This is definitely a good point. I imagine the max capacity for video models is significantly lower than for text models (there just aren't as many professionals in video as there are people who write text or code) but I could be wrong.
Unless I'm missing something, there's also nothing in the paper to indicate this is "all of human ingredients"? It looks like it's 11 data sources covering a bunch of common cuisines, with the English + Chinese sources accounting for 90% (!) of the dataset. Among others, Africa and the Arab world are not present in the data (good for about 25% of the global population).
Also, all non-English terms were AI-translated to English which is methodologically understandable but surely leaves room for error.
translation is an interesting problem in and of itself still. its kind of a miracle we can do it at all, yet in some circumstances it seems obvious for there to be objective answers (cooking ingredients being one of them), but even then you never really know even with human translators if you've got it correct. even within the same language nearly every individual has their own version of it.
for example, how would you translate "chips" to another language without first knowing which version of English you are translating from? could be an american speaker with a british relative and they use the british definition of chips while otherwise mostly speaking american english.
there's a level of pragmatism in translation that needs to be assumed, and ultimately we have to accept that translated knowledge will always have low resolution. There is a layer of work that needs to be done with the source of the materials involvement to get written content to a level of formalism needed to be representative of the language it is written in. Generally, the work of editors. Which means successful translation for wide distribution, while still not guaranteed, is predicated on the editorial skills of the translator which begs for dialogue with the source.
Meanwhile, AI provides this super convenient band aid to get translation results you can't disprove.
I genuinely think people are severely underestimating the power held by these models for being translators and how literal truth is going to be determined by them deep behind the scenes under the disguise of accessibility. Not in a dangerous way necessarily, just in a way where what languages are and what words mean is going to shift towards whatever the models think they are.
In a way, over extended time, the models will not be wrong about the translations because their results will redefine what successful formal editing of language looks like, and disagreeing with them will amount to the same difference as having local slang.
Thousands of cheeses, each of which is a unique experience. Heck, even the serving temperature completely alters the experience. Next: wines, charcuterie, ...
Pity the fool who can't taste the difference between any of these.
It's worst than useless, it's borderline criminal /s
The fabricated title targeted the sensation rather than substance, typical scenario whenever "All" is in the title, and the worst when it's in the very first word.
> Yeah agriculture is bad for the environment, but at least it feeds us to keep us alive
This is true, but don't forget a _lot_ of agriculture feeds _animals_ that we in turn eat. If you want to make optimal use of land for human needs, most modern agriculture is not that.
There's no problem the more conventional practice of letting animals graze the majority of the year. If we didn't use those fields to feed and eat the animals, the grass would turn into CO2 and methane anyway. Or turn into boring forests.
Not everything has to be optimal. That thinking leads to Thanos' snap. People generally enjoy meat. They also enjoy the landscape farmers created.
Google searches being keyword based, rather than simulated conversations?
The same reason you wouldn't put in an entire actual question/sentence, unless you either don't know how to use Google, are pissed off, or have an actual reason to suspect that it would yield proper hits (e.g. looking up an excerpt).
It is rather hard to lose of habit of using search engine with keywords given the change took place without much fanfare. I have no problem using sentences with the current ai tools through.
I didn't used to but I do now that the searches go straight to an LLM. I almost always find the model output to be much more useful than the list of search results.
I don't. I was recently doing some searching for information I thought AI would be good for: fuzzy natural language search with some conditions. And it was, but ...
Gemini at least is not great at citing and picking sources. Or providing multiple sources for the same thing.
It tends to stop at threes. So if you want more, you have to prompt it uselessly, like: "any more?"
I searched for "Hey Google" and got this in response:
Hey! I'm here and ready to help. What’s on your mind today? Whether you need to look up information, plan a trip, or get things done, just let me know!
No it's not. Where do you come up with this? Just because you searched the phrase on Google and there's a single result for it on a wiki? Who do you know that's using this expression regularly?
I don't mean to sound elitist, but in a way, Haskell's difficulty is kind of the point of the language.
The thing that's so elegant about Haskell is that it allows you to express programmatic constructs at a very abstract level. Abstraction is almost by definition difficult to grasp. That's why it takes a decade and a half for (most) people to go from arithmetic to calculus.
Difficulty is most certainly not the point. Abstraction, composability, yes, but difficulty is a language smell that CAN be fixed. (I love Haskell and it's my primary langauge, so this comes from a place of love).
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