Think you have a great idea for an application that can really leverage the horsepower of a GPU? Forget about the global recession–now might be just the time to test drive your concept with the benefit of a backer. NVIDIA, which stakes its claim as the inventor of GPU technology, just launched the GPU Ventures Program, a new global initiative charged with identifying, supporting and investing in early stage companies that are leveraging the GPU for visual and other types of computing applications.
Jeff Herbst, NVIDIA’s vice president of business development, is pitching the program as an opportunity for young, ambitious companies basing their businesses around the GPU. “Through this program, we will provide financial, marketing and other support to help start-up companies realize their full potential,” Herbst said. “We strongly encourage interested entrepreneurs, venture capitalists and others to reach out to us with their ideas.”
Through the GPU Ventures Program, NVIDIA will evaluate companies leveraging the GPU in consumer or professional applications in such areas as video, image enhancement, scientific discovery, 3-D interfaces and financial analysis. NVIDIA says it will make investments from $500,000 up to $5 million, depending upon the product, and will also enter into strategic joint marketing, development and distribution partnerships.
NVIDIA already has an investment track record having put money into such startups as Accelware, Keyhole Corp. (acquired by Google for Google Earth), Mental Images (now owned by NVIDIA) and others.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.