# The Man Who PREDICTED ChatGPT Has A New SHOCKING Prediction!

## Метаданные

- **Канал:** TheAIGRID
- **YouTube:** https://www.youtube.com/watch?v=GkgsvQ4qKeY
- **Дата:** 05.07.2024
- **Длительность:** 27:51
- **Просмотры:** 24,985

## Описание

Learn A.I With me - https://www.skool.com/postagiprepardness 
🐤 Follow Me on Twitter https://twitter.com/TheAiGrid
🌐 Checkout My website - https://theaigrid.com/

0:00 - Intro: Is hype around generative AI going too far? MIT roboticist Rodney Brooks' predictions
01:21 - Background on Rodney Brooks, AI & robotics pioneer since 1976
02:05 - Brooks: People overestimate generative AI capabilities, anthropomorphize it
03:10 - Brooks prefers practical robots (e.g. cart-like) vs humanoid for real-world use
04:07 - Hype around AI often neglects limitations; tech doesn't always grow exponentially
05:36 - Brooks: Alarms impressive but can't do everything; need control theory, math too
06:20 - Link to Brooks' AI/robotics predictions scorecard blog
07:14 - Startup fraud, overhyping risk in AI; "fake it till you make it" culture concerns
09:37 - Theranos fraud case as cautionary tale; critical thinking needed amid AI hype
10:27 - Concerns around some major AI company leadership
11:41 - Realistic view of AI startup scene; Brooks made only 3 prediction updates in 2023
13:24 - Brooks: Humanoid robots won't play significant role for 25+ years despite hype?
14:57 - 2018 prediction: next big AI breakthrough by 2023-2027 via published work
16:20 - Neuro-symbolic AI: neural nets + symbolic AI for robust AI; key future trend
17:41 - Generative AI/LLMs the clear next big AI thing as predicted; 2017 key paper
19:06 - Prediction 1
20:12 - Prediction 2
21:05 - Prediction 3
22:19 - Prediction 4
23:12 - Prediction 5
24:05 - Prediction 6

Links From Todays Video:
https://techcrunch.com/2024/06/29/mit-robotics-pioneer-rodney-brooks-thinks-people-are-vastly-overestimating-generative-ai/
https://rodneybrooks.com/predictions-scorecard-2024-january-01/

Welcome to my channel where i bring you the latest breakthroughs in AI. From deep learning to robotics, i cover it all. My videos offer valuable insights and perspectives that will expand your knowledge and understanding of this rapidly evolving field. Be sure to subscribe and stay updated on my latest videos.

Was there anything i missed?

(For Business Enquiries)  contact@theaigrid.com

#LLM #Largelanguagemodel #chatgpt
#AI
#ArtificialIntelligence
#MachineLearning
#DeepLearning
#NeuralNetworks
#Robotics
#DataScience

## Содержание

### [0:00](https://www.youtube.com/watch?v=GkgsvQ4qKeY) Intro: Is hype around generative AI going too far? MIT roboticist Rodney Brooks' predictions

so is the AI hype going too far that's what one MIT roboticist Pioneer Rodney books thinks that people are vastly overestimating generative AI this video is going to dive into someone who predicted the rise of L's language models and what he's predicting next about Ai and how it's going to shape our opinion of what's to come next and honestly this genuinely might surprise you so we can see here by this article on a tech crunch MIT roboticist Pioneer Rodney Brooks thinks people are vastly overestimating generative AI now this article is rather fascinating because it dives into the nature of his predictions he's someone that has been in the space since 1997 or in fact I do believe a little bit earlier than that and since then he actually has made predictions about the future of AI and he also keep the scorecard on his blog about how well he's doing and essentially the article States that when Rodney Brooks talks about Robotics and artificial intelligence you should listen currently the Panasonic professor of Robotics at emiritus at MIT he also co-founded three key companies including theth robotics iRobot and his current Endeavor robust. a he also ran the MIT computer science and AI laboratory for a decade starting

### [1:21](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=81s) Background on Rodney Brooks, AI & robotics pioneer since 1976

in 1997 basically he knows what he's talking about and he thinks maybe it's time to put the breakes on the screaming hype that is generative AI Brooks thinks it's impressive technology but maybe not as quite as capable as many are suggesting I'm not saying that llms are not important but we have to be careful with how we evaluate them and we're going to get into some of his predictions later but just take a look at what he says about the current state of AI he says that the trouble with generative AI is that while it's perfectly capable of performing a certain set of tasks it can't do everything a human can and humans tend to overestimate its capabilities when a human sees an AI system perform a tasks they immediately generalize it to things that are similar and make an estimate of competence of the AI system not just the performance on that but the competence around that and they're usually over

### [2:05](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=125s) Brooks: People overestimate generative AI capabilities, anthropomorphize it

optimistic because that they use that to model of a per certain performance of a person's performance on a certain task basically they think if this AI cons system can do this one thing well they think that it can do many other things well he also added that the problem is that generative AI is not human and not even humanlike and it's flawed to try and assign some human capabilities to it he says people see it as so able they even want to use applications for it that don't make sense he says Brooks offers his latest company robust. a warehouse robotic system an example of this someone suggested to him recently that it would be cool and efficient to tell his warehouse robots where to go by building an llm for his system in his estimation however this is not a reasonable use case for generative Ai and would actually slow things down instead it's much simpler to connect the robots to a stream of data coming from the warehouse management software now one thing that I do think that is really interesting is his position on humanoid robots he essentially thinks that what we are currently building in the common world with humanoid robots is quite wrong he

### [3:10](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=190s) Brooks prefers practical robots (e.g. cart-like) vs humanoid for real-world use

explains that it's also about robots and humans also working together so as company designed these robots for practical purposes related to Warehouse operations as opposed to building a human looking robot in this case it looks like a shopping cart with a handle he says so the form factor that we use is not humanoids walking around okay even though I have built and delivered more humanoids than anyone else okay these things look like shopping carts he said it's got a handlebar so if there's a problem with a robot the person can grab the handlebar and do what they wish with it after all these years Brooks has learned that it's about making the technology accessible and purpose-built I always try to make the technology easy for people to understand and therefore we can deploy it at scale basically he's stating that in his current company the form factor is not most effective for humanoids because you're not able to essentially use it and fix it in certain scenarios like he said if there's a problem with a robot a person can easily grab it and do

### [4:07](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=247s) Hype around AI often neglects limitations; tech doesn't always grow exponentially

what they wish with it and he does have a weird example here and there was a comment that kind of you know I guess you could say explains why this is somewhat of a weird comment but at the end of the day this is a very reputable source for someone that's been in the space for over two decades he said he adds that there's a mistaken belief mostly thanks to Mo's law that there will always be exponential growth when it comes to technology the idea that if chat TPT 4 is this good imagine what chat TPT 5 6 and 7 will be like he says that this is flawed logic and that Tech doesn't always grow exponentially in spite of M law he uses the iPod as an example for the first few iterations it did in fact double in storage size from 10 all the way to 160 GB if it had continued on that trajectory he figured out we would have an iPod with 160 terab by 2017 but of course we didn't the models being sold out in 2017 actually came with 256 GB or 160 GB because as he pointed out nobody actually needed more than that and I do think that whilst yes this is a point that you know Moors law doesn't always work in every single you know I guess you could say analysis of technology I don't think that this example is right you know forgive me if I am you know making a completely moronic statement here but I think the more you know applicable comparison would be processor speed because that's ESS what you know I guess you could say Computing power/ llms I guess that is essentially what you could compare it to now he says here that Brooks

### [5:36](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=336s) Brooks: Alarms impressive but can't do everything; need control theory, math too

acknowledges That llms Could at some point help with domestic robots where they could perform specific tasks especially with an aging population and not enough people to take care of them but even that he says could come with its own unique set of challenges people say oh the large language models are going to make robots do things they couldn't do but that's not the where the problem is being able to do stuff is about control theory and all other sorts of Hardcore math optimization now the most useful thing that I found about this certain post was not this entire post itself it was very insightful but the most important thing was the link to his blog post where he keeps a scorecard on his blog of how well he is doing so this is what I

### [6:20](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=380s) Link to Brooks' AI/robotics predictions scorecard blog

wanted to show you all as well because this actually shows you guys what he does believe about the future of AI on Robotics and where we're going to go in certain things you can already see his opinions on generative Ai and what he believes about humanoids but now we're going to take a look some of his predictions because whilst yes some of them have come you know to be true in the past I wonder if this is going to be the case once again where someone is underestimating the abilities of AI and the generative landscape that we're currently in so here's where we have his predictions on robotics Ai and machine learning he says it's worth reading this story the story he's referencing is one actually about Sam Alman and he says that with the increasingly number of CEOs in Silicon Valley ending up in jail for overhyping their businesses to the point of fraud many more walk that line some for multiple companies at the same time and from the story governance got a

### [7:14](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=434s) Startup fraud, overhyping risk in AI; "fake it till you make it" culture concerns

bit Loosey Goosey during the bubble vice president of financial strategy at Cruise Consulting a provider of financial services for startups lately Mr Jones said he has noticed Venture firms doing more due diligence on potential Investments but they probably shouldn't get a gold star for fulfilling their job description so basically with this article from The New York Times you can see here that he actually you know is referencing the startup fraud and how it's unraveling if you haven't been paying attention to the San Francisco startup scene and it's not just something that is you know unique to San Francisco there are many different startups that essentially it's I wouldn't say it's not their fault but I would say that startup culture breeds a situation where people always want to appear more successful than they are and in doing so they end up making ridiculous claims and in doing those ridiculous claims people will go to many attempts to have their egos you know satisfied and in some cases as far as jail so you can see basically the absence of controls at headspin is a part of an increasingly noticeable pattern at Silicon Valley startups that have run into trouble over the past decade investors in Tech startups were so eager to back hot companies that many overlooked Reckless Behavior and gave up key controls like board seats all in the service of fast growth and disruption then when the founders took the ethos of fake it till you make it too far investors were unaware or help helpless basically this entire article is stating that look there is this fake it until you make it attitude in cicon Valley people want to be the next big H big hot shot on the scene and in doing so you know this results in a remarkable level of startups that have you know been shown to be just simple frauds I mean Theos if you've ever heard about this story this was the biggest fraud ever you know there's like a 30-minute documentary on it I could go into all the details but long story short this person was pretending to be this you know genius level CEO who developed this revolutionary product that could take a prick of your blood and you'd be able to get all of your diagnosises within a matter of seconds and the thing was just a terrible machine that didn't even work and it basically you know allowed people to look okay and say take a step back for a minute let's actually analyze what on Earth happened here because we had millions of dollars of backing everyone saying that this is a good product millions of people vouching for her and

### [9:37](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=577s) Theranos fraud case as cautionary tale; critical thinking needed amid AI hype

now this woman is in jail and is convicted of Fraud and the similar thing happened with FTX but the point is that he's stating that look when things are getting really hypy we always need to have a rational voice in our heads because sometimes we can lose sight of what is actually happening at the ground level he also says that you can see here that this is what happens when everyone is entitled to their own alternate facts current icons young Brash woried CEOs are not immune to for forcing their own alternate facts upon eager investors and second people willing to set aside critical judgment from promised and magical Rosie fortune and basically this is the article here where he's actually referencing how Sam alund you know how he's been going through some trials and tribulations at the board seat or I guess you wouldn't really call this trials and tribulations

### [10:27](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=627s) Concerns around some major AI company leadership

but I guess you know how he's had a history of rebounding from leadership crises with the support of powerful allies after being fired by open eyes board for alleged dishonesty he quickly rallied support from influential figures like uh you know airbnb's CEO Brian chesky and Microsoft's CEO satian Adela and this pattern of resilience has marked his career since his first startup looped despite calling you know many people calling for his removal uh and the employees there at Y combinator where he was asked to resign for prioritizing personal product so basically they're stating that his ability to leverage a strong network has consistently helped him climb into more powerful roles however this leadership is remaining under scrutiny and investigation into recent turmoil at openi begs the question what is really going on now the reason I've included this information into this video is because it sets the tone that gives you guys a realistic view on how the market is because whilst yes you're on this channel and you're viewing this content you're kind of somewhat in bubble now it is good because I would say that the majority of people are not paying attention to AI technology and they usually just wait till it appears on the news or someone is showing off a magical new demo that is going viral but the

### [11:41](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=701s) Realistic view of AI startup scene; Brooks made only 3 prediction updates in 2023

point here is that we can see that if we actually take a fundamental view of what is going on there are a few things that do seem a bit strange about the current startup scene you can see here that he says I only made three comments in the table this year and only one of them is directly about a predicted Milestone being hit and as you guess they are all about generative Ai and large language models no question that 2023 was the year when these topics hit the general consciousness of the scientific cultural and political worlds I've officially been an AI researcher since 1976 and before that I was a high school and undergraduate hobbyist but this is the first year that I've heard politicians throughout the world say the words artificial intelligence and when they have said those words no one has been surprised and everyone knows what they are talking about and he says I had not been bothered to predict a Rosy future for human robots as when I made my predictions I had been working in that space for over 25 years and had built both research humanoids and thousands of humanoid robots that were deployed in these fact the extra difficult challenges requiring the fundamental research breakthroughs were clear to me there are plenty of naive entrepreneurs saying that work will be changed by humanoid robots within a handful of years they are wrong and I'm guessing that this statement is referring to many including Elon Musk and maybe Nvidia Jansen hang stating that look you know these humanoid robot are going to change the way work is going to be Elon Musk did say that there's going to be hundreds and thousands and even millions of humanid robots in you know in the 2030s 240s so I'm wondering if he's stating that since he's worked Hands-On you know and been an AI researcher since 1976 that you know his entire contribution to the field is more relevant than some of these quote unquote newer entrepreneurs so he says

### [13:24](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=804s) Brooks: Humanoid robots won't play significant role for 25+ years despite hype?

that my lack of predictions about humanoid robots were based on my expectations that they will not play any significant role for at least another 25 years that is an incredible prediction okay I'm going to State this again my lack of predictions about humanoid robots were based on my expectations that they will not play as any significant role for at least another 25 years so essentially he's stating that if we take today's current date which is 2024 that means that until 2050 we won't see humanoid robots in any significant roles and I don't think that's true just based on the things that we've seen but of course I could be completely wrong I could be someone that's just completely hyped up on Tech demos and you know maybe just all the demos that we've seen have been completely falsified because stuff like that does happen I mean I'm not at the companies I'm not there I'm not working behind the scenes but of course these things can't happen he says here are some of the humanoid robots that I and the teams that I've LED have built of course he shows some of these humanoids right here that you can see and what they've been able to do that are really interesting and really cool and of course robotics is much harder than you can think and yeah it's a pretty crazy statement but here's where we get onto his AI stuff he says that I had predicted that the next big thing in AI Beyond deep learning would show up no earlier than 2023 but certainly by 2027 and I also said in the table of predictions in January 2018 that for sure someone was already working on the next big thing and that papers were most likely already published about it I just

### [14:57](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=897s) 2018 prediction: next big AI breakthrough by 2023-2027 via published work

didn't know what it would be but I was quite sure that of the hundreds of thousands of AI projects that groups of people were already successful and working on one would turn out to be the next big thing that everyone just hopes is just around the corner I was right about both 2023 being when it might show up and that there were already papers about it before 2018 why was I successful in those predictions because it always happens that I just found the common thread in all the next big things in Ai and their time constants now here's where we gets into generative AI which is rather important because this is where we get to certain dat he says the next big thing generative Ai and large language models started to enter the general AI Consciousness last December then he talks about I talked a little bit about it you know in last year's prediction update I said that it was neither the Savior nor the destroyer of mankind as different camps have started to Proclaim right at the end of 2022 and that both sides should calm down I also said that perhaps the next big thing would be neuros symbolic artificial intelligence this is basically just you know combined ining the different levels and reasoning capabilities of multiple different AI systems into one that is able to kind of think like a human and I do believe that you're going to see this term neuros symbolic AI be more prominent in the next decade because this is more you know I guess you could say it more resembles what humans are in the sense that they're like an AGI system so

### [16:20](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=980s) Neuro-symbolic AI: neural nets + symbolic AI for robust AI; key future trend

neuros symbolic AI is essentially an approach in artificial intelligence that combines neural networks which are often used in deep learning with symbolic AI which focuses on High level human readable knowledge and reasoning this hybrid method aims to leverage the strengths of both paradigms to create more robust and versatile AI systems so basically you have you know the neuron networks which are deep learning which are excellent in pack and recognition you know learning from large data sets handling unstructured data um and they're particularly good at speech recognition and natural language processing but their weaknesses you know things like alms you know the Black Books nature are difficulty in incorporating explicit rules of knowledge and challenges in reasoning and understanding now symbolic AI is you know good at representing and manipulating explicit knowledge using symbols and rules excels in task in you know logical reasoning planning and understanding and essentially it's limited you know in handling unstructured data and learning from raw data which is you know pretty difficult to do so this is where neuros symbolic AI comes in combines the be of both world and we get you know really useful system so he says by March of 2023 it was clear that the next big thing had arrived in Ai and that it was large language models the key Innovation had been published before 2018 in fact 2017 so I'm going to claim victory on that particular prediction with the bracketed

### [17:41](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1061s) Generative AI/LLMs the clear next big AI thing as predicted; 2017 key paper

years okay maybe I was a little lucky and that paper had you know and that major paper for the next big thing had already been published by the beginning of 2018 okay so I was even luckier I think this might be sarcasm so you can see here that here's where we get into the actual predictions and he's already made some startling claims about the entire space but I do honestly understand what he's trying to say here so he says so we can see here you know in the table that these are some of his 2018 comments and then of course these are some of the you know updates so these are some of his 2018 predictions okay and you can see here that the emergence or generally agreed upon the next big thing in AI is beyond deep learning of course this was what he you know predicted and if you want to know you know his uh I guess you could say acronyms you can see that NE means it's not going to happen before that year so not earlier than this year then by this year means it's going to happen by that year and not in my lifetime means not before 2050 so the colors just mean that green mean you know these are accurate predictions that he made so these are correct the red ones were predictions that were too pessimistic meaning they happened earlier and the blue ones were you know too optimistic so we can go back and take a look at this so if we come back to here where he said emergence of the generally agreed next big thing in AI Beyond deep learning this was a correct predic in 2018 of no earlier than 2023 and at least by 2027 which is a pretty accurate date he says

### [19:06](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1146s) Prediction 1

whatever this turns out to be it'll be something that someone is already working on and there are already published papers about it there will be claims on this title earlier than 2023 but none of them will pan out he said it definitely showed up in 2023 it was in the public mind in December 2022 but it was not you know yet that the big thing you know became during 2023 a year ago I thought that it perhaps would be neuros symbolic AI but it is clearly llms and chat gbt and its cousins and as I predicted in 2018 something was already being worked on as the attention is all you need paper of course here he talks about the press and researchers generally mature between the so-called touring test and asimov's three laws and valid measures of progress in Ai and machine learning and he said that this would be not earlier than 2022 and of course you can see here he was way too optimistic about this that the touring test was missing from all the breathless press coverage of chat GPT and their friends in 2022 and their performance though not consistent pushes way past the old comparison now here's where we get into some humanoid robot predictions he says that the dexterous robot hands generally available are not going to be you know available essentially no earlier than 2030 and by 2040 he hopes

### [20:12](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1212s) Prediction 2

he says despite some impressive lab demonstrations we have not actually seen any Improvement in widely deployed robotic hands or end defectors in the last 40 years so he believes that this is not going to happen by 2030 and will happen by 2040 or at least he hopes also what what's here and this is a pretty crazy one cuz we're about to see you know in the next couple of years we're truly about to see here he says a robot that can navigate around just about any United States home with its steps its clutter its narrow Pathways between Furniture examples he said a lb a lab demo for this is not going to come before 2026 an expensive product that you'll be able to buy is not going to become before 2030 and an affordable product that you're able going to be having in your home is no earlier than 2035 of course what is easier for humans is very hard for robots so this

### [21:05](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1265s) Prediction 3

is something that we still have I think about a year and a half to do I mean one of the companies that I think is either going to do this is probably you know either Tesla or you know figure robot is going to do this I think that you know one of those companies could do this navigate around a us home maybe they're going to show us a different demo but it will be interesting to see what happens there and of course he says you know a robot that can provide physical assist to the elderly over multiple tasks for example getting into and out of bed washing SL using the toilet rather than just you know point to a solution this is not going to happen before 2028 he says there may be Point solution robots before that but soon the houses of the elderly will be cluttered with Too Many Robots so an interesting prediction there that you know soon the elderly you know they're going to be having So Many Robots and I do see that as being an application because you know robots that move slowly and are strong and can help someone around the house that is certainly you know a real world use application and he says here a robot that can carry out the last 10 yards of delivery getting from a vehicle into a house and putting the package onside the front door the lab demo he says it's going to be no earlier than 2025 and deployed systems you know this is actually interesting so he says deployed systems could actually be here by 2028

### [22:19](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1339s) Prediction 4

so he says that you know in the near future we could have a situation where we get you know robots that are from Amazon that are basically rolling around the neighborhoods and after they get on the truck they essentially go over and they deliver the package and this is not going to happen before 2028 but that is the time frame of where it could happen and I think that that's a rather interesting prediction because we're seeing that robots you know are already doing similar things like this if you seen things like agility robotics what they've been able to do it doesn't seem too incredible of course he's talking about you know a conversational agent that carries a long-term context and does not fall into easily recognizable patterns of course this is already there you know he's saying deployed systems is going to be 2025 uh and it's not you know hard to get you know chat GPT to connected to speakers and microphones but of course it doesn't have any updatable memory part apart from its token buffer which is what just been said and of course long-term memory has been you know it's going to be coming

### [23:12](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1392s) Prediction 5

and now he says here an AI system with ongoing existence not before 2030 you know no day is the repeat of another day so an AI system with an ongoing existence this is pretty crazy because I think this is actually really hard to achieve and this is something that I haven't really heard about or seen any research papers about um and essentially here no day is as a repeat of this another day as it is currently for all AI systems so you know how currently when you have chat GPT and you ask it exactly what's going on and it's like oh this date is you know the 23rd of December 2023 that's the current date so that's you know going to be something that's really interesting because I'm wondering if AI systems going to be like wow how you doing today you know we got this new president what's going on yada y but of course he's going to have an entire blog post to explain this and here's where we get into some similar predictions like Lun and the likes of Gary Marcus a robot that seems as intelligent and as attentive and as faithful as a dog this is so much harder

### [24:05](https://www.youtube.com/watch?v=GkgsvQ4qKeY&t=1445s) Prediction 6

than people imagine many think we are already there I say we are not all there and he says that this is not going to be you know as earlier than 2048 which is very far away like 2048 is 24 years from now and if we look at life you know 24 years ago you know technology has improved so much since then and of course he says here that you know this is never going to happen in his lifetime so not until 2050 um a robot that has any real idea about its own existence or the existence of humans in a way that is 6-year-old understands humans I'm guessing that this is not like how an llm understands humans with the sense that you know it's just got a textual based understanding of what humans are and what they do but like you know a six-year-old's understanding of humans and their place in the world and how they interact and what humans can actually do he says not in his lifetime so I mean one thing that I will say is that you know this is a prediction and predictions about the future are extraordinarily hard to do and these predictions are extraordinarily hard because the future is very hard to predict just the nature that it's a future you there are essentially unknown unknowns and if there is an unknown unknowns those unknown unknowns can change the course of what might happen so these predictions are extraordinarily hard and I know some people might say okay this guy's going to get proven wrong I mean it's going to be interesting to say because this guy has Decades of experience in the field he predicted you know chat gbt and the rise of LL LMS and he's got you know so much experience in humanoid robotics that I would argue it's pretty hard to find someone who's as well versed as him so the point here is that do you guys think that this is a prediction that reframes your mindset on where we're going to be with certain predictions and it's also important to note that he doesn't just say that look you know AI is dead nothing's coming yada y he stes that look while these tools are you know useful some of these things are going to come soon and happen you know in a pretty long lifetime of course there can be breakthroughs that can accelerate these you know I guess you could say uh predictions but it's also kind of difficult to do that without the proprietary information one thing that I would like to know is what is really going on in these labs and if he knows exactly what's going on in these Labs because research is no longer being published and I think this can kind of change the kind of nature of what kind of predictions people are going to make essentially what I'm stating here is that you know prior to 2018 2019 2020 all of the research that was done by all of these labs were essentially published and it was shared and everyone was advancing at the same Pace but now that you know we've got such this terminal race condition where all these companies are trying to compete we've got like all of these researchers that are you know having breakthroughs but they're not sharing the breakthroughs that they're making which means that currently we have a system where it's hard to make predictions because the breakthroughs that are being made internally we only get shown when we're shown a demo so we won't know what's truly capable until they kind of show us exactly what's there I'm guessing that he probably likely has fact this in considering he's working in such an advanced field but it is something that I do think has fundamentally changed this which is why I think in the future now it's going to be even harder to predict what is going to happen because like I said with gbd4 they came out and shocked us and of course with Sora so it's going to be interesting to see what what kind of things uh we're going to see here so will be interesting to see if some of these predictions come true and hopefully you guys enjoyed this video let me know if you think these predictions are going to be coming true because of course some of them do you know are a bit cont rting with you know Rayos world's Singularity but I think um some of them are pretty reasonable like a robot that can navigate around just about any United States home you know a lab demo by 2026 that is still pretty early okay and he's saying that between 2026 and 20130 that's a pretty reasonable deadline so this isn't something where he's saying it's never going to happen I just think that this is a document worth reading

---
*Источник: https://ekstraktznaniy.ru/video/14204*