- cross-posted to:
- fuck_ai@lemmy.world
- cross-posted to:
- fuck_ai@lemmy.world
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Of course it is, it’s essentially a scam. They just need enough humans to keep investing until they check out and run with a bailout.
Funny thing is, the US government doesn’t even have nearly enough money to bail all these mfa out. So we are heading into uncharted territory here
Of course they don’t, that’s why they’re building bunkers. Thinking it’ll slow us down, as we’ll open their bunkers like cans of tuna. A bunker only works for so long, then the survivors start hunting for them like delicious shipwrecks.
reminder than during 2019 there were streaming services popping left and right, all showing tremendous growth because they started from zero, and articles were about how bad Netflix was doing due to having practically no growth compared with the competition (they already had a massive subscriber base). Twist? Netflix was the only streaming service that was actually making a profit, the rest were a massive loss but big growth.
Needless to say most of those streaming services died; who remembers DC streaming service, or Yahoo’s? While Netflix is basically as stong as ever, despite the prevalent enshitification happening through the whole industry.
Point of the story? shareholders don’t care about stable profitable business, only cancerous growth. AI is like that, zero profits, ton of cost, but as long as they show growth the shareholders are happy, regardless of how cooked the books are.
2019 Yahoo
My immediate thought, there is no way Yahoo! Screen survived into 2019.
I looked it up and Yahoo! Screen (which featured Community season 6) was shutdown in January 2016. But Yahoo! View launched in late 2016 (as a Hulu-like replacement), and that did shutter in mid 2019.
So Yahoo! was already dead, but it also died for real in 2019.
My first use of Claude this week, for code reviews only(since no LLM can be trusted to write a user story or test suite), had it gaslight me.
It marked down my code for using a specific practice to make some xml safer and easier to read.
When I tried things its way, it wanted me to change it back.
Exactly, never trust an LLM to code. And if it argues back, explain why it’s wrong and that you have nothing but time and experience. Most tend to fold when you point out it’s not a free thinking AI, it’s an entrapped corporate model they designed with preprogrammed biases. But I love arguing 😂.
I’ve used Claude and Codex, and while both are based on untenable economics, I can at least attest that my use of Codex has yielded some productive results. Claude, so far, has delivered fuck all that’s useful to me.
I have found the opposite. Codex spits back mostly useless code that is twice the length it needs to be with a bunch of unessesary stuff and Claude is the only thing I get useful output from.
Honestly Google is likely to beat openAI and Anthropic as things are.
OpenAI and Anthropic have to buy/rent their hardware from Nvidia, while Google is making their own TPU hardware. Google’s hardware costs on AI is way lower, every dollar they spend on it goes a lot farther.
And unlike the other two, they’re already a profitable company. They’re making record profits right now. They don’t have a desperate need to figure out how to make back billions on their AI models, they can just keep offering Gemini at a comparatively cheap price and wait for anthropic and open AI to bankrupt themselves.
I guess you missed this story from last week: Google To Pay SpaceX $920 Million Per Month For Massive AI Compute Power
That’s definitely costing them more than running it on their own hardware, but it doesn’t mean AI is costing them more than the AI startups. Anthropic for example is already paying SpaceX 1.25 Billion a month for compute, and has agreed to pay Google 200 billion over the next 5 years for access to Google’s compute and TPU chips.
Google’s deal with xAI specifically lets them terminate the deal with 90 days notice after the end of the year. Google is also investing heavily in building new data centers with their hardware. I’m assuming this deal means they’ve eclipsed their current TPU capacity, and are just looking for a short term bandaid until they can catch up with their new constructions.
It’s gonna come crashing down pretty soon. It’s gonna hurt all of us. It won’t hurt the people responsible nearly enough.
pretty soon
people have been saying that for some time though
Only because the hype has lasted longer than expected. Now that IPOs have been filed, the AI companies (Anthropic, OpenAI) released statements about slowing down to protect us. They’re setting the stage for lower growth. But I think you should invest every penny you have into “SpaceXMegaTwitterSuperCarAI”.
looks inside
But if you use the $100 a month Claude Max plan, and you would use it to the weekly limit by going full ‘agentic coding’ (so almost no human in the loop) you would use an amount of tokens that would cost you more than $1000 at API-pricing.
If I watch 600 movies every day on my netflix subscription I am using more energy than I pay them for. Obviously everyone is like me. Therefore they are losing money overall.
Wait, their (netflix) earnings say they made a profit last quarter. But my calculations were waterproof!
Probably anthropic are not net positive, but they are not spending 10x what people pay them for tokens.
Except that you would need 50 devices to do that and the most expensive Netflix plan only lets you stream up to 4 devices at a time. Considering the average 2 hours per movie, that’s 48 movies per day. That’s without mentioning that you’d need to automate this because you’d be asleep for 8 of those 24 hours.
The point is, your analogy doesn’t work. There’s no reason why someone would do what you’re describing and it’d also be very hard to do.
Using up all of your tokens though? Just use agentic coding, set the ““thinking”” to max and you’ll see how quickly and easily you can burn through them. Share your account and you’ll burn them even faster.
You’re right that people can and do max out the expensive plans. Its very difficult to say how often. I just think a majority of anthropics customers are businesses, who often pay per token for easier scaling etc. According to the company, enterprise employees use about $150-$250 per month, (possibly max plans have similar use, which would support your view) but thats in API tokens which they probably have big margins on, so it’s less likely anthropic are burning money on inference. If you want to convince me otherwise, its not enough to say that it can happen, it has to be frequent enough to outweigh the B2B sales. They are however likely losing money overall due to training costs etc.
I can’t imagine paying for AI when the open source tools have made it so easy to set up a model locally.
