It's Not Looking Good For AI

Summary

The video discusses the challenges faced by AI companies, including high operational costs, investor dissatisfaction, and customer confusion over AI's broad capabilities. It highlights how customers prefer specialized solutions over general-purpose AI models, leading to market confusion and competition. The video also addresses the failures of certain AI products, the issue of AI-generated code requiring external supervision, and the negative impact on job applicants flagged for using AI. The creator emphasizes the importance of these discussions and thanks supporters for enabling higher production quality without corporate sponsorships.

Takeaways

• 💡 AI companies are facing challenges due to high operational costs, including expensive hardware and maintenance for AI models.
• 📉 Investors are skeptical as the billions invested in AI models have not yet yielded substantial profits, leading to backlash against AI companies.
• 🤔 Customers are confused by the broad capabilities of AI, preferring specialized products over 'one-size-fits-all' solutions.
• 📱 The script uses a smartphone metaphor to illustrate the market confusion caused by products that try to serve multiple purposes at once.
• 🛒 Customers tend to opt for specialized products for specific tasks rather than AI models that claim to do anything.
• 📉 The failure of certain AI products has led to skepticism and doubt in the market, affecting the reputation of AI in the economy.
• 🗣️ AI's 'hallucinations', such as inappropriate suggestions, have raised serious concerns about the reliability of AI models.
• 👨‍💻 AI-generated code often requires external supervision to ensure it works as intended, which can be more time-consuming and costly than writing the code itself.
• 🔍 The script discusses the difficulty of distinguishing between AI models that claim to perform similar tasks, leading to market fragmentation.
• 🚫 AI models are increasingly used in the hiring process, with some companies using AI to check if job applicants' code was written with AI assistance, potentially leading to false allegations.
• 🎓 The video creator emphasizes the negative impact on new developers, who may be unfairly rejected based on AI's misjudgment of their work.

Q & A

Why are AI companies facing backlash from investors?

AI companies are facing backlash because the billions of dollars invested in AI models are not justifying the profits generated. Investors expect returns on their investments, but AI models require expensive hardware, computational power, and maintenance costs, which are not being adequately compensated by the profits.

What is the main issue with AI products from a customer's perspective?

From a customer's perspective, the issue with AI products is that they often try to do too many things, making it confusing for customers who generally prefer specialized products that solve a specific problem rather than a 'one size fits all' solution.

How does the smartphone metaphor relate to AI products?

The smartphone metaphor illustrates that just as a smartphone with a built-in vaping machine would likely appeal to a very niche market, AI products that try to do everything may not attract a broad customer base. Customers often prefer products specialized in one area rather than multi-functional ones that may not fully meet their specific needs.

What are some of the challenges AI models face in the software development industry?

AI models in software development face challenges such as producing code that often requires external supervision to ensure it works as intended. The cost and time associated with testing and ensuring code functionality are significant, and AI models are not yet adept at guaranteeing that the code they generate meets these standards.

What impact have AI product failures had on the industry?

AI product failures, such as hallucinations in AI models and flops like Rabbit M1 and Human AI, have created skepticism and doubt among consumers and potential investors. This negative perception makes it harder for new AI companies to gain trust and succeed in the market.

Why are hallucinations in AI models concerning?

Hallucinations in AI models are concerning because they can lead to dangerous or absurd recommendations, such as suggesting harmful actions or giving nonsensical advice. These incidents undermine trust in AI and can have serious consequences for users who rely on AI for accurate and safe guidance.

How has AI affected the job application process for software developers?

AI has affected the job application process by introducing AI code checkers that flag assignments as being AI-generated. This has led to applicants being rejected unfairly if the AI incorrectly identifies their work as AI-generated, making it difficult for them to secure a job.

What is the potential downside of using AI to check code in job applications?

The downside is that AI code checkers may misidentify code written by applicants as being AI-generated, leading to unfair rejections. This could harm the applicant's career prospects and create an environment of distrust between job seekers and employers.

Why do customers prefer specialized products over AI models that can do everything?

Customers prefer specialized products because they are often more reliable and easier to use for specific tasks. A product designed to do one thing well is usually more appealing than an AI model that tries to do everything but may not excel in any one area.

What commitment has the content creator made regarding sponsorships?

The content creator has committed to not accepting any sponsorships or brand deals. They want their audience to hear their genuine opinions, without any influence from companies, to ensure that the content remains unbiased and authentic.

Outlines

00:00

📉 AI Companies Facing Economic Challenges

This paragraph discusses the current difficulties faced by AI companies, including a lack of profitability despite significant investment in hardware and maintenance. It highlights the operational costs of AI models and the discrepancy between the billions of dollars invested and the returns received by investors. The video aims to explore these issues while emphasizing that the content is based on opinions rather than facts, due to legal reasons.

05:01

🤖 Customer Confusion and Market Segmentation in AI

The second paragraph delves into the customer perspective on AI, where the versatility of AI products is causing confusion in the market. It uses the smartphone metaphor to illustrate how attempting to cater to multiple markets simultaneously can dilute a product's appeal. The paragraph argues that customers prefer specialized solutions over a 'one-size-fits-all' approach, which is currently hindering AI's success in the market due to a lack of clear, specialized value propositions.

Keywords

💡AI models

AI models refer to artificial intelligence systems designed to perform tasks that typically require human intelligence, such as understanding language or recognizing patterns. In the video, the term is used to discuss the high operational costs and the need for specialized hardware and maintenance, which are central to the theme of economic challenges faced by AI companies.

💡Operational cost

Operational cost represents the expenses incurred in running a business, including the costs of labor, utilities, and maintenance. The script mentions that AI models have high operational costs due to the expensive hardware and computational power required, which is a significant burden for AI companies and affects their profitability.

💡Investors

Investors are individuals or entities that provide capital for businesses with the expectation of generating profits. The video script discusses how the billions of dollars invested in AI models have not been justified by the profits returned to investors, indicating a disconnect between investment and return in the AI industry.

💡Customer confusion

Customer confusion arises when potential buyers are unsure about what a product does or how it meets their needs. In the context of the video, AI's broad capabilities create confusion as customers often prefer specialized products that excel at specific tasks rather than a 'one-size-fits-all' solution.

💡Market segment

A market segment refers to a group of consumers who share similar needs or characteristics that a company can target with its products. The script uses the term to illustrate the preference of customers for specialized solutions over general AI models that claim to do anything.

💡Product specialization

Product specialization is the process of tailoring a product to meet the specific needs of a particular market segment. The video emphasizes the importance of specialization, as it is preferred by customers over the broad capabilities of AI models, which can lead to a lack of focus and effectiveness.

💡Competition

Competition refers to the rivalry among businesses striving to achieve the same objective, such as gaining market share. The script discusses how the broad capabilities of AI models can lead to confusion in the market, as customers struggle to differentiate between various AI products that claim to do similar tasks.

💡Product flops

A product flop is a product that fails to meet expectations or achieve commercial success. The video mentions several AI-related product flops, which contribute to skepticism and doubt about the effectiveness and reliability of AI in the economy.

💡Hallucinations attribute

In the context of AI, 'hallucinations' refer to the incorrect or nonsensical outputs generated by AI models. The script cites examples of AI models providing dangerous or absurd advice, which raises serious concerns about the reliability and safety of AI applications.

💡Software engineering

Software engineering is the application of engineering principles to software design, development, and maintenance. The video discusses the challenges of ensuring that AI-generated code works as intended, highlighting the importance of thorough testing and the potential costs associated with debugging AI-generated code.

💡Interview process

The interview process is the procedure used by companies to assess and select candidates for employment. The script describes how AI models have been integrated into this process, with some companies using AI to check if applicants have used AI in their submitted work, which can lead to unfair allegations and impact job prospects.

Highlights

AI companies are facing challenges due to high operational costs and the inability to justify the profits from AI models.

Investors are experiencing backlash from not receiving adequate returns on their investments in AI.

Customers are confused by the broad capabilities of AI, preferring specialized products over general AI solutions.

AI's 'one size fits all' approach is not appealing to customers who seek specific solutions.

Market competition is causing confusion for customers trying to choose between various AI products.

AI product failures, such as Rabbit M1 and human AI, are creating skepticism in the market.

AI models' hallucinations, such as inappropriate suggestions, are raising serious concerns among consumers.

AI-generated code often requires external supervision to ensure its quality and functionality.

The process of ensuring code works as intended is more resource-intensive than writing the code itself.

AI models are not adept at verifying the functionality of the code they generate.

AI has infiltrated the interview process, with some companies using AI to check applicants' code for AI assistance.

Applicants are facing allegations of using AI to write code, which can negatively impact their job prospects.

The video creator emphasizes the importance of distinguishing personal opinions from facts for legal reasons.

AI models require significant computational power and maintenance, leading to high operational costs.

The creator discusses the smartphone metaphor to illustrate the confusion in the market regarding AI capabilities.

The creator highlights the need for specialized AI solutions rather than generalist AI models.

The video creator has hired a video editor thanks to the support from patrons and channel members.

The creator is committed to not accepting sponsorships or brand deals to maintain content integrity.

Transcripts

with the recent events involving Ai and

AI companies it seems like AI companies

have been Landing themselves in a lot of

hot water recently whether it's Wall

Street Turning its back on AI or

software developers reporting that their

workloads have been increased by 77%

with using AI models it seems like the

future is looking Bleak for AI companies

so in this video I'm going to be

discussing some points and discussing

some opinions about Ai and just a small

disclaimer for the video These are

opinions not facts

I have to say these things these days

for legal reasons but anyway let's jump

in so the first thing is the operational

cost of AI models and we know that AI

models require a lot of expensive

Hardware a lot of computational power

and a lot of maintenance cost to

maintain the operations of AI models to

make sure that it is operating at its

highest capacity for customers

now the billions of dollars that have

been poured into AI models and its

operations is not justifying the profits

that is generating back for the

investors which is how a usual company

survives in the economy they raise a lot

of money they develop the product and

they sell it and the profits that it

generates it's given back to the

investors so which is why AI companies

have been facing a lot of backlash from

investors with them not being able to

generate the profits from AI products so

this is something that is affecting AI

companies progresses in the latest

economy the second thing is about the

prospect of AI and its customer side of

it so for customers they usually pay for

a product that is specialized in one

thing and it's good at doing one thing

and the prospect of AI being like it can

do anything that the user can ask it is

why customers are confused with buying

AI products so I want to explain this

with a smartphone metaphor let's say

that you use a smartphone and you vape

on The Daily so you hear about a company

that is creating a smartphone that has a

waving machine built into it now on

paper it would seem like the company is

targeting two big markets people who

vape and people who use smartphones that

looks good on paper but in actuality

what happens is the company ends up

targeting the people who are looking for

both a smartphone and a vaping machine

built into one at the same time and are

willing to pay for it and what happens

in these scenarios is that the companies

are not able to generate profits for the

product that they created and this is

what the problem with AI is their

Prospect of AI models capabilities of

doing anything that the user can throw

at it is what puts the customers in a

confusing

State and it goes back to the market

segment of people wanting to have a

solution that can do a specific thing

over something that can do everything

that the user can ask it let's say that

you are a businessman and you are in a

requirement of a product that can

summarize documents for you so you go

into the market and you find out about

this AI model that can do anything for

you you would rather buy a specialized

product product that only specializes in

summarizing documents for you rather

than buying an AI model that can do

everything you ask of it and which is

why the prospect of AI is failing in in

this latest economy because customers

don't want to buy a one siiz fits all

solution they want specialized solutions

that they are willing to pay for so it's

less clutter for them and the

competition is another aspect of it

where let's say that you are uh in the

market and you are looking at open an AI

model that can summarize documents for

you and at the same time you also look

at claw or barred AI capability to do

the same thing now how will you

distinguish between the two of them and

let's say that you are in a requirement

of paraphrasing sentences for a document

so there are like five companies for it

so this creates a lot of confusion for

customers and and the market ends up

dividing itself between customers who

went with one company and with customers

who went to another company for the same

solution this is normal business

competition but the prospect of AI is to

be blamed here which claims to do

anything that the user can ask it to the

third thing is the flops that we have

been seeing regarding AI products so

whether it's rabbit M1 being a flop or

human AI flopping or some software

related AI models not being able to

generate code that is usable for uh

software developers without an external

supervision this all creates a negative

impact about AI in the economy where a

new company wanting to do something with

AI will be met with a lot of skepticism

and with a lot of

doubts which is a result of these

products failing in the current economy

okay the hallucinations attribute of AI

models are the biggest factor in it

where somebody asking for mental support

gets told that they should just jump off

the Golden Gate Bridge or uh some AI

model uh suggesting that people should

eat rocks every day so these are some

things that gets taken very seriously in

the consumer's mind where they question

the capabilities of AI and on the

software development side the code that

the AI chatbots generate have been

proved to be needing external

supervision to make sure that the code

is good enough to be used now an aspect

that has to be kept in mind about

software engineering is that making sure

that the code works as intended is lot

more expensive and time-taking than

writing the code in the first place the

code that we write it requires a lot of

testing environments and it requires a

lot of time and effort to make sure that

the code that we have delivered is

working as intended and AI models are

good at writing code but they are not

good at making sure that the code works

as intended because if we talk about

just specific modules even if we talk

about a simple example let's say a crud

form that simple crud form can function

very differently in the same product on

two different stages this is what needs

discussion over the external

investigation that needs to take place

when we take the code from AI chart Bots

and decide to use it in our projects now

I created a video before where I talked

about how how you should be careful with

using AI models for coding the video

should be right there so make sure to

check that out later and the last thing

that I would like to discuss about AI is

how AI models have infiltrated the

interview process so how it used to work

was the applicant would apply to the

company for a job position the company

would email them a task or an assignment

that they have to complete within a time

frame the applicant would complete the

assignment and submit it back to the

organization and it would be checked if

it is good enough and based on the

assign ment that the applicant submitted

the interview would go further now what

I heard from my Discord Community lately

is that the students are now getting

rejected in the assignment phase itself

because the management of the company is

passing their assignments into an AI

code Checker whether it's checked that

the code was written with the help of AI

or not and if the AI miscalculates or

mis Flags the assignment being like this

code was written with the help of AI

then the applicant gets put with an

allegation that they used AI to write

code and in my opinion this is an

allegation that you cannot walk out of

you cannot convince the management at

all that you did not use AI to write the

code because most of the code that the

AI is trained on is mediocre level or

beginner level code and the type of code

that beginers right it matches those

patterns and it's very likely that the

AI would say yes this code was written

with the help of AI now this is really

depressing scenario for the software

developers who are trying to enter the

industry this is something that we need

to discuss because the applicants have a

lot to lose on this part getting flagged

with using AI to write code is an

allegation that they cannot walk out of

and it basically ruins their chances of

ever Landing a job in the company so we

can only find out what will happen in

the future as time passes and uh yeah

there is a lot of uh problems with AI

obviously but we will have to see how

that works out so this is it for the

video um so I would like to take a

moment to thank all of my patrons and

channel members who have decided to

support the channel um as a result of

that I have been able to hire a video

editor finally so you should see the

production quality of my videos go up so

I can only thank you for that and if you

decide to support the channel even

further please do because I have made

this commitment that I will not accept

any sort of sponsorship or brand deals

on this channel I want you guys to hear

what I have got to say not any sort of

control speech uh from any company or

whatever so thanks thank you for

listening and I will see you in the next

one thank you