I’ve been an android developer for a decade at this point, I’m aware of how app deep links work.

The comparison is not “what LOE is call linking from scratch” but rather “how does call linking meshing into existing production codebases across all platforms compare in LOE to 3 buttons?” And the answer is self evidently more.

You’re minimizing the amount of effort and we’re comparing it to buttons. Adding “a few buttons” is very different than setting up 3 platforms to all use a new protocol (calls from links will require new handling - previously all calls were just based on authenticated users being allowed into webrtc calls based on their tokens. Now you have to have a new handler which joins a call with the token in the URL - that can’t be handled identically). Then we get into the Android app, much of which is still in Java, which uses multi-activity-srchitrcgure meaning you’ve gotta pass data through each layer manually, rewriting each of these activities to accept the new deep link and route to the right end.

And then you’ve got to be sure it all coordinates across iOS, Android and your backend.

It’s not hard but it’s not “a few buttons”. It’s probably 2 weeks of work for skilled and competent engineers, 1 per platform.

Do you actually have any experience in Mobile dev? You sound like a fresh outta college junior eng - cocky and confident that everyone else is wrong, making it harder than it needs to be etc.

Just like that cocky junior eng you’re too unaware of what you don’t know to realize you’re wrong. Wade through the grass a few times and you’ll realize the flowery meadow is full of snakes.

Call links are a lot more work than “a few buttons”

I heard rumors someone burned his house down. No idea if they’re true or not.

He has said that they already know everything they need to know to get to AGI.

OpenAI has not made a single thing that wasn’t just a wrapped LLM.

So either A: he has somehow been running a skunk works that has fundamentally changed everything we know limits LLMs and none of the researchers leaked anything or B: he thinks LLMs are the way.

Additional quote when he was asked about AGI:

“How did we get to the doorstep of the next leap in prosperity? In three words: deep learning worked. In 15 words: deep learning worked, got predictably better with scale, and we dedicated increasing resources to it,” Altman said.

This tracks with the whole “I need 1 trillion dollars of energy investments” plan to get to AGI that he’s asked for.

The guy’s either honestly convinced himself that we can get there with deep learning scaling or he’s a conman. Could be both.

It’s what Altman has constantly said was going to happen. Up to you to decide if he’s actually in the industry or not.

The fundamental architecture of an LLM is used across all these services - and that’s reaching its limits.

Heavy investments is a strong term for modest hedges around SMRs.

Tens of millions is low risk pocket change compared to the billions burned running the things constantly.

The problem is they’re all playing chicken with each other.

OpenAI will never back down. The question is will Google, Microsoft or Amazon blink first

Affinity is great

I’m pro nuclear as well but we absolutely can maintain this level of energy consumption on renewables alone.

The question is cost and risk - I’m for diversification of our grid which includes nuclear.

But it is getting to the point where renewables with backups will be cheaper than coal. That’s absolutely something you can run the entire grid off of. You can balance storage requirements with excess production capacity that gets shuttered over the summer etc etc

Oh my God an image macro posted to the political memes board doesn’t have 60 pages of nuanced footnotes explaining how if you’re in Nebraska then your voting system works differently I’m going to literally shit my own pants out of rage

Cause and effect reversed there buddy

New devs: “wow a new sdk version”

Old devs: “Ah fuck I’ve gotta change how we request permissions again”

You might not notice it but us Android devs do.

It is my understanding that the fundamental architecture (the general purpose transformer) is identical between the “AI” used by Black Rock and by OpenAI

If you have some evidence to the contrary I’d always appreciate the chance to learn.

But the transformer based architecture is fundamentally flawed: it will always hallucinate.

The “AI” being used by big corporations is still fundamentally an LLM and has all the flaws of an LLM. It’s not a hot wheels car vs a tank, it’s a hot wheels car vs a $2 billion RC car

I’m having an aneurysm trying to understand what’s being said here, can anyone explain?

Good to know - I didn’t opt for the 1k range personally, I sprang for a Priority Current with Enviolo hub. Love that bike - commute 9 miles to work on it.

Zoom ai transcriptions also make things up.

That’s the point. They’re hallucination engines. They pattern match and fill holes by design. It doesn’t matter if the match isn’t perfect, it will patch it over with nonsense instead.

I dug into this more because I was under the impression it was the case that most states did not: here’s what I found

https://felonvoting.procon.org/state-felon-voting-laws/

23 states let you vote after prison. 9 fully stop you off your rights. DC & 2 State let you vote from prison. The others are some level of parole or parole and probation.

Which means overall 9/51 are full loss: everywhere else you can theoretically get it back.

I like it because you mentioned it in the other thread with me and I’ve stolen it.

emoto™ is mine now… You can license it from me for $7Trillion