We have not experienced the massive increases in pricing on eggs. The supply management system effectively works to keep farms roughly below a certain size, and seems to have helped avoid large impacts on certain staple foods.

The usual rhetoric against this is that we should be getting cheaper prices by letting in foreign competition. This ignores that doing so would allow foreign subsidies to wipe out our local supply of critical foodstuffs, then making us dependent.

It's not an ideal system but it seems to have yielded some tangible results when things like bird flu are making their rounds.

Not purely. There may be some prejucide but look at Nortel[1] as a famous example of a situation where technological espionage from Chinese firms wreaked havoc on a company's fortunes and technology.

I too would want to see the evidence and forensics of such a breach to believe this is more than sour grapes from OpenAI.

[1] https://financialpost.com/technology/nortel-hacked-to-pieces

Half jokes aside, I'd love to be able to have a decent mobile style permissions experience on browser extensions and desktop apps.

Making something work really efficiently on older hardware doesn't necessarily imply less demand. If those lessons can be taken and applied to newer generations of hardware, it would seem to make the newer hardware all the more valuable.

A requirement not extended to the open source developers whose code you are using essentially a copyright and licensing laundering engine to get around.

Then again, maybe not; OCR is one of the most worked on problems, so the quality of parsing characters into text maybe shouldn't be as surprising.

Off topic: it's wild to me that in 2025 sites like substack don't apply `prefers-color-scheme` logic to all their blogs.

LLMs which were trained on the works of thousands of other developers with similar licenses, who are offered no similar credit here.

It also claims copyright of the code as though you have authored it, but you're claiming here to have used LLMs to generate it. Seems like trying to have it both ways.

The key thing here is to understand that you want the minimal correct query for what you need, not to avoid "making the database work".

The given example is silly because there's additional parameters that must be either NULL or have a value before the query is sent to the DB. You shouldn't send queries like:

    SELECT \* FROM users
    WHERE id = 1234
        AND (NULL IS NULL OR username = NULL)
        AND (NULL IS NULL OR age > NULL)
        AND (NULL IS NULL OR age < NULL)

    SELECT \* FROM users
    WHERE id = 1234
        AND age > 18
        AND age < 35

I leave allowances for `id` to be a stand-in for some other identity column that may represent a foreign key to another table. In which case I'd still expect SQL server's query planner to execute as: initial set is those where said column matches the supplied number, then further applies the logic to that subset. In fact I'd love to see where that isn't the case against a transactional DB.

The rest of the query plan probably won't need much power.

[1]: https://mosquitto.org/blog/2018/05/version-1-5-released/ [2]: https://forums.raspberrypi.com/viewtopic.php?t=287326 [3]: https://esp32.com/viewtopic.php?t=9747

There's also other limitations of it in features I don't really use, for example IIRC the RFID stuff they do with their print spools stops working.

Let's bite though, and hope that unhelpful excessively long-winded replies are just your quirk.

> This is itself a slippery move. A vague gesture at past misconduct without actually specifying any incidents. If there's a clear pattern of documented benchmark manipulation, name it. Which benchmarks? When? What was the evidence? Without specifics, this is just trading one form of handwaving ("everyone does it") for another ("they did it before").

Ok, provide specifics yourself then. Someone replied and pointed out that they have every incentive to cheat, and your response was:

> This starts with a fallacious appeal to cynicism combined with an unsubstantiated claim about widespread misconduct. The "everybody does it" argument is a classic rationalization that doesn't actually justify anything. It also misunderstands the reputational and technical stakes - major labs face intense scrutiny of their methods and results, and there's plenty of incestuous movement between labs and plenty of leaks.

Respond to the content of the argument -- be specific. WHY is OpenAI not incentivized to cheat on this benchmark? Why is a once-nonprofit which turned from releasing open and transparent models to a closed model and begun raking in tens of billions of investor cash not incentivized to continue to make those investors happy? Be specific. Because there's a clear pattern of corporate behaviour at OpenAI and associated entities which suggests your take is not, in fact, the simpler viewpoint.

> This combines three questionable implications: > - That non-journal publications are automatically "not real concrete research" (tell that to physics/math arXiv)

Yes, arXiv will host lots of stuff that isn't real concrete research. They've hosted April Fool's jokes, for example.[1]

> - That peer review is binary - either traditional journal review or nothing (ignoring internal review processes, community peer review, public replications)

This is a poor/incorrect reading of the language. You have inferred meaning that does not exist. If citations are so important here, cite a few dozen that are peer reviewed out of the hundreds.

> - That volume ("pumped out") correlates with quality

Incorrect reading again. Volume here correlates with marketing and hype. It could have an effect on quality but that wasn't the purpose behind the language.

> You're making a valid critique of AI's departure from traditional academic structures, but then making an unjustified leap to assuming this means no rigor at all. It's like saying because a restaurant isn't Michelin-starred, it must have no food safety standards.

Why is that unjustified? It's no different than any of the science background people who have fallen into flat earther beliefs. They may understand the methods but if they are not tested with rigor and have abandoned scientific principles they do not get to keep pretending it's as valid as actual science.

> This also ignores the massive reputational and financial stakes that create strong incentives for internal rigor. Major labs have to maintain credibility with:

FWIW, this regurgitated talking point is what makes me believe this is an LLM-generated reply. OpenAI is not a major research lab. They appear to essentially to be trading off the names of more respected institutions and mathematicians who came up with FrontierMath. The credibility damage here can be done by a single person sharing data with OpenAI, unbeknownst to individual participants.

Separately, even under correct conditions it's not as if there are not all manner of problems in science in terms of ethical review. See for example, [2].

[1] https://arxiv.org/abs/2003.13879 - FWIW, I'm not against scientists having fun, but it should be understood that arXiv is basically three steps above HN or reddit. [2] https://lore.kernel.org/linux-nfs/YH+zwQgBBGUJdiVK@unreal/ + related HN discussion: https://news.ycombinator.com/item?id=26887670

I think it's worth noting in this article too that the author mentions they can now heat and cool parts of their house they weren't previously, so I'm gonna guess their actual usage went up and this is basically surprise for no reason.

I'd argue here the more relevant point is "these specific people have been shown to have done it before."

> The whole comment reads like someone who has picked up some ML terminology but lacks fundamental understanding of how research evaluation, technical accountability, and institutional incentives actually work in the field. The dismissive tone and casual accusations of misconduct don't help their credibility either.

I think what you're missing is the observation that so very little of that is actually applied in this case. "AI" here is not being treated as an actual science would be. The majority of the papers pumped out of these places are not real concrete research, not submitted to journals, and not peer reviewed works.

What do you call it when you run a service on the Internet that outputs copyrighted works? To me, putting something up on a website is distribution.