Zos_Kia

"I'm asking a question on the internet but will flame you for giving an honest answer"

Then why are you here?

When you read that stuff on reddit there's a parameter you need to keep in mind : these people are not really discussing Lemmy. They're rationalizing and justifying why they are not on Lemmy. Totally different conversation.

Nobody wants to come out and say "I know mainstream platforms are shit and destroying the fabric of reality but I can't bring myself to be on a platform except it is the Hip Place to Be". So they'll invent stuff that paints them in a good light.

You'll still see people claiming that Mastodon is unusable because you have to select an instance - even though you don't have to, you can just type Mastodon on Google, click the first link, and create an account in 2 clicks. It's been ages. But the people still using Twitter need the excuse because otherwise what does it make them?

Yeah honestly i can't get anything done with a raspberry. Maybe i host too many services ?

jesus christ what a nice burn

That was a classic House MD episode 🎖️

Yeah i mean if Big Tech was aligned with the US government, they would have had front row seats at the inauguration or something.

If you take into account the optimizations described in the paper, then the cost they announce is in line with the rest of the world's research into sparse models.

Of course, the training cost is not the whole picture, which the DS paper readily acknowledges. Before arriving at 1 successful model you have to train and throw away n unsuccessful attempts. Of course that's also true of any other LLM provider, the training cost is used to compare technical trade-offs that alter training efficiency, not business models.

just like for american models, the political bias is irrelevant. Realistically you are using the model for its reasoning capabilities, not its answer to "what happened in Tiananmen".

Yeah it's ridiculous. GPT-4 serves billions of tokens every day so if you take that into account the cost per token is very very low.

So for the first 20 years or 2/3 of the entire history of the company, they were unprofitable or barely profitable.

We must have a wildly different definition of "barely profitable". Half a billion in 2004 money is a lot of profit, a billion back to back in 2009 and 2010 is a lot of profit.

I think you're confusing Amazon with the next generation of loss-leader companies. Let's talk Uber, let's talk Twitter, if we want to point at "hugely unprofitable" companies. But Amazon is a beast of its own, they have a very coherent financial story. Even during their money-losing decade they posted insane results, frequently multiplying revenue while barely increasing operating costs.

Oh thanks for clarifying in even more excruciating details how a subtraction works that is really helpful.

Why would you repeat the lie that they're "usually unprofitable" when the information is publically available in a million places on the internet ? In 2023 Amazon made :

• 575B$ in sales
• If you remove costs of goods that's 270B$ in gross profit
• If you remove operating expenses (including R&D) that's 30B$ in net income

Amazon is factually not "usually unprofitable", they have in fact made profit (as in money which actually goes into your pocket after discounting all expenses) every year for the last 15 years except in 2022 and some tiny losses in 2014 and 2012.

That's why it's important to heavily curate your corporate social media feed. If you see a community where this kind of comments are heavily upvoted just hide it and move on, there's not that many and most of the niche interests are still relatively clean places.