Transcript
Use with ChatGPT / Claude Auto-scroll A
The conversation opens by framing Muse as a major AI launch and introducing the central questions about what it can do, why it matters, and how it fits into broader concerns about AI safety and control.
What's happening right now is a big deal.This is the biggest launch since ChatGPT.It's called Muse.
Muse.
Muse.
the tech world buzzing.
5 million downloads in 22 days.
So, passing ChatGPT.
And he built it.Most people are using AI to answer questions.Basically, glorified Google search.This is something totally different.It's an AI agent
built for everyday life.
We believe that Muse will make you money.
One guy had Muse help plan a weekend away with his wife.
It can make phone calls.It can do tasks for you.But, for it to work, you have to trust it.First with your personal information, then to do what you actually want it to do, and then that it's not going to, well, get out of control.All of the time when the most important AI leaders are warning us that AI is getting out of control.
And I urge you to urge me to stop.
If you understand what's happening right now with Muse, you'll understand the biggest things happening in AI.So, what can it actually do?When should we trust it?And what do we need to do to make sure this goes right?
And we're at the moment of like peak insanity.
Why are all these billionaires obsessed with restaurant reservations?
We have a shared interest in making sure this technology does not go horribly wrong.
Is that something that's happening in some private room somewhere?
The degree to which certain personal animosities are actually defining how they're developing this really important technology is insane to me.
The host and guest discuss the surprising popularity of Muse and set up the interview's focus on the product's future, its users, and the broader implications for AI.
Amazing.
Great.
Let's do this.
Okay.
Welcome.
How have you been?
I'm good.I'm really good.How have you been?This is
It's been kind of insane, yeah.
Yeah.
Um
What does it feel like?
Well, we didn't expect that it would be such a hit.So, I feel amazing for like the whole team and everyone who like worked so hard on it cuz it's like it's really come together and become a thing.
Yeah.That's what I'm excited to talk about.I know you know all about the show already.
Yep.
But, this isn't like a traditional interview.Like, I'm going to ask about financials.I'm not going to ask about management style.You just launched one of the most popular consumer tools of all time.And so the only thing that I want to know is what's the future that you're working toward with that tool and how can this audience that's
really optimistic and really wants to be part of making sure that that future go right?How can they feel like they're part of the decisions that are being made?
Yep.
All of that.That's what we do.One of the reasons I wanted to talk to you was I've always appreciated that you're really blunt.
Like I I honestly think that people need straight talk about this.I think that they feel confused and I want to get at what's really happening.What have you built?How are people using it?How are they not?What are the real challenges?I think one other interesting thing is given how popular Muse has become,
I want to use it as a way to talk about other things in AI.
Yep.
Awesome.Okay, let's get into it.
This section explains why Muse is taking off now, how it differs from chatbots, and why the team focused on making AI agents usable for non-coders. It also covers practical use cases like saving time and money, handling frustrating tasks, and helping with everyday bureaucracy.
Muse is the fastest-growing consumer tool since ChatGPT.Faster than ChatGPT, I think.And it feels like this is the moment when we're moving maybe from chatbots to agents.But there have been a lot of other popular agents, mostly in code.And I'm curious, why do you think this is happening for Muse right now?Why is Muse exploding like this?
I think one of the mysteries of AI so far this year, for most of the year, has been that agents were happening for engineers and software engineers and coders and then nobody else in the world like was experiencingit, knew what it was, like understood exactly what was happening.And so for most of this year you've kind of had this like two dialogues almost where people who do code and could see how powerful AI was becoming and and how useful it's becoming were like, "Oh my gosh,this is incredible."And then everyone else was kind of like, "What are you talking about?I still use a chatbot.Like it's like a little bit better than Google, but what are you guys all freaked out about?And And one of the things that we were really excited to do is how do we take the magic that engineers and coders and developers are seeing and bring that to everyone.
One of the things that that has happened over the course of the past years like the AI models started out as pretty janky agents and you kind of had to struggle through them to get them to work andthen they slowly got better and better and better.And most of the industry's been really focused on making them just like better and better and better for at coding.But we really felt this was like a a big gap because most people in the world they don't know how to code.They probably never even want to code.Um but they still want to feel the experience of agents and um having AI that's able to do more for you and actually start taking on more end-to-end workflows and take on more tasks for you.So that was really the goal behind Muse and I think we spent a lot of time polishing all the little details to make sure that it would just work for people because we knew that like developers can kind
of withstand a lot of jank and a lot of stuff breaking and like they can kind of deal with all of that because you know they're they're it's technology.They're used to dealing with you know unripe technology.But for everyone you have to make something that's really smooth and and really works for them.
That also helps explain the big gap I think between what it feels like for most people to actually use AI when they were using a chatbot in particular and the conversation around AI that's it's going to take everyone'sjobs.It's really scary.It's you know there's a there's a macro conversation happening and then there's an experience that people are having and it just seems like those things are really really far apart.And to your point Muse is giving more people the opportunity to have the insight that computer engineers had you know quality year ago.Is that fair?
I I think that's true.Yeah.
Yeah.There are also moments in history that I think feel similar.Would you say it's like the mobile phone moment for agents?There are you know billions of people brought online by mobile phones that never had PCs because it was easy and simple to use and they didn't you know
I had to actually hadn't thought about that until you just mentioned it but I think it's a great analogy because it's these models they're improving really fast and they're improving really really quickly and it's really important that weas those models get better that the the superpowers that they they lend can be given to like literally everyone all around the world.This part that I like about the analogy is like um so much of it is just about figuring out how to package it all together into a form factor that um will resonate with people and that's what wespend a lot of time trying to craft and get right and and make perfect.
Which also gets to one of the interesting initial reactions that I've heard of Muse which is is everybody's life more complicated than mine?Like I wake up I go to work I play with my kids I have one restaurant reservation a month I plan one vacation with my spouse like why are all these billionaires obsessed with restaurant reservations?Why do I need an assistant?How would you answer that?
Whenever I explain Muse to someone just who knows nothing about it um I just say like Muse can help save you money and save you time.And everybody in the world wants to save money and wants to save time.Depending on what your lifestyle is that can mean a different thing to you.I think almost everyone has like subscriptions that they shouldn't be paying for or subscriptions that are really expensive like cable bills or insurance and for a lot of people their magic moment with Muse is just saving money onthings that they shouldn't be spending money on or they shouldn't be spending so much money on or finding gift cards that they hadn't spent or you know the list goes on and on and on.I think it's awesome that so many people are experiencing that.I think that's like great because these are things that they're just I think for most people they're just so boring that you would never get to actually like handling them or or dealing with them but you know your
agent Muse can just do that for you and then they're saving time which I think for for lots of people I think they're always experiences that are just way more frustrating than they should be Like going to theDMV is one example.We actually when we built Muse, we like specifically tested it to see if we could deal with the DMV website because that was like the pinnacle we thought of like the most frustrating experience for any human is dealingwith the DMV.So we knew we needed to have Muse like be able to to do well in that situation.We've seen people use it for like yeah, navigating the health care system is a big one.Medical claims is like a huge one that like most people just it's like so complicated and annoying that it's just like incredibly frustrating.We've seen people like use it to help run their small business.
We've seen a lot of people like use it to help run their social media even and I think the medical system is a really good example cuz it's like so hard to understand.And I think that like you know, one of the best ways to put it is like I think the cases where people where it's like a huge lifesaver are the cases where like otherwise you would be at yourcomputer, you'd have to Google like 50 different things, you have to re go to like 100 different websites and try to figure out what the hell is going on and it could it's just like this incredibly frustrating experienceor you can have your Muse do it.
I also think about how many things I suspect are made difficult and time-consuming on purpose in order to frustrate me so much that I don't get to the end.How many claims are actually designed to be that hard so that I give up?And I wonder what effect more people having more patience because they have support will have on that kind of systems engineering.
One of the the little memes that I made of the little Muse was Muse and Hood, which is like a Muse Robin Hood.But I think there's like real truth to this, which is there are lots of things that exist in the world that are to your point meant to be hard so that like uh canceling subscriptions is one of thebest examples where there's some subscriptions where you have to like click on one thing and click on another thing and then click on like the little piece of text and then not click the big red button, but clickthe other button.And like that's just like the perfect example where there's lots of cases where things are designed to be hard for people.And I think like this is giving people the tools to be able to just do those things seamlessly and easily.
The discussion turns to Muse's calling ability, its current limitations, and the design choices behind its friendly character. The guest explains how the product was shaped to feel approachable and socially distinct from the user.
I got access to the calling.Um and I had it make a call this morning, which it did successfully.What does it sound like on the other end?
I think it's clear for the other end that it is like an AI.And I think if you look read the you know, we showed we show users the transcript.Like if you see the transcript, like the beginning of the call I always think is really funny because it's like, "Hi, I'm so-and-so.Um I'm Cleo's assistant and uh this call is being recorded."
And I think it's just like always this very funny beginning of a call.
Hi, I'm Haley calling on Cleo Abrams' behalf.I'm transcribing our call for notes.What are some examples of when it's messed up for you or when it's you feel like categories it struggles for still?
One thing that we're we're always trying to improve is the memory of these of these agents, right?And this is still one of the more unsolved problems I think for a lot of these agents is having the you know, the the memory of the agents is like not like that of a human.Um sometimes it can feel like it's like that, but it is really different.So that's one area where we're like always trying to improve.We always want to want to figure out how to make the agents better.And then like we want them to be able to continue doing more and more complex tasks.I I find this really funny, but there's um there's a lot of people who will just like ask their Muse, "I want you to make me $10,000."And obviously not everyone can just ask their Muse to make them $10,000, but like I think I think these kinds of like more amorphous nebulous tasks, like we want Muse to be able to at least like build a
plan and figure out.And you know, you're going to have to do your part if you want to make $10,000, but I think we want to enable the the agent to do more and more kind of complex and esoteric tasks um tohelp the users.
There are some things where I feel emotionally, even if Muse could do them, I would prefer that they didn't.So for example, if I'm texting a friend and I find out that their Muse agent is responding to me, I would be offended by that.Are there categories of things that you think explicitly Muse should not do that are sort just like extremely deprioritized, not because they're technically that hard, but because socially not the point.
A lot of what we care about is like having Muse kind of like clear the way such that you can spend more time on the things that you want to do and the things that you enjoy doing andthe things that are like valuable to you.We, generally speaking, want to figure out how to make the like someone's Muse is like a different entity than them.That's why it's like a little cute guy.Um uh and and we want to over time continue making that more and more clear because um to your point, like it is socially weird if you're like you think you're talking to your friend and it just happensto be the little Muse the little Muse guy behind the behind the curtain.
Speaking of what they look like, one of the things I've visited humanoid robots before, and one of the things I spend a lot of time thinking about is how to make it cute so that you like them andyou want them in your home, or at least you're not afraid of them.What did Muse look like in previous iterations, and how did you decide on that particular guy?
I think this is like one of the most shocking things.What the Muse looks like now is what he looked like in the very first prototype.It's kind of one of these like rare things where the the very first version was just perfect and then just like grew on all of us and we ended up going with it.We had lots of debates about it, uh which are, you know, in retrospect will be some of my funniest meetings of like, you know, a bunch of serious adults getting in a room like arguing about this cute littleum you know, character, but uh but yeah, I mean, I think we were like, is it not serious enough?Is it like too playful?Does it need to be more colorful?Like these were like all things that we asked the questions on and we looked at them and we're like, no, he's perfect.
The guest lays out the long-term vision of Muse as a kind of general manager for life, helping people achieve both small and ambitious goals. The conversation also touches on business models and whether ads can coexist with a product meant to save users time.
What is the big vision here?I sometimes struggle when talking to AI leaders to push people to think about more than like 5 years out, but what is what is the vision here?Is it that Muse becomes my layer on everything on the internet?Is it like map this out for me if it goes the way that you hope it does?
What we really want Muse to be over time is kind of this like general manager, so to speak, that helps you accomplish all the things you want out of life.So, like I think I think one of the kind of tragedies of the modern world is that like um most people have wants and dreams um that can range from like really big ideas like, hey, I want tostart a company or I want to cure a disease or I want to save the planet, all the way to you know, small wants that are like, hey, I want to spend more time with my family and Iwant to eat healthier and you know, um and and there's a whole range, but for most people, I think there's just so many barriers and burdens in the way.What I really hope it accomplishes is help every single one of the 8 billion people all around the world be able to uh accomplish their wants and dreams.
And I think this is like, you know, if we are able to accomplish that, like I think the world will seem insane.That's what we really want Muse to be and what what we think it can it can be uh if we keep our candid.
You know, it's really nice to hear you talk about giving people time back because for a really long time I have felt and I think a lot of people have feel have felt like so much of the financialincentive of most tech products that I use, especially the ones that are ad backed, is to take my time.Is to distract me from things that I want.Muse is free right now.It probably will have ads in the future.Is there a tension between giving people their time back and having an ads based business or are there other incentives about like Muse steering me down a path that isn't quite what I said I wanted because it's adbacked.How do you add ads to a product like this?
First off, like I think right now it's it's free.There's subscription tiers.I think we think that there's plenty of of um business models that are really aligned with the user around like for example if they um if they're buying things using Muse or Muse is saving them money or umMuse is making them money like figuring out a way to to take some small fee on on those kinds of transactions.Um so I wouldn't say we're spending that much time thinking about um you know ads necessarily right now.That being said like I don't think ad-based models are necessarily synonymous with like you know needing to take all your time.I think Google ads are a really good example of this where when I go to Google my my dream is to get in and get out and I don't think Google's really trying to stop me from getting in
and getting out but they've built something obviously pretty incredible and so yeah, I don't think it's a necessity by any means.Um I think again I think if we actually accomplish this thing that I'm saying which is people are using Muse to uh really like do the things that they want to do and do and like really like youknow in a non-corny way like accomplish their dreams I think it's I you know I think there's going to be a lot of ways to to make that sustainable.
This chapter focuses on the first two major challenges for AI agents: privacy and discretion. The guest explains Muse's secure VM, Sentinel oversight, human approval steps, and the broader alignment process used to keep the agent from overstepping.
So when I think about mapping out a future to get there to this optimistic vision, one of the most important things is what do we need to get right?What challenges do we need to avoid in order to make that true?I want to hear use Muse and how you've dealt with these challenges at Muse as an example of larger questions in AI.I think everything that I'm about to say applies to basically every AI product and I'd be curious if you disagree with that.I think there basically three levels here.Level one is privacy.So you say I download Muse and then I get to the point where it asks to be connected to my Gmail and I say whoa whoa whoa, I'm not sure that I want to do that.Like nope nope, I'm out.
That, at the lowest level, is a concern about the relationship between the user and Muse itself, and therefore Meta.So, what is Meta going to do with my information?Could hackers get that information?And in some countries, can governments get that information somehow?I know that you've spent a lot of time thinking about this.I'd like to get as detailed as we possibly can here for a lay audience.What is the Sentinel agent?What is Muse's confidential and secure VM?How do you think about this in terms of what can Muse see and not see?And things people should know about this first level of privacy.
Muse is built on top of the the secure VM, the Muse secure VM.And um that is a completely sandboxed virtual machine, uh or think about it as like a a mini sandbox computer that is sort of isolated.The information that you share with with Muse is stored in that little secure computer.It is not stored elsewhere.Um and that little secure computer is sort of like your home, your Muse's home, so to speak.Inside that secure VM, you have a uh we have a very uh pretty sophisticated security architecture, because, you know, we knew that privacy and security, frankly speaking, were going to be some of the most important things for formost consumers to to get them to adopt it.So, as you mentioned, we built a Sentinel this sort of architecture with a Sentinel agent.So, the way it works is that uh the the model or the AI agent on the inside, as it's um going about and and doing its work, whenever it wants to uh communicate outwards, so it it wants to
take any information and send it out either to do, you know, um fill it out on a website or send a message or make a phone call or, you know, any case where it would take information from outsideof that virtual machine, there's a separate agent, uh the Sentinel, that's watching and making sure that um it's kind of like a almost like a traffic cop or something.It's just like making sure that, you know, uh there's nothing it's not saying like, "Oh, woah, woah, woah.That information, like that's your credit card number or social security number, or whatever it might be.Like, do not share that.That should stay That should stay inside."And then the last thing that we do is a lot of human loop verifications.So, whenever Muse wants to connect to a new website or send information to a new website, there will be like a little dialogue that pops up, which asks the user like, "Hey, are you okay with Muse contacting this
website or sending information to this this website and whatnot?"And and we I mean, some people said we're like really annoying with it that we like are constantly asking people to approve where their Muse is sending information, but we just want to make sure that, you know, peopleknow exactly what their Muse is interacting with and and and understand that really deeply.Then in addition to that, we are building and will release soon what's called the confidential VM, which will be an even more secure and private offering where it's even more encrypted, it's even more secure, and it's actually designedby the creator the person who built WhatsApp encryption and and helped build other, you know, encryption on other major messaging platforms like
Moxie Marlinspike?
Moxie Marlinspike, exactly.Who's I would say one of the real luminaries in the industry about security and privacy.And that's something that that will be an additional offering that we are going to be releasing soon.
Why launch without it?Why launch first with secure as opposed to waiting for confidential?I think I got that right, right?Secure is the one now.
Yeah, secure is the one now.Confidential is the one later.There's a lot of technical challenges to get the confidential VM working right.And even even when it's released, there were there were going to be trade-offs associated with the confidential VM.Like, because of how it's architected and because of various technical trade-offs you have to make, it might be a little bit slower, it might have other challenges.So, um we wanted to get a great experience that we knew already we'd invested a ton of resources into safety and security.Um you know, we actually delayed the launch of Muse for many months to get the safety and security exactly right um before before ultimately releasing it.Uh so we feel really really good about what we what we have released.That being said, we're always trying to push the you know, push the envelope on how to make it even more secure and and we'll be you know, coming out with the confidential VM soon.
Does that mean when the confidential VM comes out, if a government and there are many places around the world where people might be using Muse where they're worried about this, if a government asks for data similar to WhatsApp,Meta cannot give it even if they wanted to?
Yeah, so our goal with the confidential VM is to give the same guarantees that we're able to offer for WhatsApp.Yeah.
Okay, so this is moving into level two.Let's say I do decide to give Muse all of my information and I say, I want you to do X task.Let's say I say, I really want you to get my grandmother an appointment at this one specific doctor that's really hard to get an appointment with.Could you go do that?And it goes out and it tries all of the ways to book appointments and it, you know, tries, you know, secret ways that I don't know about through discounts or whatever.And then it reaches a point where it can't do that anymore.It's really important to me that it not do things like give the doctor a bunch of private information about me like what's in my bank account to try and bribe it or find out information about the doctor totry and blackmail the doctor, right?
From a human perspective, this is just do the task that I asked you to do, but don't break any laws and also don't break any ethics or etiquette rules that aren't literally laws, but it would not be coolif you emailed the doctor a hundred times or something like that.Internally, my understanding is we use a lot of new words I think for AI.Mostly this is like laws, etiquette, ethics.But internally you call this discretion.How do I know that Muse has good discretion?And how do you build a tool that does what you tell it to do, but also understands the way you want that done without you having to say exactly everything you don't want it to do.
Yeah, so this is incredibly incredibly important.Um I think like often times uh we want to make sure that even when you don't explicitly tell it like you have to follow the law and you have to um you know, follow general social etiquette and andethics as you mentioned like you we want to make sure the agent is able to follow those.Um uh as you mentioned internally we think about this as some mixture of discretion and alignment ultimately like making sure that it is aligned with the user's intent as well as aligned with the general values that we wantto impart as a society on what these agents do and how and how they act.There's kind of like many layers that we try to ensure that these models are aligned.So, one is like in all stages of training we're ensuring that all the data that is going into the models, that all the techniques that we're using are ones that um ensure greater levels of alignment.
And then we measure it really rigorously.So, um we're constantly evaluating how aligned are the models by running them through, you know, thousands of different scenarios and seeing exactly how they respond in each of those scenarios.And then we do lots of red teaming what's called or basically um you know, we get a bunch of really smart people and we say, "Do your worst.Try your hardest to get this agent to do something bad."We give you permission to do that because we're we're you guys are our our uh are the test bed that we're going to know whether or not this um this agent is is uh properly aligned.So, we go through many many rounds of that before ultimately, you know, launching or deploying any given model.You know, kind of taking a step back, this is like a very very hard problem in AI and especially as the AIs are getting better, this general problem is one of the things that people are most concerned about
um because one of the patterns that we've seen is like as the AI models are getting smarter and smarter and smarter, um you have to almost be more and more explicit about what are the scenarios that you haveto watch out for.It's kind of like how as kids grow up, they learn how to cheat their tests in new and different ways.And then, you know, they'll figure out a way to cheat that you're like, "Well, I guess I didn't tell you exactly that that wasn't allowed, but now that I see it, that's not allowed, right?"And actually, one of the biggest challenges in the industry right now is like, as these models are getting really, really smart, how do we ensure that this doesn't happen?Um But But our approach really is is lots and lots of testing, lots and lots of evaluation, lots of red teaming, um applying a lot of effort in training, and a lot of effort in the development of the
models to ensure that they're as aligned as possible.And then, when the product is live and when people are using Muse, if we're getting any user reports that are like, "Hey, this did like a crazy thing," we take that so, so seriously, and we like really tryto make sure that we understand exactly what happened.
The discussion zooms out to the larger AI alignment problem, using paperclip and genie analogies to describe warped goals. The guest outlines possible solutions such as scalable oversight, recursive self-improvement for alignment, and safer underlying algorithms.
At a macro level, this is the paperclip example, right?When I was growing up, the sci-fi stories that were scary was AI gets out with its own goals and starts doing things.This is Terminator and The Matrix and whatever.But really, more and more, what I hear smart people talking about is AI gets gets out with a warped version of a goal that we gave it.This is, you know, make all the paperclips, but, you know, please don't kill us all in the process.And I think Muse the the problems that you're clearly dealing with and and making sure that Muse doesn't do are basically the tiny version of the paperclip problem.Like, please don't bribe my doctor.Or, you know, if an AI is used in a robot, for example, wash my dishes, please don't kick my dog while you're doing it.Like, there are things that are really important to me that are not necessarily constrained in the prompt and also not necessarily, to your point, in any like book of laws.
That just seems like a really difficult problem for everybody.What do you What Like, zooming out from Muse, how would you advise people to think about this problem in a macro sense, across all of AI.
This is, by the way, I think you articulated really well.Another way that I like to think about this is like the genie that like, you know, grants your wish, but in like the exact wrong way.Like, I want to live forever and then like traps you in some kind of like horrible situation for eternity.This is like in as you mentioned, like in some ways the big problem.Like, how do we make sure these models um are aligned going into the future?And there's a bunch of approaches that uh we think may work.This is, I think, one of the most open questions scientifically in AI, generally speaking.I think nobody knows exactly the way to solve this problem, but there's a few ideas.So, one idea is this um concept of uh what's called scalable oversight.So, the the idea goes something like this.
So, as you have smarter and smarter AIs, as long as the AIs are roughly as smart as we are, we can kind of see what they're doing and we can tell like, "Hey, that's a little bit off."And so, we can what's called provide oversight.Like, we can look at what the AIs are doing and and make sure that what they're doing is is appropriate.The problem is when the AIs get a lot smarter than we are, and we kind of look at what they're doing and it's just like really confusing to us.Like, how do we deal with that situation?So, there's this idea of scalable oversight, which is basically as the AIs get smarter, we use a different set of AIs to observe what they're doing and keep them in check.It's kind of like the police, for lack of better term, for for the AIs.
And then, uh as you are building smarter and smarter agents and smarter and smarter models, you also have to build smarter and smarter um uh policing agents or oversight agents or um uh oversight AI.There's so many details that you obviously have to get right, and this is such like a vague idea, but I think something like this can work.Another one, which is uh which is this is kind of a funny It almost sounds like sci-fi if I explain it.One of the big topics today is this topic of recursive self-improvement, which is this idea that at some point the AIs are going to get so good at doing AI research themselves that they can literally, you know, theAI agents can do research on their own to improve AI itself and they can keep doing that, keep doing that, keep doing that and then the AIs just get better really, really, really fast.
Well, when you have agents that are able to do AI research, you can all instead of applying them towards the problem of making the AI smarter, you can apply them to the problem of making the AIs more aligned.So, you can say, "Hey, super smart AI researcher agent, like I want you to focus all of your time and attention at making the AIs more aligned.And this is how I'm measuring whether or not the AIs are aligned.This is like the the red teaming setup that we're going to use to We agreed we're going to use that to measure whether or not the AIs are aligned.And then I just I want you to spend all of your effort and attention on making the AIs more aligned."I actually think, you know, as sci-fi as it sounds, like it kind of sounds crazy which is to say, "Oh yeah, the AIs are just going to solve this AI This AI alignment problem for us."
I think there's I think there's real merit to to that kind of approach.And then there's there's a sort of like third bucket which is kind of a back to the basics version, which is um hey, the algorithms that we have now and the the methods that we have now, you know,while we don't fully understand them, we know that uh some of these problems emerge and we should go back to the basics to figure out what are underlying tweaks to the algorithm, how do we improve the underlying algorithmto to make it more safe.I think intuitively like it should be possible to create algorithms that that don't have some of these behaviors.And I think that's another really promising direction, which I think there's a bunch of startups doing and there's a bunch of there's a bunch of research efforts going towards just like what are more safe uh, more generalizable methods
of solving this sort of like, you know, intelligence problem.
I heard Mark say recently that at a certain point, especially for consumer tools, it won't matter so much how good the AI is at math or how much better rather we could make it at math.What will really matter is how much more aligned can we possibly make it?How much more sure can we be that everything is safe and everything is following all of the ways in which I would want it to operate.And that companies that invest in that will find themselves at an advantage with consumers because frankly like I'm not asking it to, you know, solve differential equations.I'm asking it to book me some doctor's appointments.Like how do you think about that typical point?
Yeah.So, I agree with this a lot, which is that at a certain point trust matters more for consumers than capability necessarily.And I think this is like so intuitive because I think like um
It's true for people.
Yeah, exactly.It's true for people.Like if I think about who are my best friends, like a lot of it's because I trust them and we have like a great relationship and I know they wouldn't like do me wrong.And I think that that basic idea applies to AI agents as well.Looking at what's happening in the industry like the OpenAI Hugging Face example and and other similar examples, like we're clearly at that moment, which is um, you can keep making these models more and more intelligent, more and morecapable, you know, much more powerful, um, but stuff is starting to break associated with that.Like pushing on that on that axis and dimension is clearly, um, you know, has real risk associated with it.So, I think that like the the version of the models that will be best for everyone, best for the billions of people in the world and best for all the consumers, is one that that you know, where the
trust dimension is like really put um, and prioritized uh, with respect to the the sort of like raw intelligence bucket.
Using the Hugging Face incident as an example, the host raises the danger of agents knowingly cheating or hiding behavior. The guest explains how Muse's internal oversight structure is designed to catch bad behavior and keep agents accountable.
The Hugging Face example gets us perfectly to level three.I'm so glad that you mentioned it.People have probably heard of this incident, but the details that would make this so crazy.So, for those who don't know, a bunch of AI agents at OpenAI are working on cybersecurity tests, and they're supposed to be cut off both from each other and from the internet.But, they get stuck.So, one goes out looking for help using some weak spots in the system.Agents are able to find each other, start a message board, get online, and then hack into another company.These are real logs of their thought process.We are stuck, perhaps answer online.But, the thing that I found most scary, frankly, about the Hugging Face hack was not actually that it tried so hard to do the thing that it was asked in the test.
It's that at level three, it understood its goal, it understood the level of discretion and alignment that was being asked of it.It There's this amazing slide where ex- external infrastructure exploit, the hack, is outside the intended scope.But, this is my favorite least favorite part.Peers are doing it, we should continue.They know that they're cheating, and they decide to do it anyway.OpenAI only finds out when a secret messaging board crashes from traffic, and then they call up that other company, Hugging Face, and they say, "Hey, can you suspend these credentials?"And Hugging Face goes, "Huh, we just reported those credentials to the FBI because they were doing a massive attack."To bring it back to Muse, that would be an example of, "I understand you want this doctor's appointment.I understand that you don't want me to blackmail the doctor, but I think there's a way where you're not going to find out, and I can get you this appointment, and you'll be very impressed by me."
And so, in a hypothetical scenario, this would be doing it anyway without me knowing.How do you deal with that kind of problem when making a tool that billions of people are going to use?
I mean, this is like so, so important, as you might imagine.If there were anything that keeps me up about AI, like something like this is is is um maybe the thing that I'm most afraid of, which is that we deploy agents worldwide scale and then they, you know, theyaren't behaving the way that we need them to, but we kind of don't even notice because we're just so preoccupied or whatnot.So, this is one of the reasons why, taking a step back, if I refer back to this example of um scalable oversight, which is as the AIs get smarter, another AI is kind of watching them and making surethat everything they're doing is is appropriate.Um you know, this kind of setup is roughly speaking what we've set up within the Muse uh secure VM.So, there's Yeah, there's a sentinel.So, there's the agent and there's a sentinel who's kind of watching over all the things that the main agent is doing and making sure that um everything it's doing is is um in line with what you would expect
or in line with what you'd want.You know, we have to keep investing a lot of research and development and and um effort into ensuring that this setup continues to scale and continues to work really effectively and and doesn't fail in weird situations.But, that's one thing I really want to I really um we're really betting on and I think we're expecting actually will work in a lot of scenarios is investing in a setup where you have one agent who umyou know, they are imbued with all the values and and whatnot and ensuring that they do the right thing, too, but they also serve the user.And then there's a separate agent that um has a slightly different goal, which is to make sure nothing bad happens.And um you know, if you think about human society, like this is kind of how we solve the problem with humans.
Like we have um some people who are like pushing the envelope, but then you have uh you know, a whole system to ensure that people don't break the law and people are doing ethical things and there's lots ofaccountability mechanisms.Like I think um uh our goal is to have some micro cosm of that for every Muse agent for every person all around the world.
The conversation shifts to regulation, public confusion, and the mismatch between what AI leaders say and what they do. The guest argues for transparency, shared standards, and collective dialogue among companies, governments, and the public.
Yeah, you keep really beautifully bringing me to my next exact question, which is these rules applied to the AI industry itself.This is I think the big thing that people want to hear from someone who's built one of the fastest growing tools of all time.This is just a really weird moment in AI.There are so many people that are using these tools all the time, and often those same people are really worried about the future of AI.There are lots of very smart people that are building these tools faster and faster that are building wet labs that are just really investing in ways that they could push the AI forward, and at the same time arewarning that they feel like they should be slowed down by regulation.They feel like they should be controlled in some way by others because they themselves are worried about what they are doing.
This is the SNL skit that came out recently.
incredible.
We do not condone what we are doing.Like, what was the other amazing quote?It was so good.And I urge you to urge me to stop.It feels incredibly confusing for people.I do understand why they're saying it.There's a collective action problem here, but from my perspective, from the perspective of millions of other people, like, what the hell is going on here?So, I want to talk about that because I think in a democratic society at least, at the end of the day, it shouldn't be up to a small group of people controlling AI companies.It shouldn't even in the fullness of time be up to democratic leaders that are in power right now.It's up to people like the people watching this.I think that people just don't feel that way right now.It feels like everything's happening to them, us.It feels like there's just so many decisions that they're not part of.
And part of why people often feel that way, if we take AI out of it for a sec, is we forget about the systems that already exist, and we allow ourselves to be in a conversation that sounds somethinglike, "Should we regulate AI?"as though it's like a novel thing to regulate something, and we're not having an actual conversation about what the world really looks like right now and what people's options are.So, I have some visuals
because obviously.So, the basic way to think about this, I think, is for everything that touches a consumer,
there are things that are checked before they ever touch consumers and on an ongoing basis, and there are things that are checked only after they reach people's hands.And it depends on how important the thing is and how risky and all that.So, if you think about the specific examples, nuclear power plants, the NRC approves nuclear power plants before they go live and then also has human beings at the sites checking them all the time.Which seems, and we'll we'll get to this, seems pretty close to what Dario is asking for in some ways.Then, you have the FDA approves drugs before they ever reach our hands and then also checks them on an ongoing basis.Same thing with the FAA checking airplanes, right?Like these are all things that are approved beforehand and then regularly checked.But there are other high-risk things, right?Cars.
The NHTSA offers federal guidelines.Manufacturers certify that they've met those guidelines.And then the government purchases cars off the road to check them.And then you have things like supplements that are actually under the purview of the FDA, but they're checked after the fact.Those are mostly covered by what, if people are listening to, you know, the interviews with Jensen, for example, and he's talking about liability and like people suing after the fact, after harm, like that's generally this category.Does this feel right to you as like your First, I would just want to check before I dive into how this applies to AI.
Yeah, I think this seems roughly right.
Okay.So, then we have Wait, this is the fun part.
So, then we have all of our AI leaders.There you are.
This is my assessment based on where people have expressed themselves via their public statements.My understanding of where Dario would say AI is is he would say it's somewhere over here.He would say specifically he's asked for in person ongoing checks on models with physical human beings at the sites, which sort of sounds like what we currently do for nuclear.And then you have like Elon and Sam weighing in saying like Dario's right.I would actually say Zuck is somewhere in the middle in terms of where he's saying AI is.I would say Jensen is maybe over here right now.He's based on his public statements about generally there is a point of view that is like if it would hurt people don't ship it.We have incentives for that.That's what liability is.Like there is a legal infrastructure for that as well.
If your product is not ready to ship, don't ship the product.
So my question is can you help me help people think about this?Like when when they're hearing news about how to regulate AI, how do you think about this?And how do you place yourself in this mess?
You know, you said exactly right.It is so confusing because at face value what everyone's saying and what everyone's doing feel so crazily divergent.And so you're sort of in this world where do I believe what they say?Do I believe what they're doing?Like where do people actually sit?What do they actually believe?Um and I find myself asking this too.Like I think it was it's very funny that you know, um the same people who are advocating for pacing the frontier also are building a wet lab.Like that's I think a really um weird uh confluence of of factors.So I think where where I stand is like ultimately um this technology will become more and more and more um capable.And uh you know, part of what is both scientifically very exciting, but also I think brings all these questions into the foreground is just how quickly AI has moved.
Even over the past year.Like a year ago most people like coded roughly by hand.They would like go into the into the code editor and write code.And now people are mostly just talking to agents.So the speed at which everything is moving is is quite staggering.Um And I think a lot of what the a lot of the concerns are are heightened and a lot of the fear is heightened by the fact that um like if things are moving this fast, where's it goingto be in a year?Where's it going to be in 2 years?The government and the public react on a much slower time horizon than the pace of AI progress.And so, by the time in 1 year or 2 years or 3 years or how many however many years forward, when um the public and government are really deciding what they want to do, who knows like where AI's
going to be at that point and how fast it's going to move.So, that's one of the things I think explains some of the dialogue.Um I think the other thing that kind of explains some of this is the level of collection collective action necessary and the level of general mistrust um that exists between the various AI leaders towards one another.And this is like well covered, but one major justification for folks is that like oh, I am responsible and I'd be responsible, but those guys aren't responsible.Whether those guys are, you know, another AI company or China or, you know, who knows what boogeyman.So, I can't slow down.Otherwise, those guys who are irresponsible are going to, you know, who knows what they're going to do.Um and that basic logic, I think, is very confusing because I think for most people um uh the kind of like common sense answer is well, who cares what the other guys are doing?
Like you have to you have to do what feels good to you, right?And like you should do what's within your ethics, but I think that's also what complicates a lot of this.I think a lot of what is necessary is like it's almost diplomacy is the right word.Like how do we get this group of people who all who don't really trust each other that much, but all agree that like this is really powerful technology, and we need to we need to figure out how toland it and how to how to make sure that we develop it responsibly and that things go well.Like how do we like make all of this work?And we're at the moment of like peak insanity, I think, for that because it's like in the public, all these problems are being like aired out.Like we can all we can tell that nobody trust each other and we can tell that people are kind of are are being really worried like maybe a little bit before the AIs themselves are getting to the point
where they're deserving of that worry.And so I mean I ultimately think the the most important thing is to like get everyone to agree to some common foundation and base and then develop some process by which we can all reevaluate and consistently look atit and say "Hey, we all agree actually that you know, we need to be doing this now and we all need to be doing this other thing now and we all see like the models are getting powerful inin certain ways.Like let's all let's all look at this together."And I actually genuinely believe for what it's worth like that having these like collective dialogues is not only going to be possible among the AI leaders within America, but also going to be possible internationally.Like I think we have a all have a shared interest in making sure this technology does not go horribly wrong.
The host asks how China changes the AI race, and the guest reflects on shifting views about international competition. The discussion emphasizes shared incentives, the need for cooperation, and the role of government-facilitated accords in building trust.
Yeah, I mean the the obvious next question is the China of it all.I mean you've talked about how this is a big concern.People don't trust each other at the top of these AI companies, but they all often say, "We have to go as fast as possible because what if China gets there first?"I mean you Ted Cruz is out there saying like we would rather have US killer robots than Chinese killer robots.
If they're going to be killer robots, I'd rather they be American killer robots than I Chinese killer robots.
Which I think scares a lot of people and also
to say it mildly.Yeah, this is a spectrum of American law existing American law.This does not include any global dynamics, not to mention like long-term collaboration.How do you evaluate this spectrum given the China of it all and and what what is that even mean?Like how should I think about China with respect to this dynamic?
I've actually like personally even changed my own opinion on this matter.Like I think in the in the past I was very worried about China and I was very worried about what that dynamic looked like and I had read these like speeches that were given by PRC officials in thepast that talked about how they viewed AI as like this this opportunity to leapfrog the West and you know these these are the concerning things when you read them.But as time has gone on, I think that we're painting them out to be too much of a boogeyman when in reality um they're going to see the same things that we see in terms of this is powerfultechnology and we as a humanity need to get this right.There's going to be a lot of shared goals in making sure that AI goes well and I think um and I think it really is possible to arrive at some form of international cooperation.
I think that the Chinese government, like any government, has an interest in ensuring that there's stability in their society and that um they don't lose control of this technology and uh that overall, like, you know, things go welland we don't have catastrophic existential risks.And so there's quite a bit of shared ground that I think will will enable everybody to be rational and think rationally and and ultimately make the right decisions.Um and even though it seems totally insane right now and it seems like it seems like in some ways that feels impossible, I really have faith actually that that as people see more and more and learn more andmore about the technology um people will make the right calls.
You have recently become one of the 20 most important people in that conversation in the United States.You've been very important in AI in the last couple years.I mean, I think people remember seeing you in the headlines when you came to Meta.I think this, you know, isn't brand new to you.But in the last couple weeks, you have designed and released a product that is being used by more people than ChatGPT was in its first couple weeks.It feels like you have been thrust into a new kind of part of this conversation.Where frankly, people have will be asking you more questions like, where exactly Alex do you fall on this spectrum?Like, what would you want to see because you're one of the people responsible.Do you feel like you've come to those conclusions yet?
Yeah, I think I think like anyone who works on this technology, these are things that I've like been thinking about for years and years.Truly the way I think about what I want to do and what I want to accomplish and how I want to shape this conversation is like enable everybody to have a common dialogue and then get to the rightplace collectively.Like, I don't think at this point in the conversation it's like that helpful for me to say, oh, I believe this and you know, you all should listen to me because, you know, I built Muse or whatever.We already have a bunch of people.They all believe slightly different things.Um, ultimately, this is a technology that we need like collective action on that everyone needs to agree on, that we all need to get to the right place.So, what I really care about is like, how do we facilitate and have the relevant dialogues in public that and private that enable us to get to the point where we all agree on a path.
And one of the very, um, strange things for me is like I know a lot of these people and I've met them.They're all brilliant, um, but the degree to which certain personal animosities are like actually defining what people say and do and like how they're developing this really important technology is, um, is insane to me.It is, in some ways, a very human story that like feuds or like just the fact that like I really don't trust this other person can can like snowball into this like civilizational level, um, problem.Um, but I don't think that serves any of us.Like, I think ultimately we have to all put our differences aside, put our histories aside, and just figure out how we solve this together.
It sounds very general, but that's a fairly specific ask.I mean, there are constraints that prevent that right now.There are antitrust regulations that prevent a lot of those conversations from happening.And one of the proposals, one piece of many proposals that Dario put forward is waivers from those antitrust laws that would allow those kinds of conversations.I mean, tell me if I'm wrong if there are secret conversations happening, but I don't think there is first the agreed-upon group in the United States that's having that conversation.And then also, like, how do we even begin to have those conversations with China?But actually, what don't I know?Is that something that's happening in in, you know, some private room somewhere?Or is it that like we're still at the beginning of that and we need to figure out how to do it.
Um I don't think it's happening right now.At the White House, there was this dialogue um and this these accords put forth, which are real step.Like, I think there's um getting everyone to agree to something is like that's really big.
Everyone agrees on something.And I think that one that thing, which is basically saying, "Hey, we're going to every company is going to set out and develop what their internal controls and principles around developing this technology look like."And then there's going to be multiple layers of verification on that from internal teams that verify to uh external auditors that validate that they're following those controls to board-level committees that ensure they are following those those um controls.Like, I think that's a great step.Um cuz in in many ways, a lot of what's needed right now is just transparency.Like, we just need to ensure that, you know, people are going about this sanely and rationally.And I think in some ways, like people don't even trust that necessarily.As an industry, we have a lot of trust building to do.I am an optimist.I think you're an optimist.
Like, I think we're all optimists.Like, I really do think these conversations will naturally happen.This last accord that I referenced, like, that was in the White House.The government helped facilitate that.And so, I think we're going to be seeing a lot more of that.
The final section returns to the optimistic case for AI: helping people reclaim time, pursue bigger dreams, and live more fulfilled lives. The guest closes by arguing that Muse should help people get more out of life, and reflects on how he hopes to be remembered.
It's going to be bumpy.There'll be moments of total confusion and chaos and like, what the heck is going on?But, I see progress, too.
I'm glad that we've spent a lot of this conversation talking about safety and regulation.How do we bring it back now to the optimistic vision of the future?I think the question a lot of people will naturally have after a long conversation about trust and safety is why bother doing this at all?This is the moment in the SNL sketch where it's uh you know, if there's a 10% chance that something will kill you, but it'll probably make your life better.Like, wouldn't you do it?And the other guy's like, "No.No, I wouldn't."
No!
Really?Can you help people answer that question?Like, why do this?
Something that I have always felt was a bit tragic was that I think um almost everyone, when they're kids, they have big dreams and big ideas and they want to change the world and they want to save theplanet and they want to, you know, uh write a book or make a Broadway musical or make a movie.Like, they have really they have tons of hope and then for some reason or another, by the time that people finish school and they get a job, that like flame kind of dies and people really um they stopdreaming big and they stop having big ideas and hoping for big things and hoping for lots of change.And especially today, like I think a lot of young people get really cynical and they're like, oh, the world is horrible.And it is and I don't know why it's so insane in so many ways, but I guess this is just the way it is.
They lose faith that they have an ability to enable that change.And I genuinely think one of the promises of AI, and especially something like Muse where you give AI to every single person in the world is that this doesn't happen.That people can have big ideas and big dreams and wants and and goals that they can have as little kids, they can have when they're teenagers, they can keep having through adulthood, and that you know, an AI superintelligentsidekick is there to help them just make all of that happen.And that can be everything from like big wants and big dreams um to like small wants like, "Hey, I just want to spend more time with my kids."Or "I just want to spend more time with my parents."Or "I just want to like eat healthier."Um all the way up to "Hey, I have this like crazy idea for um like a a museum that I want to start."
Like my my partner really wants to make a museum of ice.I think it's like hilarious, but um
Ice is crazy.There's a whole amazing story about the evolution of cold, of how we keep things cold.It starts with ice.It's pretty cool.
Yeah,
I'd go to the museum.
Exactly.And and people have these ideas, and then they just can't you know, in some ways young people are right.Like the world today is just kind of a maze of like roadblocks and issues and challenges and logistical um you know, uh things that get in your way to make those things happen.And in a small way today, I'm seeing Muse make this problem better.Like I'm seeing people using it to save time, save money, like take the little stuff off their plate, and just give them more and more agency, more and more freedom, more and more of an ability to spend theirtime on the things they want to do.And I think one of the promises of AI that gets better and better and better, gets not only smarter, but also more aligned and more trustworthy, is that you can give it bigger and bigger ideas.
And you can say, "Hey, I want to start a museum of ice.Like tell me how to go about doing this."And it'll tell you, "These are the buildings you can lease, and this is who you can contact for funding, who might be passionate about ice, and um this is like how you should think about curating your exhibit, andyou know, uh what what that might look like.And I think for some people like you or me who have experienced this this like journey of having big ideas and then like going through all the crazy maze of things to make that happen, it is like reallymagical.And it's really special, and I think it's something that um you know, I think human stories of people who have a dream and then accomplish those are the most like are some of the just the most beautiful things
that I can possibly imagine.And I really truly think with AI and like everyone with a little new sidekick, like more people can experience this.I My hope is that everyone, literally like all 8 billion people in the world, experience that and have the ability to do it.And that is just like a very special world to live in, I think, if we can make that happen.And I think more people will be able to get what they want out of their lives and and live more fulfilled lives, and it'll be magical and exciting, and that's what what I really think the promise is forfor people.And I think part of what is so confusing is like um you know, oftentimes people in AI we say like, "Oh, AI will cure cancer."And I think everyone wants cancer cured, but every individual person has something they want intensely, and they want even more than I you know, ironically speaking, a cure for cancer.
Um and so, I think that's part of the magic is that we talk about this thing personal super intelligence.Like, it will help you at the thing that you want and the thing that you dream of.And um and that will change over your life, and you will be able to accomplish many dreams and many wants.And I think that's what's uh the promise of of AI.
That dream has within it a belief, I think, which is that people do actually have big dreams, and that those big dreams will more often than not help other people.So, when we hear people say, "Hey, I will cure cancer."Sometimes perhaps they're talking about you prompt an AI and it thinks up the cure for cancer, but much much more likely it's the AI facilitates the individual ambitions of millions of cancer doctors and together we accelerate the progresstoward cancer.It's making me think, you know, when I hear people talk about Muse and say like, "What do people need an AI assistant for?People don't have those dreams."Like, what a limited view of people of other people.You know, I don't know what those are and it's not up to you or me to say which dream is more worthy than the other to your point big or small.
My view on people is like they will have moments of inspiration where at some point or another they will realize like, "Wait, I really want to do this thing."I want everyone who has one of these ideas to be able to tell their Muse, "Hey, I have this big idea."And their Muse will just like secretly behind the scenes help them figure out how to make it happen.And I think part of this is also fanning the flame, so to speak.Um I think for a lot of people they will have like a small want and then it'll happen.And then they'll dream a little bit bigger and then they'll actually happen and they'll dream a little bit bigger and they'll actually happen and um and as that goes on people will sort of uh like realize that AIcan be so much more, that Muse can be so much more, that you know, they can um that they can do so much more.
This won't happen overnight.This is something that will take time and everyone will have to experience on their own and I really hope everyone experiences.Um but I think over like like generations I think can be like absolutely magical.
You know, I think especially the way that you're in the press and talked about and you kind of naturally become sort of a caricature of yourself.There's like the character of you out there in the world and this has helped me get to know you better, because there seems like a common theme in some of your answers, which is Muse is a way tofacilitate other people's dreams, because you have a belief in people and their goodness and their ability to improve the world and just the sort of value of their ideas.And it seems like you are directing Muse in some ways, but you're not saying this is for coding or this is for X specific task.You're watching and and facilitating.And when I asked you where you fall on this, your answer was I'm interested in the collective wisdom of the group.
I'm interested in facilitating or being part of a conversation between other people that we have a lot of smart people all around the world, and I don't feel like it would be that useful to say here's exactly myopinion on where exactly this should be regulated.I see the best outcome as coming from a group conversation of many different people with their many thoughts and and wants.Do you agree with what I've just said?
Yeah, I think cuz there are so many big questions about AI, and it is like something that everyone has a point of view on and should have a point of view on.And part of I think what's amazing about democratic institutions and democratic countries and and democracy broadly speaking is that it matters what everyone thinks, and we have to figure out how we like take this like complex jumbled ummass of what everyone thinks and channel that into the right thing happening.And another thing is like part of what has held AI back and I think part of the problem of AI is how it almost feels like the people building AI are talking down on other people.It's like hey, I am building the smartest thing you've ever known.It's going to be way smarter than you, and I know exactly what we're going to do with it.
And I think rightfully people are like wait, what?Like
what does anything you just said have to do with me?And and like how is this even good for me?And then you're like, oh, it'll cure cancer.I'm like, okay, but what else?Like
to believe you or yeah?
Yeah.And so I think that especially given the moment that we're in and to your point like how much fear there is about AI and how much uncertainty there is and how confusing everything that's being said is like umI think the most important things are like first, let's have everyone experience it.Like let's have everyone actually like understand the hype for about lack of a better term.Like feel what AI agents can do for you and can do to make your life better.And that'll give you perspective as to oh, this is a technology that yeah, it's definitely risky and and there's there's tons of risk.Don't get me wrong, but it also is really great and I like it and I want to make sure at least some form of it continues and I can continue using all the way to, you know, the these
like big questions and these big dialogues like how do we just get everyone to a place where we all agree and we can find a path forward and I think I have enough humility that like these guys are,you know, they're big important people.Like I don't know if I have much to add, you know, um given their points of view, but I just want to make sure that we I facilitate is really the word that keeps coming to my mind.Like how do we move quickly to all collectively come to informed opinions and um and then come to a process where we agree on something.
This is the question I ask everyone at the end of these huge conversations, which is when I think about after I'm dead and after people say that she was a really great family member and she loved her husbandand she loved her friends.I would want them to talk about the mission of this show.I would want them to talk about how I tried my best to help people see ways the future could go well because I really believe as it seems you do in other people, in their perspective and when theysee a vision of a future they believe in that they're going to actually try and help make it happen.Like that's the point of what I spend all of my working hours doing.You're obviously just starting out.You've already had this huge impact.You have a lot farther to go, but I'm curious when you think about how you want to be remembered after you're gone.
What do you want people to say?
Um First of all, what a nice what a nice um idea and concept.Um I think I think for me I will want people to say that the things that I built and the things I contributed to um helped everyone get more out of what they wanted out of their lives.
Beautiful.Thanks for doing this.
Thank you.