September 28, 2008
Helicopters teach themselves to do aerial maneuvers
I just read this article: Helicopters teach themselves to do aerial maneuvers, about the work by my friend Andrew Ng and his grad students at Stanford. This is really impressive.
Stanford computer scientists have developed an artificial intelligence system that enables robotic helicopters to teach themselves to fly difficult stunts by watching other helicopters perform the same maneuvers. The technique is known as “apprenticeship learning.” The result is an autonomous helicopter than can fly dazzling stunts on its own.
Posted by barney on September 28, 2008 at 2:26 pm | No Comments
August 29, 2007
Barney Pell podcast with Dan Farber about the Singularity and AI
Yesterday I was interviewed in a podcast with Dan Farber about my upcoming talk at the Singularity Summit.
It’s interesting and fun to have futurist conversations while working hard in a startup. Amidst the short-term pressures of bringing technology to market it is nice to engage in long-term musings about where this all might lead in 30 years. And it will be really fun to look back at these discussions 30 years from now and see who made the best predictions.
Here is Dan’s summary of the interview:
In this podcast interview, I talked with Pell about his views on AI and how the development of machines smarter than humans will play out in coming decades. We also discussed the underpinnings of Powerset as an example of technology and collective human intelligence applied to making a smarter search engine, and how natural language understanding is at an inflection point, moving out of the labs and into the world.
Pell said that AI entities will get smarter but also humans, via intelligence augmentation, will gain new capabilities. He suggested that two approaches will meet in the middle–bottom-up complete brain simulations, which develop like human children, and top-down engineered systems.
He provided a framework for thinking about how AIs might evolve, and thoughts about the risks in developing such advanced technologies. “We are going to have to just bite the bullet–because this is going to happen. I don’t think these will be technologies you will be able to control. I do think there is strong value in looking at what are architectural aspects that may or may not be the same as people that can really dispose these systems to be the kinds of systems you want to build and to look at training and development processes that socialize these systems in the right way,” Pell said.
Posted by barney on August 29, 2007 at 10:38 pm | No Comments
August 22, 2007
Barney speaking at the Singularity Summit
I am speaking at the upcoming The Singularity Summit AI & the Future of Humanity Sat-Sun, September 8th-9th Palace of Fine Arts Theatre 3301 Lyon St, SF, CA 94123 I am speaking in the first session, on Pathways and Major Challenges to Advanced AI. Here is my title and abstract:
Pathways to advanced general intelligence: Architecture, Development, and
Funding
While there is broad consensus among the AI community that we will have artificial general intelligence (AGI) within the century, there is little discussion about the alternate technical and economic pathways that will bring this about. I present a framework for comparing different approaches, in which we view any intelligent behavior as a combination of architecture and
development, both of which can be characterized as more or less human-brain-like. Seen within this framework, one extreme strives for complete brain simulations that develop like human children. Another extreme strives for unconstrained engineered systems that acquire knowledge through diverse methods. I predict that the path to AGI will be based on a much richer interplay between these two extremes, in which top-down and bottom up approaches meet in the middle.
The hybrid development path combines the benefits of both technical extremes. It also supports applications that create incremental business advantage for incremental improvements in AGI capability, thus driving business competition that accelerates the science. These applications
include video games, virtual worlds, household robots, autonomous vehicles, search, and conversational interfaces.
I have actually been thinking about this particular topic on and off for a while. Despite believing for a long time that the most likely path to human-level AI was through very human-like systems, my professional work has tended to take heavy engineering approaches in which you focus on the required behavior (hopefully a general task) but then approach it using whatever engineering means you can. This has been true for autonomous agents, natural language processing systems, game playing programs, and search engines. Now I think the combination of human-inspired and powerfully-engineered approaches is more likely to be what really comes to pass. It will be fun to share and discuss this with folks at the Singularity Summit.
Here are a few provocative topics that may or may not wind up making it into my talk:
- How many man-hours have actually been applied to the task of creating human-level AI? The number is likely a tiny fraction of the research in AI fields to date. So with advanced computing and communications technology amplifying research and with a focused effort on the core problems, progress might come about faster than anyone thinks.
- If we simulated every neuron and connection in a specific human brain, would this give us an intelligent system?
- What if hormones are required as well, but we haven’t simulated them?
- What if the brain is a chaotic system, with sensitive dependence on the initial conditions? Then if the simulation was just a little off, it might be completely useless.
- We can take a recently dead human brain and have no idea how to revive the person. So a high-fidelity neural simulation may still be as useless as a dead human brain.
- Any AI system that will inhabit a human world would likely require some form of empathy. But is it possible to have deep empathy with humans if you have a radically different architecture?
- It should be possible in principal to create intelligence by simulating an entire history of evolution, starting with basic single-cellular life. But there are several problems with this.
- First, how do we impose the selective pressures that give rise to general intelligence and language as opposed to the wide variety of other adaptations?
- Second, this takes a lot of computing and has no guarantees to get anywhere.
- Third, intelligent minds are primitive without an intelligent culture and knowledge base. So this doesn’t get us to the singularity unless they recreate or learn our cultural advances too.
- Fourth, if this artificial evolution resulted in intelligent language-using agents, the kind of language they evolve may be very different from humans. Thus they would be isolated from human society, and we may not even be able to recognize them as intelligent. Perhaps such beings exist already and live among us?
If you read these thoughts before the conference, please feel free to post comments or send me your thoughts.
Posted by barney on August 22, 2007 at 11:55 pm | No Comments