alex_sf
alex_sf on Hacker News
I mean this doesn't seem very insane? Basic info about the model, the ability to actually use it. Google in particular is awful about getting access to their models from the UX side: I don't even bother trying them out unless it's via openrouter.
I don't understand how to make a modern CPU. I'm not involved in the manufacturing of it. From my perspective, there may as well not be any human involvement. I can still use the resulting chip (in an larger system of other things I can't make and wasn't involved in) to argue with you on the internet.
It becomes another abstraction, really. As long as we can use it for something useful, it's still valuable.
> Is this really why the rule was made? Did they really have safety of driving in mind or is this just in the interest of the profits of airlines?
Yes. There are multiple public documents showing this, ex:
> The FAA has determined it is not appropriate to mandate the use of CRSs in aircraft now. We remain concerned that if we require children under 2 years old to be in an approved restraint system (which requires a passenger seat), affected operators might find it necessary to charge a fare for transporting these children. (Currently most, if not all, operators do not charge a fare for children under 2 years old who are held in an adult's lap.) In turn, for economic reasons some adults might decide to drive in automobiles to their destinations rather than fly. The FAA is concerned because automobile injury and fatality rates are higher than aircraft injury and fatality rates. As a result, there would be a net increase in transportation injuries and fatalities as families opt, for economic reasons, to drive rather than fly to their destinations.
https://www.federalregister.gov/documents/2005/08/26/05-1678...
> * Subsidize the 2nd seat for parents with children from tax dollars
That's not something the FAA or DOT can do.
> * Criminalize many intentional driving violations
That's not something the FAA or DOT can do.
> * Build high speed rail
That's not something the FAA or DOT (unilaterally) can do.
They do when appropriate after considering all concerns. The NTSB is solely concerned with safety. The best rulemaking is not literally safety-first or nothing would actually get done.
This is really naive. 'Anthropic won't give them out'. It's amazing how creative AI doomers can get about the upcoming apocalypse, and can't seem to fathom that men with guns always override the opinions of nerds in SF.
https://xkcd.com/538/
Nothing that is really landmark legislation. Dem legislators also didn't do anything about net neutrality. They deferred entirely to the FCC (which is largely why the rules were subsequently struck down).
Do you think a private company should be able to accumulate enough wealth and power to dictate policy to the US federal government?
Just to clarify:
> 2) It generates structured output natively - guaranteed to be correct
It's not guaranteed to be correct: it's guaranteed to be _formatted in a particular way_. You can get the same thing with grammars on any LLM.
Jev and Jev-like models have other advantages, but I feel like people forget grammars exist for LLMs.
You totally can. The latency is just about ~3 miles per hour.
I have people skills; I am good at dealing with people.
The models will only get better and inference cost will go down.
I don’t see any reason to think the same thing that happens with all tech won’t happen here.
I take the specifications from the customer and type them into the AI
> It’s either a maintenance issue. e.g., Opus recommended and implemented a fix for a database corruption crash. This was ~400 lines of code with many moving parts. I reviewed, and found out Android Room library already handles this recovery case, and all I needed was a 10 liner PR that catches this exception and ignores it.
I understand this, but I just can't bring myself to care. I've been doing professional software work for almost two decades. These sorts of improvements/time savers are great without AI. With AI? Whatever. It's fine.
When the underlying lib has an issue, it'll be quicker to debug with the whole thing in context.
Whatever values you stick in there are about as accurate as the scale is, so.
Intelligence per unit of compute will almost certainly keep increasing. That doesn't mean having more compute isn't still way, way better.
My agent is currently doing the work of ~6 senior engineers, based on ticket closures. These are not trivial tasks: all of them involve a mix of code, judgement, executing remote commands in a production environment, etc.
This is at a well-known tech company operating at massive scale (and resulting complexity).
L1/L2 tech support is completely dead within a couple years. The delay is only around how long it takes people to realize.
> 1. that closed source models are more efficient than open source
Not a reasonable assumption for a variety of reasons.
> 2. Deepseek is served at a profit and not a loss
Not a reasonable assumption either.
> Why do you need to know the architecture? Just compare Deepseek V4's performance with GPT 4 and treat internals as a blackbox.
Because the internals are what actually matter and what drives inference cost.
It would be entirely reasonable to expect that GPT-5.5 has some sort of optimizations or changes to the architecture to make it easier to train, or to make runtime ablation easier, or to better handle large batches, or whatever.
Those changes, particularly if they are non-public, can easily result in worse inference performance than a comparably sized model without those changes.
> It is borderline conspiratorial to believe it this way.
It's not any sort of conspiracy. It's how land-grab tech companies have always worked. To presume otherwise is silly.
It's silicon valley and they are trying to aggressively grow. Your baseline assumption should be the exact opposite.
There's no reason to think that the latest frontier models have similar inference costs to open source models.
It would be more surprising if the surrounding architecture hasn't significantly diverged. If it _hasn't_ significantly diverged, then given the performance difference it would imply that the frontier models have significantly greater param counts, which would result in a higher cost.
The price a company charges, _particularly_ a high growth VC-backed one, is a poor signal for their costs.
That blog post is not very compelling either. Without knowing details of the architecture, comparing the various frontier models to open models doesn’t make sense.
I mean, they do (and did). If you aren't shipping, you'll be out eventually.
"shape" too, at least with gpt5.5, is coming up constantly.
> It is in the same way that educated guessing is.
I guess (heh) it depends on your definition of 'educated guessing'? Looking at the problem, considering a solution, discarding it, trying another and testing, iteratively, is how most people would approach any tricky problem.
Brute force is substantially different. It would be saying that, other than maybe setting some basic bounds and heuristics, I'm going to try literally everything and test each. That's not at all what the LLM did here.
Open models, in actual practice, don't match up to even one or two generation prior models from Anthropic/OpenAI/Google. They've clearly been trained on the benchmarks. Entirely possible it was by mistake, but it's definitely happening.
Which is why compilers decimated the software industry.
The same way companies already deal with any cost.
Most people just want something that looks nice. I understand it’s deeper to someone really into it, but the rest of us are fine with it.
Everytime I've tried a local model, and I have tried lots for a couple years now, they just seem like they were overtrained on benchmarks. They consistently perform dramatically worse than even older models from Anthropic/OAI/Google.
> Europe is behind because we do not have good leadership. The decisions taken by leadership, no matter what level you look at - local, company, national, supranational - are rarely in the best interest of Europeans. Our markets - housing, rental, labor, capital, pension - are broken and therefore the population does not find opportunities to express their talent completely and the more motivated migrate. Europeans lack well-paying jobs and pay is low because pay is not transparent.
Sounds like Europe is behind because Europeans are working less and taking more vacations. You just point to poor leadership as the cause.