No Priors Ep. 42 | With Sarah Guo and Elad Gil

Key Takeaways

hi no prior listeners time for a host only episode this week elad and I are going to talk about what's going on at open aai of course video qar uh what might be next in research and some predictions okay elad we have to start with the Saga from this past week what is your take on the outcome and the second order effects from a second order effect perspective um this seems like overall positive news for everybody involved so it looks like on the openi side they're back to being in a really positive stable situation I think they still have like the leading model in GPT 4 um they've reworked the board which seems like a positive thing so you know imagine if this had happened two years from now three years from now Etc so it it seems like it would n increase the stability of the company in governance and a few things like that or the nonprofit and the company in governance so as an external viewer seem like a uh pay painful thing to go through but the flip side of it is it seems like they're moving forward and moving ahead in a positive way um and then in parallel I think it may have ramifications to other areas um that we can talk about if useful like what are the second order aspects of this but be great to hear what you think yeah I think the first uh obvious lesson is that governance matters right and this isn't an area where I think most companies are that experimental but I think a lot of entrepreneurs are likely to think twice about placing their Destiny in the hands of groups with explicitly mixed incentives now I'd say generally nonprofit governance is not every organization but as a class known to be kind of abysmal right because performance is hard to measure objectively and so it often ends up more about politics and specific relationships and Status games than outcomes the clarity around how much you know any board matters was kind of a a wakeup call for people the second lesson that a lot of people will take away or I think should from this whole Saga is that money matters right the factors of production are labor and capital and compute is the AI specific form of capital Microsoft holds the compute here and that clearly matter this is amazingly well managed uh and supported by saan Kevin and then the class of like really special labor here the team rebelled and the board obviously underestimated the level of support that Sam and Greg had from them and then I think one thing that is often unsaid because it's a little bit less idealistic is that a lot of open AI people were very upset this last week about not just the destruction of the mission which I think was absolutely like genuine but also destruction of the value they' built and been promised a piece of with the 86 billion uh tender offer it's just a reminder that labor and capital are like leverag they're stakeholders and there's no there's no free launcher control without skin in the game and it I think they're um likely shouldn't be from the view of many of the people involved in this yeah I think you're raising an important meta point which is basically what are the incentives that different organizations have in place and ignoring open AI I think there's a lot of boards which added board members for reasons that were politically motivated or motivated by different regulations getting passed that for certain board changes Etc and you also see that in executive teams and I think it's really important for people to go back and rethink okay who should be on my board and what why what are they representing relative to the board what expertise do they provide or what insights are they bringing or what strategic views are they bringing same with your executive team and also what are their incentives and you know there's this um this view that's kind of been moving around Silicon Valley in terms of the professional managerial class right people who have Alliance not to the organizations they work at but external incentives and those external incentives could be speaking at Ted or going to Davos or getting Kudos or an award from a specific organization versus doing what's actually their Duty as a as a representative of the various shareholders of a company in the context of a corporation and so there are these fiduciary duties that may be being breached by um other incentives for different actors who've been added over the last you know 5 10 years to boards to Executive teams Etc and I think it's really worth rethinking like who do I want on board and what and it also comes back to some of the companies that have been resetting things relative to politics I think Shopify did a great job for example of saying we're performance-based culture we're focused on um you know a very specific Mission we don't want that mission to creep we're about we're not a family you know like if your uncle shows up drunk and does something bad you forgive him if a board member shows up and does that then you know you don't want them on your board right they're being irresponsible there's also that broader context of like how do you want to think about alignment incentives culture motivations and you know is this a good moment in time to sort of pause and rethink some of those things relative to to your own company yeah one friend at open aai who uh I guess publicly declared that this reignited their belief in clear incentives and some um and good intent and capitalist structures that has actually seemed somewhat radical in uh in many Silicon Valley companies over the last few years but but I think that is going to get rethought when you see what happens when there are unclear or misaligned incentives yeah there there's two actually related quotes to that there's one which is something which I'm going to get wrong which is something along the lines of like capitalism is the best way to take care of people that you don't know you know it's the means of actually growing the pie in many cases and providing for for others through the sort of incentive of markets but the other one is a Charlie merism and unfortunately Charlie Munger passed away earlier today and obviously he was sort of a giant of industry and he had this great saying which was anytime I think I understand the importance of incentives I realize that I'm underestimating the importance of incentives if we just think about what the other second order like more commercial effects are I do think that uh there is an interest in owning models more in open source models and in um at least understanding like Reliance on a single vendor what do you think here yeah I think um there's a couple people who built Solutions during the last week that for examp example Brain Trust now has a AI proxy where you can use the open AI SDK to effectively query multiple different uh models including mistol um and llama through perplexity as well as a variety of other things GPT 4 GPT 3.5 um I think potentially anthropic and so it just allows you to be able to both load balance your uh queries or prompts but also interchange models more easily so you can actually look at performance across them I think Chima similarly has done something over the last week that they've released that helps with some of the proxying and other things and so I think there's Solutions like that that have started to be accelerated into a market that would have happened inevitably right I think everybody the journey that I see people often take is they'll prototype on gp4 they'll look at how good it is and then they'll either keep it on gbd4 particularly if they need like Advanced CH logic or other things or if they need very high throughput in performance and low cost and sometimes they'll either switch to gbt 3.5 or they'll see if they can fine-tune something right and that's the only people with enormous scale like I don't see very many fine tunes happening in general unless you know somebody has enormous scale and or proprietary data that they just don't want to get out right so they'll F tune mistol or llama or something so already I think people were thinking about that and that means you need to build an orchestration layer you may need the proxy you may need a VAR of things so the dimensions that people were evaluating an llm provider on or whether not they wanted to um control or uh host or find tuned themselves just became more clear right um where like reliability um became more important but the reliability latency um cost control capability questions were sort of naturally there and to be clear like open AI leads on capability in many areas in unique capability in in some right like cod generation GPT 4V right you can do amazing things with that and people uh should go build on those tools I think the ecosystem will mature and opening eyes a great partner but uh I think the questions are just much more obvious for anybody relying on these models now yeah and I think honestly a lot of the bigger Enterprises I knew uh always wanted to make sure that if they really needed to that they could Second Source something so I don't think this is a new thing in other words you know one could argue that no matter what open does there'll always be at least one or two other suppliers or vendors or partners for Advanced llm simply because the market always wants an alternative even just for negotiation leverage and so if you look at other markets for example in the router world one of the main reasons Juniper exists is because everybody wants to make sure that they can push on Cisco for pricing and so they always want to have a second Source that's why Juniper is always 10 to 20% the size of Cisco right it's just second sourcing or AMD versus Intel for a very long period of time so I think often markets will end up with other players just because bner prizes always want to have that option if they need it even if it isn't as good and if anything I think open AI kind of emerges more stable through this in ways that people didn't expect simply because there's going to be more stability at the board level in a way that people didn't understand perhaps that there could have been instability right this is a strengthening event and a focusing event for the company at least you know from what I can tell exter do you want to talk about Pika and video yeah there are a couple really amazing launches happening in the video space what's the cause for this like we we suddenly have text to video generation and Avatar cloning in different ways what do you think is going to happen in this space interesting shift has been happening because basically if you go back a year and a half mid Journey launched staple diffusion came out Dolly 2 came out and there's a whole wave of people saying that they were going to go build on diffusion models and image gen was like the thing that everybody was going to go do for like two months and then GPT came out and then everybody was like oh my God I need to go work on llms and language and natural language and NLP and all this stuff and so the entrepreneurial ecosystem went through this sort of zigzag where everybody was going to do image gen and a bunch of companies started going down that direction and then that the llm stuff really kind of was substantiated through chat TPT and then most people went that way and a handful of Founders stuck around on the diffusion model side and diffusion models you know are really popping up and obviously there's like image Transformer and a bunch of other stuff but they're mainly being used for image gen for video and for audio actually and so there's a wave of people who've continued to work and crank on this um and they're starting to come out with really interesting products for example p is a great example where it was two um Stanford PhD students who've been working on diffusion models for some time and they made this you know really amazing creative um text to video engine there are other companies like a haen or CIA or others that are doing you know let me use these diffusion models to clone an avatar to generate an avatar person so that they can either go into the metaverse alak OR alternatively they can use it for marketing purposes they can use it for internal training they can use it for all sorts of applications and then there's some really cool like audio based things coming out too which I think are starting off more sort of tools to create music or just simulate voice in the context of um a soundtrack or you like make EDM and you want to add voice to it right and you can just now kind of do some really interesting things there so it seems like there's this really interesting Renaissance um that's happening in part due to diffusion model work and in part due due to a handful of Founders not getting distracted by llms which are Super exciting obviously um but wanting to do things in video it's a really exciting Trend and I'm I'm guessing the success of some of these companies and their their traction and growth is going to pull more people over to to work in this area again I think it was just an area of less emphasis for the last year relative to language one of my favorite dynamics that happens in sort of Technology e systems is that once people show that something is possible like a lot of talent floods in right and you kind of get oh you get a lot of competition but you also get um Innovation coming in waves that could be with mraw developing open source models that are uh actually interesting from a reasoning perspective at relatively small parameter size or it could be Demi and chenling and the Pika team creating text to video generation models that are really interesting quite efficiently from a training perspective and I know we're both investors here but I've seen a huge wave of people interested as you said in media diffusion of different kinds now that they know it's possible and it has real benefits right because it's um it's very cheap to do and from a data set perspective the data is reasonably straightforward to get I mean it's hard to get but it's not as hard as you know the entire internet and transcribing voice from videos and all the rest of it the original um stable diffusion model supposedly was trained on like 600k of GPU yeah these models cost in the millions to train not tens of millions at least initially right and so that's another big difference relative to the really big foundation models and language models and all the rest right and so you can actually imagine that in the language world you're going to have a lot more platforms that people build on in the diffusion model world uh image video Etc you're going to have more people kind of grow their own right and people should still potentially try things on stable diffusion first just to test it out it's back to the you know no GPU before product Market fit but they can still train their own model in a very economic way relative to like the amount of money a startup would raise so I think it is it is a more accessible thing in some sense unless you just get and build on somebody else's llm which people should do for most things initially as well yeah one of the things I I think is really interesting about this space as well is we've actually had leading researchers like say you know we're still very very early in video video generation is so hard it's data intensive the data's like as you said it's not the whole internet but it's problematic in that a lot of the training has happened on short clips people aren't sure how to caption it's expensive to generate you have like complex like sliding window approaches and others to um try to deal with the like temporal coherence problem there are many more unknowns about how to uh progress this type of product technically do you mean video specifically or for video specifically yeah cuz the teams for all these things are actually quite small right the Pika team is reasonably small the mid-journey team for a long time was Tiny and so I actually think this is a good example where you can do a lot with very small teams and to your point there's all sorts of technical challenges but the reality is you can get to The Cutting Edge with like a handful of people in these fields which isn't necessarily true as much for you know other types of models or certain types of models at least so I do think it's striking um how few people you actually need to do something really interesting here and to your point there's other challenges coming 3 four years maybe it becomes harder I grew with you you don't need more than a handful of people like there's empirical evidence now maybe a slightly different point which is instead of like having to have a certain size of team to go deliver an llm at scale there are more degrees of freedom in how you would innovate technically in this area um and there's more disagreement on like how to progress and I think that's actually just interesting for startups yeah I think they should just use qar so I think that's that's the main solution to most problems I feel in uh in AI today okay well do you want to give me some investment advice given qar should I go home yeah you should do mainly qar Centric companies and so you know if they're doing qar you do it if they're not doing qar you don't do it so that's one big piece of advice I think one of the things I would like to go back to and um talk about is your point of view on like hey a bunch of people moved away from diffusion models to LMS yeah one of the reasons that people moved away from diffusion models to to llms is because there's a lot more uh sort of text and code in Enterprises that is obvious right working with images and video and audio felt more verticalized like where the B2B use cases and I I think what we're seeing increasingly is the creative fields are uh are actually pretty commercial right so one of the things I'm most inspired by and I think there's a lot of of money in is if you look at Mid Journey one of the bigest like biggest knocks on them uh from investors or naysayers early on was well like how many people want to make images that's not a hobby that's not a social network like what percent of the population are artists and this was clearly wrong just in terms of the scale that mid Journey has already reached there's probably two pieces here right like one these tools like Pika and haen and audio generation and mid Journey they make the pie bigger for Creative Fields especially since if you look at Pika or hent they're really focused on all creators rather than just like the film industry professional um and like if you go look at the uh mid Journey use cases and then I suspect the Pika and Haun use cases over times they're very commercial right like a lot of the things that you named or that people are experimenting with are really about communication marketing and advertising yeah I think if you just look at it as market cap of incumbent right adop is a 28030 billion do company like that's huge right and so I don't think the creative world is small right I think a lot of Creator economy companies have failed in the past which is a different thing depending on how you think of the Creator economy right in terms of you know celebrity based marketing or whatever but if you actually look at Enterprises obviously they use enormous amounts of imagery and video and other things things to reach with and interact and brand and you know associate with their customers and you look internally you you need to create imagery for slides or for other things and communication and you know and so to some extent you're kind of looking at different proxies and you say okay well what are some of the proxies on the um on the text Spas side and you can say oh you add up Microsoft and you know a few other companies like that and you're kind of getting a rough proxy for some form of text not really but you know I'm just simplifying things dramatically and then you add up adobe and a few other companies and that's your proxy for for image gen right and so I think um both are big and then the question I think always with the diffusion model based companies was where are the biggest application areas and the application areas also were a little bit different by what where will Encompass play a role where will you get blocked by other companies in the ecosystem versus you know it's a natural new Greenfield thing most things aren't truly new capabilities most things are just like making certain things dramatically easier there's the The Duality of that there's the Market expansion and more people can do this thing and then there's a value contraction hey you can do this at a tenth or 100th of cost and so often in markets like this you see both of those things happen at the same time you're simultaneously growing the market and shrinking it yeah I mean you have the um the um famous uh strategy like your margin is my opportunity right I was going to say I mean well these are actually higher margin things I think really what you're doing if you look at the sort of um my understanding I need to look up these numbers again but I think it's something like software spend is like I don't know I'm making it up half a trillion dollars $500 billion a year and then service to spend is like three to five trillion a year right and so really what you're doing is you're taking Services Revenue which is very people intensive and low margin and you're converting it into higher margin software Revenue but less of it so maybe you take that 5 trillion and you turn it into 2 trillion but is 80% margin 2 trillion versus 30% margin right the margin dollars actually expand and you see that in other Industries that's kind of what andreil is doing in defense right they're taking a Cost Plus model right you buy a drone from Lo Martin for a million dollars and you you get paid by the government 5% Cost Plus which means you get 5% as your margin so you make 50k off of it and andero will sell the same drone or you know better drone for $100,000 with 50% margin I'm making up the margin right but that's 50k and so you're making the same margin on a tenth of the price and so I think one of the ways I think about Andel as a company is they're taking very bad low margin revenue from other defense companies and turning it into higher margin healthier Revenue right yeah uh I'm going to edit the quote and just say like your ASP is my opportunity right there's a like a democratization that happened in the like latter half of the SAS Revolution or really most of the SAS Revolution which is instead of there's a hundred very large Enterprises that have some sort of CRM because it costs X dollars to um deploy and Implement seble then you have you know tens of thousands of companies who can buy Salesforce and then companies that figure out how to efficiently distribute um S&B SAS on the internet even though that that is still hard I I think one of the things that is um interesting here is let's just take video generation as the example the ASP of you know hundreds to thousands of dollars an hour make it single digigit dollars to generate per minute and expand the audience to many more people right that's the democratization that is happening somebody told me a joke the other day like somebody really negative on AI investing there only five businesses in AI that have Breakout traction right now Foundation models wuss mid Journey co-pilot and inference platforms I think there's both truth in it and like also it's not that funny of a joke because you're like it's true like there is a set of things that people are figuring out that are really early many of which feel pretty different than like yes it's it's useful to look at the incumbent vendors like Adobe but you're not fighting really the video editing software spend you're eating into the production spend the early internet version of this by the way is there's only five things you do on the internet you go to Yahoo to look for links you buy Pez dispensers and auction on eBay you buy some books on Amazon and then there's probably like some like two bullshitty companies that you would have quoted as like hyra things right so if you were looking at the internet Circa 96 997 whatever you probably would have had a pretty short list of real use cases and then a bunch of stuff you just thought was kind of dumb right and you'd be like look you're not changing anything like you're still using Microsoft Office and you're still using whatever shrink WP software you're still watching TV right and so I feel like we're kind of in that era of AI the stuff is going to happen right now is the really easy loow hanging fruit and then a bunch of dumb things are going to get built that aren't going to work and dumb is not meant in a pejorative way it just means like it's very hard to tell what's actually a good idea in a new market like this and um that was true the internet and that was true of mobile and that was true of cloud there's a lot of these like waves where there's a bunch of stuff that gets built right um so I think it's the same thing right it's a very positive sign this has been such massive Traction in such a short period of time for so many companies if you think about it it's actually kind of amazing so I'd actually take the other side of that but I I totally get the point yeah well with the AI Focus fund I agree with you you're going to change the name of your fund you should call it like conviction star or something conviction star yeah but spell with a Q like conviction conviction star okay LP you heard it here first conviction star very exciting I should send you a t-shirt thank you please do that'll actually be the swag for no prior season one if you're a guest you're going to get the no prior tequila and then a conviction star t-shirt yeah it's very I'm very excited about the tequila anybody with the podcast has have a tequila uh we could actually call the tequila conviction star with a Q okay that'd be pretty amazing I'm serious okay it could be like a q- shaped bottle you know how they have like the really cool bottles for different things the l gil guys are are U no prior brand marketer yeah I think I mov into LA and starting the brand if you haven't yet been a guest please write into the show and you know for the low low price of one GPU we'll ship you a bottle yeah we're looking for brand marketer to join the team too or not actually if you work for Mr Beast just call me A lot's going to do it okay aad thank you for joining me on no priors thank you for joining me and I look forward to getting my conviction star t-shirt and Tequila exciting find us on Twitter at no prior pod subscribe to our YouTube channel if you want to see our faces follow the show on Apple podcast Spotify or wherever you listen that way you get a new episode every week and sign up for emails or find transcripts for every episode at no- PR 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