In coming years, computer processing, storage, and networking capabilities will continue up the steeply exponential curve they have followed for the past few decades. By 2019, parallel-processing computer clusters will be 50 to 100 times more powerful in most respects. Computer programs, more of them web-based, will evolve to take advantage of this newfound power, and Internet usage will also grow: more people online, doing more things, using more advanced and responsive applications. By any metric, the "cloud" of computational resources and online data and content will grow very rapidly for a long time.
As we're already seeing, people will interact with the cloud using a plethora of devices: PCs, mobile phones and PDAs, and games. But we'll also see a rush of new devices customized to particular applications, and more environmental sensors and actuators, all sending and receiving data via the cloud. The increasing number and diversity of interactions will not only direct more information to the cloud, they will also provide valuable information on how people and systems think and react.
Thus, computer systems will have greater opportunity to learn from the collective behavior of billions of humans. They will get smarter, gleaning relationships between objects, nuances, intentions, meanings, and other deep conceptual information. Today's Google search uses an early form of this approach, but in the future many more systems will be able to benefit from it.
What does this mean to Google? For starters, even better search. We could train our systems to discern not only the characters or place names in a YouTube video or a book, for example, but also to recognize the plot or the symbolism. The potential result would be a kind of conceptual search: "Find me a story with an exciting chase scene and a happy ending." As systems are allowed to learn from interactions at an individual level, they can provide results customized to an individual's situational needs: where they are located, what time of day it is, what they are doing. And translation and multi-modal systems will also be feasible, so people speaking one language can seamlessly interact with people and information in other languages.
The impact of such systems will go well beyond Google. Researchers across medical and scientific fields can access massive data sets and run analysis and pattern detection algorithms that aren't possible today. The proposed Large Synoptic Survey Telescope (LSST), for example, may generate over 15 terabytes of new data per day! Virtually any research field will benefit from systems with the ability to gather, manipulate, and learn from datasets at that scale.
Traditionally, systems that solve complicated problems and queries have been called "intelligent", but compared to earlier approaches in the field of 'artificial intelligence', the path that we foresee has important new elements. First of all, this system will operate on an enormous scale with an unprecedented computational power of millions of computers. It will be used by billions of people and learn from an aggregate of potentially trillions of meaningful interactions per day. It will be engineered iteratively, based on a feedback loop of quick changes, evaluation, and adjustments. And it will be built based on the needs of solving and improving concrete and useful tasks such as finding information, answering questions, performing spoken dialogue, translating text and speech, understanding images and videos, and other tasks as yet undefined. When combined with the creativity, knowledge, and drive inherent in people, this "intelligent cloud" will generate many surprising and significant benefits to mankind.