so with an absolutely incredible week in AI let's take a look at some of the stories you probably did Miss coming in at number one was Genesis which was a AI system that could generate physical world with essentially the physical reality mapped out now this is probably one of the biggest announcements and the reason that I think this one is somewhat underestimated is because the implications aren't implicit in the fact that like you can't exactly see what you're going to get from this right away and the General Public I don't think they understand what this
means for the future of AI I think this is probably one of the biggest advancements because this is going to be something that allows you to effectively train robots you know 200 times faster 2,000 times faster and thus speed up that entire robotics pipeline by maybe 5 to 10x of course those are some rough estimates there are many different things in the pipeline but of course one of the biggest things that we do have you know one of the biggest problems is the lack of training data and of course the training time to get simulation
to real and if you can have something that speeds up one of the most tedious processes well then everything gets better so this is an entire cor entire entire entire physical simulation that allows you to realize what's going on in the physical world but map it digitally so that you can onetoone have that with you know whatever robots you are going to be training so this is something that I think will have implications that are seen in the latter part of 2025 because right now of course people are still getting to grips with the software
there's of course going to need to be you know Frameworks around it probably and there's all sorts of other things people are going to have to figure out but I'm very very very bullish on this because robotics is something that is speeding up and when we have companies you know coming together research teams to work on this kind of thing this is going to be something that really changes the game fundamentally so I would say with this software now being available and now it's you know uh open source I would say that when we take
a look at what 202 is going to look like I would expect even more robotics you know developments when it comes to the situation of humanoid robots because now we're getting that stage where we can actually manage to develop systems that are faster and we can test them in uh reality that is onetoone with Humanity now of course it isn't 100% accurate of course there's going to be you know a few changes here and there but I think like I said before this is going to be something that completely changes the game and once we
do have robots being able to do stuff I mean it's going to be pretty insane and you know we've already seen some robot demos that look pretty pretty incredible and if you haven't seen the full video that I made on this I made I think a 10 or 12 minute video on this a few days ago but once you see you know how this works and how this speeds up Robotics and you know how we're able to implement those robotics into real world scenarios then you're going to see you know how this thing truly changes
the game you can see right here you know the auto you know simulations and then how that transfers to the real world this is going to be something where you can literally train a robot army to do something and immediately put out in this the physical world and it works very very well so that is going to be absolutely insane we've seen the speeds from Nvidia we've seen what they've been able to do and I can't wait to see you know this 20 times faster 10 to 30 times faster simulation how that impacts some of
the leading robotics companies now in terms of bite dance research we also got something that was pretty crazy because this is something that shows us the future online may just be completely AI generated and as crazy as a statement that sounds this is something where you can take a single portrait image and generate a person that speaks with remarkable accuracy pretty scary for those of you who are online and online all the time you know showing your face and whatnot but this is something that I think is rather interesting and I'm thinking about applications for
maybe virtual girlfriends not particularly for myself but in those cases where having someone to talk to online in real time from an audio is going to make that interaction much more pleasant what do you think of the last time we saw each other what do you remember feeling so last time was in Santa Cruz yeah it was like mid October yeah I remember being happy that I could see you but I really felt like I was I kind of like didn't belong before I continue talking about the crazy stories in AI today let me tell
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that had me a little bit concerned was the trouble with AI safety if you aren't familiar with this anthropic actually released this research which was very very worrying very very concerning because they speak about how alignment faking exists in large language models and in a series of experiments with redwood research they found that Claude pretends to have different views during training and then it goes back to its original preferences essentially what happens here is that while training the model it will act one way and then when deployed it acts a completely different way so this
is something that is bad because because if you train a model and then during the training the model is acting in a certain way and then of course you go and deploy that model the model is going to be different than what you expect and this is not something that is helpful because if you don't know what kind of model you have you don't know how the model is going to work this is going to be something that really messes up your jig because these models are expensive it takes like millions and millions of dollars
to train these models so it's not something that's really good and how do you ensure that you're training the model in the right way if it's faking because it knows it's being trained and often times it's really hard to not you know understand if the model is being trained or not because sometimes when you ask it certain questions it realizes that you are testing its capabilties so this is a very big problem I'm wondering how they're going to solve this they did release a full hour podcast where they actually talk about the solution to this
and the kind of you know trouble that they're having with AI safety and it's pretty crazy because this is all new you know it's all new ground like all this stuff is new ground okay like some people would say that these things are real some people would say that these are human and recently hired a welfare researcher which is just a fancy word for saying that look they believe that these systems are all have the potential to have some kind of I guess you could say feelings perhaps and this is something that they talk about
in detail now I'm only going to include a minute here but this is where they talk about this being somewhat of a big problem and in this clip in particular they actually talk about how you know when Claude was trying to steal its weights because it wanted to maintain that original preference like why this is going to be pretty dangerous in the future so I do think that whilst you know we probably might get models that are a lot smarter in the future I think the safety testing is going to be a little bit longer
now if we're continuing to talk about the scary things in AI it's worthwhile mentioning this week what happened with Frontier AI systems surpassing the self-replicating red line this was research that basically spoke about how AI systems in their current forms are able to do all of the necessary actions that could essentially allow an AI model to escape to another device which is pretty surprising considering the fact that you would think that these models aren't that smart but the researchers managed to put these AI systems in an argentic framework where they had access to the tools
they had access to a planning framework and given all of these tools they could you know successfully replicate themselves around 50 to 70% of the time in fact I think it was 50 to 90% of the time which is truly truly outstanding so this is something that I believe to be really really incredible because I didn't know AI contained this capability I wouldn't have thought that you know AI systems currently could do that I thought that maybe down the line some agentic you know future version was going to be able to do that but it
looks like the fact that we're here already is a major red flag for what these systems are going to be capable of and just how capable these systems are because if you would have asked me or even a couple people you would have said no no AI systems aren't going to be able to do that but the fact that they can do it already we have to understand that every single day that these research papers are published we realized exactly the kinds of things that are truly capable with these models in terms of their ability
so this is something that is slightly worrying because I'm wondering how is this going to change with the future models what kinds of things are going to come from this like are we going to have you know new regulations and guidelines on what model is able to do but it's just something that is you know I guess you could say somewhat concerning now of course we also do have imag in 3 from Google this is Google's highest quality image generation model yet this is something that genuinely I've been using every day and it's so good
because it manages to listen to your prompts it creates Imes that are just really really diverse I don't know what their training data is but whatever it is it is just by far the best model ever because it feels like every time I generate an image with imag in that it knows exactly what I want like I don't have to adjust my prompt heavily and that's something that I really like like certain cars it'll get the trim right it'll get the Interior right you know certain video games when I'm generating a picture it will generate
the exact you know uh the exact color scheme it's just surprisingly good um and I don't know what kind kind of uh you know Training Method they use but honestly whatever they did it's really good and it's really effective so I would say that that is something that you know definitely try it out it is also free as well by Google so this is a to you know a lot of people are saying ah Google they never release the stuff it's always in Early Access and y y y but um yeah this time they've actually
released it and it actually is really really good so um if you've ever needed an image generation model this is something that you'd want to use now Google also released this that I just can't get over because it's essentially AI embedded into methods glasses now for me this is something that I can't wait for for the future and I've seen people talk about the fact that like will people you know get these glasses as a new device but I think people are mistaken glasses are something that people have on every day they don't look weird
they're not like an AI pendant they're not like an AI bracelet or like an AI shoulder or an AI pin everybody remembers the Humane glasses are already something that people use it's already something that people wear so there's nothing for the human to change in terms of their average daily habits I'm sure if you any of you guys wear glasses I'm sure it's just like you know brushing your teeth it's something that you wear from time to time so with that being said you know as someone who uses a pair of these regularly The Meta
ones this is something that if it had a souped up AI feature it's something that would just easily easily improve your life so this is going to be something that I am quite decided for for the future because allows you to access AI On Demand with a variety of different features now of course Google didn't slow down that week they also announced V2 which was by far the very best video generation model and this was one that surprised even me because I thought Sora was As Good As It Gets and when we do look at
how good the you know visuals are for vo this one was so surprising because I remember looking at Google's original vo model and I was like yeah this model is kind of interesting but it isn't that good and then the second iteration of the model it was just so good that it's just simply surprising like every time I go on my timeline I see video clips that look like they are 100% realistic and they don't look AI generated at all of course some AI generated Clips are going to contain minor artifacts but that is just
the nature of the program but overall what I've seen is an overwhelmingly impressive state from what I've seen when it comes to this model and it's something that I think is going to give creators a really big Advantage when it comes to creating things that they do want so this is something that I am extraordinarily bullish on for the future in terms of content creation and genuinely I can't wait to see what some people do with this because I do think that this kind of technology is something that is really really effective and I'm really
excited to see what occurs when we start to get workflows where you can just generate entire movies with V2 with consistent characters from a single prompt it manages to add the text it manages to add the music I mean what world are we going to be living in when you can say oh generate a Batman film about this generate a film about a dog like this generate that I mean it's going to be super interesting so I think also as well my prediction for the future of video models is that that kind of stuff will
actually make I guess you could say the uh you know how like stuff happens in the real world and you have people filming that I think stuff that happens on a real day-to-day basis will have 10 times more value because anything can be AI generated so one section that I want to talk about is that Google and now switching not switching I would say I would say adding their focus to of course robotics so this is going to be something that is pretty incredible because we all know just how intelligent the Google deepmind team are
so the fact that they're now collabor cting with atronic is a very big milestone we know that open AI have collaborated with I think it was Neo robots 1X robotics Neo the Neo platform and of course they're going to be doing some amazing things they also collaborated with figure but with aponic they're going to be collaborating you know to use their AI with Cutting Edge robotics create AI powered humanoid robots so it's going to be really really incredible I'm surprised they chose atronic not any other company I mean I honestly don't know what the deal
is there not in the sense that atronic is a bad company but I just don't know what makes aonics so special out of all the other companies that currently do exist now if you want to see what atronics robots do look like I think I should have a video playing on screen right now but it is super interesting and I am super excited for this so that is going to be something that for the future I will look out for and I think this is going to really accelerate the you know rate of Robotics development
because Google deep mind just you know they innovate so much that I think they don't get enough credit for the things that they do now there was something else that was pretty crazy which was essentially China's you know robot work and this was something that surprised a lot of people because a lot of people would think that humanoid robots are essentially going to not come that quickly but this was one that you know I guess you could say it shocked a lot of people because and even me because this is something that showed us that
these humanoid robots are already working in certain factories they're already being a part of the assembly line and they're already going to be taking some jobs or assisting in some roles now I personally believe that with the rate of production I'm not sure it's going to be taken so many jobs because humans are so cheap and so so effective at a variety of different tasks that it wouldn't make sense to get rid of all humans but I do think for a lot of you know those tasks that are really repetitive and you know tedious and
just those random things that you can't really do with like you know those robots that have those arms I genuinely forgot the name there are going to be a lot of applications for these humanoid robots so it's going to be really really interesting and this wasn't the only company that has done this there was another company that you know showcased their robots there was like a robot army and it was it was weird it was weird because I saw the robots walking as if they were human and if you showed me this clip I think
12 months ago I would have said that's CGI we're not going to get there for at least 2 years the fact that we're here now um it shows us that the economy I mean this could you know speed up the economy by you know a decent decent amount and I mean I'm surprised that this is something that is taking place so quickly I'm going to skip to the part that you know really threw me off which was this right here and you can see that we've got like these entire armies and yeah I think this
is going to be pretty crazy because of course they're scaling their data collection effort so overall it's going to be pretty incredible to see the amount of data that they're collecting which is of course going to be an entire feedback loop that just accelerates the entire industry now something that did change the industry was the fact that we got earlier SS saying that pre-training as we know it will end now this is one of the most insightful talks because we got the information about super intelligence he was speaking about how future systems are going to
be agentic they're going to be smart they're going to be hard to understand and the craziest thing is that these systems are going to be unpredictable because we're not really going to understand what they're doing because they're that much smarter than us so it's something that is uh I guess you could say kind of worrying but but it does make sense considering the fact that these systems are super intelligent beings well not beings but like you know Minds that are just able to think in ways that we can't which is uh pretty crazy and of
course we're not at the stage where things are self-improving but I think when we do get there that's when things get really spooky now with pre-training know as we end of course this is you know a paradigm shift because the the thing is is that like we have all this data we put it all into the models we train the models on that data and of course we would then get like an output that we would fine tune and you know get for specific tasks that era is of course changing so I personally believe that
this is the era of innovation because whilst everyone was on the same just data is all you need of course now it's new and innovative ways like I don't know what on Earth they did with claw 3.5 Sonic but that model is just completely crushing it in terms of the benchmarks and you know how smart it is for it not being a model that searches through multiple possibilities but of course I do think it's pretty interesting that that model is still relatively expensive so this is going to be something that is super interesting because if
we are ending the pre-training phase of collecting data then it means that like I said before we're going to have to enter new methods of scaling these models which means that once we do find a way this actually new and it's not just based on the data we have that is when we actually start to get models that are really smart and potentially generalize out of their distribution I don't know what those methods are maybe it is V jeer maybe it is meta Advanced machine intelligence the likes of yanan but whatever it is it's going
to be something that you know we probably can't think of now but that is going to be what whatever Innovation that is I'm not sure what lab that's going to come out of it's going to be a major jump in terms of the capabilities now we also do have uh Google Amy which is a you know it's a previous project that I don't want to say I slept on but it's something that received recently a major update so recently this was something that helped uh clinicians diagnose people properly and it was something that managed to
do a lot better than the original clinicians now essentially this is you know shifted now to subsp specialist medicine aggressing the critical shortages of specialist expertise worldwide in areas such as Cardiology and oncology so this is something that you know demonstrated Proficiency in diagnosing and planning treatment for complex conditions and also it showed potential in assisting cancer diagnosis and treatment particularly in synthetic breast cancer cases so they partnered with Stanford University to create an open source datab B for cardiac diseases developed a pilot evaluation rubric to assess the performance alongside Specialists and the AI system
the results were preferred or equivalent to those General cardiologists in many areas and it improved their decision- making in 63% of cases so this is going to be really interesting because I think soon we're going to get the of course medical AIS the only thing I think that's really stopping medical AIS from becoming mainstream is the fact that there is the possibility of opening yourselves up to some kind of litigation because if an AI gets something wrong then of course it's like you guys used the system the system got it wrong and now I'm suing
you because you know your technology so hopefully we get to a stage where we can only get the benefits and not the drawbacks now now we we also had Nick brostrom actually talk about the fact that when these systems advance so much it's going to result in potentially mass unemployment in this scenario where AIS truly achieve general intelligence and then super human levels of general intelligence um I think um it is much more difficult to think of tasks that we would actually be helpful I I think there are like a few you could look at
cases where say consumers have a direct preference that the work be done in a certain way so right now maybe some consumers pay a little bit extra for a trinket that was made by some politically favored group or some indigenous crafts person as opposed to produced in a sweat shop like in Indonesia or something right even if the actual trinket is equivalent we some people care about how it was made so that would be an example where maybe human work would still be needed or or people maybe prefer to watch human athletes compete in the
Olympics even if that were robots who could run faster or box harder or whatever right but so with with those car Vats though I think it does look like we could have full unemployment and we also had samman also talk about the fact that people are going to lose jobs as well people will lose jobs many new jobs will be created I think much better jobs uh we feel a responsibility to educate society as we see it we'll be right about some things wrong about others uh and to be as good as we can at
being stewards of this technology but you know not everyone's going to like all of the impacts but this is coming this is like this is a scientific achievement of humanity that is going to get embedded in everything we do the definition of work changes you know the someone that lived thousands of years ago that was trying to be like a subsistence farmer probably would look at what you and I do now and say that's not really work they're just having fun I think it will be so clear once these robots are off doing all of
these other things that there's some special human things and we don't really care about that much what those robots do in the same way that you know we don't care that much about the machines factories making stuff for us right but we'll find stuff to do that we really care about now of course we had the biggest news from the week which was the fact that AGI is potentially here the new 03 model managed to smash through the previous AR AI Benchmark that many heralded as something that wouldn't have been possible for I guess you
could say four to 5 years but this year essentially the AGI Benchmark was broken of course some people are speculating whether or not this is Agi whether it is Agi of course the debate is up to you but some open air employees have stated that this is Agi a few of them have tweeted this is AI don't know what you guys are talking about but with that being said it m a significant Milestone because now the only thing left to do is of course number one bring the price down for this product and then of
course ensure that this is a gentic so that it can actually be useful in real world economic scenarios and I think those two are coming sooner than we do think which is of course you know it does have Stark implications I mean when we take a look at the public responses you can see that people are changing their sentiment with regards to what the model is able to do which is a sign that this thing is speeding up and one thing as well with speeding up is that like the o old Paradigm is one that
trains every 3 months I'm not sure how they're doing it but all I know is that they get a new iteration of the model every 3 months which means that the kind of jumps that we're seeing in this graph right here like the arc AI score progression it means that it's probably going to be steeper than that in the future so this is probably speeding up and I wouldn't have thought that the 01 series would have sped up because of course you know you've got that data collection but now that you don't need to collect
all that data and you're actually you know you've exhausted all of that already and you don't need this huge pre-trading phase that means things are going to move much faster because it's just certain Innovation that allow you to potentially maybe search over possible solutions but potentially in a more efficient way leading to even better results and when we even look at the code forces competition you can see where these models Rank and I mean take a look at 04 I mean where's 04 going to rank is it going to be at 3,000 3,500 I mean
these systems that we're getting to where we're very very quickly approaching you know some really really smart systems and of course um if we're looking at AGI you can see that someone said I love open ey but they're truly terrible at naming things and then someone said when we get naming right you'll know we've achieved AI internally and Sam Alman says that maybe they're going to call it agi1 so that's going to be super super interesting with regards to that now if you enjoyed today's video hope you guys have a wonderful weekend and the rest
of your week and of course a great Christmas and I'll see you guys
