1. Explosive drop in AI‑model cost & wider accessibility
“It blows my mind how fast models are getting better and this is the first article I’ve seen that shows just that and leaves almost no room for disagreement. Well done.” – brabel
“A year ago I had an aha moment… Gemini Flash was 9× cheaper and 3× faster than Gemini Pro, while producing identical output.” – andai
“If someone knows of a source that already tracks this, with historical prices, please share.” – bkd9
“The incentives to produce more are huge and all the fabs are booked out.” – kaashif
These points illustrate that cheaper, faster models are already being built and will democratize AI use.
2. Robotics hit practical bottlenecks despite flashy demos
“A robot can today fold your laundry. It takes ~10 mins per item. Seriously. It takes a long time to process the image, find the corner, move the claw … processing time is a major bottleneck.” – AnotherGoodName
“Sensors are a huge challenge for robotics. We have very precise force‑feedback … robots don’t have that.” – wongarsu
“Robots right now generally move at glacial speeds … folding laundry and opening doors is much more difficult.” – andai
The consensus is that current hardware and control limits keep robotics useful only in narrow, controlled tasks.
3. Questioning what “intelligence” really means
“I think this viewpoint fails to understand what ‘intelligence’ is. The idea must be that intelligence is some special thing that only humans have.” – dboreham
“AGI ≈ Ralph × Infinite persistence — Just like real life!” – andai
“The delusion humans have is that intelligence is special and magical. It’s not. It’s just nature’s prediction machine.” – perching_aix
These remarks reveal a growing debate: LLMs may be powerful, but whether they constitute true intelligence—or just sophisticated pattern matching—is still unsettled.