Category: AI

Podcast notes – Emad Mostaque (Stability AI and Stable Diffusion) – Elad Gil: Short form videos coming “within 2 years at high resolution quality”; “Run Stable Diffusion on your iPhone by next year”

(started notes around 20min in)

Bad guys have AI – they’ll create deep fakes
Community can come together to have counter measures

Elad: similar arguments to regulate cryptography in 90s

4chan has been “red teaming” trying to get the worst out of Stable Diffusion – and it’s not that bad

Especially for LLMs, should have more diverse data sets, have inter-governmental agency to monitor it

Have authenticity tool to verify source of every generated AI output

Generative AI – what are some use cases that should exist
Ali v Tyson live, Lebron v Michael Jordan
Emad wants to remake final season of Game of Thrones

Anyone can create their own models – any person, company, or culture

You need better data, more structured data
Extend models to run on edge – eg, anyone’s computers, iPhones
Make small customized models
“Run Stable Diffusion on your iPhone by next year”

Create national models and communities around them – let them leap frog ahead

Lots of emerging markets went from nothing to mobile phones, now can go to AI models on the edge

How far from short-form videos?
Phenaki, Google — getting close
Chaining these models together – they’re like parts of the brain
“Within 2 years at high resolution quality”

$100B into this sector in next 5 years

AI before today was qualified data science
Now it’s a new type of AI – not AGI yet, but incredibly small and powerful
By the time his daughter’s in university, doesn’t need to write essays

He aims (for Stable Diffusion) to be a layer 1 standardized infrastructure – create Schelling point
Mission is to “activate humanity’s potential”
Take it to India, Indonesia – give it to very smart young people to make their countries better

When AGI comes, I hope it thanks him for buying so many GPUs to help bring it into being

Many of Google’s “jobs to be done” will be displaced

Crypto is interesting – he’s in it since 2012 – focused on decentralized identity, zero knowledge proofs
“Nature of crypto is literally identity”
In a world of infinite content (AI), crypto identity is important
Need to be careful designing crypto economic systems

A year ago, if he said what they planned to do with SD, people would say he’s crazy
Surprised by how far they’ve come, the ability of others to contribute
The activation energy has been the most surprising – “they’re just excited”

“Probably see biggest breakthrough from a 16 year old in Uzbekistan” – the global open access nature of it

Will completely disrupt social networks – will move intelligence from the core to the edge
Apple is doing this – moving to AI – moving to edge

Opportunity to have personalized AIs that work for us and with us

SD is applying for B corp status – mission based
Plan to spin SD into different Foundations

Did investment round in August – didn’t give up any independence – did with investors that are open sourced and mission aligned

Which industries disrupted first?
-Call centers
-Powerpoint, forms of visual communication
-Artist won’t be that disrupted – will enable new forms of art

This tech is amazingly powerful

After releasing Stable Diffusion – people encoded it in Japanese – lots of use cases like this

So far governments have been very friendly

AI powered teaching – like Neal Stephenson’s Young Lady’s Primer

Moving forward, only release safe for work models

Licensing discussions should be more open

Will have models across all sorts of languages – recently released Korean model

“Cars get better by some modest amount each year, as do most other things I buy or use. LLMs, in contrast, can make leaps.” – Tyler Cowen on AI

Must read if you’re interested in AI and its implications; Tyler’s commentary on the recent explosion of AI into the popular consciousness (driven in large part by ChatGPT) has been, in my view, the most realistic+pragmatic:

https://www.bloomberg.com/opinion/articles/2023-01-23/chatgpt-is-only-going-to-get-better-and-we-better-get-used-to-it

“I don’t have a prediction for the rate of improvement, but most analogies from the normal economy do not apply. Cars get better by some modest amount each year, as do most other things I buy or use. LLMs, in contrast, can make leaps.”

“I’ve started dividing the people I know into three camps: those who are not yet aware of LLMs; those who complain about their current LLMs; and those who have some inkling of the startling future before us. The intriguing thing about LLMs is that they do not follow smooth, continuous rules of development. Rather they are like a larva due to sprout into a butterfly.”

Interview notes – Sam Altman on OpenAI, ChatGPT, Helion, Hermeus – StrictlyVC

He doesn’t read the news
Likes trolling on Twitter…”Twitter’s fun”
“Twitter’s gonna be fine”

HIS INVESTMENTS

400 personal investments, a few thousand including YC
All the companies he’s added value to are those he thinks about in his free time – while hiking, texting the founder an idea

Most successful investment? Stripe on a multiples basis

Helion – fusion energy
Personally invested $375M (!)
Other thing besides OpenAI that he spends a lot of time on
New energy system that works on super low cost
Hardest challenge is how to replace all (current) generative capacity on Earth really quickly
“Who can deliver energy the cheapest, and enough of it”
Simple machine, affordable cost, reasonable size
If fusion works…will change dynamics of what’s possible – enables more downstream (eg, more powerful planes)

Hermeus – supersonic jet company
Led $100M round
Was also involved with a competitor Boom – but different tech and approach
Huge market with multiple needs

Worldcoin
He’s a cofounder, on the board, but not day to day involved
Will tell its story soon – believes it will go over well (unlike earlier negative media coverage)
We give up more privacy to Facebook than Worldcoin
Phenomenal team
Launch in months
Interested in any tech to experiment with global UBI (versus what one country can do)

Re: crypto — “honestly not super interested”
“Love spirit of web3, but don’t intuitively feel why we need it”

Inception Fertility
In-vitro gametogenesis
In shadow of AI
Next 5-7 years of biotech will be remarkable
Human life extension – “yeah maybe that’s gonna work”

Investing for 20 years, president of YC for 5-6 years
Garry (new YC president) will do a lot of things differently and be wildly successful
Last few years were really hard for YC
YC can remake itself now – tourists are leaving now

—

ARTIFICIAL INTELLIGENCE

OpenAI has pulled together “most talent dense” AI team
“Gonna be tremendously good”

Why did ChatGPT and DALL-E so surprise people?
“Don’t know…reflected on it a lot”

If you make a good UX on top of something – believed users wanted to interact via dialogue
Pieces were there for awhile

Standard belief was AI would take over low skill / truck driving / generic white collar
Going exact opposite direction – taking over creativity where we thought humans might have special sauce
It’s not an intuitive finding

Released GPT-3 three years ago – thought ChatGPT would be incremental, was surprised by public reaction

ChatGPT will cause societal changes – eg, academic integrity
“Stakes are still relatively low”
Covid did show us society can update to massive changes faster than he expected

Given expected economic impact – “more gradual is better”

GPT-4 will come out when we’re confident we can do it safely and responsibly
Will release tech much more slowly than people will like
GPT-4 rumor mill is a ridiculous thing

Re: ChatGPT – built a thing, couldn’t figure out how to monetize it, put it out via an API, and users figured out how to use it

Would like to see AI super democratized, have several AGIs in the world
Cost of intelligence and energy trends down and down
“Massive surplus…benefits all of us”
Believes in capitalism – best service at lowest price

Society will need to agree on what AGI should never do
Broad absolute rules of the system
Within that, AI can do different things – safe for work one, edgier creative one – different values they enforce
A user can write up a spec of what they want, and AI will act according to it – “should be your AI…to serve you”

Microsoft – only tech company he’d be excited to partner with this deeply
Satya, Kevin Scott, Mary McHale
Values-aligned company

“We’re very much here to build AGI”
“We wanna be useful to people”

Re: Google’s AI – hasn’t seen it, assume they’re a competent org

We’re in a new world – generated text is something we all need to adapt to, like we adapted to calculators
“I’d much rather have ChatGPT teach me…than read a textbook”

Anthropic – rival AI, stressing an ethical layer
Very talented team
Multiple AGIs in the world is better than one

Society decided free speech is not quite absolute – in similar ways AI / LLMs will need to have bounds too

Video is coming… no confident prediction about when
Legitimate research project – could take awhile

AUDIENCE Q&A

When fusion online?
By 2028, could be plugging fusion generators into grid (pending regulators)

Re: AI worst and best case?
“best case is so unbelievably good that it’s hard to imagine, discovering new knowledge in a year instead of 70K years”
“Bad case is lights out for all of us”
More worried about accidental mis-use in short term, less about the AI itself being evil

How far away is AGI?
Much blurrier and gradual transition than people think

Re: state of San Francisco
Real shame we treat people like this
How elected leaders don’t fix the problem
Tech has some responsibility for it
But other cities do better than this
Super long in-person work and Bay Area

Re: ChatGPT reaction
Expected one order magnitude less hype, users, of everything
Less hype is probably better
The tech is impressive, but not robust
Use it 100x, see the weaknesses

How Sam uses ChatGPT?
Summarize super long documents, emails
For translation

Re: Google code red, threat to search
When people talk about new tech being end of a giant company, they’re usually long
Change is coming (for Google), but not as dramatically as people think

Before Google, memorizing facts was important – and now we’ll change again – and we’ll adapt faster than most people think

Prefers hybrid work, like YC – few days at home, few days in office
Skeptical that fully remote is thing everyone does
Most important companies will still be heavily in-person

Safety engineering for AI is different from standard safety engineering – consequences are greater, deserves more study

Raising capital now is hard, especially later stages – but other things easier – easier to rise above noise, hire, get customers
What he’d do now — recommends for founders – “do AI for some vertical”

Advice for AI startups
Differentiate by building deep relationships with users, some moat like network effect
Plan for AI models continually improving
OpenAI is a platform, but also wants to do a killer app (platform + killer app) to show people what’s possible

Podcast notes – ChatGPT goes prime time! – Practical AI (Daniel and Chris)

Practical AI 206: ChatGPT goes prime time! – Listen on Changelog.com

Hosts: Daniel Whitenack (Data scientist), Chris Benson (Lockheed Martin)

All about ChatGPT

Chris – feels collaborative, like having a partner

Lots of structuring in the output – bulleted lists, paragraphs

Humans get things wrong / incomplete all the time – yet we’re holding AI to a higher standard

Shifting to more open access – maybe in response to open source AI products like Stable Diffusion

Chris – expect to see more “fast followers” to ChatGPT soon

TECHNICALS

GPT language models – it’s a “causal language model” not a “mass language model”
Trained to predict next word in sequence of words, but based on all previous words
Auto-regressive – predicts next thing based on all previous things, and so forth
That’s why the text develops as if a human were typing
Few shot learning – can change answer style based on your questions and prompts

Zero shot = input that a model has never seen before
Few shot = provide a small number of inputs / prompts to guide the model

ChatGPT – trained with “reinforcement learning from human feedback” (RLHF)
Human preference is key part of this

How does it scale?
Human feedback is expensive
3 steps:
1. Pre-train a language model (aka a “policy”) – not based on human feedback
2. Gather human preference data to train a reward model – outputs prediction of human preference
3. Fine tune (1) based on (2)

eg for ChatGPT,
(1) is GPT3.5 (for ChatGPT)
(2) outputs data based on (1), add human labels of preference, and train a “reward model”

GPT3 is 100B+ parameters
ChatGPT reward model is 6B parameters

For (2), goal is to reduce harm by adding human feedback into the loop

For (3), will penalize if it strays too far from (1), and score output according to (2)
Try only to make small iterative changes (adiabatic)

What’s next?
Open research questions – (2) architecture and process hasn’t been fully optimized, lot to explore there
Will be new language models coming (eg, GPT4, Microsoft, Google) – trying different (1) and (2)

Chris Albon tweet:
—
Sci-fi got it wrong.

We assumed AI would be super logical and humans would provide creativity.

But in reality it’s the opposite. Generative AI is good at getting an approximately correct output, but if you need precision and accuracy you need a human.
—

Galerie.ai – make generative art with multiple models

A little something we’re working on, you can try it here: http://galerie.ai/

It does two things

1. Returns results from a growing library of the best AI art

2. Lets you create AI art from multiple generative models (including Stable Diffusion 1.5, 2.0, 2.1, and MidJourney)

Let me know what you think!

We auto-suggest some of the trending prompts and popular art results on the home page, try it out!

For example here is ” photorealistic portrait, a young beautiful woman Goddess wearing Echo of Souls Skull Mask armor, skeletal armor bones made from 24k gold and silver metal intricate scroll-work engraving details on armor plating, skeletal armor, gemstones, opals, halo, aura, intricate details, symmetrical,”: