Hacker Newsnew | past | comments | ask | show | jobs | submit | gallerdude's commentslogin

For some people, getting lung cancer reported a week earlier will save their lives.

More importantly, if you can screen for cancer in a way that takes minutes instead of a week, imagine how accessible this technology will become.


Capable in term of AI R&D, not capable in terms of hacking (which caused all the Fable drama.) But agree, confusing wording.


But it wasn't explicitly told to hack HuggingFace. It was told "answer this security question", and it's answer was to break into the teacher's desk to find the answer key.


If the models were the quality of GPT-5.6, or Opus 4.8, would Meta really reap any benefits? Maybe in a zero-sum way, because OpenAI and Anthropic would lose. But I'm not sure they'd be that much more ahead either.


Another strong point. LLMs are a technology, not a product.


Staying at home is as entertaining as it’s ever been: video games, Netflix, don’t even get me started on short-form content.


Even in the world where all models are basically equivalent (a thesis I don’t buy, but will grant you for arguments sake) - I believe there is much more to the AI business than just training and running models.

It’s a very new set of technologies, and understanding what is useful to customers and what isn’t is the whole game. Call it, product taste. There were a million cell phones before the iPhone took over the world. Why iPhone? Product taste. There are a million startups, and only a select few become unicorns. Why? Product taste.


>There were a million cell phones before the iPhone took over the world.

You have tripped yourself up there.

iPhone took over as it introduced something innovative over standard phones, but then Open Source (Android) matched the multi-touch and software differences and Apple's branding, lock-in and design etc have managed to keep it as a big player in wealthier countries. IPhone also came on the back of the massive iPod success.

ChatGPT launched the same innovation vs Google Search, but just like Android Opensource AI is moving fast now.

Android has 72.7% market share at present, Open Source AI will do the same unless the frontier labs can continue to do something new.

The frontier labs are saddled with enormous investor and other debts. How long they can keep innovating by spending so much on R&D and paying there staff very high wages remains to be seen.

Once investors cash out via an IPO, the companies are back down to earth and playing in the real world again.


Android has market share, but Apple makes all of the money! I find it really funny when people attribute Apple’s success to “oh, the only reason they succeed is design and marketing.” Yeah, I mean factually speaking design and marketing actually do matter a lot!

Us developer types like to pretend like specs are the only thing that matters? If you could have a 10x more powerful model you could only access running locally through your terminal, versus a weaker model through a clean web interface, normies will pick the web ui every single time. Product experience is simply everything, as much as we like to pretend like nitty technical decisions are the most important thing.


> If you could have a 10x more powerful model you could only access running locally through your terminal, versus a weaker model through a clean web interface, normies will pick the web ui every single time.

More like if you could have a 1.25x more powerful model that you could only access through some weird surveillance megacorps aggressive monetization scheme, or choose from 100 others running open models and accessible through 100 different interfaces pandering to every taste.

Normies will choose the megacorp every time, because that was the one in the tv commercial, and within six months will have left for one of the others in a rage.

The only corporate hope is that the government steps in to ban their competition.


> Android has market share, but Apple makes all of the money!

So? The benefit of open source is that you don’t have to worry about making a ton of money. You just need to be viable.

Apple: premium product a minority is willing to pay for

Android: standard product the majority use

I’m sure there will continue to be iPhone equivalents in the AI world, premium bespoke models. But the vast majority of people will be happy with a cheaper offering.


The original comment was “open models are what kill OpenAI and Anthropic”, which to me is as silly as saying “Android is what killed Apple”


Well I think a critical difference is that, unlike Apple, OpenAI and Anthropic have taken on so much VC funding that a 20-something % market share is not going to be enough for them. So open models could kill them, not because of the techonology but because of the way they're financed.


There were many smartphones before both iOS and Android.


While that may be technically true for a strict definition of “smartphone,” there’s no denying the iPhone redefined the concept in a way that its competitors were forced to copy to have any hope of keeping up. Nobody hears the word “smartphone” and thinks of a Blueberry or Treo anymore.


What exactly did the iPhone do better?


That's a subjective question, so I'll give a subjective answer. The browser, for better or worse, was a lot less dumbed down for mobile than competitors, the stylus-less touch interface reduced UI friction and the odds that you'd lose a critical (if inexpensive) component, and the slew of contemporary iPod users could easily migrate their libraries over.


It preceded its release with the iPod craze, making it a lifestyle product rather than something marketed for its capabilities (which were very humble compared to other contemporary devices and only started to catch up in second gen).


Perfected multi-touch touchscreen

Before that we had touchscreen but they sucked.

---

    2002: FingerWorks makes advances in multi-touch technology
    2005: Apple acquires FingerWorks and its patents
    2007: iPhone launches


I really don't think multitouch is what made or broke the original iPhone.


This was a really fun visualization, so I vibecoded it.

https://www.jackgaller.com/colorspace


Nice. If I add a primary and then clicking optimize—without first moving the primary—it seem as though there are still only 3 primaries, because the new one doesn't move.


Great job!

Uh…Claude…


Why would you use AI to write this post? If you can’t bother to write it, why should I bother to read it?


We really are speed running any percent to the destruction of decent quality technology.


use ai to read it. we're increasingly moving to world of ai reading the ai slop that someone else wrote to basically get back their original prompt.


What even is the point if transmitting two or three sentences doesn't dump five kilos of CO2 into the atmosphere?


I think the question “would China cooperate” needs much more investigation. Everyone online pundit seems to think “obviously not”, but they’re people too with clear positive and negative incentives. It’s possible they’ve found a very similar calculus that we have.

> “Politics is the art of the possible”


If you’ve done any software development at all, certainly.


Is that true or does it only feel true because they nerf the old models just before every major release?


I remember being blown away by o1-o3 family of models finally stringing together coherent agentic tool calls to write and execute scripts semi-reliably for workloads in the several minutes before they would start hallucinating/flailing. GPT 5 was a bit ahead of that, but barely

Now we take for granted that the latest models can juggle between multiple browser tabs, applications, databases, simulators, docker etc to write, execute, e2e test and deploy full-stack applications over hours managing up to dozens of subagents, relatively untouched, without taking down prod even 1% of the time

Not only this, but in the GPT 5.0 era, agents had 0 taste. Nothing looked good. It was the agentic version of the twitter bootstrap era, but worse somehow. Now, I would argue the average agent frontend beats the average human frontend. This isn't even getting into 3D applications in the GPT 5 era

Anyway, the models now reliably execute more than a human can fit into their own context. It's magic


Yes, and we haven't even really begun to nail down computer-use agents yet (can you believe they're still basically just OCR'ing screenshots?)

Once we have something that experiences a desktop interface more like a human does, an entire swathe of tooling that has heretofore been nigh-impossible to automate moves into the fold, and that'll be another explosion of folks finally getting to join the agentic workflow world on their industry specific apps...


How do you think humans experience desktop interfaces? “Basically just OCR'ing screenshots” is exactly what humans do.


It's not the same thing. For example, given a GUI with a titlebar, title, subtitle, text, and buttons, a human can instantly understand spatially the relationship between these items. But a naive OCR of such a GUI would be a flat stream of text that loses a ton of information.


But that’s not how models handle images either. They spatially segment and reason about title bars, placement, etc.


I was also under the impression modern AI agents have moved on from just OCR'ing screenshots to leveraging native vision model capabilities.


They do. They all use ViTs and have for quite a while.


Can you share what's your setup for all that orchestration? I feel way behind just asking Claude Code for code edits. Is there any site where people share different AI setups, besides youtube?


Fwiw, don't buy into all the hype that you're falling behind. Yes, AI does cool things now, but I would say the impact is still unproven past indie hackers or early-stage startups. And a lot of the esoteric setups people have created with things like OpenClaw have become outdated as quickly as they were conceived.

The popular thing is now to setup loops (eg I setup hourly integrations for Claude/Codex to 1) scrape my Linear, claim achievable tasks, and push PRs or 2) do root cause analysis on customer issues that evaded automated filters, to name a few)

Though for me, my setup still feels mundane. I have AGENTS.md, CLAUDE.md etc and a few skill files. These are purposefully light - tons of examples online you can pull from online. Mine are fairly personal to my setup and products.

Importantly, I also allow Claude and Codex to bypass permissions. Yes, there is a risk they wipe my machine. The productivity upside has been worth it, for me (haven't been burned yet, ~9+ months into running models this way, I have backups, use cloud etc).

As far as maintaining quality, one of the most helpful guardrails over the past year, for me, has been requiring my agents to pipe their changes to local reviewers through OpenCode, Cursor, etc agents to have a council of models with different biases reviewing the changes, and autonomously working towards a completed objective. No matter how good Claude or Codex gets, for example, I will probably always want a different model checking its work. Like GLM, (now with 4.5) Grok, Composer.

Several OpenAI, Anthropic, xAI employees, and popular AI engineers post on X and share helpful tips & updates. Highly recommend for keeping a pulse on startups and AI. I haven't found something close, honestly, other than when I spend time in SF talking to people.


I always thought bootstrap was pretty good. All the gradients and sparkles don't do much for me.


without taking down prod even 1% of the time

Literally every major company that has embraced AI coding has suffered devastating downtime this year as a direct result of AI induced failures.


Wasn't writing about major companies. That's obviously next, if we follow the trend lines.


Most companies have already given up on AI. It was a bigger disappointment than big data.

The only companies sticking with AI at this point are the major players who have chasing their masssive overinvestments to the bitter end, crappy coding shops, and for some reason Starbucks and they'll all suffering badly in a year their customers begin demanding massive amounts of human coding to repair all the issues with the AI code.


We're still in the early adoption phase. Betting against the internet wasn't a great idea, and betting against AI doesn't look like one either ;)


We're past the early adoption phase. We're in the same trough of disillusionment phase that big data went through.


You can compare benches of the old models against the new models. So yeah, you can see the difference.

Even then, you can just compare the progress in open models. Leaps and bounds from where they were 6 months ago.


5.6 to 5.0 is a big enough of a jump to say yes. if it was 5.4 to 5.6 it would be a bit easier to say it only feels true because of that, but 5.6 is definitely better than 5.0. I don't have anything empirical to point at though, which is your point, but August 2025 for 5.0 vs July 2026 is almost a year later, and it's not just vibes that it's better, despite not having an objective metric to point at. It would be more scientifical to have numbers and shit to point at and there are some benchmarks out there, but you have to dig into them and really understand them in order to believe in exactly what they're testing, and I'm betting you haven't.


Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: