FORTUNE — Last year, entrepreneur-turned-venture capitalist Vinod Khosla made waves when he said technology would someday replace 80% of doctors. This morning, at a Menlo Park, Calif.-based event hosted by one of his firm’s portfolio companies, Ayasdi, Khosla reiterated his belief that computational power — not people — will bring about massive improvements in nearly every field, particularly health care.
“Almost everything doctors know about medicine will be obsolete,” Khosla told the audience. Earlier this year, the longtime technologist and co-founder of Sun Microsystems led a $10 million funding round in Ayasdi, a newish big data company that utilizes “topological analysis” to look for patterns in massive, often disparate data points. (In plain English, Ayasdi turns mountains of linear information, like what is found in health records, into geometric shapes that people can interact with.) The Palo Alto, Calif.-based company is one of an exploding number of big data startups. But while most companies’ offerings rely on data scientists to query systems with questions, Ayasdi says its approach enables companies to glean insights they didn’t know they were looking for. General Electric (GE), Citi (C), and Merck (MRK) are among the company’s early customers.
“The most interesting things in highly complex data are the things we don’t know to ask,” says Khosla, who was attracted to Ayasdi’s ability to scale data science using more computational power, not more data scientists. Unlike coveted data scientists, computer power is actually getting cheaper.
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But Ayasdi is also tapping into another trend: data visualization. From Seattle-based Tableau to just-launched startups like Palo Alto’s ClearStory Data, companies large and small are offering up tools that help users spin beautiful, interactive graphics from massive data sets. According to technology research firm Gartner, the big data category — visualization and other tools — will drive $34 billion of IT spending this year. The companies who are buying up big data tools are almost as diverse as the disparate data sets we can now analyze, from health care to retail to professional sports.
At least one area that big data has yet to significantly affect is the venture capital world. Khosla has made more than 100 investments in his many years as a venture capitalist but says he has never calculated ROI or used any kind of data science tools to determine the likely outcome of an investment.
“There is no database large enough,” he says on the problem of using big data to inform his investing decisions. It remains to be seen how his bet on Ayasdi — or predictions on the future of health care — will pan out. Even topological data analysis has its limitations.