2024-02-04T05:14:03.039Z
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2024-01-09.29447
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deprecated
If you're not already building an AI focused side hustle, you are behind the curve.
ChatGPT freaked programmers out in the same way that Ben's motor car freaked horses out a 150 years ago.
It could be all all hype, or it could be a paradigm shift into the artificial intelligence age.
Either way, if you listen carefully, you can hear a stampede of developers around getting in on the next technological gold rush, but like I've said before, during a gold rush, sell shovels if you wanna make money.
This video is my free shovel to you, where we'll take a realistic look at how to build AI driven apps from both technical and business perspectives.
There's a lot of VC money flowing into AI startups right now.
We'll examine them all to see how their tech is implemented and how they plan on making money, and you might be surprised at how easy it actually is to build an AI app when using the right tools.
The ultimate shovel salesman is Open an AI, the creators of ChatGPT, which is based on an autoregressive language model called GPT 3 or technically 3.5.
By By now we all know how impressive it is, but what's crazy is GPT 4 is around the corner.
GPT 3 is trained on an unprecedented 175,000,000,000 parameters, but that's absolutely dwarfed by GPT 4 with 100,000,000,000,000 parameters.
Maybe we've reached the peak of what is possible with deep learning, and GPT 4 is a nothing burger.
OpenAI's CEO says you'll be disappointed, but maybe that's what he wants you to think because he knows the technological singularity is near, in which all of humanity is enslaved or exterminated.
Shit.
Either way, the only thing that really matters in life is that we make some mother effing money.
One idea you might have is to build your own superior GPT model, but that's an idea I would describe as complete.
You're up against a company with the smartest people in the world that's received 1,000,000,000 of dollars in funding from companies like Microsoft.
If you can't beat them, join them.
Their technology is available via a paid all key high and just recently became available on Azure Cloud.
And there's all kinds of use cases if you use your imagination.
One example is VideoTapIt, it, which takes a video as an input and converts it into a blog post by transcribing it and using AI to generate headers automatically.
Awfully.
An app like this could be accomplished by an independent developer or a small team.
You could use OpenAI Whisper to do the transcription, GPT to generate the headers, and you could even throw in something like DALL E to generate unique images for the blog post.
Now I realized 5 seconds ago I said you can't compete with open AI, but don't listen to haters like me.
GPT is not the only game in town.
You have DeepMind from Google with other language models like chinchilla and AlphaCode that's been out there winning coding competitions, and there's also open source language models like Bloom.
If you have access to a lot of high quality data, it is possible you could train your own predictive model then offer it as a service.
Also.
The process of turning raw data into an actual deployed machine learning model is called MLOps.
Tools on Google Cloud like Vertex AI handle every step of the process.
They ingest and process data, they train and evaluate models, and then deploy them to serverless infrastructure where you can actually use them in an app.
In addition, there are tools like Hugging Face that provides MLOps as a service, but they provide thousands of open source pre trained models that you can use as a starting point.
Most importantly, only you'll wanna get really good at some kind of a specialized use case.
An example that comes to mind is play dot h t, which can create custom AI generated voices.
They have an entire fake podcast between Joe Rogan and Steve Jobs, and for all you know, my voice could be entirely AI generated right now.
You can clone your own voice.
It is all crazy good.
Uh, it's not.
My name is Jeff.
But I did look into it, and it cost tens of 1,000 of dollars to get your voice cloned, which is understandable because there's very few companies that can actually offer this service at a high level, at least in today's world.
Another crazy example is beat oven, which I'm using right now to generate this inappropriately tense background music.
It combines generative AI with real music to create unique music.
All.
Or how about Resume Worded, a tool that can analyze your resume and LinkedIn profile?
If you never learned to read good or write good, AI can now do all the heavy lifting.
And I to you.
There are developers right now building AI apps that will help kids cheat on their homework.
At the same time, other developers are building tools to prevent AI cheating by using AI.
There's a a ton of different angles to make money here.
No matter what you decide to build, it's a good idea to build in public, which can sometimes make your business go viral.
That's exactly what happened with restore photos dot I all.
It's a simple Next JS app that was launched a few weeks ago and already has over 40,000 users.
What I love about it is that it solves one simple problem.
You upload a grainy photo, then It uses AI to restore it to a high resolution photo.
The code is all open source, and as you can see here, it uses an API called replicate Kate to perform the image transformation with an open source machine learning model.
In this case, the model is gfpgan, but there are many other models to choose from.
The key here is to find a problem, then create a no nonsense, highly focused solution for it.
Then finally, do some kind of TikTok dance while using it to make it go viral.
All another potential way to make money is to slap the label of artificial intelligence on an existing business model that already works.
We've already seen many companies do that in recent years, awful like McDonald's going fully automated, which is great because it means no unwanted reproductive fluids in your Big Mac, or like Upstart, an AI lending platform that uses machine learning or for a fancy way of doing statistics to lend money on more factors than just the credit score.
Its IPO investors are currently holding the bag for a 90% loss, but its early investors got rich.
You You could build an app like this yourself without even using deep learning.
You just need, like, 10 lines of Python code to run a regression on the input data, then boom, you're now an AI lending platform, assuming you also own your own bank.
The takeaway here is that you can use the artificial intelligence label to make your business look disruptive, even if it's running a grip that's been around forever.
Now Now if you really wanna make a lot of money, don't look around at other cheap poor people like yourself.
Instead, sell to enterprise and government.
Finish this sentence.
Blank dot ai provides a tool that will save your company 70% per year in blank cost.
Congratulations.
You just wrote a pitch for the next AI unicorn current startup.
The blank might be something like shipping logistics, talent recruitment, or business presentations as is the case with present dotai.
This startup will take a company's branding and marketing assets and automatically create tons of slide templates for business presentations.
I have no idea what their tech looks like under the hood, but it looks like a use case for generative image models or tools that can take text as a prompt and return images as a result.
One of the most impressive tools in this space is Midjourney.
You can use the beta by going to their Discord and ask for something like a business presentation for my oil and gas company.
The result you get back looks like something produced by a talented human.
Generative AI is so hot right now, but there's just as much if not more opportunity in natural language processing.
Another huge cost for enterprise is customer support.
ChatGPT has made it clear that Customer support jobs will largely go to AI in the coming years.
However, the average company has no idea how to integrate this technology into their business.
Moveworks is just one of the companies that is bridging this gap.
They build AI chatbots that integrate with your entire tech stack that can solve problems faster and cheaper than a human could ever dream of.
There are tools like AWS Lex and Google Dialogflow that you can use to build chatbots right now.
They can handle business logic on the back end with webhooks and can be integrated with GPT 3 to provide unique human like interactions.
As you can see, there are going to be tons of opportunities in the next few years for ambitious and clever developers.
However, there is a dark side to all of this.
The technology is moving so fast that an idea that might look like a guaranteed success today turns out to be completely obsolete a year from all.
In addition, the sad reality is that big tech is going to absolutely dominate this space.
They have all the data and computing power required to really push this technology forward.
It's really hard for me to compete with my Intel Pentium Processor from my mom's basement.
Even if you do manage to build a game changer, Zuckerberg is just gonna steal it anyway.
It.
Another dark side to AI is that this technology will likely be harnessed by scammers.
It's actually pretty scary.
Someone could clone my voice based on all my YouTube videos, Then call my grandma and tell her I got arrested in Mexico and that she needs to transfer some Bitcoin over to get me out.
Not cool to scare my grandma like that, man.
Also, At one point or another, everybody has wired money over to their long lost Nigerian prince relative, only to be disappointed when that big inheritance never all through.
Scams like this are only going to get better.
We can scale them up by using tools like chat gpt to automatically format letters in proper English.
All ish.
Um, well, actually, upon testing, I guess scam emails are not allowed.
In addition, you could even target a specific person and combine their face with some real Nigerian prince, so the target actually sees a long lost relative with resemblance to their own face.
We're entering a brave new world where it's going going to be very difficult to distinguish fakery from reality.
Deepfakes have been around for a while, but they're only going to get better.
Big companies that have all your data know everything about you.
They know what you read, how you write, how you look, and how you act, and they've been using that data to serve you advertisements.
But nowadays with generative AI, all.
They quite literally have the ability to become you in the digital sense.
Sounds creepy, but the good news is that we can use this technology to live forever.
Even if I get smashed by an elephant or or fall into a volcano.
I will continue making these YouTube videos because the artificial me will be indistinguishable, nay, superior to the real me and won't make silly typos.
Those.
Not only will I continue working, but I will continue to raise my family in the metaverse.
And not just my kids, but their kids, and then their kids, because I will be the Apex alpha artificial grandpa, the the first of its kind.
They could even upload me to a lifelike robotic doll so my wife and kids never even know I died.
That's actually a great business idea.
Create a company that clones a person's persona, uploaded to a doll that is automatically deployed when that person's organic form terminates.
That may sound crazy, but it's within the realm of possibility in our lifetimes.
Thanks for watching, and I will see you forever and ever until the end of time.

Speaker 0: If you're not already building an AI focused side hustle, you are behind the curve. ChatGPT freaked programmers out in the same way that Ben's motor car freaked horses out a 150 years ago. It could be all all hype, or it could be a paradigm shift into the artificial intelligence age. Either way, if you listen carefully, you can hear a stampede of developers around getting in on the next technological gold rush, but like I've said before, during a gold rush, sell shovels if you wanna make money. This video is my free shovel to you, where we'll take a realistic look at how to build AI driven apps from both technical and business perspectives.

There's a lot of VC money flowing into AI startups right now. We'll examine them all to see how their tech is implemented and how they plan on making money, and you might be surprised at how easy it actually is to build an AI app when using the right tools. The ultimate shovel salesman is Open an AI, the creators of ChatGPT, which is based on an autoregressive language model called GPT 3 or technically 3.5. By By now we all know how impressive it is, but what's crazy is GPT 4 is around the corner. GPT 3 is trained on an unprecedented 175,000,000,000 parameters, but that's absolutely dwarfed by GPT 4 with 100,000,000,000,000 parameters.

Maybe we've reached the peak of what is possible with deep learning, and GPT 4 is a nothing burger. OpenAI's CEO says you'll be disappointed, but maybe that's what he wants you to think because he knows the technological singularity is near, in which all of humanity is enslaved or exterminated. Shit. Either way, the only thing that really matters in life is that we make some mother effing money. One idea you might have is to build your own superior GPT model, but that's an idea I would describe as complete.

You're up against a company with the smartest people in the world that's received 1,000,000,000 of dollars in funding from companies like Microsoft. If you can't beat them, join them. Their technology is available via a paid all key high and just recently became available on Azure Cloud. And there's all kinds of use cases if you use your imagination. One example is VideoTapIt, it, which takes a video as an input and converts it into a blog post by transcribing it and using AI to generate headers automatically.

Awfully. An app like this could be accomplished by an independent developer or a small team. You could use OpenAI Whisper to do the transcription, GPT to generate the headers, and you could even throw in something like DALL E to generate unique images for the blog post. Now I realized 5 seconds ago I said you can't compete with open AI, but don't listen to haters like me. GPT is not the only game in town.

You have DeepMind from Google with other language models like chinchilla and AlphaCode that's been out there winning coding competitions, and there's also open source language models like Bloom. If you have access to a lot of high quality data, it is possible you could train your own predictive model then offer it as a service. Also. The process of turning raw data into an actual deployed machine learning model is called MLOps. Tools on Google Cloud like Vertex AI handle every step of the process.

They ingest and process data, they train and evaluate models, and then deploy them to serverless infrastructure where you can actually use them in an app. In addition, there are tools like Hugging Face that provides MLOps as a service, but they provide thousands of open source pre trained models that you can use as a starting point. Most importantly, only you'll wanna get really good at some kind of a specialized use case. An example that comes to mind is play dot h t, which can create custom AI generated voices. They have an entire fake podcast between Joe Rogan and Steve Jobs, and for all you know, my voice could be entirely AI generated right now.

You can clone your own voice. It is all crazy good. Uh, it's not. My name is Jeff. But I did look into it, and it cost tens of 1,000 of dollars to get your voice cloned, which is understandable because there's very few companies that can actually offer this service at a high level, at least in today's world.

Another crazy example is beat oven, which I'm using right now to generate this inappropriately tense background music. It combines generative AI with real music to create unique music. All. Or how about Resume Worded, a tool that can analyze your resume and LinkedIn profile? If you never learned to read good or write good, AI can now do all the heavy lifting.

And I to you. There are developers right now building AI apps that will help kids cheat on their homework. At the same time, other developers are building tools to prevent AI cheating by using AI. There's a a ton of different angles to make money here. No matter what you decide to build, it's a good idea to build in public, which can sometimes make your business go viral.

That's exactly what happened with restore photos dot I all. It's a simple Next JS app that was launched a few weeks ago and already has over 40,000 users. What I love about it is that it solves one simple problem. You upload a grainy photo, then It uses AI to restore it to a high resolution photo. The code is all open source, and as you can see here, it uses an API called replicate Kate to perform the image transformation with an open source machine learning model.

In this case, the model is gfpgan, but there are many other models to choose from. The key here is to find a problem, then create a no nonsense, highly focused solution for it. Then finally, do some kind of TikTok dance while using it to make it go viral. All another potential way to make money is to slap the label of artificial intelligence on an existing business model that already works. We've already seen many companies do that in recent years, awful like McDonald's going fully automated, which is great because it means no unwanted reproductive fluids in your Big Mac, or like Upstart, an AI lending platform that uses machine learning or for a fancy way of doing statistics to lend money on more factors than just the credit score.

Its IPO investors are currently holding the bag for a 90% loss, but its early investors got rich. You You could build an app like this yourself without even using deep learning. You just need, like, 10 lines of Python code to run a regression on the input data, then boom, you're now an AI lending platform, assuming you also own your own bank. The takeaway here is that you can use the artificial intelligence label to make your business look disruptive, even if it's running a grip that's been around forever. Now Now if you really wanna make a lot of money, don't look around at other cheap poor people like yourself.

Instead, sell to enterprise and government. Finish this sentence. Blank dot ai provides a tool that will save your company 70% per year in blank cost. Congratulations. You just wrote a pitch for the next AI unicorn current startup.

The blank might be something like shipping logistics, talent recruitment, or business presentations as is the case with present dotai. This startup will take a company's branding and marketing assets and automatically create tons of slide templates for business presentations. I have no idea what their tech looks like under the hood, but it looks like a use case for generative image models or tools that can take text as a prompt and return images as a result. One of the most impressive tools in this space is Midjourney. You can use the beta by going to their Discord and ask for something like a business presentation for my oil and gas company.

The result you get back looks like something produced by a talented human. Generative AI is so hot right now, but there's just as much if not more opportunity in natural language processing. Another huge cost for enterprise is customer support. ChatGPT has made it clear that Customer support jobs will largely go to AI in the coming years. However, the average company has no idea how to integrate this technology into their business.

Moveworks is just one of the companies that is bridging this gap. They build AI chatbots that integrate with your entire tech stack that can solve problems faster and cheaper than a human could ever dream of. There are tools like AWS Lex and Google Dialogflow that you can use to build chatbots right now. They can handle business logic on the back end with webhooks and can be integrated with GPT 3 to provide unique human like interactions. As you can see, there are going to be tons of opportunities in the next few years for ambitious and clever developers.

However, there is a dark side to all of this. The technology is moving so fast that an idea that might look like a guaranteed success today turns out to be completely obsolete a year from all. In addition, the sad reality is that big tech is going to absolutely dominate this space. They have all the data and computing power required to really push this technology forward. It's really hard for me to compete with my Intel Pentium Processor from my mom's basement.

Even if you do manage to build a game changer, Zuckerberg is just gonna steal it anyway. It. Another dark side to AI is that this technology will likely be harnessed by scammers. It's actually pretty scary. Someone could clone my voice based on all my YouTube videos, Then call my grandma and tell her I got arrested in Mexico and that she needs to transfer some Bitcoin over to get me out.

Not cool to scare my grandma like that, man. Also, At one point or another, everybody has wired money over to their long lost Nigerian prince relative, only to be disappointed when that big inheritance never all through. Scams like this are only going to get better. We can scale them up by using tools like chat gpt to automatically format letters in proper English. All ish.

Um, well, actually, upon testing, I guess scam emails are not allowed. In addition, you could even target a specific person and combine their face with some real Nigerian prince, so the target actually sees a long lost relative with resemblance to their own face. We're entering a brave new world where it's going going to be very difficult to distinguish fakery from reality. Deepfakes have been around for a while, but they're only going to get better. Big companies that have all your data know everything about you.

They know what you read, how you write, how you look, and how you act, and they've been using that data to serve you advertisements. But nowadays with generative AI, all. They quite literally have the ability to become you in the digital sense. Sounds creepy, but the good news is that we can use this technology to live forever. Even if I get smashed by an elephant or or fall into a volcano.

I will continue making these YouTube videos because the artificial me will be indistinguishable, nay, superior to the real me and won't make silly typos. Those. Not only will I continue working, but I will continue to raise my family in the metaverse. And not just my kids, but their kids, and then their kids, because I will be the Apex alpha artificial grandpa, the the first of its kind. They could even upload me to a lifelike robotic doll so my wife and kids never even know I died.

That's actually a great business idea. Create a company that clones a person's persona, uploaded to a doll that is automatically deployed when that person's organic form terminates. That may sound crazy, but it's within the realm of possibility in our lifetimes. Thanks for watching, and I will see you forever and ever until the end of time.
If you're not already building an AI focused side hustle, you are behind the curve. ChatGPT freaked programmers out in the same way that Ben's motor car freaked horses out a 150 years ago. It could be all all hype, or it could be a paradigm shift into the artificial intelligence age. Either way, if you listen carefully, you can hear a stampede of developers around getting in on the next technological gold rush, but like I've said before, during a gold rush, sell shovels if you wanna make money. This video is my free shovel to you, where we'll take a realistic look at how to build AI driven apps from both technical and business perspectives. There's a lot of VC money flowing into AI startups right now. We'll examine them all to see how their tech is implemented and how they plan on making money, and you might be surprised at how easy it actually is to build an AI app when using the right tools. The ultimate shovel salesman is Open an AI, the creators of ChatGPT, which is based on an autoregressive language model called GPT 3 or technically 3.5. By By now we all know how impressive it is, but what's crazy is GPT 4 is around the corner. GPT 3 is trained on an unprecedented 175,000,000,000 parameters, but that's absolutely dwarfed by GPT 4 with 100,000,000,000,000 parameters.
artificial intelligence
ibm
software development
software
neural networks
Maybe we've reached the peak of what is possible with deep learning, and GPT 4 is a nothing burger. OpenAI's CEO says you'll be disappointed, but maybe that's what he wants you to think because he knows the technological singularity is near, in which all of humanity is enslaved or exterminated. Shit. Either way, the only thing that really matters in life is that we make some mother effing money. One idea you might have is to build your own superior GPT model, but that's an idea I would describe as complete. You're up against a company with the smartest people in the world that's received 1,000,000,000 of dollars in funding from companies like Microsoft. If you can't beat them, join them. Their technology is available via a paid all key high and just recently became available on Azure Cloud. And there's all kinds of use cases if you use your imagination. One example is VideoTapIt, it, which takes a video as an input and converts it into a blog post by transcribing it and using AI to generate headers automatically. Awfully. An app like this could be accomplished by an independent developer or a small team. You could use OpenAI Whisper to do the transcription, GPT to generate the headers, and you could even throw in something like DALL E to generate unique images for the blog post. Now I realized 5 seconds ago I said you can't compete with open AI, but don't listen to haters like me. GPT is not the only game in town. You have DeepMind from Google with other language models like chinchilla and AlphaCode that's been out there winning coding competitions, and there's also open source language models like Bloom. If you have access to a lot of high quality data, it is possible you could train your own predictive model then offer it as a service. Also. The process of turning raw data into an actual deployed machine learning model is called MLOps. Tools on Google Cloud like Vertex AI handle every step of the process. They ingest and process data, they train and evaluate models, and then deploy them to serverless infrastructure where you can actually use them in an app. In addition, there are tools like Hugging Face that provides MLOps as a service, but they provide thousands of open source pre trained models that you can use as a starting point. Most importantly, only you'll wanna get really good at some kind of a specialized use case. An example that comes to mind is play dot h t, which can create custom AI generated voices. They have an entire fake podcast between Joe Rogan and Steve Jobs, and for all you know, my voice could be entirely AI generated right now. You can clone your own voice. It is all crazy good. Uh, it's not. My name is Jeff. But I did look into it, and it cost tens of 1,000 of dollars to get your voice cloned, which is understandable because there's very few companies that can actually offer this service at a high level, at least in today's world. Another crazy example is beat oven, which I'm using right now to generate this inappropriately tense background music. It combines generative AI with real music to create unique music. All. Or how about Resume Worded, a tool that can analyze your resume and LinkedIn profile? If you never learned to read good or write good, AI can now do all the heavy lifting. And I to you. There are developers right now building AI apps that will help kids cheat on their homework. At the same time, other developers are building tools to prevent AI cheating by using AI. There's a a ton of different angles to make money here. No matter what you decide to build, it's a good idea to build in public, which can sometimes make your business go viral.
machine learning
podcasts
multimedia
microsoft
technology
music
deep learning
audio
ibm
artificial intelligence
video gaming
sounds
neural networks
software development
visualization
software
languages
acting
deepgram
streaming
finance
data management
That's exactly what happened with restore photos dot I all. It's a simple Next JS app that was launched a few weeks ago and already has over 40,000 users.
What I love about it is that it solves one simple problem. You upload a grainy photo, then It uses AI to restore it to a high resolution photo. The code is all open source, and as you can see here, it uses an API called replicate Kate to perform the image transformation with an open source machine learning model. In this case, the model is gfpgan, but there are many other models to choose from. The key here is to find a problem, then create a no nonsense, highly focused solution for it. Then finally, do some kind of TikTok dance while using it to make it go viral. All another potential way to make money is to slap the label of artificial intelligence on an existing business model that already works. We've already seen many companies do that in recent years, awful like McDonald's going fully automated, which is great because it means no unwanted reproductive fluids in your Big Mac, or like Upstart, an AI lending platform that uses machine learning or for a fancy way of doing statistics to lend money on more factors than just the credit score. Its IPO investors are currently holding the bag for a 90% loss, but its early investors got rich. You You could build an app like this yourself without even using deep learning. You just need, like, 10 lines of Python code to run a regression on the input data, then boom, you're now an AI lending platform, assuming you also own your own bank. The takeaway here is that you can use the artificial intelligence label to make your business look disruptive, even if it's running a grip that's been around forever. Now Now if you really wanna make a lot of money, don't look around at other cheap poor people like yourself. Instead, sell to enterprise and government. Finish this sentence. Blank dot ai provides a tool that will save your company 70% per year in blank cost. Congratulations. You just wrote a pitch for the next AI unicorn current startup. The blank might be something like shipping logistics, talent recruitment, or business presentations as is the case with present dotai. This startup will take a company's branding and marketing assets and automatically create tons of slide templates for business presentations. I have no idea what their tech looks like under the hood, but it looks like a use case for generative image models or tools that can take text as a prompt and return images as a result. One of the most impressive tools in this space is Midjourney. You can use the beta by going to their Discord and ask for something like a business presentation for my oil and gas company. The result you get back looks like something produced by a talented human. Generative AI is so hot right now, but there's just as much if not more opportunity in natural language processing. Another huge cost for enterprise is customer support. ChatGPT has made it clear that Customer support jobs will largely go to AI in the coming years. However, the average company has no idea how to integrate this technology into their business. Moveworks is just one of the companies that is bridging this gap. They build AI chatbots that integrate with your entire tech stack that can solve problems faster and cheaper than a human could ever dream of. There are tools like AWS Lex and Google Dialogflow that you can use to build chatbots right now. They can handle business logic on the back end with webhooks and can be integrated with GPT 3 to provide unique human like interactions. As you can see, there are going to be tons of opportunities in the next few years for ambitious and clever developers. However, there is a dark side to all of this. The technology is moving so fast that an idea that might look like a guaranteed success today turns out to be completely obsolete a year from all. In addition, the sad reality is that big tech is going to absolutely dominate this space. They have all the data and computing power required to really push this technology forward.
artificial intelligence
software
customer support
robotics
technology
software development
computer science
machine learning
finance
stock market
modeling
investing
ibm
banking
neural networks
computers
tiktok
deep learning
visualization
business
marketing
intellectual property
industry
databases
multimedia
infrastructure
photography
economics
It's really hard for me to compete with my Intel Pentium Processor from my mom's basement. Even if you do manage to build a game changer, Zuckerberg is just gonna steal it anyway. It. Another dark side to AI is that this technology will likely be harnessed by scammers. It's actually pretty scary.
computer science
Someone could clone my voice based on all my YouTube videos, Then call my grandma and tell her I got arrested in Mexico and that she needs to transfer some Bitcoin over to get me out. Not cool to scare my grandma like that, man. Also, At one point or another, everybody has wired money over to their long lost Nigerian prince relative, only to be disappointed when that big inheritance never all through. Scams like this are only going to get better. We can scale them up by using tools like chat gpt to automatically format letters in proper English. All ish. Um, well, actually, upon testing, I guess scam emails are not allowed. In addition, you could even target a specific person and combine their face with some real Nigerian prince, so the target actually sees a long lost relative with resemblance to their own face.
We're entering a brave new world where it's going going to be very difficult to distinguish fakery from reality. Deepfakes have been around for a while, but they're only going to get better. Big companies that have all your data know everything about you. They know what you read, how you write, how you look, and how you act, and they've been using that data to serve you advertisements. But nowadays with generative AI, all. They quite literally have the ability to become you in the digital sense. Sounds creepy, but the good news is that we can use this technology to live forever. Even if I get smashed by an elephant or or fall into a volcano. I will continue making these YouTube videos because the artificial me will be indistinguishable, nay, superior to the real me and won't make silly typos. Those. Not only will I continue working, but I will continue to raise my family in the metaverse. And not just my kids, but their kids, and then their kids, because I will be the Apex alpha artificial grandpa, the the first of its kind. They could even upload me to a lifelike robotic doll so my wife and kids never even know I died. That's actually a great business idea. Create a company that clones a person's persona, uploaded to a doll that is automatically deployed when that person's organic form terminates. That may sound crazy, but it's within the realm of possibility in our lifetimes. Thanks for watching, and I will see you forever and ever until the end of time.
youtube
ibm
artificial intelligence
google
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If you're not already building an AI focused side hustle, you are behind the curve. ChatGPT freaked programmers out in the same way that Ben's motor car freaked horses out a 150 years ago. It could be all all hype, or it could be a paradigm shift into the artificial intelligence age. Either way, if you listen carefully, you can hear a stampede of developers around getting in on the next technological gold rush, but like I've said before, during a gold rush, sell shovels if you wanna make money. This video is my free shovel to you, where we'll take a realistic look at how to build AI driven apps from both technical and business perspectives. There's a lot of VC money flowing into AI startups right now. We'll examine them all to see how their tech is implemented and how they plan on making money, and you might be surprised at how easy it actually is to build an AI app when using the right tools. The ultimate shovel salesman is Open an AI, the creators of ChatGPT, which is based on an autoregressive language model called GPT 3 or technically 3.5. By By now we all know how impressive it is, but what's crazy is GPT 4 is around the corner. GPT 3 is trained on an unprecedented 175,000,000,000 parameters, but that's absolutely dwarfed by GPT 4 with 100,000,000,000,000 parameters. Maybe we've reached the peak of what is possible with deep learning, and GPT 4 is a nothing burger. OpenAI's CEO says you'll be disappointed, but maybe that's what he wants you to think because he knows the technological singularity is near, in which all of humanity is enslaved or exterminated. Shit. Either way, the only thing that really matters in life is that we make some mother effing money. One idea you might have is to build your own superior GPT model, but that's an idea I would describe as complete. You're up against a company with the smartest people in the world that's received 1,000,000,000 of dollars in funding from companies like Microsoft. If you can't beat them, join them. Their technology is available via a paid all key high and just recently became available on Azure Cloud. And there's all kinds of use cases if you use your imagination. One example is VideoTapIt, it, which takes a video as an input and converts it into a blog post by transcribing it and using AI to generate headers automatically. Awfully. An app like this could be accomplished by an independent developer or a small team. You could use OpenAI Whisper to do the transcription, GPT to generate the headers, and you could even throw in something like DALL E to generate unique images for the blog post. Now I realized 5 seconds ago I said you can't compete with open AI, but don't listen to haters like me. GPT is not the only game in town. You have DeepMind from Google with other language models like chinchilla and AlphaCode that's been out there winning coding competitions, and there's also open source language models like Bloom. If you have access to a lot of high quality data, it is possible you could train your own predictive model then offer it as a service. Also. The process of turning raw data into an actual deployed machine learning model is called MLOps. Tools on Google Cloud like Vertex AI handle every step of the process. They ingest and process data, they train and evaluate models, and then deploy them to serverless infrastructure where you can actually use them in an app. In addition, there are tools like Hugging Face that provides MLOps as a service, but they provide thousands of open source pre trained models that you can use as a starting point. Most importantly, only you'll wanna get really good at some kind of a specialized use case. An example that comes to mind is play dot h t, which can create custom AI generated voices. They have an entire fake podcast between Joe Rogan and Steve Jobs, and for all you know, my voice could be entirely AI generated right now. You can clone your own voice. It is all crazy good. Uh, it's not. My name is Jeff. But I did look into it, and it cost tens of 1,000 of dollars to get your voice cloned, which is understandable because there's very few companies that can actually offer this service at a high level, at least in today's world. Another crazy example is beat oven, which I'm using right now to generate this inappropriately tense background music. It combines generative AI with real music to create unique music. All. Or how about Resume Worded, a tool that can analyze your resume and LinkedIn profile? If you never learned to read good or write good, AI can now do all the heavy lifting. And I to you. There are developers right now building AI apps that will help kids cheat on their homework. At the same time, other developers are building tools to prevent AI cheating by using AI. There's a a ton of different angles to make money here. No matter what you decide to build, it's a good idea to build in public, which can sometimes make your business go viral. That's exactly what happened with restore photos dot I all. It's a simple Next JS app that was launched a few weeks ago and already has over 40,000 users. What I love about it is that it solves one simple problem. You upload a grainy photo, then It uses AI to restore it to a high resolution photo. The code is all open source, and as you can see here, it uses an API called replicate Kate to perform the image transformation with an open source machine learning model. In this case, the model is gfpgan, but there are many other models to choose from. The key here is to find a problem, then create a no nonsense, highly focused solution for it. Then finally, do some kind of TikTok dance while using it to make it go viral. All another potential way to make money is to slap the label of artificial intelligence on an existing business model that already works. We've already seen many companies do that in recent years, awful like McDonald's going fully automated, which is great because it means no unwanted reproductive fluids in your Big Mac, or like Upstart, an AI lending platform that uses machine learning or for a fancy way of doing statistics to lend money on more factors than just the credit score. Its IPO investors are currently holding the bag for a 90% loss, but its early investors got rich. You You could build an app like this yourself without even using deep learning. You just need, like, 10 lines of Python code to run a regression on the input data, then boom, you're now an AI lending platform, assuming you also own your own bank. The takeaway here is that you can use the artificial intelligence label to make your business look disruptive, even if it's running a grip that's been around forever. Now Now if you really wanna make a lot of money, don't look around at other cheap poor people like yourself. Instead, sell to enterprise and government. Finish this sentence. Blank dot ai provides a tool that will save your company 70% per year in blank cost. Congratulations. You just wrote a pitch for the next AI unicorn current startup. The blank might be something like shipping logistics, talent recruitment, or business presentations as is the case with present dotai. This startup will take a company's branding and marketing assets and automatically create tons of slide templates for business presentations. I have no idea what their tech looks like under the hood, but it looks like a use case for generative image models or tools that can take text as a prompt and return images as a result. One of the most impressive tools in this space is Midjourney. You can use the beta by going to their Discord and ask for something like a business presentation for my oil and gas company. The result you get back looks like something produced by a talented human. Generative AI is so hot right now, but there's just as much if not more opportunity in natural language processing. Another huge cost for enterprise is customer support. ChatGPT has made it clear that Customer support jobs will largely go to AI in the coming years. However, the average company has no idea how to integrate this technology into their business. Moveworks is just one of the companies that is bridging this gap. They build AI chatbots that integrate with your entire tech stack that can solve problems faster and cheaper than a human could ever dream of. There are tools like AWS Lex and Google Dialogflow that you can use to build chatbots right now. They can handle business logic on the back end with webhooks and can be integrated with GPT 3 to provide unique human like interactions. As you can see, there are going to be tons of opportunities in the next few years for ambitious and clever developers. However, there is a dark side to all of this. The technology is moving so fast that an idea that might look like a guaranteed success today turns out to be completely obsolete a year from all. In addition, the sad reality is that big tech is going to absolutely dominate this space. They have all the data and computing power required to really push this technology forward. It's really hard for me to compete with my Intel Pentium Processor from my mom's basement. Even if you do manage to build a game changer, Zuckerberg is just gonna steal it anyway. It. Another dark side to AI is that this technology will likely be harnessed by scammers. It's actually pretty scary. Someone could clone my voice based on all my YouTube videos, Then call my grandma and tell her I got arrested in Mexico and that she needs to transfer some Bitcoin over to get me out. Not cool to scare my grandma like that, man. Also, At one point or another, everybody has wired money over to their long lost Nigerian prince relative, only to be disappointed when that big inheritance never all through. Scams like this are only going to get better. We can scale them up by using tools like chat gpt to automatically format letters in proper English. All ish. Um, well, actually, upon testing, I guess scam emails are not allowed. In addition, you could even target a specific person and combine their face with some real Nigerian prince, so the target actually sees a long lost relative with resemblance to their own face. We're entering a brave new world where it's going going to be very difficult to distinguish fakery from reality. Deepfakes have been around for a while, but they're only going to get better. Big companies that have all your data know everything about you. They know what you read, how you write, how you look, and how you act, and they've been using that data to serve you advertisements. But nowadays with generative AI, all. They quite literally have the ability to become you in the digital sense. Sounds creepy, but the good news is that we can use this technology to live forever. Even if I get smashed by an elephant or or fall into a volcano. I will continue making these YouTube videos because the artificial me will be indistinguishable, nay, superior to the real me and won't make silly typos. Those. Not only will I continue working, but I will continue to raise my family in the metaverse. And not just my kids, but their kids, and then their kids, because I will be the Apex alpha artificial grandpa, the the first of its kind. They could even upload me to a lifelike robotic doll so my wife and kids never even know I died. That's actually a great business idea. Create a company that clones a person's persona, uploaded to a doll that is automatically deployed when that person's organic form terminates. That may sound crazy, but it's within the realm of possibility in our lifetimes. Thanks for watching, and I will see you forever and ever until the end of time.
If
if
you're
you're
not
not
already
already
building
building
an
an
AI
ai
focused
focused
side
side
hustle,
hustle
you
you
are
are
behind
behind
the
the
curve.
curve
ChatGPT
chatgpt
freaked
freaked
programmers
programmers
out
out
in
in
the
the
same
same
way
way
that
that
Ben's
ben's
motor
motor
car
car
freaked
freaked
horses
horses
out
out
a
a
150
150
years
years
ago.
ago
It
it
could
could
be
be
all
all
all
all
hype,
hype
or
or
it
it
could
could
be
be
a
a
paradigm
paradigm
shift
shift
into
into
the
the
artificial
artificial
intelligence
intelligence
age.
age
Either
either
way,
way
if
if
you
you
listen
listen
carefully,
carefully
you
you
can
can
hear
hear
a
a
stampede
stampede
of
of
developers
developers
around
around
getting
getting
in
in
on
on
the
the
next
next
technological
technological
gold
gold
rush,
rush
but
but
like
like
I've
i've
said
said
before,
before
during
during
a
a
gold
gold
rush,
rush
sell
sell
shovels
shovels
if
if
you
you
wanna
wanna
make
make
money.
money
This
this
video
video
is
is
my
my
free
free
shovel
shovel
to
to
you,
you
where
where
we'll
we'll
take
take
a
a
realistic
realistic
look
look
at
at
how
how
to
to
build
build
AI
ai
driven
driven
apps
apps
from
from
both
both
technical
technical
and
and
business
business
perspectives.
perspectives
There's
there's
a
a
lot
lot
of
of
VC
vc
money
money
flowing
flowing
into
into
AI
ai
startups
startups
right
right
now.
now
We'll
we'll
examine
examine
them
them
all
all
to
to
see
see
how
how
their
their
tech
tech
is
is
implemented
implemented
and
and
how
how
they
they
plan
plan
on
on
making
making
money,
money
and
and
you
you
might
might
be
be
surprised
surprised
at
at
how
how
easy
easy
it
it
actually
actually
is
is
to
to
build
build
an
an
AI
ai
app
app
when
when
using
using
the
the
right
right
tools.
tools
The
the
ultimate
ultimate
shovel
shovel
salesman
salesman
is
is
Open
open
an
an
AI,
ai
the
the
creators
creators
of
of
ChatGPT,
chatgpt
which
which
is
is
based
based
on
on
an
an
autoregressive
autoregressive
language
language
model
model
called
called
GPT
gpt
3
3
or
or
technically
technically
3.5.
3.5
By
by
By
by
now
now
we
we
all
all
know
know
how
how
impressive
impressive
it
it
is,
is
but
but
what's
what's
crazy
crazy
is
is
GPT
gpt
4
4
is
is
around
around
the
the
corner.
corner
GPT
gpt
3
3
is
is
trained
trained
on
on
an
an
unprecedented
unprecedented
175,000,000,000
175,000,000,000
parameters,
parameters
but
but
that's
that's
absolutely
absolutely
dwarfed
dwarfed
by
by
GPT
gpt
4
4
with
with
100,000,000,000,000
100,000,000,000,000
parameters.
parameters
Maybe
maybe
we've
we've
reached
reached
the
the
peak
peak
of
of
what
what
is
is
possible
possible
with
with
deep
deep
learning,
learning
and
and
GPT
gpt
4
4
is
is
a
a
nothing
nothing
burger.
burger
OpenAI's
openai's
CEO
ceo
says
says
you'll
you'll
be
be
disappointed,
disappointed
but
but
maybe
maybe
that's
that's
what
what
he
he
wants
wants
you
you
to
to
think
think
because
because
he
he
knows
knows
the
the
technological
technological
singularity
singularity
is
is
near,
near
in
in
which
which
all
all
of
of
humanity
humanity
is
is
enslaved
enslaved
or
or
exterminated.
exterminated
Shit.
shit
Either
either
way,
way
the
the
only
only
thing
thing
that
that
really
really
matters
matters
in
in
life
life
is
is
that
that
we
we
make
make
some
some
mother
mother
effing
effing
money.
money
One
one
idea
idea
you
you
might
might
have
have
is
is
to
to
build
build
your
your
own
own
superior
superior
GPT
gpt
model,
model
but
but
that's
that's
an
an
idea
idea
I
i
would
would
describe
describe
as
as
complete.
complete
You're
you're
up
up
against
against
a
a
company
company
with
with
the
the
smartest
smartest
people
people
in
in
the
the
world
world
that's
that's
received
received
1,000,000,000
1,000,000,000
of
of
dollars
dollars
in
in
funding
funding
from
from
companies
companies
like
like
Microsoft.
microsoft
If
if
you
you
can't
can't
beat
beat
them,
them
join
join
them.
them
Their
their
technology
technology
is
is
available
available
via
via
a
a
paid
paid
all
all
key
key
high
high
and
and
just
just
recently
recently
became
became
available
available
on
on
Azure
azure
Cloud.
cloud
And
and
there's
there's
all
all
kinds
kinds
of
of
use
use
cases
cases
if
if
you
you
use
use
your
your
imagination.
imagination
One
one
example
example
is
is
VideoTapIt,
videotapit
it,
it
which
which
takes
takes
a
a
video
video
as
as
an
an
input
input
and
and
converts
converts
it
it
into
into
a
a
blog
blog
post
post
by
by
transcribing
transcribing
it
it
and
and
using
using
AI
ai
to
to
generate
generate
headers
headers
automatically.
automatically
Awfully.
awfully
An
an
app
app
like
like
this
this
could
could
be
be
accomplished
accomplished
by
by
an
an
independent
independent
developer
developer
or
or
a
a
small
small
team.
team
You
you
could
could
use
use
OpenAI
openai
Whisper
whisper
to
to
do
do
the
the
transcription,
transcription
GPT
gpt
to
to
generate
generate
the
the
headers,
headers
and
and
you
you
could
could
even
even
throw
throw
in
in
something
something
like
like
DALL
dall
E
e
to
to
generate
generate
unique
unique
images
images
for
for
the
the
blog
blog
post.
post
Now
now
I
i
realized
realized
5
5
seconds
seconds
ago
ago
I
i
said
said
you
you
can't
can't
compete
compete
with
with
open
open
AI,
ai
but
but
don't
don't
listen
listen
to
to
haters
haters
like
like
me.
me
GPT
gpt
is
is
not
not
the
the
only
only
game
game
in
in
town.
town
You
you
have
have
DeepMind
deepmind
from
from
Google
google
with
with
other
other
language
language
models
models
like
like
chinchilla
chinchilla
and
and
AlphaCode
alphacode
that's
that's
been
been
out
out
there
there
winning
winning
coding
coding
competitions,
competitions
and
and
there's
there's
also
also
open
open
source
source
language
language
models
models
like
like
Bloom.
bloom
If
if
you
you
have
have
access
access
to
to
a
a
lot
lot
of
of
high
high
quality
quality
data,
data
it
it
is
is
possible
possible
you
you
could
could
train
train
your
your
own
own
predictive
predictive
model
model
then
then
offer
offer
it
it
as
as
a
a
service.
service
Also.
also
The
the
process
process
of
of
turning
turning
raw
raw
data
data
into
into
an
an
actual
actual
deployed
deployed
machine
machine
learning
learning
model
model
is
is
called
called
MLOps.
mlops
Tools
tools
on
on
Google
google
Cloud
cloud
like
like
Vertex
vertex
AI
ai
handle
handle
every
every
step
step
of
of
the
the
process.
process
They
they
ingest
ingest
and
and
process
process
data,
data
they
they
train
train
and
and
evaluate
evaluate
models,
models
and
and
then
then
deploy
deploy
them
them
to
to
serverless
serverless
infrastructure
infrastructure
where
where
you
you
can
can
actually
actually
use
use
them
them
in
in
an
an
app.
app
In
in
addition,
addition
there
there
are
are
tools
tools
like
like
Hugging
hugging
Face
face
that
that
provides
provides
MLOps
mlops
as
as
a
a
service,
service
but
but
they
they
provide
provide
thousands
thousands
of
of
open
open
source
source
pre
pre
trained
trained
models
models
that
that
you
you
can
can
use
use
as
as
a
a
starting
starting
point.
point
Most
most
importantly,
importantly
only
only
you'll
you'll
wanna
wanna
get
get
really
really
good
good
at
at
some
some
kind
kind
of
of
a
a
specialized
specialized
use
use
case.
case
An
an
example
example
that
that
comes
comes
to
to
mind
mind
is
is
play
play
dot
dot
h
h
t,
t
which
which
can
can
create
create
custom
custom
AI
ai
generated
generated
voices.
voices
They
they
have
have
an
an
entire
entire
fake
fake
podcast
podcast
between
between
Joe
joe
Rogan
rogan
and
and
Steve
steve
Jobs,
jobs
and
and
for
for
all
all
you
you
know,
know
my
my
voice
voice
could
could
be
be
entirely
entirely
AI
ai
generated
generated
right
right
now.
now
You
you
can
can
clone
clone
your
your
own
own
voice.
voice
It
it
is
is
all
all
crazy
crazy
good.
good
Uh,
uh
it's
it's
not.
not
My
my
name
name
is
is
Jeff.
jeff
But
but
I
i
did
did
look
look
into
into
it,
it
and
and
it
it
cost
cost
tens
tens
of
of
1,000
1,000
of
of
dollars
dollars
to
to
get
get
your
your
voice
voice
cloned,
cloned
which
which
is
is
understandable
understandable
because
because
there's
there's
very
very
few
few
companies
companies
that
that
can
can
actually
actually
offer
offer
this
this
service
service
at
at
a
a
high
high
level,
level
at
at
least
least
in
in
today's
today's
world.
world
Another
another
crazy
crazy
example
example
is
is
beat
beat
oven,
oven
which
which
I'm
i'm
using
using
right
right
now
now
to
to
generate
generate
this
this
inappropriately
inappropriately
tense
tense
background
background
music.
music
It
it
combines
combines
generative
generative
AI
ai
with
with
real
real
music
music
to
to
create
create
unique
unique
music.
music
All.
all
Or
or
how
how
about
about
Resume
resume
Worded,
worded
a
a
tool
tool
that
that
can
can
analyze
analyze
your
your
resume
resume
and
and
LinkedIn
linkedin
profile?
profile
If
if
you
you
never
never
learned
learned
to
to
read
read
good
good
or
or
write
write
good,
good
AI
ai
can
can
now
now
do
do
all
all
the
the
heavy
heavy
lifting.
lifting
And
and
I
i
to
to
you.
you
There
there
are
are
developers
developers
right
right
now
now
building
building
AI
ai
apps
apps
that
that
will
will
help
help
kids
kids
cheat
cheat
on
on
their
their
homework.
homework
At
at
the
the
same
same
time,
time
other
other
developers
developers
are
are
building
building
tools
tools
to
to
prevent
prevent
AI
ai
cheating
cheating
by
by
using
using
AI.
ai
There's
there's
a
a
a
a
ton
ton
of
of
different
different
angles
angles
to
to
make
make
money
money
here.
here
No
no
matter
matter
what
what
you
you
decide
decide
to
to
build,
build
it's
it's
a
a
good
good
idea
idea
to
to
build
build
in
in
public,
public
which
which
can
can
sometimes
sometimes
make
make
your
your
business
business
go
go
viral.
viral
That's
that's
exactly
exactly
what
what
happened
happened
with
with
restore
restore
photos
photos
dot
dot
I
i
all.
all
It's
it's
a
a
simple
simple
Next
next
JS
js
app
app
that
that
was
was
launched
launched
a
a
few
few
weeks
weeks
ago
ago
and
and
already
already
has
has
over
over
40,000
40,000
users.
users
What
what
I
i
love
love
about
about
it
it
is
is
that
that
it
it
solves
solves
one
one
simple
simple
problem.
problem
You
you
upload
upload
a
a
grainy
grainy
photo,
photo
then
then
It
it
uses
uses
AI
ai
to
to
restore
restore
it
it
to
to
a
a
high
high
resolution
resolution
photo.
photo
The
the
code
code
is
is
all
all
open
open
source,
source
and
and
as
as
you
you
can
can
see
see
here,
here
it
it
uses
uses
an
an
API
api
called
called
replicate
replicate
Kate
kate
to
to
perform
perform
the
the
image
image
transformation
transformation
with
with
an
an
open
open
source
source
machine
machine
learning
learning
model.
model
In
in
this
this
case,
case
the
the
model
model
is
is
gfpgan,
gfpgan
but
but
there
there
are
are
many
many
other
other
models
models
to
to
choose
choose
from.
from
The
the
key
key
here
here
is
is
to
to
find
find
a
a
problem,
problem
then
then
create
create
a
a
no
no
nonsense,
nonsense
highly
highly
focused
focused
solution
solution
for
for
it.
it
Then
then
finally,
finally
do
do
some
some
kind
kind
of
of
TikTok
tiktok
dance
dance
while
while
using
using
it
it
to
to
make
make
it
it
go
go
viral.
viral
All
all
another
another
potential
potential
way
way
to
to
make
make
money
money
is
is
to
to
slap
slap
the
the
label
label
of
of
artificial
artificial
intelligence
intelligence
on
on
an
an
existing
existing
business
business
model
model
that
that
already
already
works.
works
We've
we've
already
already
seen
seen
many
many
companies
companies
do
do
that
that
in
in
recent
recent
years,
years
awful
awful
like
like
McDonald's
mcdonald's
going
going
fully
fully
automated,
automated
which
which
is
is
great
great
because
because
it
it
means
means
no
no
unwanted
unwanted
reproductive
reproductive
fluids
fluids
in
in
your
your
Big
big
Mac,
mac
or
or
like
like
Upstart,
upstart
an
an
AI
ai
lending
lending
platform
platform
that
that
uses
uses
machine
machine
learning
learning
or
or
for
for
a
a
fancy
fancy
way
way
of
of
doing
doing
statistics
statistics
to
to
lend
lend
money
money
on
on
more
more
factors
factors
than
than
just
just
the
the
credit
credit
score.
score
Its
its
IPO
ipo
investors
investors
are
are
currently
currently
holding
holding
the
the
bag
bag
for
for
a
a
90%
90%
loss,
loss
but
but
its
its
early
early
investors
investors
got
got
rich.
rich
You
you
You
you
could
could
build
build
an
an
app
app
like
like
this
this
yourself
yourself
without
without
even
even
using
using
deep
deep
learning.
learning
You
you
just
just
need,
need
like,
like
10
10
lines
lines
of
of
Python
python
code
code
to
to
run
run
a
a
regression
regression
on
on
the
the
input
input
data,
data
then
then
boom,
boom
you're
you're
now
now
an
an
AI
ai
lending
lending
platform,
platform
assuming
assuming
you
you
also
also
own
own
your
your
own
own
bank.
bank
The
the
takeaway
takeaway
here
here
is
is
that
that
you
you
can
can
use
use
the
the
artificial
artificial
intelligence
intelligence
label
label
to
to
make
make
your
your
business
business
look
look
disruptive,
disruptive
even
even
if
if
it's
it's
running
running
a
a
grip
grip
that's
that's
been
been
around
around
forever.
forever
Now
now
Now
now
if
if
you
you
really
really
wanna
wanna
make
make
a
a
lot
lot
of
of
money,
money
don't
don't
look
look
around
around
at
at
other
other
cheap
cheap
poor
poor
people
people
like
like
yourself.
yourself
Instead,
instead
sell
sell
to
to
enterprise
enterprise
and
and
government.
government
Finish
finish
this
this
sentence.
sentence
Blank
blank
dot
dot
ai
ai
provides
provides
a
a
tool
tool
that
that
will
will
save
save
your
your
company
company
70%
70%
per
per
year
year
in
in
blank
blank
cost.
cost
Congratulations.
congratulations
You
you
just
just
wrote
wrote
a
a
pitch
pitch
for
for
the
the
next
next
AI
ai
unicorn
unicorn
current
current
startup.
startup
The
the
blank
blank
might
might
be
be
something
something
like
like
shipping
shipping
logistics,
logistics
talent
talent
recruitment,
recruitment
or
or
business
business
presentations
presentations
as
as
is
is
the
the
case
case
with
with
present
present
dotai.
dotai
This
this
startup
startup
will
will
take
take
a
a
company's
company's
branding
branding
and
and
marketing
marketing
assets
assets
and
and
automatically
automatically
create
create
tons
tons
of
of
slide
slide
templates
templates
for
for
business
business
presentations.
presentations
I
i
have
have
no
no
idea
idea
what
what
their
their
tech
tech
looks
looks
like
like
under
under
the
the
hood,
hood
but
but
it
it
looks
looks
like
like
a
a
use
use
case
case
for
for
generative
generative
image
image
models
models
or
or
tools
tools
that
that
can
can
take
take
text
text
as
as
a
a
prompt
prompt
and
and
return
return
images
images
as
as
a
a
result.
result
One
one
of
of
the
the
most
most
impressive
impressive
tools
tools
in
in
this
this
space
space
is
is
Midjourney.
midjourney
You
you
can
can
use
use
the
the
beta
beta
by
by
going
going
to
to
their
their
Discord
discord
and
and
ask
ask
for
for
something
something
like
like
a
a
business
business
presentation
presentation
for
for
my
my
oil
oil
and
and
gas
gas
company.
company
The
the
result
result
you
you
get
get
back
back
looks
looks
like
like
something
something
produced
produced
by
by
a
a
talented
talented
human.
human
Generative
generative
AI
ai
is
is
so
so
hot
hot
right
right
now,
now
but
but
there's
there's
just
just
as
as
much
much
if
if
not
not
more
more
opportunity
opportunity
in
in
natural
natural
language
language
processing.
processing
Another
another
huge
huge
cost
cost
for
for
enterprise
enterprise
is
is
customer
customer
support.
support
ChatGPT
chatgpt
has
has
made
made
it
it
clear
clear
that
that
Customer
customer
support
support
jobs
jobs
will
will
largely
largely
go
go
to
to
AI
ai
in
in
the
the
coming
coming
years.
years
However,
however
the
the
average
average
company
company
has
has
no
no
idea
idea
how
how
to
to
integrate
integrate
this
this
technology
technology
into
into
their
their
business.
business
Moveworks
moveworks
is
is
just
just
one
one
of
of
the
the
companies
companies
that
that
is
is
bridging
bridging
this
this
gap.
gap
They
they
build
build
AI
ai
chatbots
chatbots
that
that
integrate
integrate
with
with
your
your
entire
entire
tech
tech
stack
stack
that
that
can
can
solve
solve
problems
problems
faster
faster
and
and
cheaper
cheaper
than
than
a
a
human
human
could
could
ever
ever
dream
dream
of.
of
There
there
are
are
tools
tools
like
like
AWS
aws
Lex
lex
and
and
Google
google
Dialogflow
dialogflow
that
that
you
you
can
can
use
use
to
to
build
build
chatbots
chatbots
right
right
now.
now
They
they
can
can
handle
handle
business
business
logic
logic
on
on
the
the
back
back
end
end
with
with
webhooks
webhooks
and
and
can
can
be
be
integrated
integrated
with
with
GPT
gpt
3
3
to
to
provide
provide
unique
unique
human
human
like
like
interactions.
interactions
As
as
you
you
can
can
see,
see
there
there
are
are
going
going
to
to
be
be
tons
tons
of
of
opportunities
opportunities
in
in
the
the
next
next
few
few
years
years
for
for
ambitious
ambitious
and
and
clever
clever
developers.
developers
However,
however
there
there
is
is
a
a
dark
dark
side
side
to
to
all
all
of
of
this.
this
The
the
technology
technology
is
is
moving
moving
so
so
fast
fast
that
that
an
an
idea
idea
that
that
might
might
look
look
like
like
a
a
guaranteed
guaranteed
success
success
today
today
turns
turns
out
out
to
to
be
be
completely
completely
obsolete
obsolete
a
a
year
year
from
from
all.
all
In
in
addition,
addition
the
the
sad
sad
reality
reality
is
is
that
that
big
big
tech
tech
is
is
going
going
to
to
absolutely
absolutely
dominate
dominate
this
this
space.
space
They
they
have
have
all
all
the
the
data
data
and
and
computing
computing
power
power
required
required
to
to
really
really
push
push
this
this
technology
technology
forward.
forward
It's
it's
really
really
hard
hard
for
for
me
me
to
to
compete
compete
with
with
my
my
Intel
intel
Pentium
pentium
Processor
processor
from
from
my
my
mom's
mom's
basement.
basement
Even
even
if
if
you
you
do
do
manage
manage
to
to
build
build
a
a
game
game
changer,
changer
Zuckerberg
zuckerberg
is
is
just
just
gonna
gonna
steal
steal
it
it
anyway.
anyway
It.
it
Another
another
dark
dark
side
side
to
to
AI
ai
is
is
that
that
this
this
technology
technology
will
will
likely
likely
be
be
harnessed
harnessed
by
by
scammers.
scammers
It's
it's
actually
actually
pretty
pretty
scary.
scary
Someone
someone
could
could
clone
clone
my
my
voice
voice
based
based
on
on
all
all
my
my
YouTube
youtube
videos,
videos
Then
then
call
call
my
my
grandma
grandma
and
and
tell
tell
her
her
I
i
got
got
arrested
arrested
in
in
Mexico
mexico
and
and
that
that
she
she
needs
needs
to
to
transfer
transfer
some
some
Bitcoin
bitcoin
over
over
to
to
get
get
me
me
out.
out
Not
not
cool
cool
to
to
scare
scare
my
my
grandma
grandma
like
like
that,
that
man.
man
Also,
also
At
at
one
one
point
point
or
or
another,
another
everybody
everybody
has
has
wired
wired
money
money
over
over
to
to
their
their
long
long
lost
lost
Nigerian
nigerian
prince
prince
relative,
relative
only
only
to
to
be
be
disappointed
disappointed
when
when
that
that
big
big
inheritance
inheritance
never
never
all
all
through.
through
Scams
scams
like
like
this
this
are
are
only
only
going
going
to
to
get
get
better.
better
We
we
can
can
scale
scale
them
them
up
up
by
by
using
using
tools
tools
like
like
chat
chat
gpt
gpt
to
to
automatically
automatically
format
format
letters
letters
in
in
proper
proper
English.
english
All
all
ish.
ish
Um,
um
well,
well
actually,
actually
upon
upon
testing,
testing
I
i
guess
guess
scam
scam
emails
emails
are
are
not
not
allowed.
allowed
In
in
addition,
addition
you
you
could
could
even
even
target
target
a
a
specific
specific
person
person
and
and
combine
combine
their
their
face
face
with
with
some
some
real
real
Nigerian
nigerian
prince,
prince
so
so
the
the
target
target
actually
actually
sees
sees
a
a
long
long
lost
lost
relative
relative
with
with
resemblance
resemblance
to
to
their
their
own
own
face.
face
We're
we're
entering
entering
a
a
brave
brave
new
new
world
world
where
where
it's
it's
going
going
going
going
to
to
be
be
very
very
difficult
difficult
to
to
distinguish
distinguish
fakery
fakery
from
from
reality.
reality
Deepfakes
deepfakes
have
have
been
been
around
around
for
for
a
a
while,
while
but
but
they're
they're
only
only
going
going
to
to
get
get
better.
better
Big
big
companies
companies
that
that
have
have
all
all
your
your
data
data
know
know
everything
everything
about
about
you.
you
They
they
know
know
what
what
you
you
read,
read
how
how
you
you
write,
write
how
how
you
you
look,
look
and
and
how
how
you
you
act,
act
and
and
they've
they've
been
been
using
using
that
that
data
data
to
to
serve
serve
you
you
advertisements.
advertisements
But
but
nowadays
nowadays
with
with
generative
generative
AI,
ai
all.
all
They
they
quite
quite
literally
literally
have
have
the
the
ability
ability
to
to
become
become
you
you
in
in
the
the
digital
digital
sense.
sense
Sounds
sounds
creepy,
creepy
but
but
the
the
good
good
news
news
is
is
that
that
we
we
can
can
use
use
this
this
technology
technology
to
to
live
live
forever.
forever
Even
even
if
if
I
i
get
get
smashed
smashed
by
by
an
an
elephant
elephant
or
or
or
or
fall
fall
into
into
a
a
volcano.
volcano
I
i
will
will
continue
continue
making
making
these
these
YouTube
youtube
videos
videos
because
because
the
the
artificial
artificial
me
me
will
will
be
be
indistinguishable,
indistinguishable
nay,
nay
superior
superior
to
to
the
the
real
real
me
me
and
and
won't
won't
make
make
silly
silly
typos.
typos
Those.
those
Not
not
only
only
will
will
I
i
continue
continue
working,
working
but
but
I
i
will
will
continue
continue
to
to
raise
raise
my
my
family
family
in
in
the
the
metaverse.
metaverse
And
and
not
not
just
just
my
my
kids,
kids
but
but
their
their
kids,
kids
and
and
then
then
their
their
kids,
kids
because
because
I
i
will
will
be
be
the
the
Apex
apex
alpha
alpha
artificial
artificial
grandpa,
grandpa
the
the
the
the
first
first
of
of
its
its
kind.
kind
They
they
could
could
even
even
upload
upload
me
me
to
to
a
a
lifelike
lifelike
robotic
robotic
doll
doll
so
so
my
my
wife
wife
and
and
kids
kids
never
never
even
even
know
know
I
i
died.
died
That's
that's
actually
actually
a
a
great
great
business
business
idea.
idea
Create
create
a
a
company
company
that
that
clones
clones
a
a
person's
person's
persona,
persona
uploaded
uploaded
to
to
a
a
doll
doll
that
that
is
is
automatically
automatically
deployed
deployed
when
when
that
that
person's
person's
organic
organic
form
form
terminates.
terminates
That
that
may
may
sound
sound
crazy,
crazy
but
but
it's
it's
within
within
the
the
realm
realm
of
of
possibility
possibility
in
in
our
our
lifetimes.
lifetimes
Thanks
thanks
for
for
watching,
watching
and
and
I
i
will
will
see
see
you
you
forever
forever
and
and
ever
ever
until
until
the
the
end
end
of
of
time.
time
success
The potential for AI to disrupt businesses is becoming more popular, with developers pushing for a more AI-friendly side hustle. The success of deep learning and machine learning in creating AI apps like Open AI is also highlighted, with a focus on creating game-changer apps like Open AI. The potential for artificial intelligence to disrupt businesses is also discussed, with a focus on deep learning and machine learning to create AI lending platforms and personalized human interaction through chatbots. A potential company is suggested to create a digital experience through a chatbot that automatically format letters in proper English.
5 ideas for your own AI grift with ChatGPT
ChatGPT could start a new technological gold rush for artificial intelligence startups. Let's look at 5 business ideas for GPT-3 and analyze the tech stacks of real companies using deep learning today. 

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🔗 Resources

ChatGPT https://openai.com/blog/chatgpt/
MidJourney https://midjourney.com/
DeepMind https://www.deepmind.com/
Tech Trends in 2023 https://youtu.be/1v_TEnpqHXE

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🔖 Topics Covered

- How to make money with ChatGPT
- What are the drawbacks of AI?
- Will AI replace humans?
- What is the technological singularity
- Ways to integrate AI into an app
- What is MLOps?