Will Generative AI Take Over the World Soon? What is the Truth?

Many LinkedIn members follow the wind. For 2 years Generative AI would take the world was the motto.
The last few weeks or months the wind has changed and there are clouds in the horizon.
The question is what is the truth of the matter?

Let's analyze the situation with the clarity of hashtag#simplicity but not simpler than that:

1. hashtag#Generative hashtag#AI models from hashtag#OpenAI, hashtag#Google, hashtag#Amazon, as well as open source models like Llama 3 or hashtag#Mistral etc are making mathematical predictions based on huge datasets; these models do not really "understand" the content they generate and especially they do not understand our physical world. They cannot feel, touch, smell, move,.... etc

2. To take over the world Generative AI needs to transition from today narrow AI (even it can do various tasks related to accessing huge databases, has huge memory, high speed of processing, compare and summarize) to a more advanced and broader AI some call it hashtag#AGI (Artificial General Intelligence) which isn't merely a matter of incremental improvements but requires foundational breakthroughs in how AI learns and interprets the world. Among other things, AI needs to become physical AI with technologies like "Liquid Networks " which are mimicking natural organisms. This process will take some years or even decade(s) to achieve various levels of sophistication.

3. While humans, can learn from a few examples or even from a few experiences, AI systems need thousands—or better millions—of data points to master even simple tasks while the data sets include hashtag#bias and various mistakes creating wrong outcomes called hashtag#hallucinations. The difference above highlights a fundamental gap in how humans and machines process information.

4. The market innovators like OpenAI and the investor and supporter Microsoft among others want as many as possible early adopters to support their technology and create hashtag#hype even if the technology and especially it's applications are not at the level of maturity needed.

Concluding with simplicity: In the medium term AI is here to assist and augment human capabilities, not to replace them.
Additionally like all technologies, Generative AI will follow the hashtag#Gartner Cycle when after a period of inflated expectations (we just passed this milestone) there will be a period of sharp downturn reaching the trough of disillusionment followed from a period of technological improvements of the shortcomings called the slope of enlightenment where the technology starts to mature. Normally this process takes a few years even for a faster growth than Moore's law.

Any comments?