bjorney

and I’ve encountered zero bugs so far

This is my only complaint - it crashes a lot for me

The content of the email is very laissez-faire, e.g. "we legally have to send these ¯\_(ツ)_/¯ "

I collect these like pokemon 🙃

What's confusing about it? It's the amount of flour that fills a 236ml cup. It's no different than measuring 1L of water

You may say "yeah well it depends on how finely ground the flour is or how tightly packed the broccoli is" and the answer is "it either doesn't matter or it's a bad recipe"

Dry ingredients by weight isn't a metric exclusive thing, it's an "accurate recipe" thing. Plenty of American recipes call for ounces and pounds. Cups are also a unit of volume, so 1c of milk occupies the same volume as 1c of water even though their masses are different (at a given temperature; which is why it's better to use weight for liquid ingredients as well)

The confusion is when you have no idea whether they are calling for 28.4ml, 29.5ml or 28.3g when they say "ounce"

Cups are ~235ml regardless of wet or dry. They are one of the sane-er measurements

You may be confusing your frustration with the ounce, which may refer to:

• avoirdupois ounce, used for mass in most cases
• Troy ounce, used for mass when referring to precious metals
• the imperial fluid ounce, used for volume sometimes
• the us customary fluid ounce, used for volume sometimes
• the us food labelling ounce, used for volume like the customary fluid ounce, but rounded to a nice number of milliliters

I've only ever heard this non-ironically from these types

"the media sucks at factchecking DeepSeek's claims" is... an interesting attempt at refuting the idea that DeepSeek's claims aren't entirely factual.

That's the opposite of what I'm saying. Deepseek is the one under scrutiny, yet they are the only one to publish source code and training procedures of their model. So far the only argument against them is "if I read the first half of a sentence in deepseeks whitepaper and pretend the other half of the sentence doesn't exist, I can generate a newsworthy headline". So much so that you just attempted to present a completely absurd and unverifiable number from a guy with a financial incentive to exaggerate, and a non apples-to-apples comparison made by WSJ as airtight evidence against them. OpenAI allegedly has enough hardware to invalidate deepseeks training claims in roughly five hours - given the massive financial incentive to do so, if deepseek was being untrustworthy, you don't think they would have done so by now?

if you mean to argue that DeepSeek wasn't being underhanded at all and just very innocently presented their figures without proper context (that just so happened to spurn a media frenzy in their favor)... then i have a bridge to sell you.

What do you mean proper context? I posted their full quote above, they presented their costs with full and complete context, such that the number couldn't be misconstrued without one being willfully ignorant.

OpenAI is very demonstrably pissing away at least that much money every time they add one to the number at the end of their slop generator

It sounds to me like you have a very clear bias, and you don't care at all about whether or not what they said is actually true or not, as long as the headlines about AI are negative

but it's pretty clear that some people walked away with a false impression of the cost of their product relative to their competitors' products

Ask yourself why that may be, as you are the one who posted a link to a WSJ article that is repeating an absurd 100m-1b figure from a guy who has a vested interest in making the barrier of entry into the field seem as high as possible the increase the valuation of his company. Did WSJ make an attempt to verify the accuracy of these statements? Did it push for further clarification? Did it compare those statements to figures that have been made public by Meta and OpenAI? No on all counts - yet somehow "deepseek lied" because it explicitly stated their costs didn't include capex, salaries, or R&D, but the media couldn't be bothered to read to the end of the paragraph

DeepSeek-V3 costs only 2.788M GPU hours for its full training. Assuming the rental price of the H800 GPU is $2 per GPU hour, our total training costs amount to only $5.576M. Note that the aforementioned costs include only the official training of DeepSeek-V3, excluding the costs associated with prior research and ablation experiments on architectures, algorithms, or data.

Emphasis mine. Deepseek was very upfront that this 6m was training only. No other company includes r&d and salaries when they report model training costs, because those aren't training costs

I'm sorry but this says nothing about how they lied about the training cost - nor does their citation. Their argument boils down to "that number doesn't include R&D and capital expenditures" but why would that need to be included - the $6m figure was based on the hourly rental costs of the hardware, not the cost to build a data center from scratch with the intention of burning it to the ground when you were done training.

It's like telling someone they didn't actually make $200 driving Uber on the side on a Friday night because they spent $20,000 on their car, but ignoring the fact that they had to buy the car either way to get to their 6 figure day job