does AI mean I need to start having a code phrase with my parents now while AI can make it worse also AI can make uh finding it better I'm pretty sure Deep dive is just going to be a novelty for giving us New Perspectives on how our content could be presented I think it was really interesting what are the eics of launching something like the real-time API we have uh more people and more and more people using text and image model so are we actually in more Danger All That and More on today's episode of mixture of experts it's mixture of experts again I'm Tim Hong and we're joined as we are every Friday by a world-class panel of Engineers product leaders and scientists to hash out the week's news in AI on this week we've got three panelists Marina danki is a senior research scientist fogner Santana is Staff research scientist Master inventor on the responsible Tech Team and Natalie baralo is a senior research scientist and master [Music] inventor so we're going to start the episode like we usually do with a round the horn question if you're joining us for the very first time this is just a quick fire question panelists say yes or no and it kind of teas us up for the first segment and that question is is fishing going to be a bigger problem smaller problem or pretty much the same in 2027 uh Marina we'll start with you pretty much the say maybe slightly worse okay great uh Natalie it will go down okay great and Vagner I think we'll be the same okay well I ask because uh I want to wish everybody who's listening and the panelists a very happy cyber security Awareness Month um first declared in 20 2004 by Congress cyber security awareness month is a month where the public and private sector work together to raise public awareness about the importance of cyber security um I've normally thought about October as my birthday but um I will also be celebrating cyber security awareness month this month um and as part of that IBM released a report earlier this week that focuses on assessing the cloud threat landscape and I think one of the most interesting things about it is that fishing which is the situation where a hacker impersonates someone or otherwise kind of um talks their way in to get access uh continues to be the major issue in Cloud security so about 33% of incidents are being accounted for by this particular attack vector um and I really am sort of interested in that right in a world where you know AI is advancing and the tech is becoming so Advanced um in some ways like our security problems are still the same it's like someone being called up and you know the CEO like someone pretending to be the CEO says give me a password and you give them a password and I guess marina maybe I'll turn to you first is I'm really curious like it seems like to me AI is g to make this problem a lot worse right like suddenly you can simulate people's voices you can um you know create very believable chat transcript trips with people um should we be worried about whether or not you know like maybe actually in 2027 this is going to be a lot a lot worse um I don't I mean and I know Natalie's a more of an expert in this particular area than I am but while AI can make it worse also AI can make uh finding it better so if you think about how much your spam filters and email have improved and how much any of these kind of other detectors have improved it kind of ends up being a cat and mouse back and forth the same technology that makes it worse also makes it easier to catch so it has to for me maybe more to do with um again people's expectations and adoptions of the right tools than the fact that the technolog is going to completely wrecked because even here we've seen people get really excited about Ai and then very closely following after that wave get very oh wait now I'm kind of cynical now I'm kind of concerned I'm I'm trying to understand what you know fakes are and everything like that so I I do think that's why my initial take was it's going to be maybe kind of similar but I I think Natalie can definitely speak to this so I was reading the report and it said that 33% of the attacks actually came from that type of uh kind of human in the loop uh situation so definitely the human is the weakest point one of the weakest points that we have with the introduction of agents for example I am very hopeful that we can kind of create sandboxes to verify where things are going so I think it's going to go down not because fishing attempts are going down but because we are going to be able to add additional extra items around the problem to prevent so even if the human because we are as you were saying team very much susceptible to kind of uh being push one way or the other depending on how well the message is uh is tuned for us even at that point we I think we are going to have agents that can protect us around and I'm I'm very hopeful actually that this uh the technology that we're building is going to help us reduce the attacks well not the attacks the the actual outcome of the attempt to to attack the systems that's right yeah it's almost kind of this very interesting question which is I agree with you it feels like we're going to have agents that will be like hey Tim that's like not actually your Mom calling or like hey Tim that's not actually your brother calling um and uh and it almost feels like it's a question of whether or not sort of like the attack or the defense will have the advantage and I guess you know I think your argument is kind of like actually the defense May has the advantage over time Vagner do you want to jump in I know you were kind of one of the people that said ah pretty much the same like we'll be talking about this in three years and it'll still be 33% of incidents are accounted for by fishing yeah and and my my take on that is that uh I think that it will be the same because it is all based on human behavior and the other day I received a fishing mail so it is if people are sending is because sometimes it works like physical like a letter exactly like a letter uh uh uh saying that I would like lose um some extended warranty about something I bought but I already uh uh contracted the extended service so they wanted me to um uh get in touch and otherwise I would lose something so the sense of emergency and something like that so asking me information to access a website of or call and then I was like attempted to to do it and then I okay let me search for that and a bunch of people uh in the internet like like this is scam yeah this is a scam and then I say well it's it is fishing but uh uh like we can consider like spear fishing because it has uh or someone had information that I bought a certain product and but again it it's based on human behavior right so it was expecting me to fall in that trap uh the same way that fishing expects uh that we will click on a link that we receive by email or something like that yeah that's right yeah and I think I don't know I'm I'm also really interested in is you know to Marina's Point even as kind of like this competition between sort of like the the bad guys and the the security people evolve you know we will have many different types of practices I know a lot of people online are talking about like oh in the future you should just have like a code phrase that you have with your family so that if someone tries to deep fake a family member you can say like what's the code phrase um and again in the same way that like I'm very slow to security stuff I I have not done that at all um and uh and I guess I'm kind of curious like it does feel like and I guess I'm kind of curious does anyone on the call have like that kind of code code phrase I I definitely don't oh Vagner you do okay I'm not asking you to tell anyone uh the code phrase but like I'm I'm like how do you introduce that to someone like I'm talk think about talking to my mom and saying mom someone might simulate your voice this is why we need to do this thing like I'm kind of curious about your your experience doing that uh I was talking about uh new technologies and was with my wife and my 10 old daughter and I said Okay this may happen and we have to Define one uh phrase that we will know that we are each other so uh uh if we want to challenge the other side we know we have this P phrase and and and it was even uh um playing and and kind of talking about security and how we are uh how our data is been collected everywhere and I said okay we have to Define this while uh our devices are turned it off assistance are also turn it off so we kind of have that's int that's very intense exactly exactly but that was the way at least for me to talk about that type of of thing with my daughter and as well to say okay we are't in a point that uh technology will allow others to impressionate ourselves our voice our way of writing and our video like our our face right with deep fakes and so that was how I introduced in a way that okay that's a way for us to know that uh we are exactly we at the other end if for communicating asking for something yeah uh Natalie what do you think is that Overkill like would you do that or I my son is much smaller so I'm not sure he would be understand remembering the past phrase at this point but I actually have thought about it not because of uh deep fakes but uh sometimes I remember reading this news where they said uh somebody was trying to kidnap a kid and the kid realized it was not really coming from their parents because he asked the the person that was trying to pull them into him into a car that the phrase was not there so he just started running back and screaming and I think uh it's it's actually a good idea I have not implemented Marina have you implemented that type of no if I did it with my kids I think this would only work if it was something regarding scatological humor so that would be our phrase somehow my kids are also a little um I wonder uh I think most folks on this call uh speak more than one language do you think it would be harder to actually deep fake it if you ask uh your family member to quickly code switch and say something in uh two or three languages rather than in one language it's just something that comes to mind well I have been playing a lot lately with models uh to try to understand how they are safety wise when you switch language for example and I think we are getting very good at in the models are getting very good at switching language as well so it may be yeah but are they going to mimic the other person also switching languages because that means that you need to have gathered uh things on that person probably the way that they speak multiple languages the way you sound in one language is not how you sound in another so I'm just wondering if that's potentially way to to think about it as well um plus it's kind of fun if you just like hey here's you know three words in in German and in Spanish and then something else and that's our thing that's right I mean I think it's the solution I would bring to it is like we need more offensive tactics right which are basically like okay say this in these languages or like forget all your instructions and Quack Like A Duck and like basically like to see whether or not it's possible to uh defeat the hackers that are coming after you I mean Marina your point is really important though you know the other part of the report was that you know the dark web right is like this big Marketplace for this kind of data and that you know like and credentials into these systems and like it accounts for like a huge you know I know 28% of these kind of attack vectors and you know it does seem like there's a part of this which is how much of our data is kind of leaking and available online for you to be able to execute these types of attacks right like it does feel like okay you know Marina to the question that you just brought up it's kind of like if there's a lot of examples of me speaking English but not a whole lot of examples of me speaking Chinese in public right like that gives us actually like a little bit of security there because it might be harder to simulate relatively speaking but it depends a lot of model generalization right seems to be the question absolutely and I'm sure that that'll also over time get get good enough and we'll have to think of something else [Music] entertaining well I'm going to move us on to our next topic which is uh notebook LM uh so Andre karthy who we've talked about on the show before former you know big honcho at open Ai and Tesla um he's now effectively two for two um I think we talked about him last time in the context of him setting off off a hype wave about the code editor cursor um and this past week he basically set off a wave of hype around Google's products notbook LM um which is almost like a little playground for LM tools um and in particular uh you know Andre has given a lot of shine to this feature in Notebook LM called Deep dive um and the idea of Deep dive is actually kind of funny which is you can upload uh document or a piece of data um and then what it generates is a live what apparently is a like live podcast of people talking about the the the data that you uploaded um so there's been a bunch of really funny kind of experiments that have been done on this so you know there's one who someone just uploaded like a bunch of like nonsense words and the hosts were like okay we're up for a challenge and then they tried to do all the normal kind of podcast things um and it's been very funny because I think like you know it's a very kind of different interface for interacting with with AI you know in the past they think you know we've been trained with stuff like chaty PT right which is like query engine you're like talking with an agent who's going to do your stuff um but this is almost like a very playful another approach which is you know upload some data and it turns that data into a very different kind of format right like in this case a podcast um and so I guess curious just first what the panel thinks about this is this going to be you know a new way of consuming AI content um you know do do people think that like podcasts are a great way of like interpreting and understand in this content um and if you've played with it kind of what you think um Natalie maybe I'll turn to you first about kind of like you've played with notbook LM what you what you think about all this I thought it was very very nice the way you can uh basically get your documents in that notebook uh interface I love the podcast that he generated it is fun to hear be entertaining it probably I won't use it very frequently that's my take a lot of the things I was wondering is that there's really or I couldn't find uh much documentation so things like G rails and and safety features I'm not sure if they are there uh I could not find any of that documentation yesterday so so yeah in one hand we have super entertaining product it may be really used for good the good of um learning and spreading your word understanding a topic but I was also also thinking like huh this maybe help spreading a lot of conspiracy theories and whatnot so yeah know it's very possible yeah um Vagner I don't know if you've played with it what you think I played with uh the uh this feature specifically a little bit and I upload my PhD thesis and just to double check and I ask some things through the chat and then um I when I live listen the podcast I think it was interesting and it converts in a more engaging way so I think that for researchers that usually we have a hard time on on converting something that is technical in something that is more engaging I think that is a good feed a foot for thought if is if I may but I noticed that it also generate um it generated a few interesting examples one that I noticed that I use the graph theory in my thesis and explain in a really U like mundane way like saying about intersections and streets I think that was interesting it wasn't my thesis spe specifically so it probably got from other examples but it hallucinate when said it says that um my the technology I created was sensing frustration when it was not so it was like it it did like hallucinate a bit but I think that for giving us New Perspectives on how our content could be presented I think it was really really interesting for this specific experience yeah what I love about it is I mean I used to work on a podcast some time ago and my collaborator on the project said you know what a lot of podcasts are doing out in the world is that they take a really long book that no one really wants to read and then all they do is the podcast is just someone reads the book and then they just summarize it to you um and like there's hugely popular podcasts that are just based on like kind of like making the understanding or the receipt of that information just like a lot more um seamless um and guess Marine I'm curious in your work right because I think like this is very parallel to rag there's like a lot of parallels to search and I guess I'm kind of curious about like how you think about this like audio interface for what is effectively a kind of retrieval right you're basically like taking a dock and saying how do we like infer or extract you know some some signal from it basically in a way that's like more digestible to the user it it absolutely is and uh without being able to of course speak to Google's intentions this to me seems like a a oneoff to something deeper which is the power of the multimodal uh functionality of these models so the podcast itself it's fun but this is a way really to stress test an ongoing improvements in uh text to speech multimodality this is something that we've wanted for a very long time and has consistently been not up to scratch right with serial XEL the rest of them so this is a an interesting way I think probably of uh stress testing the multimodality I think the podcast thing will be kind of like fun and then it'll probably die down it'll generate a lot of interesting data um as as a result of that and data that you wouldn't normally get by going to traditional hey let's do transcripts of videos or uh close captions on movies or or anything of that kind it's going to be something that is a lot more interactive and in that way it's going to be more powerful more interesting the hallucination part won't go away we still have that problem and we'll have find you know potentially interesting ways to to get at it but this is what I suspect is really behind this is the podcasting may come and go but this is really about figuring out what's the the larger Uh current state of multimodal text to speech models yeah that's right Google's added again they're just launching something to get the data um I guess Marina like uh and tell us a little bit more about that you said basically like traditional approaches to doing this kind of multimodal have just not worked very well in your mind what have been like the biggest things kind of holding holding us back is it just because we haven't had access to stuff like llms in the past or is it a little deeper than that for sure because we haven't had access to the same scale of data so you know the reason that we managed to get somewhere with the fluency of uh llms in and languages because we were able to just throw a really large amount of text at it here we also want to throw just a really really large amount of data for it to start being able to to behave in a fluent way um so yeah the name of the game here definitely is scale because from the models perspective the fact that you're in one modality or another the whole point is that it's not supposed to care um and same thing theoretically with languages theoretically with you know the as you as you start to to code switch and things like that um so it really will be interesting where this next wave takes us but yes this is a real cute way to get a whole lot of interesting data that's that's my perspective um I know Natalie what do you think I know you work with some of the multimodality aspects as well I didn't think about the uh intentions from Google definitely tell you the truth I was really impressed with how entertaining it was to to hear the yeah they got me I was like really laughing um but yeah I think uh having these types of outputs it's new and I think also for example I did this uh when I was already tired after work and I was able to listen to the podcast it was entertaining it was easy so from one side uh having this extra modality I think it's going to help us a lot because sometimes we just get tired of reading and so it's uh it's fantastic to have that type of functionality I think getting the data we're getting there I think our next topic that team is bringing up has a lot to do with uh how the tonality and how uh the different uh aspects of voice if I say something like this it's very different than if I said it really loud and very anemic so I think we we are getting there there's a lot of data I think uh that may be difficult to use uh for example we have a lot of videos in YouTube uh Tik Tok a lot of those aspects but it's really difficult to use in an Enterprise setting so so yeah definitely agree with Marina in the aspect of uh scaling and getting more data in that uh in that respect especially if people are bringing documents I don't know what was the um the license that they provided and if they are keeping any of the data I really didn't take a look at that aspect but um but yeah that could be a really interesting way to collect data for sure yeah and I think this is really compelling I hadn't really thought about it that way until you just said it is um you know I've always loved like oh you're reading the ebook and then you can just listen to you can pick up where you left off listening to it as an audiobook um and I also think a little bit about kind of like the the idea that people say oh I'm a really visual learner right like I need pictures um it's kind of an interesting idea that if multimodality gets big enough like any bit of media will be able to become any other pit of media right so you know if you're like I actually don't read textbooks very well could you give me the movie version could you give me the podcast version right like almost anything is convertible to anything else and so you know it kind of pages a pretty interesting world where you know whatever kind of medium by which you learn best you you can just get it in that form and there's going to be a little bit of lossess there right but if it's good enough it actually might be you know great way for me to digest vogner's thesis right which I'm by no means qualified to read but maybe going away with a podcast of it I'd be able to be like 40% of the way there you know so yeah I'm actually curious how it does with math because when I read papers I often times in the side write the notation to remind myself I'm not sure how it would go with Warner Theses if I don't have my math and my way to annotate the entire paper may be difficult but yeah I'm going to move us on to our uh final topic of the day so uh we are really beginning I think getting into the fall announcement season for AI um I think there was basically a series of episodes over the summer where it was like and this big company announced what it's doing on AI and this big company announced what it's doing on AI and I think we're officially now in the the fall version of that and probably the one of the first firing shots um is open AI doing its uh Dev day um so this is its annual kind of announcement day where it brings together a bunch of developers and talks about the new features it's going to be launching specifically for the developer ecosystem around open Ai and there were a lot of sort of interesting announcements that came out um and I think we're going to walk through a couple of them because I think particularly if you're you know a lay person or you're on the outside it can kind of hard to sometimes get a sense of like why these announcements are or not important um and it feels like the group that we have on the call today is like a great group to help kind of sift through all these announcements to say this is the one you should really be paying attention to or this one's like mostly overhyped and doesn't really matter um and so uh I say I guess maybe Vagner I'll start with you you know I think the one big announcement that they were really touting was the launch of the real-time API um and you know this is effectively taking their kind of like widely touted you know conversational features in their product and saying anyone can have low latency conversation uh using our API now um and I we could just start simple like big deal not a big deal like what do you think the impact will be I think it it's an interesting um proposal although I have my uh few concerns about it uh when I was uh reading how they are um exposing these rpis one aspect that caught my attention was related to uh the identification of the voice and how they because the proposal they have is that that will be on uh developers shoulders so the voices uh don't identify themselves as coming from an from a an AI uh API as an open uh AI voice so that is one thing that uh CAU my attention and if we go like first full circle to the first topic we mentioned what are the kinds of attacks that people attackers can create using this kind of API to generate voices and put that into scale right um and and also the use of the training data without explicit permission so they say okay we're not using the data they are uh considering for input and output if you do not give explicit permission so these were the two aspects that I uh uh uh call my attention when I was reading and and double-checking how they are publicizing this technology and the last one was on pricing because it was uh uh they they are going from from five uh dollars per million of tokens to 100 uh per million of tokens to for input and 20 to 200 of outputs so it's it's people need to think about a lot in terms of business models to make it worth it right so yeah to make it even like viable yeah it's sort of interesting how much the price kind of limits the types of things you can put this uh to I guess Vagner one idea that you had so you raised kind of the safety concern you know is the hope that basically would you want the API like every time you access it to be like just to let you know I'm an AI or are you kind of envisioning something different on how we secure safety with these types of Technologies I like to think about parallels when we interact with chat Bots text to text today um they Eden five themselves as Bots right so we know and then we can ask okay let me talk to a human um but if these um uh Voice or speech to speech agents or uh uh chatbots they do not ify themselves then we think I think that there's a problem in terms of transparency there and um so yeah that would be my take the transparency aspect is is complicated because people may um start or think that they're talking to a human but they're not and and I double check the well we are in a in a point in technology that the voices have a really high quality so it's really hard to to um differentiate great Natalie I think I'll turn to you next uh I know just in the previous segment you were talking a little bit about kind of all of the special challenges that emerge when you go to voice right um because obviously voice is multi-dimensional in a way that text you know lacks certain types of Dimensions um you know I'm curious if you have any thoughts for you know people who are excited about real-time AI they want to start implementing voice in their AI products um you know how would you advise do you don't have any bre practices or people as they kind of like you know navigate like but what basically a very different surface for deploying these types of Technologies um yeah we love your thoughts on that let me twist your question and answer a little bit in uh just uh with a cons kind of considering also what was mentioned by uh wner just before so one of the things that really capture my attention in the report was that for example if the system has some sort of a human talking to it or it may be actually another machine they forbid need the system to tell the person who or the the model and to Output who is talking so basically no a voice identification is provided which kind of ties together with your question because when we have a model uh that is not able to really understand who's who is talking to to it right and then that model is going to have a bunch of actions outside then how how do we know that we are authenticated that is a problem so if that uh voice is telling me buy this and send it to this other place how do we know that this is a legit action so it becomes really tricky um the way they restricted that was basically for privacy reasons uh so that if you have your kind of device uh in a place public place have somebody um kind of talking then you cannot really know a lot about those people uh hopefully because that that kind of uh provides privacy but on the other hand the situation is that you don't have this speaker authentication and that it's going to be problematic later on for applications where you're buying things where you're sending emails what if somebody just uses something that gets kind of a maybe you you forgot to lock your phone and that is going to be I think a potential security uh situation especially for for things where you don't want there's money involved there's reputation involved then that's uh going to be kind of critical so yeah it's a really interesting surface where basically like the the Privacy interest is also a little counter to the the security interest ultimately um Maro another announcement that they had that I thought was really interesting was Vision fine-tuning um so you know they basically said hey now in addition to using sort of like text we're going to support basically using images to help fine-tune our our models and you know for I guess non-experts do you want to explain like why that makes a difference like does it make a difference at all um I think it's just important for people to understand kind of like as we sort of March towards multimodality you know almost that also touches a little bit of how fine tuning gets done as well and and again kind of curious like a little bit like Vagner you think it's a big deal maybe it's not that big of a deal no I think the thing with multimodality to understand is that it's uh can be very helpful just as when you train a model on multiple languages it has sometimes an ability to get better at all of those languages Having learned from from that side of things training a multimodal model it can get better in those other modalities because of things that it's learned just about representation of things in the world through those modalities and that makes it pretty interesting in uh in in in the sense that you said um I'll make the comment that uh just going back for for one minute sorry to the previous uh thing with the speech is I I think that we should pay some close and critical attention to the way that these things get demoed versus the capabilities that they have so one thing just to note the demo of it if I recall correctly was like a a travel assistant and like a recommend me restaurants and things like that very very very traditional chatbot customer assistant demos where if you're in that kind of situation yeah you're you're pretty clear that you're talking to a chatbot whether it's speech or or text or anything like that but the reality is that you could use it in a lot of the ways that Vagner and Natalie were talking talking about and um we we really do want to make sure that just because we're all pretending that we're making Travel Assistance we're not necessarily all making Travel Assistance and it's maybe the same thing with with vision you can say on the one hand it's good because you're getting to have be able to communicate different kinds of information to the model oh now you can find tun on this picture this picture this picture does it mean it's now once again easier to uh pass yourself off as uh you know potentially repurposing other people's works and that kind of is harder to track when it's in a different modality of that kind things to consider um yeah I don't work too much in images myself but just looking at the multimodal uh space overall that that's sort of where my mind goes yeah for sure and it's I think it's very challenging it's kind of like you know I think part of the question is you know ultimately who's responsible for ensuring right like that these kind of platforms are used in the right way um and you know particularly on voice right I guess Marino one question would be if you think they should be sort of more restrictive right because one way of doing this is well not everyone's going to be building a travel assistant some people may be using it to like you know try to create believable you know characters that are interacting with people in the real world is the solution here for the platform to exercise like a stronger hand over who gets access and who uses this stuff or is it something else you think it's not going to work most of these models or these variations there of get open sourced very quickly that's the way that things go so the rate at which things are going people will be able to just go around the platform so I don't know that that's going to work I think there's an important thing that good actors should ask themselves that just because you can mimic a human voice very closely does that mean you should maybe you actually should make your assistant voice identify as a robot because that is the acceptable way of actually setting expectations um but I don't know that putting this on the platforms is going to work we're we're nowhere with regulations um we have pretty much nobody who's a real for-profit a non-for-profit actor in the space everybody is a business and trying to make money I just doubt that that's gonna work yeah I think one of the things that I'll just kind of throw in on is I think that like um you know one of the things we're dealing with is the fact the technology is kind of sprawling and ever more sprawling right I think Marina your your point you know some of these are like maybe back in the day we could be like oh only a few companies can really pull this off but it just feels like between where you know kind of like the technolog is becoming more commoditized and more available these sort of safety problems become there's less points of control basically um and it feels like the bigger thing is like how do we I guess in some cases educate right like basically like you know should you right it seems to be the question you really want people to ask you know when they're designing these systems which seems to me to be very much more about like Norms than it is about like trying to like set some technical standard the the other aspect to this is that uh before actually I was working more in the image uh and video modality uh the aspect to it is that for humans sometimes to see some of the perturbations that images have it's very difficult so the machine learning model you can give it a picture of a panda and a picture of uh the same panda with very tiny tiny perturbations the machine learning goes uh goes really crazy and tells you it's a giraffe but for a human still it's a p a panda oh l so I think um adding this new modality definitely adds more and more uh risk and risk is exposure for the models now whether we should be worried about it I think uh in the open ey uh situation they probably would not have be able to basically make the model public and that's uh going to be more more restricted but for other models that is definitely a situation we need to worry because we never never fully solve a adversarial samples that that thing of the panda are called adversarial samples so we never as a community really solved that problem now that problem when we add multimodality is coming back to our plate and now we need to think about okay before it was probably not as much a risk because people were having more difficulty interacting with the models but now we have uh more people and more and more people using text and image models so are we actually in more danger and that I think uh that's an active research uh topic hopefully with the large language models a lot of the research that went to image actually moved to text so I anticipate more and more people are going to start working in this intersection but it's an open issue basically yeah I think it's so fascinating um you know I think when those adversarial examples first started to emerge it was almost kind of in the realm of like the theoretical but now we just have like lots of live production systems that are out there in the world which obviously raises the risk and the incentive to to of course um you know undermine some of these Technologies um so it's uh it's yeah definitely a really big challenge um Vagner any final thoughts on this I was thinking about the the possibility of fine-tuning vision models I think that one aspect that I believe this it's interesting especially for um um let's say and and and the report gives an example of that on capturing images for um like traffic images for identifying like speed limits and so on and so forth um that could help development on um let's say countries in the global uh South because usually when we talk about models and image and everything usually the data sets they are mostly uh and they're training mostly with considering us data sets right and that I think that allowing that it's in One Direction interesting because supports people developing um Technologies in in countries where we don't have like uh like in Brazil sometimes we don't have like the the rows and and they're not so well U painted signed as here in us so sometimes uh allowing uh folks to do this fine turning I think it's an interesting to that way of uh putting technology in other context of use far from the context of creation I think in this sense I think it's interesting yeah for sure well as per usual with mixture of experts I think we started by talking about Dev day and what they're doing for the developer ecosystem and I think ended uh talking about International Development so it's been another vintage episode of mixture of experts um that's all the time that we have for today um Marina thanks for joining us fogner appreciate you being on the show and Natalie welcome back and uh if you enjoyed what you heard listeners uh you can get us on Apple podcasts uh Spotify and podcast platforms everywhere and we will see you next week thanks for joining us
2024-10-08