So basically I agree with you: there's no generic march-of-progress that assures a world of Kurzweillian wonders. I want to see more concrete evidence of progress in relevant areas before I start entertaining life after the Singularity. (I expect a future profoundly shaped by many "narrow" AIs rather than AGI precisely because there has been so much concrete progress with the former compared to the latter.)
I suspect at a layman's comprehension level that sapience is mostly what we are reproducing in research and industry today, and not sentience, because sentience is far more difficult to plumb. Your explanation of the challenges in quantum methods of simulation and the uncertainty on whether it is even necessary seems to bring up this line of questioning to me. This has interesting ramifications. Like we can build OCR and even put out of work lots of formerly middle-class attorneys who made their living in trial discovery phases. But we have yet to create a second Industrial Revolution with general purpose humanoid-form robots that everyone can own that can clean houses, mow lawns, fold clothes, make beds, wash and chop vegetables, pick strawberries, etc., all supposedly "simple" tasks.
There's a strong argument that our rational intelligence evolved to serve the drive to survive--and that emotions are the signals of that drive. It's becoming more clear that even though most animals aren't capable of symbolic reasoning and language, they do experience emotions and make decisions accordingly.
Who is programming a computer to feel emotions? I'm not aware of any significant work in the direction. (If anyone is, please link it!)
The money is in putting that lawyer out of work nor hector, the immigrant strawberry picker
Affectiva is working on reading emotions, and there is some philosophy work on whether or not an AI can feel emotions [1]. A Russian group claims they will release an emotional robot around 2018, but scant details on what that even means [2]. More scholarly work [3] [4] [5] is ongoing, but slow going.
[1] https://en.wikipedia.org/wiki/Philosophy_of_artificial_intel...
[2] http://www.dailymail.co.uk/sciencetech/article-3680874/Scien...
[3] http://www.sciencedirect.com/science/article/pii/S0747563204...
[4] http://link.springer.com/chapter/10.1007/978-94-009-2792-6_1...
[5] https://books.google.com/books?hl=en&lr=&id=OqbMnWDKIJ4C&oi=...
A humaniform robot imbued with sentience and what little progress we've made on (emulating?) sapience is sufficient to substantially (not entirely replace) disrupt the human labor demand from the following industries.
* Residential lawn care for Single Family Residences, a $10B annual industry in the US alone. http://bit.ly/2eu4Ulm
* Residential maid service, a $30B annual industry in the US alone. http://bit.ly/2eSQ3oL
* Residential home senior health care, a $180B annual industry in the US alone. http://bit.ly/1ufk95Y
* If residential meal prep and cooking were mostly or possibly entirely automated, then that can convert the personal chef
industry from hundreds of millions into one that poaches a significant portion of the $780B fast casual industry.
http://bit.ly/2dJweO0
Suppose you offer a $100K humaniform robot with OTA software updates that can perform most household chores, geofence young children into a specific locality, and basically the sense range, kinesthetic sense of a human, object recognition depth of current AI software, but with only the sapience of what we associate with AI today. Amortize the payments over 30 years, and I expect a billion households will beat a path to your door and happily pay that amount.
It would be hard to predict the knock-on economic and other effects of the development of mass-produced personal household robots. Probably similar to trying to predict the demand upon lithium supplies a century from when the Model T was introduced. Perhaps something similarly unexpected like divorce rates dramatically drop due to fewer domestic disputes over household chores because most of those chores disappear.
My thesis is that the people building robots are not dumb, and already realize the financial potential in figuring out sentience, and already are aware at some level that the sentience I speak of is incredibly difficult to build because we understand so little about it, and the AI field focuses upon coming in at the problem from the sapience angle/level for the good reason that sapience is closer to our current form of computer technology than sentience.
I still keep up with molecular and biological simulation research efforts because it's intrinsically interesting to me. The models are improving and better results are also possible due to the increase in computing power since 2006. But the progress appears slow compared with AI/ML research over the same period.
Any time covalent bonds are made or broken, quantum effects are at work. Eliminate all the chemistry that involves forming or breaking bonds and you're throwing away most of the chemistry in a living organism. Getting quantum effects right with ad hoc modifications to molecular dynamics models based on classical physics is very difficult; there's a lot of risk of overfitting to what's easy to observe. Full quantum calculations have terrible scaling properties -- O(N^7) for CCSD(T), the most popular high accuracy approximation of QM, where N is proportional to the number of electrons in the system. Even the best, slowest quantum methods (CCSD(T) and even more exotic methods) still have many cases where they fail to reliably reproduce experimental results.
It's possible that you don't need to simulate anything down to the molecular level to reproduce all the biologically interesting features of cells. I don't want to rule it out completely. But the enormous financial incentives to simulate biology in silico (for e.g. accelerating pharmaceutical development), the large research investments made so far, and the limited progress to date tend to make me think that all those tiny and extremely computationally expensive details at the molecular level are biologically relevant.