Kazuki
@kazuki
Cofounder of Glasp. I collect ideas and stories worth sharing 📚
San Francisco, CA
Joined Oct 9, 2020
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www.patagonia.com/ownership/
Sep 28, 2022
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www.youtube.com/watch?v=14V8Mrkvo9E
Sep 27, 2022
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fs.blog/brain-food/september-25-2022/
Sep 26, 2022
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www.ryanhoover.me/post/do-shitty-work
Sep 26, 2022
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medium.com/@rrhoover/request-for-crazy-startups-f3262fd62e24
Sep 26, 2022
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blog.eladgil.com/2021/01/substack-most-interesting-consumer.html
Sep 25, 2022
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medium.com/positiveslope/what-is-seeing-the-matrix-for-a-product-leader-9441e400d9a2
Sep 25, 2022
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bloomfire.com/blog/history-of-knowledge-sharing/
Sep 24, 2022
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www.paulgraham.com/work.html
Sep 23, 2022
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nymag.com/intelligencer/2012/10/joint-venture-rap-genius-as-internet-talmud.html
Sep 23, 2022
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every.to/napkin-math/the-ai-writer
Sep 23, 2022
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experimentalhistory.substack.com/p/youll-forget-most-of-what-you-learn
Sep 23, 2022
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www.scotthyoung.com/blog/2022/07/25/basics/
Sep 20, 2022
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paulgraham.com/users.html
Sep 20, 2022
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medium.com/personal-growth/seeking-wisdom-lessons-on-becoming-an-outstanding-thinker-e9668079a939
Sep 19, 2022
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nesslabs.com/comparison-anxiety
Sep 19, 2022
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every.to/almanack/the-merge-is-done-now-what
Sep 18, 2022
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a16zcrypto.com/what-the-merge-means/
Sep 18, 2022
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adamnash.blog/2022/09/16/figma-a-random-walk-in-palo-alto/
Sep 18, 2022
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www.youtube.com/watch?v=tnBQmEqBCY0
Sep 16, 2022
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greylock.com/greymatter/sam-altman-ai-for-the-next-era/
Sep 15, 2022
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pmarchive.com/luck_and_the_entrepreneur.html
Sep 15, 2022
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bryce.medium.com/most-people-won-t-ff0959cdefc6
Sep 15, 2022
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foundersatwork.posthaven.com/grow-the-puzzle-around-you
Sep 15, 2022
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waitbutwhy.com/2015/12/the-tail-end.html
Sep 15, 2022
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www.albertbridgecapital.com/post/stay-in-the-game
Sep 15, 2022
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www.youtube.com/watch?v=tyL0OwAgc_I
Sep 12, 2022
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nfap.com/wp-content/uploads/2022/07/Immigrant-Entrepreneurs-and-Billion-Dollar-Companies.DAY-OF-RELEASE.2022.pdf
Sep 12, 2022
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hardfork.substack.com/p/the-breaking-of-the-modern-mind-the
Sep 11, 2022
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www.youtube.com/watch?v=qvHhhIfu7Lo
Sep 10, 2022
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ruben.verborgh.org/articles/redecentralizing-the-web/
Sep 9, 2022
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arxiv.org/pdf/2205.06345.pdf
Sep 9, 2022
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hbr.org/2007/07/the-knowledge-creating-company
Sep 9, 2022
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aigrant.org/
Sep 8, 2022
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www.gatesnotes.com/Health/Why-do-children-die
Sep 6, 2022
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digitalnative.substack.com/p/the-long-tail-the-internet-and-the
Sep 6, 2022
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e-tarjome.com/storage/panel/fileuploads/2019-12-16/1576487113_gh76.pdf
Sep 6, 2022
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www.quantamagazine.org/self-taught-ai-shows-similarities-to-how-the-brain-works-20220811
Sep 3, 2022
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www.forbes.com/sites/robtoews/2022/03/27/a-wave-of-billion-dollar-language-ai-startups-is-coming/?sh=32af08f62b14
Sep 3, 2022
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www.sciencedirect.com/science/article/abs/pii/S0148296319300992
Sep 3, 2022
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“If you just think about that alone as a way to unlock the applications people will be able to build, that would be a huge victory for all of us and just a massive step forward and a genuine technological revolution,” says Altman. “I think that these powerful models will be one of the genuine new technological platforms, which we haven’t really had since mobile. And there’s always an explosion of new companies right after.”
what I think will happen is there’ll be a whole new set of startups that take an existing very large model of the future and tune it, which is not just fine tuning, all of the things you can do.
I think if I had time to do something else, I would be so excited to go after a bio company right now. I think you can just do amazing things there.
"I'm a big believer that the only real driver of human progress and economic growth over the long term is the societal structure that enables scientific progress, and then scientific progress itself."
the alignment problem is: how do we build AGI that does what is in the best interest of humanity? How do we make sure that humanity gets to determine the future of humanity?
We have some ideas about what to do next, but we cannot honestly look anyone in the eye and say we see out 100 years how we’re going to solve this problem.
I think language models are going to go just much, much further than people think, and we’re very excited to see what happens there. I think it’s what a lot of people say about running out of compute, running out of data. That’s all true. But I think there’s so much algorithmic progress to come that we’re going to have a very exciting time.
right now, if you use GPT whatever, it’s stuck in the time that it was trained. And the more you use it, it doesn’t get any better and all of that. I think we’ll get that changed. So I’m very excited about all of that.
I think it is just an area where people are going to say everything is now, “This plus AI.” Many things will be true. I do think this will be the biggest technological platform of the generation.
I doubt we’ll still be using the transformers in five years. I hope we’re not. I hope we find something way better. But the transformers obviously have been remarkable. So I think it’s important to always look for where I am going to find the next totally new paradigm.
Don’t pay attention to the AI for everything.
I think [AI] is going to just seep in everywhere. My basic model of the next decade is that the marginal cost of intelligence and the marginal cost of energy are going to trend rapidly towards zero, surprisingly far.
I think you have to assume that’s going to touch almost everything because these seismic shifts that happen when the whole cost structure of society changes, which happened many times before, the temptation is always to underestimate those.
The synthetic bio companies that I’ve seen that have been most interesting are the ones that find a way to make the cycle time super fast. And that benefits an AI that’s giving you a lot of good ideas, but you’ve still got to test them, which is where things are right now.
I’m a huge believer in startups that the thing you want is low costs and fast cycle times. And if you have those, you can then compete as a startup against the big incumbents.
"I don't think all the deep biological things will be changed by AI. I think we will still really care about interaction with other people. I think the stuff that people cared about 50,000 years ago is more likely to be the stuff that people care about 100 years from now than 100 years ago."
I don’t think we’ll still be doing prompt engineering in five years. And this’ll be integrated everywhere. Either with text or voice, depending on the context, you will just interface in language and get the computer to do whatever you want.
I think the fundamental interface will be natural language.
"What will always matter is the quality of ideas and the understanding of what you want."
the artist will still do the best with image generation but not because they figured out to add this one magic word at the end of it. Because they were just able to articulate it with a creative eye that I don’t have.
for me, AGI is basically the equivalent of a median human that you could hire as a coworker. And then they could do anything that you’d be happy with a remote coworker doing just behind a computer, which includes learning how to go be a doctor, learning how to go be a very competent coder.
What is the new social contract? My guess is that the things that we’ll have to figure out are how we think about fairly distributing wealth, access to AGI systems, which will be the commodity of the realm, and governance, how we collectively decide what they can do, what they don’t do, things like that.
I think it’s interesting that if you ask people 10 years ago about how AI was going to have an impact, with a lot of confidence from most people, you would’ve heard, first, it’s going to come for the blue collar jobs working in the factories, truck drivers, whatever. Then it will come for the low skill white collar jobs. Then the very high skill, really high IQ white collar jobs, like a programmer or whatever. And then very last of all and maybe never, it’s going to take the creative jobs. And it’s going exactly the other direction.
in some sense, the startups will train their own models, just not from the beginning. They will take base models that are hugely trained with a gigantic amount of compute and data, and then they will train on top of those to create the model for each vertical. So in some sense, they are training their own models, just not from scratch. But they’re doing the 1% of training that really matters for whatever this use case is going to be.