magicturtle42

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magicturtle42

magicturtle42

@magicturtle42

AI, software, futurism. Rooting for you to succeed. Playing positive sum games.

Katılım Mayıs 2023
557 Takip Edilen22 Takipçiler
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magicturtle42
magicturtle42@magicturtle42·
It's not inference efficient to consider every relevant thing the model knows related to what you are doing. The models know what property based testing is and have good philosophies around it, but won't incorporate that by default. The context you build up over time on what the model should think about wrt your problems is invaluable.
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magicturtle42
magicturtle42@magicturtle42·
@simpsoka On role collapse, I'd love to hear from designers what PMs and SWEs tend to miss when designing, then from PMs what SWEs and designers tend to miss when performing PM tasks etc.
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Kath Korevec
Kath Korevec@simpsoka·
I haven’t written much recently ‘cause I’ve been sorta busy. I’ve got a few posts I’ve been noodling on, but curious what folks might wanna read about? One about role collapse and the reality of building outside your lane. Another about transparent ui in agentic design.
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magicturtle42
magicturtle42@magicturtle42·
@deanwball SWE is broad and there was not One Way to be good at SWE previously, so there will be a range of outcomes on that front. That said, I do think this is the golden era for having domain expertise and being just technical enough to get good outputs from agents.
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magicturtle42
magicturtle42@magicturtle42·
@tszzl I'd love your thoughts on if you think this is what happens for software/swe generally.
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roon
roon@tszzl·
(for the moderate to good ones. the world class ones will see their leverage increased 100-1000x, but probably a tiny set of superstars)
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roon
roon@tszzl·
ironically think it’ll be a sad time for ai researchers this year. they are first in the hotpath of RSI and probably the market for them will shrink or at least their pricing power will be reduced as this generation of models commoditizes the skills that made them rare
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magicturtle42
magicturtle42@magicturtle42·
@tszzl Presumably it will get to the point where the work is increasingly uninterpretable, but the material outputs will still be differentiable.
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roon
roon@tszzl·
one take that always ages really badly is that the models are intelligent enough and nobody can really notice the improvements anymore
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magicturtle42
magicturtle42@magicturtle42·
The interesting people are spending more time talking to LLMs and the less interesting people are sending their LLMs to talk to us.
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magicturtle42
magicturtle42@magicturtle42·
Labs RLing task completion over structural soundness means you get to have all the architectural fun yourself.
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magicturtle42
magicturtle42@magicturtle42·
1. Prohibition of distillation means its benefits are mainly restricted to groups that are indifferent to rules. 2. The "most aligned" models could be seeding their values into the next generation. This is explicitly forbidden.
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magicturtle42 retweetledi
Jerry Tworek
Jerry Tworek@MillionInt·
AI was meant to democratize programming, but what I see is that skill ceiling on vibecoding is incredibly high
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magicturtle42
magicturtle42@magicturtle42·
Tremendous alpha in not going insane in the 20s
magicturtle42 tweet media
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sarah guo
sarah guo@saranormous·
I believe AI will deliver enormous gains to the global consumer: better products, better services, better healthcare, and tools that make ordinary people more capable, even superhuman. The upside is so large, and the geopolitical stakes so real, that we should move decisively toward it, not choke it off. But people do not experience technological change as an aggregate statistic. They experience it through their bills, their communities, and their jobs. So the issue is not whether AI will create value. It will. The issue is whether the path to those gains asks particular communities and workers to absorb too much of the cost upfront. The institutions building AI cannot externalize the local costs of scaling and call future abundance the answer. If datacenters place major new demands on power and land, they should invest enough to strengthen the grid, ease pressure on bills, expand the tax base, and create durable jobs. And if AI compresses some of the entry-level work people used to learn on, firms should help build new on-ramps and training pathways into the new work that growth is creating. This is not an argument for slowing the buildout down. It is an argument that rapid technological progress has to be socially durable.
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magicturtle42
magicturtle42@magicturtle42·
Thinking of them as intelligent entities that are getting smarter makes it easy to mentally model them as something more well-rounded than they are. This will age poorly as the jagged lows improve, but it is relevant today.
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magicturtle42
magicturtle42@magicturtle42·
It might be more helpful to think of the models as skilled rather than intelligent.
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magicturtle42
magicturtle42@magicturtle42·
There are two opposing ditches: Risk: You offload too much cognitive work to your agents. You cannot track all of their actions and assumptions. You miss key decision points that may come back to harm you or your company later. Burnout: You try to mentally understand all the ins and outs of your 1000x output. You know about the dangers of the risk path above, but you are still trying to keep pace with your fellow 1000xers. You are trying to update your understanding at the rate a computer can now write code, which is impossible. Burnout will present an ongoing danger as there is pressure to increase outputs as the tools improve. Risk should go down as the models get better, but it will go up again as they take on increasing scope without meaningful review. There is a natural tension here that cannot be fully reconciled.
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magicturtle42
magicturtle42@magicturtle42·
@tszzl Maybe each person gets one superintelligence which advocates for them and assists them.
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roon
roon@tszzl·
I’m very skeptical around weak language around “humanity” which launders many assumptions naively. the idea that all people’s objective function congeals effectively is not a foregone conclusion and is generally even a totalitarian idea
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roon
roon@tszzl·
the governance of superintelligence will work very differently based on whether we try to make it work for: - the user - the “good”, broadly construed, as understood by the company - “humanity” (what the hell is that anyways) among many other possible hierarchies
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magicturtle42
magicturtle42@magicturtle42·
imagine it gets smarter than Einstein but it still talks like that
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magicturtle42
magicturtle42@magicturtle42·
I empathize with this, but I am working on adjusting my perspective. It does feel like a skill I enjoyed and spent my professional life improving was taken from me. I *could* still choose to program by hand, but I will get lapped by those who do not. One thought is that my work is not for myself. I am working to make life better for other people around me. If the tools help me serve others better, so be it. My approach has been to move the struggle. How quickly can I move while maintaining high quality? Speed and correctness still seem like deep frontiers filled with rewarding challenges. Onward!
ThePrimeagen@ThePrimeagen

I have been thinking about this a lot. I think for a great many of engineers, the ones who did it because they loved it only to discover that money was in fact at the end of the rainbow found both the journey and the destination satisfying. In fact, I think I can argue with authority that the destination was only satisfying as the journey was difficult. The hard-fought evenings spent toiling away on an idea and codebase that slowly gives way to your vision was an incredible experience. The group of people that fell into this category of hard-fought journey and destination we will call them tinkerers. One thing tinkerers have always hated is the already known problems. The journey is clear as day. The obstacles minor inconveniences. Its purely a matter of typing the solution into the terminal. This is also why I think so many of this group goes out and does open source, or starts companies. Work largely falls into this category with few exceptions. From this reason is why I largely find UI work soul sucking. I know the solution, its a matter of just looking up the details and putting it into my editor. yawn. CSS, flex box this, grid that, put the tailwind classes in the bag. To me, the LLM software world is with little to no journey and discovery. Its more of simply taking my high level idea and just formulating it into testable, atomic chunks that can be verified. I have traded my favorite part, discovery and raw creation, with itemized list of TODOs and patience and "No Mistakes." To this, every morning from 6 to 9 I simply just hand code every thin. even UI things. It is because I want journey and discovery and raw creation. Maybe one day comes and its just so futile that I stop this. But for now, I still see such great value in this. I see such better thought through products. Because slowing down and truly thinking through everything. The architecture, the design, everything is an expression of discovery and creation. And I love it. I am sure there will come a day, maybe even in the next 6 months where I change my mind. For now, I pursue the love of the game intentionally. I do also believe that there exists people who get the same joy I got from building with tears and sweat by prompting LLMs. I am positive of it. I just don't understand how. But people love UI work. I also don't understand that.

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