Oracle spending ~$340 billion to build infrastructure that generates ~$75 billion annually, financed almost entirely with off-balance-sheet debt, while its free cash flow is negative $24.7 billion.
Amazon just did something unprecedented: they're forcing a 90-day safety reset across 335 critical systems after their AI coding tool caused catastrophic outages. The March 5th incident alone lost 6.3 million orders and triggered 21,716 peak Downdetector reports.
Those who think Gary Marcus, Ed Zitron and Yann LeCunn are wrong, and believe in AI: How do you reconcile things when AI thinks the market is highly likely to collapse?
Quote: "The entire system only works if AI revenue grows fast enough to outrun the obsolescence treadmill. For that to happen, Microsoft would need approximately $130 billion per year in new AI revenue, Google $100 billion, Amazon $120 billion, and Meta $70 billion. Against a current reality of $18 billion in total industry AI revenue and zero profits, that gap is not a rounding error. It is the entire bet."
Stock market collapses and technological success are two very different things. The internet led to a market collapse just as it started showing real promise. One of the problems is that you can't invest in a technology, only in companies, and oftentimes the companies that turn a technology into financial success are not the ones that exist when the technology is in its infancy. It's not unlikely that LLM will be a huge success while Nvidia, OpenAI, and Anthropic collapse.
When people are talking about an AI bubble, they are explicitly talking about the stock market. It’s not at all about the question if LLMs are useful or not.
Of course, but I was responding to a comment that contrasted "believing in AI" with the stock market. People believed in the internet, it still led to a bubble and a market crash, and that didn't mean those people were wrong. Part of the cause for a bubble, then and now, is that you can't invest in a technology, only in companies. Investors want to invest in AI, but they can't, so they invest in OpenAI, which may well go bankrupt. Those early internet pioneers didn't deliver on the inflated financial expectations from them even while the internet as a whole eventually did.
What's interesting to me is how quickly the big AI labs are losing their competitive edge even before becoming profitable. Models that are less than one year behind the leading ones are effectively commoditised already. If OpenAI and Anthropic disappear tomorrow, it will be no more than a brief inconvenience to LLM users. They're spending a lot of money for an almost negligible advantage.
From skimming that chat: it doesn't, no matter how much you tried to steer it into that direction. It barely reluctantly agreed under some hypotheticals, but it never agreed to the hypotheticals actually being true.
This submission is junk, and the the title is editorialized.
In practice this simply doesn’t pan out. There are many many terrible freelancers out there. And without someone technical in-house vetting their work, you’ll have no choice but to judge their based on their output. This is a huge problem.
Software needs to be designed with an understanding of the business needs and goals. You need someone who understands how to keep the software well designed (ie. Easy to debug, update and extend in the future).
Judging solely as a user of the software gives you no insight into whether or not a plate of spaghetti code could be holding behind the scenes.
Good code has two traits: It does the job it was designed to do. It is easy to update and maintain.
Everything else you read online is nonsense. And you need someone trusted inside your company to ensure the second trait is being adhered to.
In practice this simply doesn’t pan out. There are many many terrible freelancers out there. And without someone technical in-house vetting their work, you’ll have no choice but to judge their based on their output. This is a huge problem.
Why? There are many terrible everything out there. Eventually you are always relying on the quality of your developers' output and their honesty in explaining it whether they are hired as employees or working freelance.
Crucially that is as true of the technical in-house person as the outside freelancer. I've seen scenarios with my own eyes where an experienced freelancer was better - sometimes much better - than the in-house "senior" people but the latter made critical reports about the freelancer to management. Maybe they were defensive because someone better than them was brought in. Maybe - and I suspect this is more likely in at least some of the situations I'm remembering here - the in-house person was so far below the outside freelancer in ability that they simply didn't realise how much better the freelancer's work was than their own or understand the reasons the freelancer was following certain good practices and the risks they were mitigating by doing so.
So my question to you is this: Why do you believe you can trust someone to evaluate the quality of the work more accurately and honestly just because they are inside your company?
"Engineering Jeopardy" -- perfect summation! And good point about companies that are very one-sided in their interview process. What message are YOU sending to the candidate by drilling them like this, for example?
Oracle spending ~$340 billion to build infrastructure that generates ~$75 billion annually, financed almost entirely with off-balance-sheet debt, while its free cash flow is negative $24.7 billion.
Yikes.