https://github.com/ralusek/streamie

allows you to do things like

    infiniteRecords
    .map(item => doSomeAsyncThing(item), { concurrency: 5 });

    infiniteRecords
    .map(item => doSomeAsyncSingularThing(item), { concurrency: 5 })
    .map(groupOf10 => doSomeBatchThing(groupsOf10), { batchSize: 10 })
    // Can flatten back to single items
    .map(item => backToSingleItem(item), { flatten: true });

AI made “basically zero” difference in U.S. economic growth last year. https://www.youtube.com/watch?v=zZHN0-ZNe_4&t=399s

He had a family and their descendants naturally look like him.

Inconsistent execution/application of the law is how bias happens. If a judgement done to the letter of the law feels unjust to you, change the letter of the law.

It's also just not as good at being self-directed and doing all of the rest of the agent-like behaviors we expect, i.e. breaking down into todolists, determining the appropriate scope of work to accomplish, proper tool calling, etc.

Codex is the best at following instructions IME. Claude is pretty good too but is a little more "creative" than codex at trying to re-interpret my prompt to get at what I "probably" meant rather than what I actually said.

It won't make any changes until a detailed plan is generated and approved.

I am familiar with copilot cli (using models from different providers), OpenCode doing the same, and Claude with just the \A models, but if I ask all 3 the same thing using the same \A model, I SHOULD be getting roughly the same output, modulo LLM nondeterminism, right?

Using Gemini 2.5 or 3, flash.

The PIN interface is also an HSM on the backend. The HSM performs the rate limiting. So they'd need a backdoor'd HSM.

However, most users can't be bothered to choose such a PIN. In this case they choose a 4 or 6 digit pin.

To mitigate the risk of brute force, the PIN is rate limited by an HSM. The HSM, if it works correctly, should delete the encryption key if too many attempts are used.

Now sure, Meta could insert itself between the client and HSM and MITM to extract the PIN.

But this isn't a Meta specific gap, it's the problem with any E2EE system that doesn't require users to memorize a master password.

I helped design E2EE systems for a big tech company and the unsatisfying answer is that there is no such thing as "user friendly" E2EE. The company can always modify the client, or insert themselves in the key discovery process, etc. There are solutions to this (decentralized app stores and open source protocols, public key servers) but none usable by the average person.

Every time you sign in to the web interface or resign into the app you enter it. I don’t remember an option for an alphanumeric pin or to offload it to a third party.

The Messenger PIN is rate limited by an HSM, you merely enter it through the web interface.

Of course, the HSM could be backdoored or the client could exfil the secret but the latter would be easy to discover.

Harder to do any better here without making the user memorize a master password, which tends to fail miserably in real life.

It would not surprise me at all if self-driving models are adopting a lot of the model architecture from LLMs/generative AI, and actually invoke actual LLMs in moments where they would've needed human intervention.

Imagine if there's a decision engine at the core of a self driving model, and it gets a classification result of what to do next. Suddenly it gets 3 options back with 33.33% weight attached to each of them and a very low confidence interval of which is the best choice. Maybe that's the kind of scenario that used to trigger self-driving to refuse to choose and defer to human intervention. If that can then first defer judgement to an LLM which could say "that's just a goat crossing the road, INVOKE: HONK_HORN," you could imagine how that might be useful. LLMs are clearly proving to be universal reasoning agents, and it's getting tiring to hear people continuously try to reduce them to "next word predictors."