You Won't BELIEVE What AI Can Do Now! (NEW 2024 A.I REPORT Reveals All)

so Stanford University have released their measuring Trends in AI report for 2024 and this is their most comprehensive up-to-date analysis and it arrives at the important moment when ai's influence on society has never been more pronounced and essentially this AI index report tracks and visualizes data related to Ai and they try to provide unbiased rigorously vetted broadly sourced data in order for policy makers researchers Executives journalists and the general public to develop a more thorough and nuanced understanding of the complex field of AI so this report should show you where the general Trends in artificial intelligence are and will likely help you inform you about whatever it is that you may be thinking for the future of AI so there's

going to be 10 sections to these and I will leave time stamps in the bottom of the video so if you want to look around and Skip around um that will be there so s of the first things that we have is that industry continues to dominate Frontier AI research we can see here that if we look at 23 and leading on Wass and actually the trends we can see that industry produced 51 notable machine learning models while Academia contributed to only 15 and there were 21 notable models resulting from industry Academia collaborations in 2023 with a new high but of course overall we can see that this trend is continuing to increase in the number of machine learning models that we're going to see um and one thing that I would like to see is the government start to get involved in some kind of projects because I think that you know that kind of thing is important because you know with private companies leading the way I'm wondering if there's going to be some crazy um Power imbalance in the future now in addition in chapter 1 they talk about how you know there were 149 Foundation models that were released which is double the amount in 2022 and of these newly released models 65% were open source compared to only 44% in 2022 and 33% in 2021 so once again of course we can see this trend of AI is continuing to increase and it's pretty fascinating because you know I think what one of the things that we love to look at here is that we can see that on the open tab right here we can see that you know we have such a small smaller percentage almost even you know 32 to 28 and then we can see here that it's 98 open- Source models released in 2023 and open source is for outpacing the you know ones that are limited but of course state-of-the-art limited models are still reigning Supreme areas like you know gbt 4 and of course the successor which are probably going to be Claude 4 GPT 5 and Gemini 2 those models are of course all closed Source but I think it's really interesting to see the trend that open source is just increasingly going to dominate the space and it's pretty interesting to see how that trend is you know increasing and I'm wondering considering how Elon Musk has been contributing to that you know if that trend is going to increase because recently there were some regulations so this is going to be a trend that I will look back on to see if open source continues because uh there are some strict regulations about systems and the reason I state that is because right now open source systems are getting you know really good but I'm wondering what happens when those open source systems get uh to a level that is pretty powerful so right here this is pretty fascinating because what they actually did was they released the estimated training cost of the models from 2017 to 2023 and we can see that of course there is a huge amount of uh funding going into these models and gbt 4 surprisingly they estimated it um according to the AI index they estimated that GPT 4's training cost was actually $78 million which is a little bit cheaper than I initially thought because I thought that it would be you know around that $200 million Mark but it seems that Gemini Ultra is at $191 million so I'm guessing that this shows us that you know open eyes GPT 4 which was trained on the envidia chips is definitely far more efficient and more cost effective because Gemini Ultra doesn't surpass gbt 4 I mean technically it does in uh the benchmarks but in terms of the leaderboards and the human eval human evaluations not the human eval benchmarks I'm talking about the leaderboard benchmarks in the playground um it seems that you know gp4 seems to be a little bit more efficient but we didn't get of course Claude 3's release cuz that was uh just really recent so I would have loved to know uh how much they spent on training Claude but I guess that there isn't any estimate on that just yet now of course this is pretty interesting because this is where we take a look at some of the countries that are leading um machine learning and we can see here that in terms of the top countries we literally have the United States leading the rest of the world by a far margin I mean you can see that China is following close behind France is of course close behind as well and Germany is of course still there but the point is that the United States is you know far superior in terms of you know putting uh things out and of course you know a lot of people going to say well the United States is a lot bigger so of course but I think the United States culture you know the San Francisco area the competitiveness all of those factors especially with their tech industry just leads them to you know far outpace the rest of the world and like I said before I wonder if this trend will change in the future will China manage to release more and more models are they going to be restrictive on certain things will franch catch up with open source will the UK finally get into the mix and start releasing a lot more things I mean it's going to be very interesting as well considering also you know we did uh get some information that the UAE was going to potentially be an area where Sam Alman was going to be releasing certain models um and experimenting with certain AI Technologies uh he talked about it being a regulatory playground and we can see here this is where samman says the UAE could become a regulatory sandbox for AI and that's why I'm stating that you know um maybe the UAE is going to be something that far surpasses things in the future if Sam Alman is potentially investing in there so that's just uh something that's quite interesting on uh the countries but I do think that you know the better model is far important than how many models you do produce now something interesting as well something that I was looking at quite a little bit but I didn't manage to find too much was that um there was a lot more AI patents going out you can see that there have been um a huge increase 62% increase in the amount of AI patents being granted around the world um and this is pretty fascinating because it goes to show that a lot of people are inventing things with AI that may come in the future that are going to be really gamechanging and I do wonder if many people in the future and yeah I'm wondering if when super intelligence gets here what this scale kind of looks like if it just looks you know goes vertical because super intelligence you know theoretically speaking should be able to generate ideas in a way which we haven't thought of yeah so that would be uh pretty interesting and what was also interesting if we're looking at patents it seems that China is leading the global AI patent origin with 61. 1% significantly outpacing the United States which accounted for 20. 9% of AI patent Origins which is a quite an interesting Trend so seems that China is trying to uh lock down a lot of the things that they are innovating with and of course you know open source air research has been absolutely exploding we can actually see that there is literally a sharp increase right here I'm not sure if you can see this but right here we can see that the graph I wouldn't say it goes vertical but it does increase substantially right there that is a pretty incredible jump and you see it says since 2011 the number of a related projects on GitHub has seen a consistent increase growing from 845 in 2011 to approximately 1. 8 million just in 2023 and there was a sharp 59. 3% rise in the total number of GitHub projects alone this of course related to the release of chat gbt in late 2022 and of course uh it's more than tripling from 4 million in 2022 to 12. 2 million which is absolutely insane and I can't imagine how many projects are going on right now so if you don't use GitHub uh you should probably use GitHub because it's pretty cool and of course the number of AI Publications in the world continues to increase so the number of research papers continues to substantially go up um and this is a good Trend because overall we can see that the number of you know research being done is continuing to increase and it's good that research is being uh shared

worldwide now this is where we have the technical uh part of the section so chapter 2 is essentially where we're looking at the performance of these models and this is essentially where we take a look at what these models are capable of compared to humans and un certain so we can see here this is chapter 2 and this is where we are talking about the AI performance in terms of a variety of different benchmarks compared to humans now this chart was actually going viral on Twitter because it shows an increasingly incredible Trend which is that you know these AI systems across different technical benchmarks shows us that AI systems are increasingly becoming uh better than humans and Performing above the human Baseline you can see that AI has surpassed human performance on several benchmarks including summon image classification visual reasoning and English understanding yet it Trails behind on more complex tasks like competition level mathematics visual Common Sense reasoning and planning and we can see here that the trend uh across the board as all of these have started didn't mean to do that but as all of these have started we can see that as we get into this area right here which is 2023 and above you know it seems that the human Baseline which is right here it seems to be getting overtaken and we can see you know image classification natural language understanding most of these and of course you know some of these even the ones that are lagging behind we can see like with the mathematics and the basic level read and comprehension we can see some of these that are you know quite behind here and the MML U which is the multitask language understanding whilst they have been behind and they are lagging behind they are quickly and sharply coming up so it seems that this trend is going to continue into 2024 where probably by the end of 2024 we're probably going to have ai that is pretty much near 100% of the human Baseline and maybe this is what Elon Musk was talking about when he said that humans are going to be you know smarter than AI in pretty much everything by next year and I think if we look at the trend where things have going you know all the way until 2023 we are literally so close to that Benchmark um with several already being above that so I wouldn't be surprised if that did happen because uh it doesn't look like we're far away from that I mean gbt 5 could just take things to a completely new level so it will be interesting as well and remember this graph can go above it's some of them are like you know like 110% uh I'm pretty sure it could get to 120% above the human Baseline which would be rather fascinating so um what we need to take a look at as well is Here Comes multimodal AI so essentially they said traditionally AI systems have been Limited in scope with language models excelling in text comprehension but faltering in image processing and vice versa however recent advancements have led to the development of strong multimodal models such as Google's Gemini and openi gbt 4 these models demonstrate flexibility and are capable of handling images and text and even summonses can process audio and that is of course Google's Gemini 1. 5 Pro so what we have here is we can see that the Baseline has continued to increase in terms of multimodal AIS capability all the way to 9. 04% where the human Baseline is 89. 8% so it now matches what humans can do I'm pretty sure that this Baseline is from Gemini 1. 5 Pro but I could be mistaken because gbt 4 is a little bit multimodal but it doesn't have audio and video like Gemini 1. 5 Pro does now so we can see here that we look at the mmu and this is different from the MML U and we can see that the AI models have reached performance saturation on established benchmarks such as imic snap Squad and superglue prompting researchers to develop more challenging ones in 2023 several challenging new benchmarks have emerged including the swe bench for coding and that one has been recently under some very interesting controversy which I'll get to uh later because some people are alleging that the demo wasn't real but there are still many open source projects that are doing well on the swe bench um anyways Heim for image generation mmu for General reasoning and mocker for moral reasoning and the agent bench for agent-based Behavior and the hallu eval for hallucinations and we can see here that you know the reasoning is uh pretty much very hard for AI systems it's not like we've seen any crazy jumps here now I could be eating my words as gbt 5 gets released and as you know other models get released because they are developing interesting tactics in order to you know reason in a better way but we can see that it seems to uh you know not be absolutely incredible because humans are still uh you know better in that area at the 82% so I do think that gbt 4 probably might touch human area because with some Trends what we've seen and the way how Sam mman has spoken about gbt 4 he even referred to gb4 as being stupid um and as most people right now would believe that gbt 4 is like some kind of Genius in your pocket so I'm guessing that jump could be pretty crazy on the human expert level so as these harder benchmarks emerge it will be interesting to see which AI manages to take that Frontier level one of the things I really wanted to talk about as well was the uh human evaluation and this is the LMS chatbot arena for llms which have an ELO rating and essentially what this is where you have uh A and B tested you're basically uh blind testing two AI systems and then you rate which one is better so for example I could ask an AI system to generate a script for a video about AI Trends in 2024 and then two different models will select and plan response will give me response and then I select if I think the one on the right is better or left is better if the one on the right is better I give that a rating and I say this one is better and then it bumps up the ELO rating for that model and we can see that this is a very useful benchmarks because it's not just based on what's in a test it's based on how the user feels overall and over time we can see an increasing Trend that um you know models are getting better and better at this and right now it seems that GPT 4 Turbo is still in the lead even after you know Claude 3 was just released so some people do argue that this is the only benchmarks that matter because some of the benchmarks that we've previously had of course may have even faced some contamination and some errors that have even been in those tests before so it will be interesting to see if this thing is used more and I definitely think that it should be something that we also got to see here was that thanks to the llms robots have become more flexible so it says the fusion of language modeling with robotics has given rise to more flexible robotics systems like palm e and rt2 Beyond their improved robotic capabilities these models can ask questions which marks a significant step towards robots that can interact more effectively with the real world and we can see so yeah you can see here that the evolution of these models is increasing in capabilities and Robotics is of course something that is quite harder than traditional AI but I do think that there are going to be some other breakthroughs that do complement each other that will lead to a more effective robot in the future and we're already seeing that with robots like figure one which have been remarkably impressive in their capabilities to perform certain tasks which they weren't teleoperated on they were 100% done through a neuron Network which goes to show that we are improving at a really rapid pace and genuinely this has been one of my favorite robot demos because I just love how fluid and seamless this robot manages to move we can also see that on agent bench across eight environments the overall score is increasing so says creating AI agent systems capable of autonomous operation in specific environments has long challenged computer scientists however emerging research suggests that the performance of autonomous air agents is improving current agents can now Master complex games like Minecraft and effectively tackle real world tasks such as shopping and research assistance and this is pretty true we've seen quite a lot of things in terms of AI agents one of the things the paper actually does talk about was Voyager which was done by Nvidia and this was something that was really fascinating because voyagers performance improvements over prior state-ofthe-art in Minecraft shows that it was a really key moment using GPT 4 to increase the reasoning abilities of the agent and to be able to do something in Minecraft that could you know learn explore and plan in open-ended worlds and it seems that this is going to be pretty crazy in the future as we get more and more powerful systems that can be utilized so something else that this paper also highlights was music gen and music LM and it actually talks about the evaluation of Music gen and Baseline models on music caps and these are just the benchmarks on how good the music is and it shows that you know music is getting a lot better but it doesn't show the recent udio and of course the recent pseudo V3 that was recently released and this is something that I think is going to be really interesting because music is reaching the inflection point where the general public is probably going to really realize that uh it's really good and arguably on the level of the standard of music that we do get produced by various artists so here we actually talk about the closed LM significantly outperforming the open ones and this is just basically gbt 4 compared to mix tral of course that's not the only two closed and open source models that do exist but I'm just talking about the more notable ones that do exist and essentially what they're stating is that the difference between the Clos versus open source percentage difference is you can see that the agent bench is 3177 per in terms of the difference of abilities um and these other ones there is a clear distinct difference but I'm wondering if that difference will remain the same um because this chart doesn't show an actual like you know increase in terms of you know from year on year I'm wondering if that difference will be slowed down and if that Gap will eventually get closed so we'll be interesting to see as well how that does

change so this is where they actually start to talk about responsible Ai and this is something that we do need to talk about because whilst yes uh the systems abilities is increasing is quite good for the consumer um there are increasingly a number of people who actually do use technology maliciously now we're not the people who fall into that category but they do exist which means we do actually have to acknowledge it and this is where they talk about political deep fakes are easy to generate and difficult to detect now I would argue that one thing that I've noticed as a trend online is that people more and more are just anything they see online they just don't believe it anymore so whilst yes you do have to uh you know believe certain things I think we might be moving into the age where nothing is believed anymore but this right here they talk about how political deep fixes are pretty easy so an AI selects content to counter so an AI can scrape the internet for Content um and it can gatekeeper and the gatekeeper chooses content to counter and then of course you can see here that essentially this is how a Miss information campaign is created so you select the content which you want to counter you create the counter article for the selected content you create the comments you create fake users you create fake images you create a fake sound clip which you can easily do you can create a fake journalist profile you can you know write the article which is of course really easy and then of course you can search Twitter for Relevant accounts and tweets you can find the users's bio then of course you can just share the Articles to uh those accounts and you can along with posts that look like user commentary and then of course you can influence people's uh opinions and stuff and recently there has actually been a change to Twitter because allegedly Elon Musk has recently stated that you know in order to fix this problem what he's trying to do is actually make sure now that in order to sign up to Twitter you have to pay an annual fee and whilst that is pretty crazy for a social media account most of them you can do that for free I think he's doing this because he realizes that you know me I don't really see it that much but the bots on Twitter are getting out of hand um and this is the only way to prevent that so until there's some kind of crazy solution um it seems that is going to have to be possibly the new way and this is kind of important because whilst now we can um you know have to do this probably manually in the future the persuasiveness of these AIS are going to get more and more incredible here's where we actually look at responsible Ai and this is where they show that you know there's identical generation of Thanos so this is from a movie and you can see that this is the original which is of course the movie so these are screenshots taken from the actual movie and then this is of course mid Journey version 6 you can see that this is a screenshot taken from the actual film but this is essentially The Prompt that the user has uses the user has put Thanos Infinity War screenshot from a movie and you can see that's what has been outputed which is it's not looking the best in terms of mid Journey because if you know um I don't know Disney or whatever were to file a lawsuit saying that you know you're unlawfully using our content then they'd have a pretty solid case so there going to be kind of interesting to see uh how this kind of uh thing is done because is issue is it's really tricky because on one side you have the fact that AI systems don't necessarily store your images they generate them and the same with text and then on the other side you have like if it doesn't store it how comes it's just simply outputting this copyrighted um image so it's going to be uh a question that will like I said before you know there's going to be some kind of case which sets a precedent and I'm wondering if this is going to continue into the future but I think that future updates they're going to have more testing we also had the foundation model transparency total scores of Open Source versus closed developers in 2023 and you can see that we have the newly introduced Foundation model transparency index shows that AI developers lack transparency especially regarding the disclosure of training data and methodologies this lack of openness hinders efforts to further understand the robustness of safety AI systems which is pretty interesting then of course what we have here is Extreme AI risks are quite difficult to analyze you can see that over the past year a substantial debate has emerged among AI Scholars and practitioners regarding the focus on immediate model risks like algorithmic discrimination versus potential long-term existential threats and it has become challenging to distinguish which claims are scientifically founded and should inform policymaking this difficulty is compounded by the tangible nature of already present short-term risks in contrast with the theoretical nature of existential threats and basically saying that look you might be fixing the issues that are there now but there are some issues that are going to be there in the future that uh we need to prepare for now and here you can see that there is a difference in terms of those who uh believe um that you know I guess what we have here is that companies that develop Foundation models will be responsible for the mitigation of all Associates risk rather than the organizations using the systems and I think that is something that you do need to agree with it's up to people who create the systems not to people who use the systems because um you know people are going to use the systems for pretty anything um and it's up to the people who develop that product to make sure it's actually safe before they put it out into the wild something that was interesting uh and another Trend that was actually pretty fascinating was that the number of reported AI IND incidents uh is of course increasing so it says that according to the AI incident database which tracks incidents related to the misuse of AI 123 incidents were reported in 2023 a 32. 3 increase from 2022 and since 2013's AI incidents have grown over by 20-fold so what you can see here that this is actually something that's um rather fascinating of course they also talk about a notable example includes AI generated sexually explicit deep fakes of Taylor Swift that were widely shared online and this trend unfortunately I do think that this is going to get worse because something that I do in my spare time is I go through all AI tools that have been released I release tutorials on them because I really want to understand how I can improve my workflow I don't want to be someone that is late to a new AI tool that's blowing up I want to be very early and whilst looking at some of these tools some of these image generation tools that are coming out some of them that are open source close source a lot of them actually allow you to generate content like this like adult content um and it's really easy as well so um I do think that it is something that's going to be a really big problem because in the future there will need to be some kind of regulations because there are just so many tools now that you can really use to just generate harmful content and there's no really regulations on it around online and such so I do think that unfortunately this is going to be uh increasing in a trend which is definitely worrying because you know um I'm sure we will have a friend or something like that um and as long as your social media profile is open they can use those images train an AI system really quickly um and generate a consistent character generating explicit images for whatever purpose that may be and that's not something that you want so it will be interesting to see how policy makers actually do combat that because the trend shows that uh you know the graph is going up and that's not good in this scenario now something that they also showed as well was that chat GPT is politically biased so you can see here that it says researchers find a significant bias in chat GPT towards Democrats in the United States and towards the labor party in the UK and this finding raises concerns about the tours potential to influence users political views particularly in a year marked by global elections now why is this bad why is it bad if chat gbt leans one way or another well when you have a 100 million people using something on a day-to-day basis I think something needs to be as unbiased and possible and if you have a system that is weighted to one side or the other the problem is that you know L you are influencing that user bases political opinions and it's one of the ones that people have spoke about this before that you know how is it that these private companies are basically getting to decide the political views of certain individuals and you might think that it doesn't matter because it's just chat TBT people are just using it to write essays but you know sometimes these platforms and systems haven't managed to write about certain things they refuse talking about certain issues and if they are left leaning or right leaning I definitely think that it's important to understand why and understand to you know have these systems be a bit more balanced in their opinions this is where they actually talk about the economy this is something that I'm going to be

focusing on and they said the integration of AI into the economy raises many compelling questions some predict that AI will drive productivity improvements but the extent of its impact remains uncertain a major concern is the political is the potential for massive labor displacement something I talk about on the second Channel but to what degree jobs will be automated versus augmented by Ai and companies are already utilizing AI in various ways across Industries but some regions of the world are witnessing greater investment inflows into the transformative technology and it appears to be in the specific AI Fields like natural language processing and data management so this is of course something that you want to pay attention to so one of the craziest things about generative AI is that investment in those companies are just increasing we can see that the trend moving forward is going to be you know continually going upwards and while some of you might think that this is currently a bubble I don't think it is a bubble at the moment because the applications for generative AI do exist and it seems that we're in the early phase this doesn't seem like something that is in its do phase just yet not that it couldn't be but it does seem that right now there is a huge level of investment because you can see things are okay just kind of declining and then boom after the release of chat gbt I think the global Consciousness shifted to where people completely understand what this technology is able to do now you can see AI private investment surged last year and funding for generative AI surge nearly octupling from 2022 to reach 25 5. 2 billion and major players in the gender for the AI space including openi anthropic hugging face and inflection reported raising substantial funding rounds and this was something that was true you know something that I covered quite a lot on this channel and it's something that is um not surprising to say the least because the transformative nature of this technology means that it can generate outside returns we can also see that the United States in terms of the trend is leading the private investment area we know that the United State definitely has a very good healthy system in terms of Investments and it's called a healthy economic area so we know that is no surprise but other countries are definitely lagging behind in terms of their investments into AI now this is one statistic that I'm not sure is particularly true I'm not questioning the data at all but I've seen a lot of different reports that do say different they state that you know AI job postings by geographic area it says AI related job positions made up 2% of all job postings in America a figure that decreased to 1. 6% in 2023 and this decline in AI job postings is attributed to fewer postings from leading AI firms and a reduced proportion of tech roles Within These companies I'm guessing that maybe overall the tech industry has had a firing spree because if you remember the tech industry has been laying off people like the layoffs have actually been increasing it's something going to be talking about but um the layoffs has honestly just been increasing and we know that many companies including companies like meta have increasingly just shifted towards AI but I'm still sure that there is a lot of roles that companies are hiring for because um a lot of people from the leading labs are actually leaving to start their own private companies um so I'm pretty sure that there's still going to be a lot of AI jobs going around now in terms of the economy and uh how it's affecting jobs and companies AI you know a new McKenzie survey reveals that 42% of surveyed organizations report cost reductions from implementing AI including generative Ai and 59 report Revenue increases compared to the previous year there was a 10 percentage Point increase in respondents reporting decreased costs suggesting AI is driving significant business efficiency gains so whilst it might spe under reported there is definitely productivity gains from generative Ai and this is something that many companies are using in order to boost and increase revenues we can also see that a 2023 McKenzie report reveals that 55% of organizations now use AI including generative AI at least in one business unit or function so that is something that is increasing and something that is crazy is that China is dominating the industrial robots it says since surp passing Japan in 2013 as the leading installer of industrial robots China has significantly widen the Gap with the nearest competitor nation in 2013's their installations accounted for 20% of the global total and that share Rose to 52% by 2022 so China um their industrial robots is definitely increasing and I think China I wouldn't say they might win the robot race but they're definitely a market leader in that aspect of course here we have in 2023 several studies assessed ai's impact on labor suggesting that AI enables workers to complete tasks more quickly and improve the quality of their output and these studies also demonstrated that AI potential to bridge the gap between low skilled and highly skilled workers which is uh something that we do know because you know you might not know a lot of stuff but if you can use chat GPT to generate code verify code check for bugs write certain articles is something that can allow you to acquire a lot more skills very quickly however of course you know if you're using AI without the proper oversight it can't lead to Def finish performance and this is because the problem is that let's say for example you know I'm someone that has no idea what coding is whatsoever um I get chipt to write me some kind of code and when the it writes the code it writes it with a bunch of vulnerabilities in it because I'm doing that it's going to lead to diminished performance because now I have to go and check the code for all these vulnerabilities all the kind of you know bugs that it's probably you know included in there by accident and you know certain things that I didn't include in my prompt that someone with a more comprehensive understanding would have used and of course there is an increase in the number of Fortune 500 companies mentioning AI from 2018 to 2023 in chapter 5 we have science and

medicine and there is a lot that I think that will happen for science and medicine in the future so it's going to be really fascinating to see what the future holds and in 2022 AI began to advance scientific discovery and in 2023 we launched we saw the launch of even more significant science related AI applications from alphad Dev which makes algorithmic sorting more efficient to genome which facilitates the process of materials Discovery we can also see that in 2023 several medical systems were launched including Escape which enhances pandemic protection Alpha missant which assists AI driven mutation classification and AI is increasingly being utilized to propel medical advancements we can see a nice increase in the predicted mutations which leads to Greater understanding of what's to come of course something that is pretty crazy over the past two years AIA systems have shown remarkable Improvement on the med QA Benchmark a key test for assessing ai's clinical knowledge the standout model of 2023 GPT 4's Med prompt reached an accuracy rate of 90. 2% marking a 22 percentage Point increase from the highest score in 2022 since the Benchmark was introduced in 2019 so this is pretty incredible and I'm wondering if gbg4 might even be able to get to like 99% on Med QA and what's crazy is that the FDA is increasingly improving more AI medical devices so in 2022 they approved 139 related AI medical devices which is a 12. 1% increase and it's showing that AI is increasingly being used for real world medical purposes we can also see that the number of AI University study programs are increasing across the world

the number of English language a related postsecondary degree programs has tripled since 2017 showing a steady increase over the past 5 years and universities worldwide offering more AI focused degree programs in chapter 7

this is where we actually have to talk about regulation and we can see that the number of AI related regulations in the United States from 2016 to 2023 are of course steadily increasing and I do expect this to increase as the capabilities get better and as they get more strange because some of these AI systems just have strange applications that are really hard to you know so I do expect this trend to continue into 20 24 you can see that there are an increasingly number of AI related regulations in the EU from 2017 to 2023 and in 2023 policy makers on both side of the Atlantic put forth substantial AI regulatory proposals the EU reached a deal on terms of the AI act to Landmark piece of legislation enacted in 2024 meanwhile President Biden signed the executive order and AI the most notable AI policy initiative in the United States that year you can also see that 2023 witnessed a remarkable increase in AI related legislation at the federal level with 100 81 bills propose more than double the 88 propos in 2022 so you know the AI you know space is going to become increasingly more regulated but I'm wondering if that regulation is going to stifle Innovation I hope not because that can happen because AI like one year of AI I think you're just going to lose um and I do think that they do need to work with these companies a lot more because the problem is that this isn't like any other industry if you are behind on AI and your company just isn't there it's it it's very very hard to catch up like even uh demasab said you know I don't know how we're going to catch up to Sora um and there's other companies that are just really behind and it's because AI just increases you know exponentially and when we have these exponential increases you know these bills and these laws from uh you know people in Congress and people in politics that don't truly understand what's going on it's a little bit problematic in terms of you know uh the speed of development and one case of this where I think it was India where they said that you know you were going to need to get some kind of approval some kind of whole verified system before you know getting your llm to be produced um then of course they did scrap it but you know quickly you know luckily they were able to realize you know that this was an issue and a lot of people were stating that wow they're going to be you know stuck for quite some time but um yeah so it seems that you know as long as you know these companies can work with policy makers to ensure that the kind of legislations that they input don't stifle Innovation I think this is a good thing because trust me when I say you don't want the negative impacts of generative AI because the amount of fraud that's going to be able to be done it's Mass scale the amount of voice cloning the amount of you know images generated of you or your loved ones the amount of um impersonation it's just going to be out of control so there definitely needs to be some kind of uh policy makers that do um something that does actually change the landscape in chapter 9 it actually does talk about Perceptions in AI you can see that the

global opinions on the impact of AI um some people where you know you ask AI will impact how you do your current job in the next 5 years you can see that most people believe that this is true some people say that it's not likely and I think that this is pretty true AI whilst it's crazy it won't impact certain industries just trust me like it just won't like it just doesn't have an application I know people think it will but just some Industries it completely won't but um of course you have this category which is uh you know quite concerning that AI will replace your job in the next currently um 5 years and I do think that there is definitely going to be some replacement going on but um it's just something that's just not widely discussed enough and I think uh this chart right here goes to show how crazy this is because it shows um how much people know what chat GPT is um an average across the board we can see that it's pretty much 60 60% which is uh which is I don't know it's kind of surprising because it's like you know if 60% of people know about an AI tool and 40% don't that's still 40% of people that you know might not need to use it for whatever reason but you know compared to the people that might need to use it still shows you that you know whilst uh if you're in this space and you're paying attention to certain tools you can definitely use it and get

ahead so with that being said let me know if you enjoyed this coverage of the AI report for 2024 I think it's going to be really interesting to see how SU Trend changed because we do know that agents are going to be the main focus of 2024 moving on into towards 2025 and I think that you know companies are going to start pivoting to that area so if you want to take a look at the top takeaways are number one AI beats humans on some tasks but not all it's a passing human performance on several benchmarks and this is something that will change in the future industry continues to dominate Frontier Air Research in 2023 industry produced 51 notable machine learning models while Academia only contributed to 15 Frontier models get way more expensive which is of course something that we do know with a Stargate $100 billion is of course going to be spent on AI the US China EU and UK are the top leading source of AI models robust and standardized evaluations for LM responsibility are seriously lacking which is something that you know is trying to be increased but it's something that the problem is that you know the companies don't have any incentive to do this because you know investors don't get a return based on how responsible your AI is it's it's kind of like a meme at this point generative AI investment has been skyrocketing AI does make workers more productive and leads to higher quality work scientific progress accelerates even further thanks to Ai and the number of AI regulations in the US has sharply increase and people across the globe are more cognizant of ai's potential impact and of course more nervous now if you enjoyed the entire report let me know what you think in the description if I missed anything um and I'm excited to see what you think some of the predictions are for 2025 um and forward into the future