leading programming language in AI, machine learning, and data analysis due to its simplicity, readability, and the extensive ecosystem of libraries and frameworks it supports, such as TensorFlow, NumPy, and Pandas. The script underlines the advantage of Python for both seasoned developers and researchers new to programming, positioning it as a critical skill for those looking to enter the AI field. Python's prominence in AI research and application development makes it an essential tool for future programming jobs in the AI sector.

💡Sector-specific AI applications

Sector-specific AI applications refer to AI solutions tailored for particular industries or sectors, such as agriculture, shipping, or food production. The video illustrates this concept with examples like optimizing wheat cutting for agriculture or improving fuel efficiency in shipping. These applications demonstrate the potential of AI to address specific, practical problems within different sectors, highlighting the growing trend towards specialized AI that can provide significant value beyond the tech and consumer software industries.

💡Cloud certification

Cloud certification refers to the validation of an individual's expertise in cloud computing services and technologies, such as those offered by Azure. In the video, cloud certification is recommended as part of a professional development path for individuals entering the AI and programming field. This certification is portrayed as a strategic asset for developers, equipping them with the knowledge to deploy and manage AI models and applications in the cloud, a common practice for modern AI solutions.

💡AI Engineers

AI Engineers are professionals specialized in designing, building, and implementing AI models and systems. The video discusses the role of AI Engineers in conjunction with application developers to create comprehensive solutions that incorporate AI into various business processes and industries. This multidisciplinary approach, combining AI and application development, is essential for realizing the full potential of AI in addressing specific industry challenges.

💡Machine learning

Machine learning is a subset of AI that involves training algorithms to learn from and make predictions or decisions based on data. In the video, machine learning is implicitly referenced through examples like sentiment analysis and image recognition for pizza quality control. The emphasis on machine learning illustrates its importance as a foundational technology that enables many of the AI applications discussed, from agricultural optimization to quality control in manufacturing.

💡Ecosystem

The term 'ecosystem' in the context of the video refers to the comprehensive environment that supports AI development, including programming languages (like Python), libraries, frameworks, cloud services, and tools. The ecosystem is critical for enabling the development and deployment of AI solutions. The video emphasizes the importance of this ecosystem in providing the necessary tools and infrastructure to support AI innovation and application across different sectors.

💡Opportunities in AI

Opportunities in AI, as discussed in the video, refer to the new job roles, business ventures, and sector transformations that AI technology is expected to generate. The video argues that, contrary to fears of job displacement, AI will create a wealth of opportunities, especially for developers proficient in relevant technologies like Python and machine learning. This concept is central to the video's message, encouraging viewers to prepare for and embrace the upcoming changes in the industry brought about by AI advancements.

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