Saved by Prashanth Narayan and
Deep Learning Is Hitting a Wall
Gary Marcus • Deep Learning Is Hitting a Wall
What does “manipulating symbols” really mean? Ultimately, it means two things: having sets of symbols (essentially just patterns that stand for things) to represent information, and processing (manipulating) those symbols in a specific way, using something like algebra (or logic, or computer programs) to operate over those symbols.
Gary Marcus • Deep Learning Is Hitting a Wall
Classical computer science, of the sort practiced by Turing and von Neumann and everyone after, manipulates symbols in a fashion that we think of as algebraic, and that’s what’s really at stake.
Gary Marcus • Deep Learning Is Hitting a Wall
Such signs should be alarming to the autonomous-driving industry, which has largely banked on scaling, rather than on developing more sophisticated reasoning. If scaling doesn’t get us to safe autonomous driving, tens of billions of dollars of investment in scaling could turn out to be for naught.
Gary Marcus • Deep Learning Is Hitting a Wall
Indeed, we may already be running into scaling limits in deep learning, perhaps already approaching a point of diminishing returns. In the last several months, research from DeepMind and elsewhere on models even larger than GPT-3 have shown that scaling starts to falter on some measures, such as toxicity, truthfulness, reasoning, and common sense
Gary Marcus • Deep Learning Is Hitting a Wall
In time we will see that deep learning was only a tiny part of what we need to build if we’re ever going to get trustworthy AI.
Gary Marcus • Deep Learning Is Hitting a Wall
Deep learning, which is fundamentally a technique for recognizing patterns, is at its best when all we need are rough-ready results, where stakes are low and perfect results optional.
Gary Marcus • Deep Learning Is Hitting a Wall
What are symbols? They are basically just codes. Symbols offer a principled mechanism for extrapolation: lawful, algebraic procedures that can be applied universally, independently of any similarity to known examples. They are (at least for now) still the best way to handcraft knowledge, and to deal robustly with abstractions in novel situations. A... See more
Gary Marcus • Deep Learning Is Hitting a Wall
With all the challenges in ethics and computation, and the knowledge needed from fields like linguistics, psychology, anthropology, and neuroscience, and not just mathematics and computer science, it will take a village to raise to an AI.