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There's a hacker news link at the end of the document, under "Blocklist used for Humanity’s Last Exam". It links to https://news.ycombinator.com/item?id=44694191

According to my App Store history, on May 30, 2010, I downloaded the app "Ian's Laces — How to tie and lace shoes (Lite)". Since then, I've very rarely had to tie my shoes :)


AIs should look at something like this to have more humility when interacting with humans: Andrés Gómez Emilsson making AIs "aware" of their own lack of awareness: https://x.com/algekalipso/status/2010607957273157875


I’m wondering if anything in their setup is worth incorporating into the “status quo”

The most immediately relevant thing is equity-based comp that doesn’t have a tax hit.

Another thing I find interesting is whether this comp might be more “mission-aligned”:

- It’s likely this is all just to accomodate their “non-profit with limited profit subsidiary” structure

- But there's still a deeper question there: do current specifics of how startups do comp / investment / exits somehow result in societally suboptimal outcomes?

- If so, how exactly, and is it fixable, or are those inherent properties of an ecosystem of competitive, high-growth startups?

- One way that might be the case is if there’s a pressure for “growth at all costs”, which is something OpenAI would want to avoid.

- The pressure for that could come from a lot of sources — intrinsic desire for growth; financial expectations from shareholders (employees, VCs, public market investors, even customers); regulatory requirements around fiduciary duty; existential risk of going under or competition, or needing to hit a certain size to achieve whatever it is you want to achieve

- Another way this could be the case would be limited exit opportunities, or limited creativity around them / sticking to well-trodden paths, ultimately resulting in control of the company being handed over to either poor management or groups prioritizing growth at the expense of good product

- Thinking about twitter and reddit’s API shutdowns here — how much do unpopular product decisions like that come from legal specifics? Or perhaps those would have happened no matter what, to keep the companies from going under or to have enough profits to fund further innovation.

- It’s not obvious that this setup avoids a motivation for “growth at all costs” — employees’ pay is still based on increasing profit, and if it doesn’t grow as fast as competitors it may just become irrelevant. But it’s possible it affects other strings around company control. Not sure — IANAL :)


I wonder whether AT Proto, the protocol used in bluesky, might make for a good base for a decentralized reddit alternative.

- public

- extensible

- bring your own client

- domains as usernames

- federated but with escape hatches so you're never tied to a single host

- considerations for twitter-scale from the start, eg with "big graph servers"

Still under a waitlist / closed for now / under very active development, but seems very promising.


"In the province of the mind, there are no limits."

I do wonder to what degree this is true

There are claims that other animals see more colors than us. But what if that's not actually the case? Maybe conscious minds are only capable of seeing the same rainbow that we do

The mapping could be quite different, and even if you can't add more letters to "RGB" you can add more letters to "HSL", making things look neon, stereoscopic, brushed, iridescent, hyperbolic, etc. But perhaps what we see is already all the possible "base" colors?


Apple wants the iPad OS developer experience to be bad

Their #1 focus is lock-in, preventing being commodified, and extracting value

No apps that run operating systems, no apps with windowed environments, no app-store-like apps / third party app stores, no browser engines, no Flash, terrible mobile safari experience, no OS mods / jailbreaks, no desktop-style cursors, physical iPad keyboards lacking escape keys. Wanting 30% of all payments for digital goods that occur on an iPhone.

Being able to eg "run Docker on your iPad" would go against all that. I think it's also a big part of why they charge $99/yr for being a developer - otherwise people would be able to sideload apps much more easily

Nice article related to this: https://subconscious.substack.com/p/aggregators-arent-open-e...

Hard to imagine just how different things might be right now if things were more open. iPhones are always on and connected to the internet - you could run servers from them! maybe mesh networking could actually be a thing?

The mother of all demos would not be allowed on the app store. Squeak/smalltalk would not be allowed. Feels disrespectful to humanity that the most popular platform in the US is so locked down. Idk how things would change here without government intervention -- this all seems to be in shareholders' interests.

Seems like a good time to be running a competitor. iOS being so locked down means they'll have lackluster support for the long tail of desired AI use cases. And cross platform development via react native is really good now, imo.


Congrats on the launch!!

Any plans on adding "in-memory" / "virtual" file support to Bun.build? I'd be interested in using it for notebook-style use cases

--

Also, ways to do "on-the-fly" "mixed client/server" components (ala hyperfiddle/electric) + sandboxing (ala Deno) would be extremely exciting

Some projects in this vein - https://github.com/jhmaster2000/bun-repl and https://www.val.town/

Also, bun macros are very cool -- they let you write code that writes over itself with GPT-4. Just mentioning as a thing to keep on your radar as you keep pushing the boundaries of what's possible in javascript :) making it more lispy and preserving eval-ability is great


Had a homeless guy sit behind me on the bart repeatedly saying he'd slice my neck if I turned around or moved at all. It was a mostly-empty car, and it seemed like he was serious and that nobody else was going to do anything. Wound up sitting still and bolting out at the next stop. Tried calling the cops after and they didn't care in the slightest. Just one of many incidents.

I live in Cambridge, MA now, and it's a million times better. Only thing remotely close that I've seen was one time biking past the Woods-Mullen Shelter in Boston (saw two other comments here call it "Mass and Cass"), except it's just one block and extremely tame compared to what you find all over the Mission, SOMA, and Tenderloin.


Speaking of python performance, I recently benchmarked "numpy vs js" matrix multiplication performance, and was surprised to find js significantly outperforming numpy. For multiplying two 512x512 matrices:

    python
      numpy:               ~3.30ms
      numpy with numba:    ~2.90ms

    node
      tfjs:                ~1.00ms
      gpu.js:              ~4.00ms
      ndarray:           ~118.00ms
      vanilla loop:      ~138.00ms
      mathjs:           ~1876.00ms

    browser
      tfjs webgpu:          ~.16ms
      tfjs webgl:           ~.76ms
      tfjs wasm:           ~2.51ms
      gpu.js:              ~6.00ms
      tfjs cpu:          ~244.65ms
      mathjs:           ~3469.00ms

    c
      accelerate.h:         ~.06ms

Source here: https://github.com/raphaelrk/matrix-mul-test


Numpy runs on CPU. Tfjs runs on GPU. Not a fair comparison.


You're right, it's not a fair comparison -- I think it's still interesting though, since numpy is the standard people would reach for, which made me think it would be the fastest / use the GPU. I expect a python library that uses the GPU would be just as fast as the others.


For that, you can use cupy[0], PyTorch[1] or Tensorflow[2]. They all mimic the numpy's API with the possibility to use your GPU.

[0] https://cupy.dev/ [1] https://pytorch.org/ [2] https://www.tensorflow.org/


It adds a great deal of complexity (and often user frustration) for a Python package to support both CPU and GPGPU.


People don’t reach for numpy because it’s the absolute fastest…


What I meant was I expected numpy to be faster than the js libraries I was testing, simply because people use it so much more, for real "scientific computing" work. And indeed it is very fast given it only uses the CPU, but that still leaves its matrix multiplication as ~100x slower than what my mac is capable of.


TensorFlow.js matrices are immutable, which puts more restrictions on your programming style that standard Numpy. You cat get immutable, GPU-enhanced matrices for Python, too.


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