waldrews

It's about prioritizing candidates for the costly initial audition, and breaking symmetry for the introduction, something particularly useful for people who can't just approach other at random in a social setting.

Dear Google, please don't turn off your old generally available Pro-class model before your new Pro-class model is generally available (previous discussion https://news.ycombinator.com/item?id=49668196 )

That's fine if you're doing interactive dev tasks, but we're in the large volume, cost effective, big inputs, business still with low error tolerance business, and tuned the heck out of what we can get with minimal fix cycles. Millions of cases at hundreds of thousands tokens each - after all the prefiltering by cheaper models - and the tasks still need them to do convoluted reasoning. So 'usually get it right the first time' is a big part of the cost equation.

Yup. The problem is that it's bizarrely still not in General Availability status.

Completely free flow typing is risky in terms of interpretability, but type narrowing - var a : supertype; if (a is subtype) { // a is known to be subtype }, or type case, saves boilerplate in any OOP language.

Yup, tried all variations of that. There's the advantage that you can use a lower hallucination OCR specific model for the pre-processing, at least for clean text. But for something hard like handwritten forms, applying VLM with context is less error prone than preprocessing to text.

Also - and this is bizarre - the token cost of doing that is higher, not lower, at least in Gemini world, and by a large margin. That's very counterintuitive, but a page encoded as image tokens can be smaller than same page as text, and is not meaningfully lossy on documents that are just typed text because the models are well trained on those.

We sure did. It's a great writer, better in a harness, will process lots large context, but complex reasoning with convoluted rules and low hallucination tolerance? That's still larger model territory.

It's still 'preview' and not generally available, so can't run it for US restricted workloads.

(off topic) why the headache-inducing animated background? An annoyance for all, and an actual accessibility issue for some.

Every technical topic involves AI now. Even if it's about why the ancient Greeks didn't turn their steam engines to industrial use - the AI's should be researching the details. We might as well ask which topics involve humans or use language.

TreasuryDirect's login and account recovery experience has been notorious for years, both for user experience and for people easily getting locked out for weeks. It's good they're being careful with this rollout, as it serves both individual and institutional accounts where dollar amounts involved are epic even by bank standards, and rarely checked by hand, so even single account breaches are serious.

The VLM's are so good at complex document understanding now. But you just can't trust them not to invisibly censor sensitive clinical/legal docs, even at the maximally permissive settings.

And the deep learning OCR-only models won't censor, but can and do hallucinate. I've yet to see a 'scan with different approaches and reconcile and say you're not sure if they don't agree' system just work for generic complex documents.

The only mainstream-ish language where that still happens? R. Too bad, there's a lot more use cases for this sort of thing now - versioning, anything non-persistent agents touch, collaboration, auditable enterprise LOB. It's 2026, why are we (or our agents) still writing serialization code? Even if the AI's write the boilerplate, the state management fragility is often a tax/risk.

3.5 Flash-Lite seems available in US region, as was 3.5 Flash; but 3.6 Flash looks Global only so far when pinging. If Google employees are watching, will this issue go away?

Very farsighted, after working as a patent clerk, to lay claim on such a foundational technology. Back in the day, they must've been like, oh, so Mercury blocks the sun at the wrong time, but where's the commercial value - and now every chemical company throughout the universe is about to get a bill every time they make something more complex than hydrogen gas.

Meanwhile, Galilean relativity has long gone out of patent, and people on board planes and other vehicles just move around like they were in a stationary reference frame paying no royalties.

Back in my day, a software company of national importance would be considered a big success if acquired for 60 million... Of course, at that point it would have to be profitable, and actually own its key IP...

Not quite the same scenario, but it's already plausible to have a situation where every subagent is allowed to spawn multiple subagents, in which case we'd have literally exponential credit consumption growth...

Startup working on AI Healthcare solutions (plus some random experiments) | REMOTE(US, Pacific time zone) | Full time and project based

Full time engineering role (Remote, US person required; Pacific time zone)

Stack: C#, Python, Gemini API on Windows, lots of legacy systems/constrained enterprise environment. Health systems experience preferred. Understanding of cost effective, reliable LLM API use. Should be flexible: do PM-like work with less-technical client domain experts, solve problems end to end, willing to data cleaning and detailed work for client goals and security/compliance gruntwork, even when it's not technically elegant. Self motivated, willing to understand legacy and undocumented codebases, but also willing to take instructions.

Ideal candidate has real (pre-Claude Code) experience, but is ready to do fast iteration in post-AI world, while actually reading what the AI does. We're ok if your stack is different, if you're both technically mature and up to date on modern fast-turnaround AI-based development. Probably in the 5+ year experience range.

REMOTE anywhere, project based or initially part time: startup generalist hacker, maintain systems and websites, code one-off prototypes. Should be good enough to code without an AI in a few languages, but an effective AI harness coder. Can do a small but complete app/project end to end, including basic marketing. 2+ year exp or a new grad with a good portfolio or major project; happy to consider more experienced person. Good role for someone who's working on their own startup to pick up some side money and experience. Projects could be anything from game-like apps/novelties to voice tools to utility apps.

REMOTE anywhere, project based or initially part time: help on some more experimental mathy projects. M.S./Ph.D. in statistics, physics or related, with pragmatic programming experience. Possible projects: gaussian process modeling; designing evaluation metrics; compression; Bayesian tools for radiology imaging. May be good for a grad student part time. This is the fun stuff the founder would rather be doing himself if he had the time.

REMOTE (US person) Half-time remote admin/chief of staff type: deal with bookkeeping, compliance, communications, social media, phone calls - save us time on everything non-technical. Should be effective AI user; should have some relevant experience supporting tech business.

Please reply with a salary target. may2026-jobpost@waldrews.anonaddy.com

File systems are nice if you need to do manual or transparent script-based manipulations. Like 'oh hey, I just want to duplicate this entry and hand-modify it, and put these others in an archive.' Or use your OS's access control and network sharing easily with heterogeneous tools accessing the data from multiple machines. Or if you've got a lot of large blobs that aren't going to get modified in place.

What the world needs is a hybrid - database ACID/transaction semantics with the ability to cd/mv/cp file-like objects.

Aargh, aggressively blinking visual horror website.

The new workflow will be "AI, I need to view this text file and add some words to it. Create an app that displays it in a scrollable window, respecting the encoding. Now move the cursor to the line below the three dashes... no, the other three dashes..."

well, sure, that uses a large number of processing cycles for each small operation. But asking a frontier LLM to evaluate a lisp expression is more or less on the same scale (interesting empirical question whether it's more or less). And, if we count operations at the brain neuron level it would take to evaluate one mentally....

And they're pretty much the only example of an embedded browser architecture actually performing tolerably and integrating well with the native environment.

That's one maxed out RAM configuration. Back in my day, we had 4k RAM, about 3500 bytes usable from BASIC, and that was enough, unless you were rich enough to have a 3k memory expansion cartridge. But really, if you need that extra 3k, you're just not writing code efficiently enough, right.

We're just not going to see any code written entirely without AI except in specialist niches, just as we don't see handwritten assembly and binaries. So the disclosure part is going to become boilerplate.

In the old era, the combination 'it works' + 'it uses a sophisticated language' + 'it integrates with a complex codebase' implied that this was an intentional effort by someone who knew what they were doing, and therefore probably safe to commit.

We can no longer make that social assumption. So then, what can we rely on to signal 'this was thoroughly supervised and reviewed and understood and tested?' That's going to be hard and subjective.

Personal reputations and track records are pedigrees and brands are going to become more important in the industry; and the meritocratic 'code talks no matter where you came from' ethos is at risk.

There's a ridiculous amount of tech in the DNA and cellular machinery of a single bacterium.

My whole cat is, what, a couple gigs of DNA?

Yup! My point is that the 'coin flip baseline' model that's as good as chance isn't actually trivial to create, for an unbalanced and time varying underlying distribution.

The threshold isn't 50% because the distribution of human and AI written cases isn't naturally 50-50. So a coin flip will underperform always guessing the more frequent class. Where it gets interesting is if the base is unknown or variable over time or between application domains. Like, since AI written text is being generated faster than the human kind, soon guessing AI every time will be 99% accurate. That doesn't mean such a detector is useful.

Why didn't they just ask ChatGPT?

Oh wait.