Seven creators, $1,000 a week in AI tokens, one summer

Possible

Reid Hoffman and Parth Patil recap the 'Tokens to the Future' program, which provided seven creators with $1,000 weekly in AI tokens for exp

Key takeaways

• The 'Tokens to the Future' program demonstrated that diverse creators use tokens to map out the long-term frontiers of AI.
• AI agents are evolving from simple tools into proactive personal assistants that act as a cognitive 'exoskeleton'.

Main topics

• Tokens to the Future program recap
• Human-AI collaboration and orchestration

Notable quotes

You have to burn tokens to learn tokens.

Conclusion

The episode highlights that as AI masters execution, human excellence

Transcript preview

Speaker 2 (0:00) You want to combine the superpowers of these AI agents with our superpower. The likelihood that we actually, in fact, are much better in collaboration is high. Speaker 3 (0:09) Arguably, probably the most important agent is that personal agent, the one that is looking out for you. How Speaker 2 (0:14) do we orchestrate to something that's really new, that is improbable? I think that there is a much more enduring role for us. You know, one of the things we've been doing this summer has been this great Tokens to the Future program. Speaker 2 (0:29) And, you know, Parth has been the primary architect of this because it intersects his, you know, personal mission to try to get everyone understanding how to get on their, you know, surfboards and, you know, kiteboards and e-foils and everything else, you know, windsurfers and get into AI. And, you know, undoubtedly it's a bunch of the token grantees have been a bunch of people Parth's met. and are doing creative things. So Parth, why don't you kick us off on our summer kind of wrap up? Speaker 3 (1:05) This year, this summer, we did something very experimental, something new and interesting. We ran this token grantee program and we picked seven grantees this season. We picked people from a wide range of industries, everything from creative to media to security, coding, game development, robotics. really picked a pretty wide group of people. And we basically deployed $1,000 a week in each person's hands to deploy AI, to experiment with technology, see what's possible, see what new capabilities are coming online, explore the frontier. And I mean, I had my expectation going in like, oh, this will be fun. I genuinely think you have to burn tokens to learn tokens. You have to like... you have to it's a 10 000 prompts right you have to put 10 000 prompts in to understand even a fraction of what's coming out of these models um especially with how good they're getting and i can't do that alone so i i had to pick people i thought that would help me map this out people that had their own you know unique superpowers and interests and passions people that could see the many frontiers of of this this kind of like moment in ai and so we created this program and I think it's been, you know, it's, it's been very eyeopening. It's, it's surprised me in so many more ways than I expected. And I guess like, I'm really excited to have, you know, I'm really excited to talk about it and recap this and hopefully inspire others to run similar programs, you know, others to also pick up the tools and experiment and see where the frontier is headed. Speaker 2 (2:38) So, you know, you handpicked this group of grantees, which I think was exact right way. to start. And, you know, again, as it was mentioned, it's kind of like it's different zones, but in depth and with a willingness to be, you know, bold pioneers across this kind of AI landscape. So looking back at the season, you know, what patterns show up for you across them? And especially those that you didn't design for because you had a going in theory, like what? What emerged? One thing that surprised me, okay, Speaker 3 (3:17) maybe Speaker 2 (3:17) I was biased towards the tools that I had already used. And I was like, Speaker 3 (3:20) oh, you know, people, everyone's going to want to use this model. And then I realized like, well. actually like the different the best model for the task might be different or you know the best model for the workflow might be different and so i was like and just watching where people like oh i'm gonna spend you know i'm gonna spend the tokens on this set of video models this set of image models because it unlocks this new format and storytelling or i like these are the coding agents that i like so it's very interesting getting to see like oh you know, why do you like that agent? What's special about that agent? You know, factory AI, like the factory approach to software. Why do you like this versus like a quad code or a codex? So seeing a wider range of the, because I can only see as far as the tools that I use, but then seeing all the other tools that I'm missing, it shows that there's a pretty healthy ecosystem of options out there. But I think one of the interesting patterns, I think every single grantee demonstrated was that So independent of where AI is right now, they're kind of projecting out the capabilities over a six month, two year, three, four year timeline, right? So AI is like good at X, not quite good at Y. But they're all aware of those limits in the current form. And none of them are like, well, it'll never be better at that thing. They're actually, there's this common mindset of like, once it can do this, then these are the seven things that we're going to want to do with it. And so they're kind of like. drawing that exponential out a little bit and helping us paint a picture of like well when you can you know if you can use a use a video model and two people can tell a short story well how far is it from you know what kind of short story can you do science fiction can you do you know can you do a western can you do a western sci-fi and then how many people can make like a longer form movie and so the connecting the dots Helping us connect the dots on like where this is going over a three to five year timeline is something that is probably every single person did in their own way, in their own domain, right? So whether it was robotics, whether it was storytelling, film, game development, coding, we can kind of see a little bit further into the future because people are in the areas they're very passionate. They're able to kind of see and connect the dots on some of the what the model capabilities are going to make bring online in the next couple of years. Speaker 2 (5:33) We're going to dive into, I think, some of these specific patterns. But before we get there, I think one of the things that's important about this kind of frontier work is what it means to be AI native. And I think part of the thing to kind of go into kind of what AI native is, is what does that mean, how you operate as an individual, you know, kind of, you know. kind of my classic, all the way back to startup of you, you know, kind of stuff is OODA loops and decisioning and activity and, you know, exoskeleton, you know, how do you become, you know, you know, I am Ironman, you know, kind of as an, as an angle. And I think one of the things that we saw is it's not coding pedigree. It's not per se technical background. It's a, it's kind of a mindset. And so. What did, across all of this, you know, what did you kind of say, hey, this is how my sense of being AI native evolved, you know, for like what, how you, because actually you were also asking questions. You should say like how you are AI native, then how that evolved and then how that, how we should be helping people think about that. Speaker 3 (6:52) Yeah, I think. You know, there's the themes of kind of, if I think about the shape of the superpowers that are coming online, there's the superpowers in automation, you know, being able to automate things using agents, but then what should we be automating? And then that's a judgment call, right? So the superpower of being able to use code to, you know, blitz through cognition is really interesting. But then what becomes more important is like, well, when should we not do that? When should we use our judgment? Now that we can scale our cognition, what are the things that uniquely require the human taste and the human experience? And part of this is not thinking of everyone as, I'm not just a data analyst. You're not just an investor. We're actually very multifaceted. You have an engineer, but it's not just an engineer. It's much more interesting when you take that person and you look at them as a multifaceted. you know, person with many, many passions and interests. And then when you think about the more general human, the general human with many, with many different facets to them, the way they use AI will always surprise you because we're not one dimensional people. Right. And so this is why I thought it was really important that we would bet more on people and not on like specific roles or categories, right? Because people always surprise you when, when you kind of like. give them a chance to explore and expand the way they think. Speaker 2 (8:24) Let me add a little bit to this, I think. Because I think part of, you know, one of the things I can add since you've selected all the people is I think part of the thing is people frequently think of work or process too mechanically versus organically. And a little bit of what I like about kind of investing is You know, one of the major things I like about investing is kind of betting on people. And I think that part of what we saw is we kind of went across all of these, you know, very different fields, you know, film, social, VFX, security, gaming, energy. You know, the same shift showed up in each of them, but that's because the people are being pioneers across them. And I think that part of the thing. is getting this kind of shared mindset this kind of curiosity exploration pioneering um willingness to experiment i mean like one of the things that you know i try to give people advice is if you're not trying to do things with ai that don't work you're not trying hard enough on the edges right and like doing things you shouldn't wait until i don't know i'm gonna wait until i know exactly what works and then i'm gonna do that it's like no no you you're like we've all landed in this this this This like magnificent new world with lots of new capabilities, lots of new possibilities. And so it's people doing them. And I think that's one of the great things we did with you selected a great group of token grantees. And we saw their. curiosity and their boldness and their willingness to set off on new terrain and new journeys. Speaker 3 (10:02) So going back through everyone's conversations reflecting on the summer so far, I think like at least two totally different ways people use the tokens, use the intelligence jumped out to me. And a lot of that actually went into building, a lot of people were building games. And I think, you know, I like games, you like games. Maybe I pick people that also like games. These are the people we like. But what do you make about that? Like, what do you make of that? Like a lot of people were like Dungeons and Dragons inspired in the past and like how that, is there a connection there to like why people make things? Speaker 2 (10:38) Well, you know, there's this, one of the things that comes into kind of talking