Object recognition relies on sensors, computer memory and processing speed, and software.
Sensors:
Camera technology has run ahead very quickly. I believe that today the amount of input from cameras into the server farm can be made significantly greater than the amount of input from the eye into the brain.
I only put a single camera into my scenario, but if we are trying to max out the room’s ability to recognize objects, we can put in many.
Likewise, if the microphone is helpful in recognition, then the room can exceed human auditory abilities.
Machines have already overtaken us in being able to accept these kinds of raw data.
Memory and Processing Power:
Here is a question that requires expert thinking: So, apparently machines are recording enough video today to equal the data stream people use for visual object recognition, and computers can manipulate these images in real-time.
What versions of the object recognition task require still more memory and still faster computers, or do we have enough today?
Software
Google Goggles offers some general object recognition capabilities.
We also have voice and facial recognition.
One useful step would be to find ways to measure how successful systems like Google Goggles and facial recognition are now, then plot over time.
Continuing the example:
Object recognition relies on sensors, computer memory and processing speed, and software.
Sensors:
Camera technology has run ahead very quickly. I believe that today the amount of input from cameras into the server farm can be made significantly greater than the amount of input from the eye into the brain.
I only put a single camera into my scenario, but if we are trying to max out the room’s ability to recognize objects, we can put in many.
Likewise, if the microphone is helpful in recognition, then the room can exceed human auditory abilities.
Machines have already overtaken us in being able to accept these kinds of raw data.
Memory and Processing Power:
Here is a question that requires expert thinking: So, apparently machines are recording enough video today to equal the data stream people use for visual object recognition, and computers can manipulate these images in real-time.
What versions of the object recognition task require still more memory and still faster computers, or do we have enough today?
Software
Google Goggles offers some general object recognition capabilities.
We also have voice and facial recognition.
One useful step would be to find ways to measure how successful systems like Google Goggles and facial recognition are now, then plot over time.
With that work in hand, we can begin to forecast.