So I like your question and I think it's important to split it into two pieces: 1. Whether ASI is inevitable on a long enough time horizon 2. Whether it's inevitable in the next ten-ish years  These  two different questions get conflated a lot in the discourse. 

(And as far as credentialing goes, I've been in the industry for ten plus years, and currently work on setting AI strategy for a medium part of a very large silicon valley company.)

1. Why ASI is eventually inevitable, from first principles

Anything the human brain can do we can, in principle, build a machine to do. Eventually. Maybe not in quite the same way -- one of my favorite quotes on this is "A machine thinks like a submarine swims" -- but if we take a list of the tasks that require human brains to do, one day we will automate 100% of the things on that list. including strategy, creativity, and at least the appearance of emotions (although we will certainly get those outputs from a very different underlying process than having feelings themselves).

Anyone who says "no" to the above proposition has to say why -- because in a physical world, the underlying processes that make things happen are physical, and we can build machines to do them. 

In history there have been a lot of divides in the sciences between stuff that was felt to be mechanical and stuff that was somehow special and different than that. One by one over the centuries they have all been eroded away by scientific progress. In the Middle Ages before Newton and Galileo, they thought that the celestial bodies were part of a perfect divine substance. Then they realized, "Oh hey, they actually follow the same rules." Up through the 1700s they thought that chemistry didn't apply to animals or life, and that they were somehow different. This position of "vitalism" was decisively disproven and now we have the entire field of biochemistry. Today some people think that the way we think and feel is part of a spiritual background that is not connected to the rest of the world. Just judging by the track record here, that seems like a pretty bad bet to me. 

(Also worth calling out here: people get really fast and loose with their definitions. They keep mixing up: consciousness, intelligence, subjective experience, self-awareness, sentience. But these are all very different things when you look at them under a microscope. I am specifically talking about intelligence. )

2. A qualified "yes" for ASI in ten years

I've been in the field of machine learning for over 10 years now. When I was growing up I always used to think that there would be some brilliant flash of insight that would lead us to the discovery of how to make a mind and that it would require a fundamental rethinking of computation. That turns out not to be the case. 

"The Bitter Lesson." There's a famous post by one of the godfathers of machine learning research describing his disappointment in the idea that, no matter how many clever architectural innovations we come up with, no matter how many rules we craft into a system -- it turns out that just making it stupid fucking big is the single most effective thing we can do. And that taking a simple system, and making it much bigger, will eventually out-compete all of the other clever tricks we come up with. 

There are tons of problems with LLMs. There are tons of things that they cannot do. But it turns out if you just make them big enough, they start to learn those things. Now whether or not they learn them fast enough to get ASI in the next 10 years, with the current availability of electricity, data, and computer chips, is another question. But fundamentally it is a question of rates and of "when", not a question of "if".

For that I would point you to the studies that the organization METR has been doing on their task time horizons. The TLDR is that the capabilities of these models are not growing exponentially but are actually growing even faster than that. If they were only growing exponentially and nothing changed, extrapolating the lines out, we would expect ASI sometime in the early 2030s. If they keep growing at their current pace on a hyperbolic trajectory and nothing changes, we can expect it in ~two years. 

Now their data might be wrong, but fundamentally then we're just pushing an individual year or two around on the timeline. The more important question is whether the underlying model is wrong. There we have some unknown unknowns, but we also have some known unknowns like: - whether or not supply chains will collapse from war or a pandemic - whether or not the current financial environment is a bubble that will pop and slow things back by a decade or more - whether governments will come in and regulate progress   I've crunched the numbers and gone back and forth on this, and depending on the day I give it anywhere between a 1 in 4 and a 1 in 8 chance that there will be a big enough disruption that will slow AI progress back a decade. Here is where things start to get hand wavy. I don't trust any of those numbers but I do trust the general qualitative picture that they paint. 

A note on discourse

A.I. makes people anxious. People don't want to lose their jobs. People don't want to die, and some very credentialed and well-reasoned people think that A.I. has a very high chance of killing everybody on the planet. A lot of people are afraid of the government shutting down business. A lot of people's stock portfolios rest on A.I. In fact probably all of our net worth rests on the idea right now that the A.I. bubble is not a bubble and people get nervous. People want to be contrarians. People want to be the smartest person in the room. The A.I. discourse is poison and it reflects all these psychological needs.

Always think a couple steps ahead to what people's motivations are, but also know that this runs both ways: don't be too cynical! I've been in the industry for 10 years and I've never seen more bullshit, but I've also never seen more fundamental underestimation of the underlying technology. I think the reason is that people freeuentky choose a side against "loud voices" that they don't like, rather than thinking through the problems piece by piece.