“Now the rise of AI is sparking a new discussion: If automation takes over more physical tasks and artificial intelligence takes over more intellectual ones, humans will be defined by their social abilities, said Raman.”

M doomed!

The knowledge economy is on the way out, and a new economy is on the way for us humans at work, he said. I’m calling it the innovation economy.

In this new era, human innovation and our uniquely human skills, like social and emotional intelligence will be key, he added.

I wondered when this would start!

“This means that should everything go according to plan, the humanoid robot will eventually be put to work building itself.”

Apptronik, an Austin-based maker of humanoid robots, on Tuesday announced a new pilot partnership with American supply chain/manufacturing stalwart, Jabil. The deal arrives two weeks after Apptronik announced a $350 million Series A financing round aimed at scaling up production of its Apollo robot.

The Jabil deal is the second major pilot announced by Apptronik. It follows a March 2024 partnership that put Apollo to work on the Mercedes-Benz manufacturing floor. While the company tells TechCrunch that its partnership with the automaker is ongoing, it has yet to graduate beyond the pilot stage.

With the availability of high throughput electron microscopy (EM), expansion microscopy (ExM), Calcium and voltage imaging, co-registered combinations of these techniques and further advancements, high resolution data sets that span multiple brain regions or entire small animal brains such as the fruit-fly Drosophila melanogaster may now offer inroads to expansive neuronal circuit analysis. Results of such analysis represent a paradigm change in the conduct of neuroscience.

So far, almost all investigations in neuroscience have relied on correlational studies, in which a modicum of insight gleaned from observational data leads to the formulation of mechanistic hypotheses, corresponding computational modeling, and predictions made using those models, so that experimental testing of the predictions offers support or modification of hypotheses. These are indirect methods for the study of a black box system of highly complex internal structure, methods that have received published critique as being unlikely to lead to a full understanding of brain function (Jonas and Kording, 2017).

Large scale, high resolution reconstruction of brain circuitry may instead lead to mechanistic explanations and predictions of cognitive function with meaningful descriptions of representations and their transformation along the full trajectory of stages in neural processing. Insights that come from circuit reconstructions of this kind, a reverse engineering of cognitive processes, will lead to valuable advances in neuroprosthetic medicine, understanding of the causes and effects of neurodegenerative disease, possible implementations of similar processes in artificial intelligence, and in-silico emulations of brain function, known as whole-brain emulation (WBE).