After so much hype and trillions of dollars of investment, the AI bubble seems like it might finally be bursting. Much of the market crash that happened last Monday was concentrated among technology companies, all of which are deeply invested in AI. The biggest loser was the famed chip company Nvidia, which, according to writer Chis Taylor, “lost a trillion dollars of valuation, 30% of the total, since its 2024 high.
Taylor goes on to list the reasons for this downturn: excessive hype from AI gurus like Sam Altman, burnout from consumers who are now turned off by products using AI, and impatient investors like Goldman Sachs wanting a quicker return on their investment. So, like most bubbles, AI businesses overpromised and underdelivered, causing the market to correct itself.
Unfortunately, it doesn’t end there. AI technology seems to be hitting a wall in its advancement. As many people have observed, the AI data servers suck up colossal amounts of energy, putting a huge strain on electrical grids. They also require equally colossal amounts of capital (running in the billions of dollars) and continuous funding — for reference, ChatGPT is estimated to cost OpenAI $700,000 a day to operate.
Worse still, Taylor explains that AI programs “have run out of stuff to train on, and the more they are trained on ‘the internet,’ the more the internet contains a body of work written by AI — degrading the product in question.” Originally, a Large Language Model (LLM) like ChatGPT could review
