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xwowsersx

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email: xwowsersx [at] fastmail [dot] com

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www.reuters.com 9mo ago

Starbucks CTO resigned Monday amid tech revamp

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www.nytimes.com 1y ago

Psychologist Shows Embryo of Computer Designed to Read and Grow Wiser (NYT 1958)

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news.ycombinator.com 2y ago

Ask HN: Are companies building models or leveraging existing ones to add AI?

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web.eecs.umich.edu 2y ago

Datacenter as Computer: Intro to Design of Warehouse-Scale Machines (2013)[pdf]

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blog.levinotik.com 2y ago

Taming State Mutation: Rust's Ownership vs. FP's Immutability

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arxiv.org 2y ago

Disco: A Functional Programming Language for Discrete Mathematics

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www.youtube.com 2y ago

Learning Nim: Write an Interpreter Episode 04 [video]

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www.youtube.com 2y ago

Learning Nim: Write an Interpreter Episode 03 [video]

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arstechnica.com 2y ago

95% of OpenAI employees have threatened to quit in standoff with board

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www.youtube.com 2y ago

Learning Nim: Write an Interpreter – Episode 02 [video]

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www.youtube.com 2y ago

Learning Nim: Write an Interpreter [video]

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blog.cleancoder.com 2y ago

SJWJS (2018)

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www.umass.edu 2y ago

Umass Amherst Computer Scientists Boost Computing Speed with AI

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travisbrady.github.io 2y ago

Moving from Zsh to Fish (2020)

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bitwarden.com 2y ago

Bitwarden releases free and open-source E2EE Secrets Manager

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www.aip.org 2y ago

The Panama Canal, an engineering marvel (2014)

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stackoverflow.com 2y ago

You can't parse [X]HTML with regex

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medium.com 3y ago

Lessons learned about rewriting code in my 10 years as a developer

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news.ycombinator.com 3y ago

Ask HN: What are my best options for building on top of AI today?

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news.ycombinator.com 3y ago

Ask HN: Do you use text-to-speech / dictation much?

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www.businessinsider.com 3y ago

Slack's Decreased Value If Sold to Appease Activists

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blog.levinotik.com 3y ago

I Tried JetBrains' “New UI” and I Liked It

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martinrue.com 3y ago

To be productive, be prepared

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www.thinkingdevops.com 3y ago

What Is DevOps?

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www.nber.org 3y ago

Schooling during pandemic: in-person school associated with more teen suicides

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www.nytimes.com 3y ago

In the Bahamas, a Lingering Sympathy for Sam Bankman-Fried

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blog.ngrok.com 3y ago

Ngrok Raises $50M for Ingress Without Infrastructure

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i.imgur.com 3y ago

Got a smudge you can't see? Try this color as a background

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news.ycombinator.com 3y ago

Ask HN: Which RFCs do you think most developers should read?

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github.com 3y ago

Future of Hastebin

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Study seem to have addressed point #2 in several ways.

1. They measured maternal vitamin D before supplementation began. They explicitly adjusted for these preintervention levels.

2. the two groups started at essentially the same vitamin D levels.

3. They specifically tested whether baseline vit D status changed the effect of supplementation

Intuit has a pretty broad financial software portfolio, not just a tax company.

Also, yes the actual arithmetic at the end should be handled by deterministic code. I doubt anyone, including Intuit, thinks otherwise. But there's a ton of uses for LLMs before you get to 2+2 = 4, explaining concepts, document extraction, understanding the full financial picture, etc.

Kind of feels like you're criticizing a cartoonish idea of AI's place in their products.

Nah. A forcing function creates pressure toward an outcome...a standing meeting just creates pressure toward the meeting. Those aren't the same thing.

The moment you put a recurring block on the calendar, the implicit contract shifts from "we make progress on this work" to "we show up on Tues at 2". The meeting becomes the deliverable. And it always stays long after the original need has passed because nobody wants to be the one who kills it.

What you want is to call a meeting when you need one. When there's a decision to make, a blocker to clear, or a plan to align on... get the right people together and do that thing. A meeting you call as needed stays honest, or at least has a higher chance of staying honest. A standing meeting just becomes calendar furniture and most of the people in it know it.

This looks great. I've been looking for something simple like this...assuming I’m understanding it correctly.

I recently picked up a refurbished Lenovo ThinkStation, and it's an absolute beast. I keep it next to my main work machine and offload all the heavy work to it like running multiple agents, jobs, etc. It's connected via Tailscale, and I’m usually just SSH'd into it.

What I'm missing is a clean, easy way to see what's actually going on on that machine at a glance. Looks like this might fit the bill?

What is the memory system you are referring to? I've been trying Memori with OpenClaw. Haven't had a ton of time to really kick the tires on it, so the jury's still out.

It sounds appealing at first because it flips the trust model... instead of the service initiating contact the user proves control of their email up front That feels cleaner and arguably more robust against certain classes of abuse

But from a UX standpoint its a nonstarter

Youre asking users to

- leave the site/app

- open their email client

- compose a message or at least hit send

- wait for a reply

- then come back and continue

Thats a lot of steps compared to enter email -> click link. Each additional step is a dropoff point especially on mobile or for less technical users. Many people dont even have a traditional mail client set up anymore, they rely on webmail or app switching which adds even more friction

It also introduces ambiguity

- What exactly am I supposed to send

- did it work

- What if I dont get a reply

From the service side youre trading a simple well understood flow for a much more complex inbound email processing system with all the usual headaches (spoofing parsing delivery delays spam filtering)

In practice most systems optimize for minimizing user effort even if that means accepting some level of abuse and mitigating it elsewhere. A solution that significantly increases friction... no matter how principled...just wont get adopted widely

So while the idea is interesting from a protocol design perspective its hard to see it surviving contact with real users

I feel like we're still stumbling about a bit and don't know all the answers, which is fine. But NVIDIA frames AI agents as the next computing paradigm, but most of what's described here still looks like orchestration + retrieval + tool use on top of LLMs.

What actually has to change at the systems level (data layout, memory, scheduling, storage, networking, etc.) for agents to become a first-class workload rather than just another application pattern on existing infrastructure?

True enough. But to be clear, that's a separate issue from what users are reporting here.

Both hobbyists and professionals are understandably frustrated that tokens are being consumed quickly without justification, or at least in ways that seem entirely avoidable.

How unimpressive the first iPhone was??

Yeah, totally... a full touchscreen computer in your pocket with no physical keyboard, pinch-to-zoom magic people thought was CGI, a browser that wasn't a joke, visual voicemail, and an OS so smooth it made every other phone look like it ran on car batteries. Truly underwhelming stuff.

It literally redefined an entire industry, vaporized half the product lines at Nokia/BlackBerry/Palm/Microsoft, and set the blueprint for every smartphone that exists today.

But sure..."unimpressive."

This is the weirdest revisionist history I've ever heard.

If you mean that the iPhone has come a long way and that it was unimpressive relative to the phones we have 18 years later, sure. But unimpressive it was not.

I think what PG meant by "do things that don't scale" is earnest effort in service of building a real product: talking to users, manually onboarding, hand-holding early customers so you can learn fast and iterate toward something that eventually does scale.

What this startup did isn't that, AFAICT. It wasn't manual work in service of learning...it was just fraud as a business model, no? Like, they were pretending the technology existed before it actually did. There's a bright line between unscalable hustle and misleading customers about what your product actually is.

Doing unscalable things is about being scrappy and close to the problem. Pretending humans are AI is just straight up deceiving people.

How so? Read the paper. The methodology was entirely observational. They did not intervene in the prosper.com loan market or interact with the borrowers. If anything, the paper identified a form of bias that exists in the real world, namely that people commonly "perceived" as less trustworthy are penalized despite their actual creditworthiness.

Yeah, exactly. The context here was about the profitability part of OP's comment. The parent said "plenty of businesses fail to find a way to make a profit," and my point was that OP's statement doesn't contradict that. OP was saying they'll need AGI to be profitable, not that they're guaranteed to become profitable.

Sure, they phrased it as "they will reach AGI," but that's clearly tongue-in-cheek...the underlying idea is "they better reach AGI, because that's the only way they could make money." So my comment ("necessary, not sufficient") was just pointing out that even if AGI is required for profitability, it doesn't mean they'll actually get there or succeed once they do, and that the original comment was perfectly compatible with the idea that not every business reaches profitability.

Well, of course you're correct that SQL is text, but that's not what the article is arguing about. The point isn't whether SQL is text... it's about the kind of text it is.

SQL is a formal language, not a natural one. It's precise, rigid, and requires a specialized understanding of schema, joins, and logic. text-to-sql systems don't exist because people are too lazy to type; they exist because most people can't fluently express analytical intent in sql syntax. They can describe what they want in natural language ("show me all active users who registerd this year"), but translating that into correct, optimized sql requires at least familiarity, and sometimes expertise

So the governance challenges discussed in the article aren't about "oh SQL is too hard to type"...they're about trust, validation, and control when you introduce an AI intermediary that converts natural lang into a query that might affect sensitive data