Stanford Artificial Intelligence Laboratory
From Free net encyclopedia
The Stanford Artificial Intelligence Laboratory (commonly called the Stanford AI Lab, or SAIL), was one of the leading centres for artificial intelligence research from the 1960s through the 1980s.
It was started by John McCarthy after he moved from MIT to Stanford in 1963. From 1965 to 1980, it was housed in the fabled D.C. Power building (named after an executive of G.T.E., which donated the building and site to Stanford, not the type of electricity), in the foothills of the Santa Cruz Mountains overlooking Stanford. In 1980, it moved into Margaret Jacks Hall in the main Stanford campus, and its activities were merged into the Computer Science Department.
The old SAIL building was located far enough away from campus that you needed a bicycle or car to get there. Combined with the rather extreme 1960s architecture of the place, this led to a certain isolation and feeling of being already in the future. Unfortunately, the building was damaged during an earthquake and the university decided to level the site. Pictures can be seen at http://www.pgc.com/pgc/sail/.
SAIL alumni played a major role in many Silicon Valley firms, including Sun Microsystems. Research accomplishments at SAIL were many, including in the fields of speech recognition and robotics.
SAIL also created the WAITS operating system. WAITS ran on various models of Digital Equipment Corporation PDP-10 computers, starting with the PDP-6, then the KA10 and KL10. At one time, the SAIL system was a triple processor KL10/KA10/PDP-6. The SAIL system was shut down in 1991.
SAIL, the Stanford Artificial Intelligence Language, was developed by Dan Swinehart and Bob Sproull of the Stanford AI Lab in 1970.
SAIL shut down in the 1980, but reopened in 2004. Professor Sebastian Thrun became the director of the new SAIL. Today, SAIL's primary mission is to advance our understanding of Artificial Intelligence. Researchers in SAIL publish in areas such as bioinformatics, cognition, computational geometry, computer vision, decision theory, distributed systems, game theory, image processing, information retrieval, knowledge systems, logic, machine learning, multi-agent systems, natural language, neural networks, planning, probabilistic inference, sensor networks, and robotics.