Shocking Report Shows Why AI WONT Take Your Job (New Report)
The video addresses a recent report from MIT that suggests AI won’t take away jobs anytime soon due to the high cost of AI systems. The researchers suggest that only 23% of worker compensation exposed to AI computer vision would be cost-effective for firms to automate. The large upfront cost of AI systems, such as the GPT-4 Vision API, makes it economically infeasible for many companies to adopt AI for various tasks. The researchers also argue that the findings apply to language-related tasks as well, as all areas of AI deployment require fine-tuning or customization to adapt to specific characteristics, which is another obstacle for rapid adoption.
The video discusses how the cost of AI development is expected to decrease by 20% per year, but it would still take decades for AI systems to become economically efficient for firms. However, the host questions this timeline, suggesting that advancements in AI development could potentially speed up this process. Additionally, the video mentions that open-AI is trying to change the obstacles to adoption with the introduction of GPT-4 and its plugins, allowing companies to use AI trained on their specific data. While the report from MIT raises valid points about the cost of AI systems, the video raises questions about the feasibility of widespread AI adoption and suggests that advancements in AI development may ultimately lead to a more rapid adoption in the future.
Watch the video by TheAIGRID
Video Transcript
So there was a recent report from MIT that was rather fascinating on how AI won’t steal your job anytime soon and of course since MIT is a well esteemed university in the United States I thought that their report SL resarch is rather important for the AI space so
We’re going to be taking a look at the article what the report says and a few other things that many people aren’t really thinking of when they look at the future of work with AI so here you can see this is an article on Forbes and it
Clearly states that AI will not steal your job anytime soon MIT researchers say so essentially in this article they break down exactly why and the reasons that they give are rather intriguing because whilst they do POS some really good stuff there are some factors that this paper didn’t discuss and I would
Argue that some bits of it are a little bit narrow in the sense that it doesn’t cover a lot of stuff but it still is a very good piece of research because it does show us why the innovation in AI doesn’t necessarily mean that many jobs are going to be disappearing right now
So so essentially what the main point of this research is is that they are talking about the cost of AI systems now when I’m referring to AI systems it could be llms it could be Vision based systems it could be robots as well so just bear that in mind when I refer to
AI systems so essentially what we can see here is that it says to address these shortcomings and construct what they call the first endtoend AI automation models the MIT researchers focused on Vision related tasks where the cost estimates for the AI systems are more devel the model evaluates the level of
Proficiency needed for a task based on surveys of the relevant workers the cost of achieving that proficiency via human workers or AI systems which are pretty expensive develop and the economic decision by firms whether or not to adopt AI for a particular task basically what they’re saying here is that you
Know AI systems aren’t cheap to run in their current state we do know if you you know look back at gbt 4 we remember that GPT 4 currently only has 70 messages every 3 hours or around 40 messages every 3 hours hours depending on which API you’re using that is the
Current limit and essentially they make a point that this is pretty expensive to run and of course because of how expensive how computationally expensive it is that essentially means that it might not be as feasible for people to be replaced with AI at its current state
And they do use some examples in the paper where they basically say that this isn’t going to be feasible so there’s some other points here that they do talk about so they said that using the new and improved model the MIT researchers found that only 23% of worker compensation exposed to AI computer
Vision would be costeffective for firms to automate because of the large upfront cost of AI systems lowering the cost of AI development and or the cost of AI deployment by increasing scale possibly using AI as a service platform would lower these costs however even with rapid decreases in costs of maybe 20%
Per year it would still take decades for computer vision tasks to become economically efficient for firm terms so I mean what they’re stating here is pretty true from based on what we’ve seen there was someone I remember who even used the GPT 4 Vision API and essentially if you don’t know what that
Is that’s essentially just GPT 4 with a vision you know it’s chat GPT with images and it was pretty expensive I remember them saying that they racked up a pretty large bill in only about an hour and this was not economically feasible at all although you know if it
Was realistically really really cheap it would be feasible but you know even if it decreases at 20% per year they stay that it would still take decades now I think that the cost decreasing at 20% per year is going to be something that happens a lot quicker than that because
There’re saying it’s going to take decades um and I just don’t know if that is the case because we’ve seen AI development rapidly rapidly increase so for them to say it’s going to take decades I’m not sure where that fits on the timeline with other things in AI
Because for example of course if you know that with Ray cwell he actually predicted that there would be a singularity in around I think it was 2040 and he also did predict that in around I think it was 2027 or 2029 that there would be the first AGI system so
With that being said I’m not sure how they’re saying it’s going to take decades and decades just means like a really long time so I’m I’m I’m suggesting that maybe they’re looking at some pieces of research that maybe we just haven’t considered now essentially they also state that the MIT researchers
Argue that their findings apply also to generative AI or the automation of language related tasks all areas of AI deployment require fine-tuning or customization to adapt them to firm specific characteristics a crucial cost factor and obstacle for Rapid adoption now I’m not going to lie this is a very
Good point now there are two things to consider here because this is rather incredible because one thing that I know a lot of people didn’t notice when gbt 4 was released and opening I talked about custom fine tune models they actually talked about you know if you are a
Company essentially if you want to get your custom tune model like for example and I’m not talking about this where we’re talking about you know fine-tuning a model which is just you know like a simple version talking about you know them like building like a complete thing
For like a company I’m not sure if this is true but the rumors stated that it was starting at around a million which is pretty insane but I do think of course some of the larger conglomerates can easily easily pay that amount but we have seen that you know training a model
On your data is becoming easier and easier because of course if you remember there was also this thing that was just recently released and of course this is the GPT store so essentially if you remember there was this thing that was released because of course this is the
GPT store and with this you have I guess you could say a simpler way to essentially use your AI that is I guess you could say trained on your data in a way that could be applied to certain companies now we’ve seen time and time again that sometimes this doesn’t work
Due to hallucinations and due to the guard rails not being stuck by which is something I’m going to explore later but um it definitely is an obstacle to adoption that open AI realize and of course they are trying to change with the adoption of gpts and of course there
Of course are these things so these things of course are plugins as well and these are ways that companies can use these different chat Bots as well so I think that the obstacles to adoption is a very very very good point because that is of course true but I think like I
Said in the future we’re going to have systems that are going to be able to you know be trained on data really rapidly there are some new advancements that I’m going to be talking about and of course adapting them to firm specific characteristics I do believe that
There’s going to be a very large automated process soon now essentially what they said here was that another obstacle to adoption not always considered by economists and other people was what another study callus the societal acceptability of AI some professionals May seamlessly integrate AI tools whilst others could face
Resistance because of cultural ethical or operational concerns and this is a very very big truth that I will explore in a moment because although AI might be good it’s not human and the inherent nature because it’s not of course not human does mean that some things just won’t be accepted because they aren’t
Human and I will you know elaborate on that more because I have some fascinating examples to to show you so then essentially they say here that you know essentially in advanced economies you know this IMF report which we already you know looked over it says
About 60% of jobs may be impacted by AI roughly half of the exposed jobs May benefit from AI integration enhancing productivity and of course this thing which you know people did freak out about but essentially you have to remember the word impact doesn’t mean negatively or positively it just means
That it’s going to affect it in some way okay so the 60% of impact just essentially means that you know it’s going to affect it it could affect it positively of course it could be negative but according to the research it was that you know 50% of the jobs
Would be negative essentially meaning that it could remove demand for that work and then of course the other half it means that it would make your life easier so of course a shift in the economy but of course the effects of this would be longterm now one of the
Things I do want to talk about is I wanted to actually talk about if cost is actually going down because remember if we look back to the first point they talk about how cost going down is of course one of the first things that we
Need to look at if this is going to be a reality and if the systems are going to be feasible for future use so you can see right here that this is a paper that many people did actually miss but this is going to be a conference paper at LR
2024 and this is called slice GPT compress language models by deleting rows and Commons so columns so essentially they said here that slice GPT effectively compresses models by up to 30% while retaining a high percentage of the original models performance on zero shot tasks notably for llama 2 70
Billon parameters OPD 66 biling parameters and 52 models and it maintains 99% 99% and 90% of dense model performance respectively with 25% slicing so essentially they were able to you know make these models smaller and retain most of the quality so I think that this kind of research shows us that
You know whilst they state that of course cost is one of the major things and even if they get 20% down it’s going to be decades I tend to disagree just a little bit because I think that what we’re seeing is that these models are really really effective even even if
They’re not huge now there was also something that I wanted to also elaborate on a bit because if we do look at Cost reduction one of the main things that we do talk about is that this is crazy okay so right here you can see
That we do have f 2 and 5 2 is a 2.7 billion parameter large language model that outperforms other models that are 25 times larger and essentially right here you can see it says f 2 matches or outperforms models that are 25 times larger thanks to new Innovations in
Model scaling and training data curation so essentially what researchers found was that even if the model isn’t as good if you just surely focus on those you know parameters not like just Giga scaling the model to like a trillion parameters if you just focus on the
Model and if you focus on the kind of data that you’re feeding it you can definitely get a lot more performance out of a much smaller size and that’s essentially what they did and this is something that is you know it was pretty much groundbreaking and I’m pretty sure
In future models they’re going to be as much smaller than the ones we have now but they’re also going to retain the same level of quality now this next thing actually does come from Sam Alman because Sam Alman does actually talk about the cost of AI coming down in this
Interview with Bill Gates and it was something that a lot of people did Miss but I think it is rather important because it goes to show that cost is of course something that samman is thinking about because that limit that’s been on GPT for quite some time we’ve been
Wondering whenever is it going to come down see but I’m very optimistic and I agree with you what a contribution would that be in terms of equity technology is often expensive like a PC or internet connection and it takes time to come down and cost I guess the costs of
Running these AI systems it looks pretty good that the cost per evaluation is going to come down a lot it’s come down an enormous amount already uh gpt3 which is the model we’ve had out the longest and the most time to optimize in the three years that’s three and a little
Bit years that’s been out we’ve been able to bring the cost down by I think a factor of 40 so for 3 years time that’s like that’s a pretty good start for uh 3.5 we’ve brought it down I would bet close to 10 at this point four is newer
So we haven’t had as much time to bring the cost down there but we we will continue to bring the cost down I think we are on the steepest curve of cost reduction of ever of any technology I know way better than mors law and it’s
Not only that we figure out how to make the models more efficient but also as we understand the research better we can get more knowledge we can get more ability into a smaller model and so I think we are going to drive the cost of intelligence down to so close to zero
That it will be just this before and after transformation for society like right now my my basic model of the world is cost of intelligence cost of energy those are the two kind of biggest inputs to like quality of life particularly for poor people but overall if you can drive
Both of those way down at the same time the amount of stuff you can have the amount of like Improvement you can you can deliver for people it’s quite enormous and we are on a curve at least for intelligence we will really really deliver on that promise but even at the
Current cost which again this is the highest it will ever be and much more than we want for 20 bucks a month you get a lot of gp4 access and way more than 20 bucks worth of value so I think we’re already so I think from that clip
You can see clearly that the path in terms of the cost of intelligence is actually going to go down and I think you know the comments from Sam Alman clearly show us the direction that we’re heading in and that is pretty much someone who really does know exactly
Where AI is going so you couldn’t have got a better spoke person for that now the next thing I did actually want to talk about was the fact that people do hate AI now hear me out on this point because it’s a point that doesn’t get
Brought up a lot but people have to understand that a lot of people don’t actually accept AI now remember previously when we talked about how there are you know societal cultural and ethical you know reasons why AI acceptance is going to struggle but one of the examples I did actually want to
Bring up was of course this channel so a lot of people will say that you know AI is great it’s just going to replace everyone but for example on this channel I rarely ever use AI voices and when I do it’s because I’m just so completely busy that the environment doesn’t allow
Me to record a voice or you know I have like maybe like a health issue and I’m not able to use my voice because like of a cough maybe a cold maybe something like that and it just you know would sound awful but people still need their
News or upto-date information now if you take a look at some of these comments on this singular video you can see exactly why this isn’t the case so people are saying that you know we prefer and are used to your natural voice can you not just clone it with lemon labs when you
Can’t record please no more AI voices now if you think those comments are just you know cherry-picked take a look at this one it says the problem with using an AI voice is that the audience is left guessing whether real eth synthesis was involved when while creating the content
Or not and we want people who are trained on real world data far vaster than AI is currently training to do with the research because current AI aren’t familiar with subtitles and it’s not that we hate the I voice it’s more like we doubt the expertise level you can see
That this got 23 likes as well so um and I’m going to show you guys one more comment as well because there is another comment that is rather fascinating and it says right here I prefer a real human voice it’s warmer more engaging when I can tell the voice is generated I
Honestly tune out I believe the content more when a real person speaks to me and that one had 82 likes it was the most um liked comment on that video and the video wasn’t bad by any means you can you can go ahead and watch the video it
Was a video about lk99 um but on that day I was just specifically really just drained tired I had a cold I was just like there’s no way I could get this video out but it was rather important and of course you know some people just
Didn’t enjoy that video now that is 100% completely understandable because at the end of the day you’re making a video for real people and real humans and humans get to decide whether or not they enjoy a piece of content now I think in some video pieces AI voices are okay for
Example there’s some YouTube channels that do completely well with it and that’s completely fine but in some areas you know on some channels I think the majority people want to talk to people and these where this is where these kind of comments come from and it’s completely understandable because people
Don’t just want to hear some droned out AI voice over that is you know pretty much you know it it doesn’t have human emotion it doesn’t have inflections it doesn’t have paus it doesn’t have stops um and I think that that is going to show you that whilst yes AI can replace
People and you might be thinking why on Earth are you just talking about voiceovers I’m going to get into some more examples to show you that this is like you know across many different Industries this is a real thing I think humans interacting with humans unless it’s like completely robotic like data
You know 1 plus one is two kind of automation software stuff um I think where the human approach is usually there I think humans will always prefer a human approach now there was also if you hadn’t heard about this there was a huge game if you’re not familiar with
The gaming industry and how big it is there was essentially a huge game that Rose to the top of the team steam charts and this game got a lot of hate like a lot more hate than I would have liked to see and it says Twitter was annoying all
The big hate posts I found is focus on one thing AI they say the game models and game was created using AI so they hating on the game but before you ask them for proof is I have no Pro basically okay um there was a game that
Was created and it was really popular and you know some of the devs were basically saying that they used AI to help them create the game better and make more assets quicker and a lot of the hate that was coming from was around this and I mean the game is great it’s
Loved worldwide and I don’t think a lot of people care but there were a lot of people who were just simply saying I’m not going to play the game it’s just like an AI generated game it’s just you know soulless y y y um and once again
That goes to show that you know when people understand that you know something is AI generated or an AI contributed towards that they really do tend to steer from that kind of content even if the end product is somehow valuable so another thing as well and
This is why I want to talk about customer service and um chatbots this has been a long time thing if you’ve ever spoken to like you know those and don’t know I guess you could say it’s a rudimentary form of AI but you’ve ever
Spoken to you know a chat B and you can hear like it’s you know like a woman like a Siri kind of voice on the phone you know how frustrating that is especially if you have a really dire issue that you need a human to take care of and you completely understand that
The robots are never going to understand because those ones are just like you know like branches where if you say one thing it’s going to lead you to another thing it’s like press five people people really do hate those things I can completely understand why because when
You call up you’ve paid your money you expect a kind of service and you’re met with like a bot it just feels soulless and um you know customer service whilst people are trying to replace them with llms I don’t think that’s going to happen too crazily because this person
Here you can see if you weren’t familiar with this we covered this in a week in a week in AI um and essentially this person bought a Chevy Tahoe for $1 and essentially they were able to trick the customer service chatbot into you know getting that deal of course it wasn’t
Legally binding so they weren’t able to actually get the car for a dollar but the point is is that hallucinations are still a big thing and whilst yes there will be guard rails to improve this in the future I think um this it’s going to be kind of interest it’s going to be
Kind of interesting to see how people circumvent those guard rails in the future and if they’re able to and what kind of things are there in the future to prevent these kind of things from happening because once people realize it’s AI people always try and go around
The guard rails um and I’m wonder if there’s going to be some kind of question or some kind of chain of thoughts or some kind of prompting to be able to always reveal if it’s an AI or not maybe there’s going to be some kind of new touring test and of course this
As well you can see dpd customer service chatbot swears and calls company worst delivery firm so um you know the point I’m trying to make here guys is that yes AI can take your job and in some Industries it might um you know reduce demand I think that where people realize
That humans are really valuable or even just you know humans are you know like I guess you could say the ones that are supposed to be there replacing it with the eye isn’t always going to go down well and remember AI art you know some organizations banned AI art because they
Were like you know there’s legal issues and there was even some controversy about AI artw works so for example there was this artwork and he created something called The Space Opera theater using mid Journey submitted it as an entrance to the Colorado state fairs annual art competition and he won first
Place and people were pretty pretty furious and I can completely imagine and the problem was is that you know um this is outrageous prompting a machine to make you something does not make you an artist as an artist of any sty and Technique we put the time to handson
Create something and this guy can type and refresh in the process a few times and that is being compared to craftsmanship and I completely understand this entire Twitter thread I mean some people are saying that choosing the right prompts selecting the best image and post postprocessing and Photoshop are all Creative Expressions
Then it’s art you’re judging work based on the effort behind it but many works of abstract are technically effortless and considered art anyways and that is of course a true point because how many Modern Art Museums have you seen where it just looks like something that you
Could have done in 5 seconds and some people are saying that it’s you know magnificent so I guess art isn’t of course the best example but the point is is that when you use AI to create something like this person did and of course you win first place it brings up
A whole host of other issues that where you think okay because AI can do it better it means that instantly people are going to Value it and of course we always come back to the same example of Chess where chess is something that could replace people like oh chess is
The best AI nobody wants to watch chess play play play AI nobody wants to watch AI play chess because it’s just completely boring now something that uh I think this is one of the most fascinating things because health is of course good but essentially it says right here that 60% of Americans would
Be uncomfortable with their healthcare provider relying on AI in their own Healthcare so it says yet many see promise for AI to help issues in the bias of medical healthare so there was essentially some research that basically stated uh I think it’s right here so it says that generally the American public
Still prefer a human physician to be responsible for their medical care over an AI so um it says however the general public seems mixed when the survey results are taken as a whole so essentially people just prefer humans in terms of the you know medical issues and
That’s crazy because if we look at the contrast if we look at the health is good but so essentially if you haven’t paid attention to this um there was this thing called Google’s Amy and it essentially AI assisted doctors performed better than uni assisted doctors but AI on itself actually
Performed better than AI assisted doctors and even though that is better overall it’s still clear from the research that humans prefer humans and I think you need to understand that this is a recurring theme so you know there’s going to be some companies I do think in
The future that do get a lot of positive PR from stating that they’re not going to use Ai and that they prefer using humans and of course until we get AGI there was this video I wanted to show you from an upcoming video on robotics
That um you know this is from prin and it’s it’s just amazing stuff essentially a uh delivery robot that can go ahead um and Vault over curbs and they made this robot to deliver packages and the point is is that you’re still going to need humans to do some things until we get
General purpose AI human humanoid robots because some people are always going to steal the robots some people are going to just do stuff where I guess like what the situation you’re seeing is going to be a zero shot situation and you’re going to need to get that right and
Humans do very well in those scenarios where you know these kind of robots just really don’t do well in so um I think largely we’re still going to pretty much need humans for quite some time I mean it will be also interesting to see the emerging fields and overall whilst AI
Probably won’t steal a job anytime soon I think the way how the industries will shift will be something to take a look at and of course pay attention to because whilst new research and new studies are always good It’s always important to see what’s going on in
Reality and what people actually do want and you know surveys based on how they do feel so with that being said let me know what you thought about this if you have any questions
Video “Shocking Report Shows Why AI WONT Take Your Job (New Report)” was uploaded on 02/04/2024 to Youtube Channel TheAIGRID