Raw LLM Responses

One small issue with the entire discussion is, that nobody opens up the question, if humans fullfill the expectations, that we have for a.i. to call is consious. How shure are we, that creativity isn't just some kind of emergent behaviour, influenced by the external circumstances. Most breakthrough technologies were invented at roughtly simultainusly by multiple people doing independant work in different places. The wright brothers were the first to officially acieve powered flight, but others were close. A.I. has already found new mathematical proofs and algorithms, that are better than what humans invented. Here's some back of the envelope math: ~ 50% of all neurons are in the brain, with ~ 86 billion neurons we get ~ 2*10^11 neurons. Each neuron has between 10^5 and 10^6 synapses. To simulatde a synaps,m routhly 10^2 ai neurons are needed. Each neuron can fire every 5 ms, so in total that gives us 2 * 10^11 * 10^6 * 10^2 * 2*10^2 calculations per second. That's 4* 10^21, or 4 000 0000 petaflops compute power. A current top of the line grace blackwell gb200 nvlink72 (1 server rack) manages 360 pflops in fp16 resolution (probably good enough). So if someone manages to hook up ~12 000 racks, it can be done. On the feasibility: One rack neds ~ 120kW of power so total power consumption would be ~ 1,5 GW. And Stargate ? (not shure if they were the ones doing it) is currently building a server farm with a total power consumption of 1.2 GW. Now cooling takes a lot of power and it's still lower than the estimated 1.5GW, but it is an estimation to the upper side. Most neurons don't rund on max frequency and not every neuron has the one million synapses. this means the raw compute performace is currently being build. the question is, well the software have emergent behavior, that will result in something we recognise as consious?