2 Ex-AI CEOs Debate the Future of AI w/ Emad Mostaque & Nat Friedman | EP #98

Summary

在这段视频脚本中，讨论了人工智能（AI）的快速发展及其对社会的深远影响。提到了5G投资和AI的比较，强调AI在多个领域的能力已超越人类，并预测了AI的未来发展。讨论了AI模型的内部工作原理，尽管对其工作原理尚未完全理解，但AI的“成长”方式类似于人类大脑的思考过程。强调了开放模型与专有模型的不同，以及它们在促进创新和适应性方面的重要性。还提到了AI在医疗、教育和科学领域的应用潜力，以及AI如何帮助解决复杂问题，如疾病诊断和药物设计。最后，强调了AI作为人类智能的延伸，将如何增强我们的能力和创造力，以及如何通过AI实现个人和组织的目标。

Takeaways

• 🚀 过去一年AI领域的快速发展，特别是大型语言模型的应用，已经开始对各行各业产生深远影响。
• 🌐 5G投资巨大，但AI的影响力可能更大，因为它关乎智能和决策能力的提升。
• 🤖 尽管AI模型的能力日益增强，我们对其内部工作机制的理解仍然有限，需要进一步的研究和解释性领域的探索。
• 📈 AI技术的快速发展带来了对标准化的需求，以及对数据透明度和模型可解释性的重视。
• 💡 AI的快速发展为医疗、教育和科学研究等领域带来了新的机遇，有望解决以往难以攻克的难题。
• 🌟 AI的“开放模型”与“专有模型”之间的比较，强调了开放模型在创新和适应性方面的优势。
• 🔍 AI在图像和视频生成方面的进步，展示了从静态图像到动态视频的转变，以及实时编辑和控制的可能性。
• 📊 AI的商业化进程正在加速，从初创公司到大型企业都在积极探索AI的商业应用。
• ⚙️ AI的自主性和代理性是未来发展的关键，能够执行复杂任务的AI代理将极大提高效率和创新能力。
• 🌱 AI作为人类集体智慧的扩展，有潜力解决全球性问题，并推动社会向更加智能和自动化的方向发展。
• ⛓ 随着AI技术的进步，需要考虑其对就业市场的影响，以及如何培养未来所需的新技能和职业。

Q & A

过去一年中，AI领域有哪些重大的发展？

过去一年中，AI领域的发展非常迅速，特别是大型语言模型（LLM）的商业化。例如，GitHub Copilot的发布，以及随后的Chat GPT、Stable Diffusion和GPT-4的推出，都展示了AI在理解和生成文本、图像等方面的新水平能力。

5G和AI相比，哪个对现代社会的影响更大？

虽然5G技术非常重要，但AI对现代社会的影响更大。AI不仅改变了数据处理和分析的方式，还推动了自动化、个性化服务和智能决策的发展，其影响力远超5G。

AI模型的内部工作原理是什么，我们真的了解它们吗？

AI模型，特别是大型神经网络，是通过大量数据训练而非直接设计得到的。尽管我们可以测量模型的每一个权重和连接，但对于模型内部的具体工作机制，我们的理解仍然有限。这类似于我们对大脑工作机制的理解，尽管可以观察到神经元的活动，但对其深层次的认知过程了解不足。

AI在医疗领域的应用有哪些潜力？

AI在医疗领域的应用潜力巨大，包括提高疾病诊断的准确性、个性化治疗计划、药物设计、以及通过分析大量医学文献来发现新的治疗方法。AI还可以帮助患者和医生更好地理解疾病，提供定制化的健康建议。

AI如何帮助解决科学问题，特别是在生物学和化学领域？

AI可以通过分析和学习大量的科学数据，帮助科学家发现新的科学规律和原理。在生物学领域，AI可以帮助设计和合成蛋白质，加速药物开发过程。在化学领域，AI可以预测化学反应的结果，帮助设计新材料。

AI技术的发展速度有多快，我们如何适应这种快速变化？

AI技术的发展速度非常快，每年都有新的突破和应用出现。为了适应这种快速变化，个人和组织需要不断学习和更新知识，同时积极寻找将AI技术应用到实际问题中的方法。

AI技术的进步对社会和经济有哪些潜在的影响？

AI技术的进步可能会极大地提高生产效率，改变劳动力市场，创造新的就业机会，并可能导致某些职业的消失。同时，AI也可能加剧社会不平等，因此需要政策和教育的配合来确保技术进步惠及社会各个阶层。

AI在教育领域的应用有哪些可能性？

AI可以在教育领域提供个性化学习计划，辅助学生理解复杂概念，自动评估学生作业，以及提供虚拟助教来解答学生问题。此外，AI还可以帮助教师更好地理解学生的学习进度和需求，从而提高教学质量。

AI的可解释性是什么，为什么它很重要？

AI的可解释性指的是理解AI模型的决策过程和内部机制的能力。这对于建立对AI系统的信任、确保AI的公正性和透明度、以及优化和改进AI模型都非常重要。

如何平衡使用开放模型和专有模型的优缺点？

开放模型允许用户访问和修改底层代码，适合需要定制化和隐私保护的应用场景。专有模型则提供服务，但用户无法看到底层代码。两者的平衡取决于具体的应用需求、隐私和安全性要求，以及对定制化程度的需求。

AI在艺术创作中的应用有哪些？

AI可以在艺术创作中提供灵感，生成新颖的设计图案，辅助音乐作曲，甚至创作视觉艺术作品。AI还可以帮助艺术家探索新的创作风格和技巧，但AI艺术作品的创意和表达仍然需要人类的参与和指导。

Outlines

00:00

🚀 5G与AI的快速发展及其影响力

讨论了5G投资和AI的快速发展，强调AI的潜力和影响力远超5G。提到了AI模型的内部工作原理不完全透明，尽管我们可以测量一切，但仍不完全理解其内部机制。强调了AI比人类更有能力，并且这种能力将不断增强。讨论了AI在商业化和产品开发中的应用，以及需要围绕AI制定标准和法规。

05:03

🌟 开放与封闭AI模型的对比及未来

解释了开放模型与封闭（专有）模型的区别，开放模型允许用户自行调整和使用，而封闭模型则作为服务提供。讨论了开放模型如何促进创新，并且已经有数百万次的下载。同时指出，尽管专有模型在技术上可能始终领先，但开放模型允许用户针对自己的数据进行优化，因此两者都需要存在。

10:04

🎨 AI在图像和视频生成中的进步

讨论了AI在图像生成方面的巨大进步，包括速度的提升和对生成图像的控制能力。提到了AI模型如何结合Transformer架构和扩散模型来生成图像，并且展望了未来视频游戏和视频内容的实时生成能力。

15:06

💰 AI的商业化和资金流动

讨论了AI在商业化方面的进展，包括收入和盈利能力。提到了Fountain Life公司，它提供先进的诊断服务，使用AI和医生团队来发现疾病。强调了AI在医疗保健领域的潜力，以及它如何帮助人们延长健康寿命。

20:08

🤖 AI作为企业和个人的合作伙伴

探讨了AI在未来企业中的角色，预测AI将如何成为企业运营的核心部分，以及AI原生公司的发展。讨论了AI在特定任务中的超人能力，以及如何将AI集成到业务流程中，提高效率和创新。

25:09

🌐 AI的全球影响和治理

讨论了AI对全球经济的潜在影响，以及如何通过AI创造财富和税收基础。提到了一些地区如何通过制定新法规来吸引AI公司。探讨了AI在长文本处理和上下文理解方面的能力，以及这些能力如何帮助创建业务和内容。

30:10

🚀 AI的未来发展和投资

讨论了AI的未来发展，特别是其在教育和健康领域的应用。强调了AI作为下一代人类操作系统的潜力，以及它如何增强我们的能力。提到了AI投资的增长，以及它可能对全球GDP的影响。

35:11

🌟 AI在医学和科学发现中的潜力

讨论了AI在医学诊断和科学研究中的潜力，以及它如何帮助发现新的治疗方法和科学原理。强调了数据集透明度和模型可解释性的重要性，以及AI如何帮助我们理解和应用现有的科学知识。

40:13

📚 AI对教育和知识获取的影响

讨论了AI如何改变我们获取和应用知识的方式，特别是在教育和科学研究领域。强调了AI在提供个性化指导和连接患者信息方面的潜力，以及它如何帮助我们解决健康和科学问题。

Keywords

💡5G

5G是第五代移动通信技术，它比4G快100倍，能够支持大量设备连接，为物联网和智能城市等应用提供基础设施。在视频中，提到了5G技术的投资，暗示了它对未来通信和AI应用的重要性。

💡人工智能（AI）

人工智能是模拟人类智能行为的技术，包括学习、推理、自我修正和感知。视频中讨论了AI对人类社会的影响，以及它如何比5G技术更具影响力。

💡机器学习模型

机器学习模型是AI中用于数据分析和预测的算法结构。视频中提到了对这些模型内部运作的理解有限，尽管它们的能力已经超过了人类。

💡标准化

标准化是指制定共同遵循的规则和指南。在AI领域，标准化有助于确保技术的一致性和互操作性。视频中提到了围绕AI技术的标准化需求。

💡投资

投资指的是将资金、时间或资源投入到某个项目或领域以期望获得回报。视频中讨论了各国和公司对AI技术的大量投资。

💡深度学习

深度学习是机器学习的一个子领域，它使用类似于人脑的神经网络结构来学习复杂的模式。视频中提到了深度学习在AI发展中的作用。

💡商业化

商业化是指将技术或发明转化为商业产品或服务的过程。视频中提到了大型语言模型的商业化，以及它如何推动了AI技术的快速发展。

💡GitHub Copilot

GitHub Copilot是一个AI配对编程助手，它可以帮助开发者编写代码。视频中提到了GitHub Copilot作为大型语言模型商业产品的例子。

💡开放模型与专有模型

开放模型是指源代码和权重对公众开放的AI模型，而专有模型则是封闭的，不公开其内部工作原理。视频中讨论了这两种模型的优缺点和它们在AI发展中的作用。

💡模型的可解释性

模型的可解释性是指对AI模型的决策过程进行理解和解释的能力。视频中提到了尽管可以测量模型的所有参数，但对其内部工作机制的理解仍然有限。

💡AI的未来发展

AI的未来发展涉及对AI技术进步速度和对社会影响的预测。视频中讨论了AI在未来可能达到的能力和对社会的潜在影响。

Highlights

在过去一年中，5G投资达到万亿美元，但AI的影响力被认为更大。

AI模型的内部工作原理尚不完全清楚，尽管可以测量一切，但仍缺乏机械性理解。

AI的能力已超越人类，预计未来会变得更好，但需要围绕AI制定标准并扩大其应用。

过去一年中，AI领域发生了巨大变化，从Chat GPT到Stable Diffusion和GPT 4的发布，展示了AI能力的飞跃。

AI的商业化进程正在加速，例如GitHub Copilot的推出，预示着大型语言模型商业产品的浪潮。

Chat GPT的收入在一年内从几乎为零增长到20亿美元，显示出AI技术的商业潜力。

Google的Gemini模型展示了AI在处理大量数据和复杂任务方面的能力，远超人类。

图像生成技术的进步使得在几毫秒内生成图像成为可能，预示着实时视频生成的未来。

开放模型与专有模型的对比，开放模型允许用户根据自己的数据进行调整和优化。

Hugging Face平台的模型下载量达到3.3亿次，显示了AI技术的广泛采用。

AI的未来发展将更多关注于如何利用现有模型，而不仅仅是模型本身的进步。

资本正在迅速流入AI领域，预示着未来几年可能会有更大规模的投资和增长。

AI在医学领域的应用，如提高诊断准确性和患者护理，展现了AI在改善人类生活方面的潜力。

AI的长期愿景是成为人类集体智能的扩展，解决我们面临的所有问题，而不是被个别实体控制。

AI的快速发展可能导致社会结构和工作性质的巨大变化，需要思考新的就业形式和人类的角色。

AI在科学发现方面的潜力，包括新药物设计和未知生物学领域的探索，预示着科学领域的未来突破。

AI作为新大陆的发现，为人类提供了巨大的机会，建议人们积极拥抱AI并探索其可能性。

Transcripts

what I think happened in the last year

really is the starting gun was

fired we spent a trillion dollars on 5G

is AI more impactful than 5G of course

it is do we actually know what's going

on inside the models we can measure

everything and still we don't really

quite understand mechanically what's

happening inside them they're not

engineered and designed they're kind of

grown AI is clearly more capable than

humans now we know this is going to get

better

when does it slow down right now it's a

few companies doing this but we need

standards around it and we need the

expansion and again every country will

invest in this every company will invest

in

this we're here to talk about what

happened I almost to say WTF just

happened in the past year because a lot

has happened imod you were on stage with

me a year ago and things were amazing

then but a lot has happened so I want to

split this into a couple of Parts like

what just happened the last year and

then I want to talk about how how far

forward can you see what do you expect

is going to happen uh you know I'd love

to talk about the companies the models

the dramas what did Ilia

see I think that's going to become a

meme um Nat do you want to kick us off

what what what's the big things that

happened in the last calendar year in

your mind um well yeah it's it's been

kind of an amazing year I I do think for

people who just started paying attention

to the sort of new Ai and deep learning

revolution in November of 22 when chat

GPT came out uh things probably seemed

very fast because we had um stable

diffusion come out over the summer

previously in 22 we had chat GPT in

November and then just a few months

later GPT 4 came out sort of

demonstrated a new level of capabilities

that you know were shockingly improved

over what was there previously and so I

do think there's a set of people who

sort of um extrapolated from those three

data points in terms of the progress

that was going to happen from there and

it's incredible actually how quickly

people can adapt to these new things and

there was a point at which kind of chat

gbt blew everyone's minds and then a few

months later uh it was sort of just

something we accepted as part of the

world as part of reality and there and

we can very quickly enter this kind of

slump where's the new model gpt3 is four

is boring now when do we get GPT 5 come

on Sam put it out already what are you

waiting for you know this kind of thing

so I think we had a little bit of that

this year and then uh over the course of

the year though what we started to see

and and um I'd been waiting this for a

while for this for a while but we

started to see real adoption taking off

and so um you know back in 2020 gpt3 had

come out in 21 when I was running GitHub

we put out GitHub

co-pilot and uh was I guess one of the

first llm commercial products and I

thought that immediately after that

there would be this rapid wave of

commercialization of large language

models because developers would have

seen how capable they were what they

could do and start building products

with them but it really took this kind

of chat gbt moment before entrepreneurs

developers and product people started to

do this and so what I think happened in

the last year really is the starting gun

was fired on the actual um exploitation

of these ra capabilities the building of

products the working of them into

companies and organizations and now what

that's what we see the adoptions been

incredible chat gbt is rumored to have

gone from basically Z to2 billion doar

in Revenue in just about a year um

that's amazing there's uh you know

organizations like stability that put

out models that have you know hundreds

of millions of users um you have you

have mid Journey you have now Google in

the game finally with Gemini I thought

it was exciting to see them not only

release Gemini but very quickly follow

up with Gemini 15 and so there's a way

in which Google is clearly internalized

the pace here and the need to iterate

and ship and so that I don't think a lot

of people realize how far ahead Google

was for a decade yeah right so Google

had really developed a lot of the the

early Tech here and said it's not ready

for release right they were being

responsible uh to a great degree and

then and then how do you not release

after chat p goes gets released they're

shipping pilt now they're going to ship

they're going to going to ship yes um

Iman um the open model uh story that you

told us last year has really blossomed

and in fact it's become sort of a an

ethos in the organization right it's a

Elon is like really twisting the knife

in with uh with Sam and then says but

you know grock's going to be open now

can you talk about what's happened in

last year in in open will open Win do

you think and I'm curious for both you

guys and and describe what open is

versus closed for the audience here yeah

so proprietary AI is you don't see the

code the weights anything and it's

provided as a service whereas open

models and code are ones that you can

adapt yourself you can take bring to

your own data and you own and that's

important CU these models are something

a bit different they're like extensions

of our mind and so the best analogy I've

said is that these are actually like

graduates so they can code they can

write they can say they sometimes go a

bit crazy when they try a bit too hard

you know we'll give them better

education and so open models are like

graduates that you hire and then

proprietary models are like Consultants

you bring in interesting and in the

early stages we all needed Consultants

now people saying well I want this for

my own data I want this for that and

open allows for Innovation to happen so

we've had now 330 million downloads of

our models on hugging face wow um so we

just and what is hugging face for folks

it's GitHub but for AI models so it's

where you go as a developer download the

models and so people millions and

millions of developers are using this

technology but then you look at the

language model side people are taking it

adapting it and optimizing it um to have

innovations that now catching up with

even proprietary guys but they're

complimentary you will have your own

team and then you'll bring in the

Specialists and I think that's the best

way to think about this because you

can't Outsource your internal

intelligence from a personal company or

even country level to models that you

don't know what the provenant are and

this is one of the debates that we saw

over the last year the first step was oh

my God exponential extrapolation you

know as Nat said kind of actually the

foundations for this were dug like maybe

a decade ago and now we've been filling

in the cement and now we're all building

houses and we're like well the houses

will become skyscrapers so it was like

well they could kill us all and those

and those are valid things discussed

then it became about sovereignty and

well gp4 is amazing but I want my own

version as well for my own private data

and so I think as we advance proprietary

models will always beat open models

proprietary will always be what open

models open okay because you can take

the open model and bring your private

data to it and optimize it CU open

models are like generalized graduates as

it were but both of them need to exist

and I think we'll see both of them

continue to take off do we actually know

what's going on inside the models I was

listening to a conversation with the

chief scientist at uh uh anthropic who

will be on stage with us next year um

and he's saying we actually don't

understand really how these models work

is that is that a fair statement yeah we

I I mean I just just so you understand

all right it's like they're amazing but

we actually don't understand yeah how

how the weights and connections and all

are really working I mean we we

understand it at this like very micro

level you know we can see the

multiplications happening and we can see

the signal moving to the next layer in

the neural network but um it's actually

sort of similar although not the same

mechanisms to the way we don't have a

perfect understanding the way thinking

happens in our brains um we don't even

though in the case of our brains when we

try to you know do the neuroscience and

understand what's happening at the

neuron level and the organel level um

we're limited by our measurement right

we can't measure the state of every

single neuron in your brain while you're

thinking that would that's not something

we have the sensing technology to do now

that's not a problem we have with these

AI Minds that we're building we can

measure everything and still we don't

really quite understand mechanically

What's happen happening inside them

they're not engineered and designed

they're kind of grown you know they're

the products of us actually because we

have the internet which digitized the

world and put the sort of all the data

we've produced online and there's a way

in which that process of building the

internet was like a bootstrapping

process for building AI because it was a

precondition to making AI we digitized

the world we put all the contents online

and then we could use all of that to

sort of grow and train these AI models

but we don't quite know how they work

now there's a new field um new not in

time but but relatively small field uh

called interpretability which is about

trying to understand what's going on in

these things what are they doing how do

they make the decisions that they make

obviously there's benefits if you can do

that to making them better in all sorts

of ways you can make them smarter maybe

and make make better decisions and you

can also hope to make sure they do the

thing you want them to do and not not

something else um but it's new Elon put

a tweet out which I read during my

opening remarks that said by 20 yeah

we're going to have human level AI next

year and by 2029 AI will be equivalent

to all 8 billion people uh do you agree

with that emod um do you think it's

going to move that fast I think we had a

big discussion about generalized AI that

can do everything and that was the focus

of Deep Mind and open AI but for

specific tasks AI is clearly more

capable than humans now so for example

uh Google's Gemini Ultra model has a

million 10 million token context window

what does that mean it means that

someone can upload themselves debugging

a piece of code in the code base and

it'll correct it and no human could ever

do that you know Ram isn't big enough

you know on image now we can generate

images faster than anything songs in

seconds and other things so let's talk

let's talk about that a second um Sora

was I mean pretty like holy moment

right um and

someone is doing it right at open AI

with chat GPT and then Sora uh but I

remember last year you told us it used

to take like 30 seconds to generate on

stability a single image and then it was

down to a second and you've Advanced the

technology orders magnitude since then

yeah so I think um if we can put the

thing up but yeah put up the slide um

stable image yeah and then if we

actually go to the next slide talk about

speed here

um I'll should I click this let's see oh

we can click this to give an idea of

where it's gone so image was kind of one

of the things that kicked us off in 2022

all of these images can be generated on

a MacBook on a MacBook just from

description and now we've perfected text

and other things but the next step after

you can generate all these beautiful

images is that you want to move to

control so the models are just the first

step you have to have chat GPT and other

things to make them useful but then you

want to be able to take that guy and say

upscale and that's all we said and it

upscaled him you want to say replace a

lion with a cat and we can now do that

real time you know or tiger with a

unicorn replace background with a forest

forest so all of this you can do pretty

much real time because if you look at

the next slide from

this okay I'll I said it was 20 seconds

to 1 second this is live real time you

can just type and it automatically

adjusts the cat it gives them a hat but

then if you look at the optimization of

that with the next

slide oh back one we missed it this one

okay well we missed it go back one slide

sorry with this process here we're just

releasing a new distillation model today

we've got it to 200 cats with Hats per

second 200 cats with Hats per second so

that's your speed of of image generation

that's a new unit of image generation 50

milliseconds per image yeah exactly it's

cuz there's not enough cats on the

internet right so we're going to add

more cats to the internet oh 5

milliseconds 5 millisecs 5 milliseconds

yeah but I think with the new chips that

are coming and video is going to

announce another one we'll get up

towards 1 th000 images per second so

that's real live that's live video times

times times 30 yeah and so open ai's

Innovation there were two major things

there was the Transformer architecture

the language models and diffusion that

drive the media models they combine the

two together so our new image model

stable diffusion 3 which is the best

performing image model combines those

together as well so if you go forward a

few slides from

here skip um another one another one

that's the upscaling you know so you're

basically said upscale this image on the

left and you get you get the image on

the right you'll have that real time in

a couple of years so your boxy video

games will look a lot more realistic so

just literally as you're you can take an

old game and play it in real life yes

but if you go to the next slide these

videos with our video model all

generated on a consumer graphics card

with 5 GB of

vram so I mean the the point is it's

this is in everybody's hands it's in

everyone's hands and again we haven't

even optimized the data so in an hour uh

next

slide we're releasing in the world's

most advanced 3D model so all of these

are generated just from descriptions and

so the fastest version of this does it

in 1 second so you can generate that

Dragon but then the next step is you'll

be able to control every element make

its horns bigger make these adjustments

so how long would that take for a normal

creative person in kind of industry a

huge amount of time but now it works on

the edge and it works even faster in the

cloud so a future here where you can be

describing the video game you want

created and it's generating all the

characters and generating the play yeah

and so if you go back a few slides to

that thing with all the nodes I think

this is an important thing sorry I

didn't do the slides

properly I think one of the things that

we're having right now is this is a

system we buil called comfy UI that's

used by just about everyone now so you

take the face the pose the dress and

then you have the output but if I share

that image with you it reconstructs the

entire flow because last year was the

year of creation model that create then

chat GPT com UI allowed you to control

and compose them and the next bit is

bringing that all together because chat

GPT all the knowledge that you build

from writing your speech you don't have

files anymore you have flows with these

models and assets there and I think

that's the next step because you know

when you go beyond just spitting out

ideas to be able to control them like

that that's a huge

deal amazing uh and you're announcing

this in an hour uh the 3D models

releasing in an hour open source to

everyone give it up for emod

here um you really have uh I now don't

know if you're able to say this I mean

um uh you're uh driving revenue and Su

net profitability what's your financial

I can't say that publicly you can't okay

but it's going well we're ahead of

forecasts as can say all right he told

me backstage was good yeah okay do all

right yeah everybody I want to take a

short break from our episode to talk

about a company that's very important to

me and could actually save your life or

the life of someone that you love

company is called Fountain life and it's

a company I started years ago with Tony

Robbins and a group of very talented

Physicians you know most of us don't

actually know what's going on inside our

body we're all optimists until that day

when you have a pain in your side you go

to the physician or the emergency room

and they say listen I'm sorry to tell

you this but you have this stage three

or four going on and you know it didn't

start that morning it probably was a

problem that's been going on for some

time but because we never look we don't

find out so what we built at Fountain

life was the world's most advanced

diagnostic Centers we have four across

the us today and we're building 20

around the world these centers give you

a full body MRI a brain a brain

vasculature an AI enabled coronary CT

looking for soft plaque a dexa scan a

Grail blood cancer test a full executive

blood workup it's the most advanced

workup you'll ever receive 150 GB of

data that then go to our AIS and our

physicians to find any disease at the

very beginning when it's solvable you're

going to find out eventually might as

well find out when you can take action

Fountain life also has an entire side of

Therapeutics we look around the world

for the most Advanced Therapeutics that

can add 10 20 healthy years to your life

and we provide them to you

at our centers so if this is of interest

to you please go and check it out go to

Fountain

life.com back/ Peter when Tony and I

wrote Our New York Times bestseller life

force we had 30,000 people reached out

to us for Fountain lifee memberships if

you go to Fountain life.com Peter

will'll put you to the top of the list

really it's something that is um for me

one of the most important things I offer

my entire family family the CEOs of my

companies my friends it's a chance to

really add decades onto our healthy

lifespans go to fountainlife

decomp it's one of the most important

things I can offer to you as one of my

listeners all right let's go back to our

episode um I am curious about the idea

of how far are we from having an AI that

I can have a conversation with and say

I'd really like to create a new business

that does this this this and this and

just have that like a brainstorm partner

Ai and it will do the

incorporation um it will write the code

it will generate the marketing

materials um and it will be able to you

know we're all entrepreneurs here that's

all we you know find a problem build a

business find a problem build a business

how far are we from that that reality of

an AI created well I'll come back to the

second part in a minute but an AI that

can that can be your thought partner and

really sta up a company I think it's

it's already happening gradually um and

then maybe suddenly so we have I think

companies will these models are neural

they're neural networks and so I think

the right way to think about it is that

companies in the future will just be

increasingly neural and there will be

more and more of the company and what

used to be the Departments of the

company that are single models or swarms

of models that are doing work I think

it'll you know at some point probably

very soon we'll look back on 2024 and

say God do you remember when companies

had like hundreds of people in the

finance department doing accounts

payable and just like transforming

information from one form of text to

another essentially and doing this

coordination and um it so I think you

will have some form of both existing

companies that just adopt more and more

AI because it gives them advantages it

makes them more efficient maybe it gives

them better customer service people

enjoy the responsiveness intelligence

politeness Clarity Etc of the AI

counterparty and um you'll also have new

companies that'll be AI native started

from scratch neural from the beginning

so we you some people may remember when

Instagram was acquired by Facebook for a

billion dollars everyone was just

marveling at the fact that a a small

company 13 employees 13 people could be

worth a billion dollars how is that

possible and the joke was you know gosh

could you ever get down to a one person

company that's worth a billion dollars

and while like this is clearly going to

happen maybe eventually a zero person

company that's so we talked about this

getting ready and I said when are we

going to have a scenario where uh a

government and we have some governance

in the room here uh says we're going to

create a new regulation that allows an

AI to incorporate on its own in our

jurisdiction I think it's I think it's a

winning scenario because all of a sudden

the AI incorporates you get the tax base

and every AI Incorporated company will

move there I think Wyoming's done that

what's that Wyoming's done that they

have a new structure called aduna for a

decentralized autonomous organization

I'm s who has Wyoming Wyoming Wyoming

all places yeah yeah we have some

Wyoming fans here in the audience yeah

so technically that could happen

today amazing uh I mean I I do think

that that is a so the speed of wealth

creation

um how how should F so let's talk about

what are the wow moments that might be

possible in the next year what are some

crazy wow moments that might you might

see I I think one of the most important

things is uh the accuracy and then these

long context windows so explain what the

long context window is again so you're

absorbing information right now and it's

quite high definition because you can

see everything here and other stuff but

you're still writing it down and the

reason organizations get big is because

text is a lossy trans transmiss format

we lose so much context the final PDF

loses all of that stuff now with the new

Google models Nat has some amazing

companies in this space as well you can

upload hundreds of thousands of words

thousands of documents and the AI can

interpret them all at once there doesn't

need to be trained on it so you can

upload all of your ideas and say build a

business based on this and it will do

that or you can upload like a whole

bunch of movies and then tell it to

write a script that incorporates all of

that and it'll do that in reference time

that again is something super human but

we all have these massive like

repositories of all these ideas we've

had being able to dump that now and then

the AI without having to be trained spit

back answers ideas and things like that

I think is a really huge step along with

that composition step that kind I've

discussed before I think yeah I totally

agree with that I think there will be a

couple things coming probably pretty

soon um it's hard to predict exact

timelines on these things uh sometimes

things happen faster than you expect

effect and sometimes a little slower but

one of the clearly amazing clearly

possible now U products to build is a

voice too model that's indistinguishable

from talking to a human maybe for a

conversation of up to a couple minutes

where what happens after a couple of

minutes well maybe you can kind of just

tell somehow that it's not quite human

after a couple of minutes uh I'm I'm

setting a milestone that I think is

achievable this year maybe when if you

can do 2 minutes you can do 12 minutes I

I don't know um but uh

yeah you know you would it's it's

actually about all the Technologies

there it all just has to be integrated

and so you need the sort of the ability

to recognize speech is there the ability

to interpret it with a language model

and generate responses is there and then

the ability to turn that text into

incredibly realistic voices there and

kind of putting that all together into a

package that has very low latency that's

talking the way we talk where you can

kind of interrupt me and maybe there's

an avatar that's giving you this human

like I mean Aristotle was very

impressive but I knew that that was not

a real person right and so um I think we

could yeah he was a real person yeah

that's right and then I think the other

thing that's a very big deal is this

this idea of autonomy and agents um

there's been a lot of talk of it with AI

over the last year today these things

are not agents they're tools they're

call and response you go to chat gbt you

type something you hit enter you watch

the response kind of scream back and I

think what people don't necessarily

understand is that when these language

models are responding to you that it's

it's almost like a rap battle they have

a fixed amount of time to generate each

word and so they can't sort of sit there

and Ponder for a minute you know what

they're going to say they have to talk

to a metronome and um so that's why when

you see the words that they're writing

out that's not like they've thought

about it a lot and then you see the

words it's actually the thinking is

happening during the output would you

say that's how a human does it too I

often a lot of times sometimes I'm

really pissed off at what came out my

mouth cuz I didn't think about it in

advance yeah yeah I think so I mean

sometimes you have a conversation with a

smart friend and you just forming the

words to respond you have a better idea

and so I think we we definitely do that

too but um the agent the autonomy is

about kind of increasing the unit of

work you can trust the AI to do without

making a mistake so right now you can

ask it one question get a response you

interpret it you figure out the next

thing but what if it could go do 10 or

100 steps you're talking about an AI

business you know do you trust it to

come up with the title of the blog post

that you're going to post or do you do

you trust it to actually come up with

the whole idea of the marketing campaign

right come up with a strategy for how to

execute it all of the content it's going

to generate the partners it will reach

out to and negotiate advertising or or

whatever it's going to do have those

conversations that'll multi-step

successfully all the way to like

measuring its results without

supervision and I think that agency

thing we're starting to see it in

programming there was a very impressive

demo a week or two ago of a company

called cognition that um I think it was

maybe the it was arguably the first

really impressive demo of working agents

in Ai and and they did it with gp4 so

not with a new brand new model they did

it by being very clever about the way

they squeeze and distill the

intelligence out of gp4 by repeatedly

calling it and and analyzing and

evaluating its results and choosing the

best ones and so sort of going from rap

battle to like draft and redraft and

sort of think and ponder about it a

little bit harder mode and uh it can do

hundreds of steps in programming

successfully

so okay I was going to ask you one quick

question then please jump into that how

far out can you imagine right now about

three years three years is a Max yeah

how about

you well you can dream uh you can dream

yeah so um I actually the thing I I I

find easier is to think about the long

term because the the where the ASM toote

of where we're yeah and that's the key

question of our time is the ASM toote

it's like we know this is going to get

better when does it slow down and what's

the shape of the curve to get there you

mind I I cut you off apologies uh no

it's fine uh I think probably the thing

to look forward to is the last couple of

year F the first year was about the

technology and the breakthroughs and the

research last year was about the models

next year going forward no one give a

down about the models it's all about

what you can do with the models bringing

them together because the models have

satisficed they've got good enough fast

enough and cheap enough they will get

even better and there's probably two

orders of magnitude Improvement still in

the speed and reliability of the model

but this will really become about and

the stories of the next year will be

about we used this model to do this and

it was amazing you know and so I think

that's one of the things to look at and

that's what Nat said about tying them

all together you've got the ingredients

now what are the recipes we're going to

make very quickly capital and regulation

uh I was in a conversation with the CEO

of one of the major um AI companies and

uh just he was saying he's raising three

billion and I said you know have a

venture fund I said great and and I said

what's your minimum and he said probably

100 million I said okay well that's out

of my ballpark um but uh and and how

Quil you think I'm you're going to raise

it he goes next month I mean there is a

lot of capital flowing in yeah I mean

have you ever seen a capital Rush faster

than

this um no no I mean I think there are a

couple of comparisons you can look at um

I think the railways at when Railway

infrastructure was being laid in the UK

I think it was some double digit percent

of GDP investment um I think the solar

explosion that's happening right now is

actually pretty amazing it's something

like half a point of global GDP is being

invested in solar so those are pretty

big um we're nowhere near that yet with

AI and so I I actually think if AI keeps

working which it seems like it will um

you should expect the future to look

more like that Railway or solar

situation where there's you measuring

the investment in intelligence because

it's so valuable intelligence AI is

intelligence intelligence is power

power is valuable it's power over nature

it's power over others and so you'll

probably measure the amount of

investment in it in points of global GDP

and whether that happens in two years or

10 years I'm I'm not sure but it seems

likely I mean to put this in context

less money has been spent on private AI

companies than the Los Angeles San

Francisco Railway that hasn't started

yet there you go wow right but that's

almost done I heard so really fantastic

they haven't even started we wrote down

on it the ai ai right now isn't

infrastructure but it should be which

talk about your vision there because I

find it very powerful um your your your

vision there in education in health talk

to me this is the next Generation human

operating system because these AIS

extend our capabilities and again you'll

need the AIS that are open and the ones

that are proprietary to have the best

outcome for everyone cuz all of our

companies here are all information

systems and we've seen how better it can

be so the total amount of spending in

this will be trillions of dollars we

spent a trillion dollars on 5G is AI

more impactful than 5G of course it is

should it be infrastructure of course it

should be should the data be transparent

of course it should be because you need

to know how our Railways are made the

information knowledge Super Highway of

the future right now it's a few

companies doing this but we need

standards around it and we need the

expansion and again every country will

invest in this every company will invest

in this I mean is anyone here who runs a

company not investing in this in some

way at least your time right yeah

multiplied by every company in the world

why where are we percentage wise at the

investment in AI are we at a fraction of

1% still I would say so yes how about

you Nate seems likely so a lot of upside

still opportunity uh it is crazy though

I saw a tweet the other day I mean I

live through do and um all these you

know little attack Bubbles and um uh I

saw I saw a tweet the other day from

someone that said if you don't secure

equity in an AI startup now then your

children will be chattles slaves for the

machine God for all eternity and I

remember thinking I don't remember

anyone saying that

during like then you switched around and

bought some more G right this is somehow

a little bit more extreme than the prior

bubbles

so I mean look I think web 3 kind of

received a lot without any results

whereas now you're seeing impact here

yes but again you multiply this by the

number of people it effects the value

created it's insane because it will go

all abstraction you've had the base the

found found ations now the base now

you're building the houses you're

building a whole ecosystem around this

and the transformation that that has and

the amount of capital is bigger than

anything we've seen let me ask the

question we're going to be debating

today on the ASM toote How concerned are

you about digital super intelligence I'm

defining this for a purpose of

conversation as AI a billionfold more

advanced than the human being

um how do you think about that what's

your position in that

debate Pro con anywh I can kick off my

belief is that humans can break the atom

or we can go to Mars and so my vision is

every single nation person company

country culture has their own AI data

sets and self- Sovereign needs to figure

out the governance of this because it's

important and then that AI is our

collective intelligence it's the human

Colossus so it isn't controlled by

anyone individual it isn't embodied like

that but again it's amplifying all of us

and it's solving every single problem

that we can have I think that's a

positive version of the

future I think it seems really likely

that I mean it seems undoubtable to me

actually that intelligence is just a

material process like muscle strength we

have organs called muscles we use them

to to move we have an organ called the

brain and we use it to think and so if

you look at if you just sort of ask what

that means well we've managed to exceed

muscle strength with artificial

artificial machines with with machines

uh hundreds of years ago and um you know

we're going to do that with brains too

we're going to have artificial Minds

that are much more powerful than ours

it's um and you it's almost like you

just have to be an AI doubter not to

believe that or you have to not believe

in human Ingenuity all the most

brilliant people in the world are now

working on this and there's a huge

amount of capital going into to it in a

way we've just started and so the idea

that it wouldn't improve seems hard to

believe did you know that your

microbiome is composed of trillions of

bacteria viruses and microbes and that

they play a critical role in your health

you know research has increasingly shown

that microbiomes impact not just

digestion but a wide range of health

conditions including digestive disorders

from IBS to Crohn's disease metabolic

disorders from obesity to type 2

diabetes autoimmune disease like

rheumatoid arthritis and multiple

sclerosis mental health conditions like

depression and anxiety and

cardiovascular disease you know viome

has a product I've been using for years

called full body intelligence which

collects just a few drops of your blood

saliva and stool and can tell you so

much about your health they've tested

over 700,000 individuals and used their

AI models to deliver key critical

guidelines and insights about their

members Health like what foods you

should eat what foods you shouldn't eat

what supplements or probiotics to take

as well as your biological age and other

deep Health insights and as a result of

the recommendations that viome has made

to their members the results have been

Stellar as reported in the American

Journal of Lifestyle medicine after just

6 months members reported the following

a 36% reduction in depression a 40%

reduction in anxiety a 30% reduction in

diabetes and a 40 8% reduction in IBS

listen I've been using viome for 3 years

I know that my oral and gut health is

absolutely critical to me it's one of my

personal top areas of focus best of all

viome is Affordable which is part of my

mission to democratize healthcare if you

want to join me on this journey and get

20% off the full body intelligence test

go to vi.com Peter when it comes to your

health knowledge is power again that's

vom.com SL Peter here's the challenge it

feels like potentially win or take all

scenarios where if all of a sudden my

company is able to utilize the most

advanced Ai and build out the next

generation of systems and I'm doing it

with you know me and my my versions of

Haley and and and Aristotle that there's

you know they're working 24/7 I'm

feeding them as as many gpus as possible

and I have a chance to really

outrun um outrun the competition and it

used to be that in the early days in the

mechanical world if you were using

mechanical systems to outrun the horse

that was a local phenomenon right but

now this is a global phenomenon because

my my bits are reaching around the world

and you know when you say yeah it can do

my marketing do my marketing campaigns

it can do my scientific analysis it can

do everything

and you know I keep on hearing that is

like not 10 years from now not 5 years

from now but that's like a three-year

scenario I don't know how to think about

that I think the the pace of change you

know is going to be very high and um

Global GDP growth has been kind of in

the 2% range and we have a society and

civilization that's able to adapt to

that amount of change per year mostly

not entirely it's been a little bit

higher before um maybe it's going to be

much higher very soon and uh whether

there's a huge spread of outcomes that

come from that I mean even if you don't

have the extermination scenarios the

extinction scenarios in mind um I think

I think you actually should have other

scenarios in mind what does it mean to

be human uh is the economy human human

dominated you know 10 years from now or

15 where are decisions made and and who

makes them um and then just uh you know

this this vision of of sovereign AI you

know it's a new level of potentially

cooperation and competition between

countries and sources of this kind of

power and so um a lot of changes coming

I think you should I think uh you know

we went through this before we had the

sort of five big inventions of like the

1880s to the through the 1920s and that

was a a wild time of transformation it's

like almost unimaginable people who grew

up with horse carts you know and up

riding on jet planes and um we're going

to have at least probably much more than

that amount of change happen this time I

go to uod next but when you're you're

about to go after this to part two of

that tool and I want you to be thinking

about how can AI help you solve the

challenges you listed how will AI

threaten the dominant positions or the

strengths that you have and how will AI

this year help you meet your 20

24 goals right that's that's the goal to

putting it to use you might do you want

to comment on that and I want to also

talk about medicine and you know you're

dedicated to using AI models to solve

autism and cancer and death um or let's

just

say sick sickness yeah

sickness yeah I mean uh I just had a

thought actually you know we had Steve

Jobs qu earlier maybe the AI is jet

planes for the mind right there you go

here we go but the kind of the impact

here there's a sociological impact we

can extrapolate forward but an ASI is

just something we can't think if you've

got super intelligence if you've got too

infinite supply of graduates what do the

existing graduates do if the floor is

raised you don't need to hire as much

you become more efficient what are the

new jobs of the future in a knowledge

based economy we have to think about

that because as Nat alluded to it's like

slowly slowly then all at once like a

turkey you know at Thanksgiving I think

if you look at this though there's the

negative side but then there's a

positive side so I think mentioned kind

of last year Google's medpar model

outperforms human doctors in medical

diagnosis accuracy but also empathy and

we have medical models like that anyone

here who's had someone who's had

multiple sclerosis Alzheimer's autism

something like that you don't have

comprehensive authority to up toate

knowledge and nobody to guide you

through that process and you lose

agency well guess what we will make open

source models and they'll be available

to everyone and you'll never be alone

again through that and then be used for

diagnosis and organizing all lar so

describe that a little bit more so

people can can feel what that feels like

it means again anyone's experienced that

someone comes to you and says you have a

diagnosis of Alzheimer's for your father

or Autism for your child you lose agency

because you're like what now there's no

cure there's no treatment where do I

even go for information a lot of our

stuff is a coordination issue whereas if

we have a specialized medical model for

that topic and retrieval augmentation

and tie it into all these systems you

can have all that knowledge at your

fingertips and it can help guide you

empathetically through that it can

literally talk to you it can connect you

with other people going through the same

process and then the next step is it can

organize all the knowledge in this area

because there's so many promising

treatments but what how does anyone here

find out all the treatments about autism

or cancer you used to be patients like

me but it's hasn't survived but this is

supercharges that and then you do that

once and it's infrastructure for the 50%

of people around the world that will

have a diagnosis of cancer and again

you've transformed it because there will

always be someone with every single

person that can connect them to the

right information at the right time so

this is the positive view of the future

and that creates boundless new potential

in terms of both addressing our health

but science and again most of our

Science is based on files a PDF and we

throw away all the stuff that doesn't

work if you look at that knowledge flow

of that image with a different things

and again if I drag and send you that

image it'll reconstruct the whole flow I

think most of our things will go from

files to CL so we can remix our

knowledge so that we can find out what

works and what doesn't work and that's

how we get breakthroughs and is it true

that most the large language models were

built on top of all the social media

Facebook websites and so but not

crawling science magazines and most of

the scientific databases out there

science was a part of it but again what

we did is Big compute was a substitute

for bad data it was like cooking a steak

for too long now we see that high

quality data is even better but we're

only understanding what high quality

means and this is why we need

specialized models which are transparent

especially for things that affect things

like health education and others so I

think data set transparency will be a

big deal and this goes to Nat's point

about interpretability as well like you

were given that example of ariv earlier

right um science you know one of the

things that I think is amazing is the

potential for these AIS to help us

discover new science

Beyond interpolation or extrapolation

new laws of physics new understandings

of fundamental biology and chemistry uh

do you think that is possible when are

we going to see that and speak one

second to the vvus challenge that you oh

sure yeah um I think definitely they

will um which by the way for me is like

the most exciting thing if you could

unleash these AI models and say go and

create room temperature superconductors

go and cre you know uh life extension

processes so there's uh in biology

especially biology you know there's this

sort of analogy that's been put out

there that uh the language of of you

know physics was was mathematics the

language of biology might be machine

learning because you're dealing with

enormously complex systems machine

learning is great at sort of

understanding those and so the potential

for AI to transform biology is enormous

I think it's all in the very earliest

stages right now and we have not yet had

the kind of gpt3 let alone on the chat

GPT moment for biology and AI I think

it'll come soon since Google is our

sponsor I say the Gemini moment there

you go the Gemini moment hasn't occurred

yet The Bard what is it The Bard moment

maybe I don't know but it's coming and

um you know I'm involved with some

companies that are training enormous

models to help uh synthesize and design

proteins there are a few great efforts

out there to do this and um the

capabilities that are popping out of

these things are incredible the ability

to you describe a Target describe a

structure and just have it produce a

sequence of amino acids that you can

then synthesize and test in the lab for

safety and efficacy it can short circuit

a huge part of this uh sort of cognitive

work and experimental work that's been

necessary historically for drug design

and so I think that's one thing I think

another thing is is um there will be a

surge of new discoveries that happen as

we as AI digests all the existing

scientific literature and so there's

there's a whole area of study which is

metaanalysis where people will study

across papers to find connections and

correlations across existing research

that haven't been noticed I so I mean

I'm bubbling with excitement on that

notion that idea yeah so imagine you

know I I have a friend uh shaa Swan

she's a a scientist at Berkeley and does

a bunch of uh research on environmental

toxins she spent two years running one

metaanalysis that you know I'm now

working with her and trying to support

her and the effort to use AI to automate

this and it'll I mean in theory with

these long context Windows this could

potentially happen in in minutes and so

I think new discoveries will pop out of

that immediately and just because we're

short on time I'm going to say you found

Mount Vesuvius oh yeah after the

eruption buried a number of uh parchment

Scrolls that were if you imagine buried

under all of the ashes and so and so

forth you took some of those Scrolls you

x-rayed them gathered the X-ray d from

those Scrolls and then you ran a order

an order of a million dooll uh vus

challenge like an X prize yeah and your

the winner solved it it worked yeah no

it's true so yeah 2,000 years ago Mount

vuia erupts it buried the town of

herculanum under 65 ft of Ash and mud

and then in the 1700s some Farmers

digging a well found the Villa 65 ft

down and then later during these

tunneling excursions people kept running

into these little chunks of char Co they

didn't know what they were they turned

out to be carbonized Papyrus Scrolls

that were not openable physically they

just sort of turn to dust in your hands

when you open them they've been stored

in a library in Naples for years and we

used a particle accelerator to scan them

at super high resolution but then we

needed to use Ai and machine learning to

to unroll them they're so badly

distorted by how cool is that being a

volcano

[Applause]

yeah um want you close us out here with

what you're most excited about um going

forward what's a vision of the world in

the next 1 to three years that you want

people to take away from here I I think

this AI is augmenting not replacing and

so you see what kind of nat said and I

look how creatives use it AI can't do

art it can do content right now but you

can use it to riff and jam with so

you're in flow more often so the thing

I'm most excited about is its impact

upon education science over the coming

years is because everyone will have

access to all the knowledge that

amplifies them I think things like

creativity are also great because it's

great to create but realistically again

every single person in this room will

just have access this is the worst it

will ever be that's so important this is

the worst AI will ever be and view it

and the lowest Bitcoin will ever be

too yeah and then view it amplifying

yourself and there's no there's nothing

you can't achieve with this I

think um

people are sitting down here with goals

for the year uh objectives they want to

achieve what is your top piece of advice

for the CEO entrepreneur philanthropist

here that has like oh man I I'm trying

to do more and more what should they

what should they think about well I

think um what's happening or what's

about to happen it's sort of like we've

just discovered a new continent with 100

billion people on it and there willing

to work for free for us and you should

probably factor that into your plans

over the next few years

because uh your competitors will and U

because it'll benefit you enormously at

home at work and your family we just

discovered a new content with 100

million brilliant workers willing to

work 100 billion 100 bil they're going

to outnumber us yeah yeah 100 billion

okay and they'll work for a few watts of

power and um so this is the good

scenario and I think it's very very

likely and uh so I would and I think you

know this sort of like being an internet

native you want to be an AI native and

you want to spend time using the stuff

and not looking for the problems but

looking for the looking for the value

and how to what's it good at what's it

not good at how do you interact with it

it's amazing to see people use stable

diffusion for example um you've improved

uh it so much over time but there are

there's a skill to being good at

interacting with these models and

partnering with them and and so I think

we all have an advantage just to get

that hands- on ourselves you know

imagine being a CEO of a company when

electrification was happening and um you

know obviously every company should

Electrify uh and then not doing it in

your own home like that would be

strange amazing imod you're going to be

with us for the next few days so thank

you so much for that uh Nate it's a

pleasure to get to know you thank you

for joining us this morning let's give

it up for Nate and mod

[Music]