Quotes: Thoughts on AI by Pioneers
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 Eric Drexler - Nanotechnology Pioneer 1989 - "As I discuss in "Engines of Creation", if you can build genuine AI, there are reasons to believe that you can build things like neurons that are a million times faster. That leads to the conclusion that you can make systems that think a million times faster than a person. With AI, these systems could do engineering design. Combining this with the capability of a system to build something that is better than it, you have the possibility for a very abrupt transition. This situation may be more difficult to deal with even than nanotechnology, but it is much more difficult to think about it constructively at this point. Thus, it hasn't been the focus of things that I discuss, although I periodically point to it and say: 'That's important too..'"  Hans Moravec - Robotics Pioneer 1997 - "There are very good reasons why things will go much faster in the next fifty years than they have in the last fifty... Since 1990, the power available to individual AI and robotics programs has doubled yearly, to 30 MIPS by 1994 and 500 MIPS by 1998. Seeds long ago alleged barren are suddenly sprouting. Machines read text, recognize speech, even translate languages. Robots drive cross-country, crawl across Mars, and trundle down office corridors. In 1996 a theorem-proving program called EQP running five weeks on a 50 MIPS computer at Argonne National Laboratory found a proof of a Boolean algebra conjecture by Herbert Robbins that had eluded mathematicians for sixty years. And it is still only Spring. Wait until Summer. "[ref]  Nick Bostrom - Director, Future of Humanity Institute 1997 - "In the seventies and eighties the AI field suffered some stagnation as the exaggerated expectations from the early heydays failed to materialize and progress nearly ground to a halt. The lesson to draw from this episode is not that strong AI is dead and that superintelligent machines will never be built. It shows that AI is more difficult than some of the early pioneers might have thought, but it goes no way towards showing that AI will forever remain unfeasible." [ref]  Marvin Minsky - Father of AI 2000 - "No one has tried to make a thinking machine… The bottom line is that we really haven't progressed too far toward a truly intelligent machine. We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack. We have got to get back to the deepest questions of AI and general intelligence and quit wasting time on little projects that don't contribute to the main goal."[as interviewed in "Hal's Legacy", Edited by David Stork]  Lloyd Watts - Computational Neuroscientist 2002 - "The neuroscience community has advanced our collective knowledge of brain function to the point where it is now possible to build accurate and meaningful computational models of major brain pathways... The next two decades promise an exciting period of advances in our understanding of the nature of human intelligence, and the development of increasingly intelligent assistants and prosthetics that enrich human life in ways we can now only imagine." [World Congress on Computational Intelligence]  Bill Gates - Founder, Microsoft 2004 - "If you invent a breakthrough in artificial intelligence, so machines can learn, that is worth 10 Microsofts." [ref]  Ray Kurzweil - Founder, KurzweilAI.net 2005 - "I set the date for the Singularity- representing a profound and disruptive transformation in human capability- as 2045. The nonbiological intelligence created in that year will be one billion times more powerful than all human intelligence today." [Pg. 136 "The Singularity is Near, When Humans Transcend Biology"]  Alan K. Mackworth - President of the American Association for Artificial Intelligence 2005 "In AI's youth, we worked hard to establish our paradigm by vigorously attacking and excluding apparent pretenders to the throne of intelligence, pretenders such as pattern recognition, behaviorism, neural networks, and even probability theory. Now that we are established, such ideological purity is no longer a concern. We are more catholic, focusing on problems, not on hammers. Given that we do have a comprehensive toolbox, issues of architecture and integration emerge as central." ["The Coevolution of AI and AAAI," AI Magazine 26(4): Winter 2005, 51-52]  Eliezer Yudkowsky - Founder, Research Fellow, Singularity Institute for Artificial Intelligence 2005 "We exist, thus we know general intelligence is possible within at least one physical system. If general intelligence cannot be created on computing systems, then programmable artificial neurons, modeled after human neurons, will need to be created. Regarding assumptions, the attempt to create human-similar general intelligence is dependent on our matching or surpassing the design intelligence of natural and sexual selection. In light of the design power of deliberate human intelligence, relative to the design power of evolution, I think this is a safe assumption. Also, there are no noncomputable aspects in SIAI's theory of mind, deliberative general intelligence (DGI). "Levels of Organization in General Intelligence" accounts for many qualities that are attributed to the presumed magical nature of biology, and explains the origins of qualities that are stereotypically "mechanical" in today's AI programs. I believe that the advantages of silicon, such as massive serialism, should be enough to build a mind without the advantages of biology, even if biology quantum computes on specific algorithms." [SIAI's Eliezer Yudkowsky Q&A - Intelligence and Seed AI]  Ben Goertzel - Founder, CEO/CSO, Novamente LLC 2006 "Many AI researchers seem to take the position that, while AGI is in principle possible, it lies far beyond our current technological capability. This is a reasonable enough contention, since according to the best available estimates (which are admittedly very speculative), current computing hardware falls significantly short of the computing power of a single human brain. Furthermore, existing operating systems and programming languages are arguably ill-suited to the task of creating general intelligence; and current compilers for languages that appear to be best-suited (LISP, Haskell and the like) are not pragmatically capable of robustly supporting applications that make the most of multiprocessor architectures and multi-gigabyte RAM. But still, these arguments are not terribly convincing. Even if it’s true that current computers are much less powerful than the human brain, this isn’t necessarily an obstacle to creating powerful AGI on current computers using fundamentally non-brain-like architectures. And the shortcomings of contemporary software frameworks are surely just an inconvenience rather than a fundamental obstacle." [ref] |
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