| Long horizon problems are a completely unsolved problem in AI. See the GAIA benchmark. While this surely will be beat soon enough, the point is that we do exponentially longer horizon tasks than that benchmark every single day. It's very possible we will move away from raw code implementation, but the core concepts of solving long horizon problems via multiple interconnected steps are exponentially far away. If AI can achieve that, then we are all out of a job, not just some of us. Take 2 competing companies that have a duopoly on a market. Company 1 uses AI and fires 80% their workforce. Company 2 uses ai and keeps their workforce. AI in its current form is a multiplier, we will see company two massively outcompete the first as each employee now performs 3-10 people's tasks. Therefore, Company two's output is exponentially increased per person. As a result, it significantly weakens the first company. Standard market forces haven't changed. The reality, as I see it, is that interns will now be performing at Senior SWE, senior SWE engineers will now be performing at VP of engineering levels, and VP's of engineering will now be performing at nation state levels of output. We will enter an age where goliath companies will be common place. Hundreds or even thousands of mega trillion dollar companies. Billion dollar startups will be expected almost at launch. Again, unless we magically find a solution to long horizon problems (which we haven't even slightly found). That technology could be 1 year or 100 years away. We're waiting on our generation's Einstein to discover it. |
On the other hand that means they are weaker if competition comes along as it's expected that consumers and business would demand significantly more due to comparisons.