Oliver Heins

[Teddy Blank @teddypowday]

Your CEO should be strong.

Your CTO should be wise.

Your COO should be wicked, cunning, of mysterious origins, fluent in the dark arts, blurry in pictures,

[Oliver Heins @OliverHeinss]

@dimiwonders Eleven Labs

[Oliver Heins @OliverHeinss]

@PrivatEquityGuy Can you share what you’re reading/studying ?

[Oliver Heins @OliverHeinss]

@guilleflorvs FOUNDER

[Akshit @akshitwt]

this is a great read by jack morris. gives such a fresh perspective on what really matters.
TLDR: with every "new" architecture, we unlocked a new source of data to use at scale. it was the large amount of data we unlocked that boosted performance not the architecture itself, and videos are the next big thing to harness.

2012: alexnet unlocked the entire imagenet dataset
2017: transformers unlocked the entire internet (as text)
2022: RLHF unlocked learning from humans
2024: reasoning unlocked learning from verifiers
2026: ???

when you look at progress this way, it becomes very very clear what the next pillar to unlock is: videos. or more specifically, youtube.

youtube stores an insane amount of video data. people upload 720.000 hours of videos to the platform every single day. thats 4.3 Petabytes of new data every day that need to be stored. for comparison, currently models are trained on a few terabytes of text.
this means that the data uploaded to youtube daily is 1000x the data used to train a typical LLM.

once we come up with an architecture that can harness videos at scale, we will see the next big jump in our quest to AGI

[Oliver Heins @OliverHeinss]

@pmddomingos Certainly agree for developing countries with free access to info and learning with AI. But tend to think the average IQ in the US decreases as the majority of people will not think critically anymore as they rely on AI.

[Sully @SullyOmarr]

i think we got "ai memory" all wrong

everyone is focused on making models remember facts about you when its way more useful in a work setting

ex: when you explain something to a coworker it's basically:
- the task (this is what we do now with prompts, memory has very little importance)

- how to do the task -> this is where "raw intelligence" matters (reasoning etc) and ability to follow instructions

- where to get the required information (context) - this is the important and what everyone is missing about memory

e.g (look at notion for HR, and then check slack and linear for xyz)

with any agent right now it can do points 1 and 2 pretty well, but fails at 3. you have to explain the same thing over and over each time. its not figuring how do the job better over time

we need to solve for an agent doing a task and remembering exactly how it did, what it learned, etc

eg: once it figures out that revenue data lives in stripe → sheets → mixpanel, it should just know that for every interaction onwards

[Saif @khawajasn]

We've raised $22M Series A to restore American food sovereignty. 

Co-led by @foundersfund and @interlagoscap.

One of our most important supply chains is broken. @ShinkeiSystems is here to fix it. 🧵

[Oliver Heins @OliverHeinss]

@karpathy Directionally seems very plausible, but there are a lot of interesting implications.

What happens to shared culture when no one is reading and everyone is consuming videos unique to them ?

[Andrej Karpathy @karpathy]

Very impressed with Veo 3 and all the things people are finding on r/aivideo etc. Makes a big difference qualitatively when you add audio.

There are a few macro aspects to video generation that may not be fully appreciated:

1. Video is the highest bandwidth input to brain. Not just for entertainment but also for work/learning - think diagrams, charts, animations, etc.
2. Video is the most easy/fun. The average person doesn't like reading/writing, it's very effortful. Anyone can (and wants to) engage with video.
3. The barrier to creating videos is -> 0.
4. For the first time, video is directly optimizable.

I have to emphasize/explain the gravity of (4) a bit more. Until now, video has been all about indexing, ranking and serving a finite set of candidates that are (expensively) created by humans. If you are TikTok and you want to keep the attention of a person, the name of the game is to get creators to make videos, and then figure out which video to serve to which person. Collectively, the system of "human creators learning what people like and then ranking algorithms learning how to best show a video to a person" is a very, very poor optimizer. Ok, people are already addicted to TikTok so clearly it's pretty decent, but it's imo nowhere near what is possible in principle.

The videos coming from Veo 3 and friends are the output of a neural network. This is a differentiable process. So you can now take arbitrary objectives, and crush them with gradient descent. I expect that this optimizer will turn out to be significantly, significantly more powerful than what we've seen so far. Even just the iterative, discrete process of optimizing prompts alone via both humans or AIs (and leaving parameters unchanged) may be a strong enough optimizer. So now we can take e.g. engagement (or pupil dilations or etc.) and optimize generated videos directly against that. Or we take ad click conversion and directly optimize against that.

Why index a finite set of videos when you can generate them infinitely and optimize them directly.

I think video has the potential to be an incredible surface for AI -> human communication, future AI GUIs etc. Think about how much easier it is to grok something from a really great diagram or an animation instead of a wall of text. And an incredible medium for human creativity. But this native, high bandwidth medium is also becoming directly optimizable. Imo, TikTok is nothing compared to what is possible. And I'm not so sure that we will like what "optimal" looks like.

[Isaiah Granet @zaygranet]

Without Supabase there is no vibe coding revolution

[Hyde 💨 @BreatheLesss]

If you notice, children make their world smaller in order to make it bigger. Tree houses, pillow forts, sheet tents, etc. I wonder what adults do.

[Oliver Heins @OliverHeinss]

@wolfejosh It seems like this is the catalyst that forces Apple to finally open up its walled garden.

[Oliver Heins @OliverHeinss]

@boringmarketer Mail and IRL events

[Marc Seitz — oss/acc @mfts0]

Uber just invented …

… the bus

[lusso @luusssso]

The world could use more colorful architecture

[Oliver Heins @OliverHeinss]

Unfortunate that AI ruined the em dash — it was a cool piece of punctuation.

I wasn’t even a power user, but if I were, I’d be pretty annoyed everyone now assumes my writing is AI.

[MIT Athletics @MITAthletics]

MIT Athletics Statements on the Passing of Karenna Groff ’22, MEng ’23 and James Santoro ’23

🔗- https://t.co/EI9vbfys7x

"This is a devastating loss for our athletics department and for the MIT community." -- Dr. G. Anthony Grant, Director of Athletics

[Gergely Orosz @GergelyOrosz]

I am coming around to why MCP is so impressive.

For one of my side projects, I used to have to log onto my database admin (PgAdmin) to query stuff.

I connected an MCP server to Postgres and can "talk" with my database (and data!)

An uplevel in my productivity + ease of work.

[Aditya Agarwal @adityaag]

Probably the best time in around 15 years to release a radically new take on a phone.

I would have never considered switching away from an iPhone but it feels like using "old tech" right now.

Wonder if anyone is going to step up to the plate to take a shot.