Machine Insight is a Cambridge, MA based company that is developing new technologies in Machine Learning and Artificial Intelligence (AI). It is currently applying these technologies to online ad targeting through a partnership with a leading ad firm.

If you are a researcher in AI, statistics, or a related field, who also likes to see technology applied to real-world problems, or if you are an outstanding developer excited to work at the bleeding edge of technology, please see our job listings.

Machine Insight's Philosophy

We live at a time where is has become apparent that technological growth is occurring at an exponential rate. The rate of growth implies that ten years from today, computers will be one thousand times more powerful, and that in twenty years, they will be a million times more powerful. What will we do with all this computing power?

One answer is Artificial Intelligence (AI), the branch of computer science where people attempt to make computers do things that would be considered intelligent if done by people. The field of AI has languished for nearly 20 years, but in the last 10 has been making large strides forward. Why?

Hans Moravec, an AI researcher at Carnegie Mellon wrote that:

... for several decades the computing power found in advanced Artificial Intelligence and Robotics systems has been stuck at insect brainpower of 1 MIPS. While computer power per dollar fell rapidly during this period, the money available fell just as fast. The earliest days of AI, in the mid 1960s, were fuelled by lavish post-Sputnik defense funding, which gave access to $10,000,000 supercomputers of the time. In the post Vietnam war days of the 1970s, funding declined and only $1,000,000 machines were available. By the early 1980s, AI research had to settle for $100,000 minicomputers. In the late 1980s, the available machines were $10,000 workstations. By the 1990s, much work was done on personal computers costing only a few thousand dollars. Since then AI and robot brainpower has risen with improvements in computer efficiency. By 1993 personal computers provided 10 MIPS, by 1995 it was 30 MIPS, and in 1997 it is over 100 MIPS. Suddenly machines are reading text, recognizing speech, and robots are driving themselves cross country.
Today, a $1,000 PC is over 100,000 MIPS, and the rate is increasing exponentially. We all have at our desks what just a few years ago would have been considered a supercomputer. This inexpensive computing power is driving a renaissance in AI research, where algorithms can be tried that were simply infeasible to compute back in the heyday of well-funded AI research. Much of this new AI research is driven from the bottom up by computing over large quantities of data.

Machine Insight's mission is the application of existing and new AI technologies towards solving real-world problems. If you would like to join us, please see our job listings.