Intel with 30MUSD investment in cloud and embedded R&D;
These centers represent the next $30 million installment of Intel’s recently announced 5-year, $100 million ISTC program to increase university research and accelerate innovation in a handful of key areas. As with previously announced ISTCs for visual computing and secure computing, the new centers encourage tighter collaboration between university thought leaders and Intel. To encourage further collaboration, the ISTCs use open IP models with results publically available through technical publications and open-source software releases.”These new ISTCs are expected to open amazing possibilities,” said Justin Rattner, Intel Chief Technology Officer. “Imagine, for example, future cars equipped with embedded sensors and microprocessors to constantly collect and analyze traffic and weather data. That information could be shared and analyzed in the cloud so that drivers could be provided with suggestions for quicker and safer routes.”The cloudThe researchers will explore technology that will have has important future implications for the cloud, including built-in application optimization, more efficient and effective support of big data analytics on massive amounts of online data, and making the cloud more distributed and localized by extending cloud capabilities to the network edge and even to client devices.In the future, these capabilities could enable a digital personal handler via a device wired into your glasses that sees what you see, to constantly pull data from the cloud and whisper information to you during the day — telling you who people are, where to buy an item you just saw, or how to adjust your plans when something new comes up.EmbeddedWith the growing popularity of mobile real-time and personalized technology, there is a corresponding rise in demand for specialized embedded computing systems to support a broad range of new applications — including many not yet envisioned.A key area of research is to make it easier for these everyday devices to continuously collect, analyze and act on useful data from both sensors and online databases in a way that is timely, scalable and reliable. For example, in cars, this data could be used to customize in-vehicle entertainment options when specific passengers are recognized, and provide them better routing, retail, dining, and entertainment recommendations while on-the-road.