Slashdot Mirror
Intel Aims To Take on Nvidia With a Processor Specially Designed for AI (fastcompany.com)
An anonymous reader shares a report: In what looks like a repeat of its loss to Qualcomm on smartphones, Intel has lagged graphics chip (GPU) maker Nvidia in the artificial intelligence revolution. Today Intel announced that its first AI chip, the Nervana Neural Network Processor, will roll out of factories by year's end. Originally called Lake Crest, the chip gets its name from Nervana, a company Intel purchased in August 2016, taking on the CEO, Naveen Rao, as Intel's AI guru. Nervana is designed from the ground up for machine learning, Rao tells me. You can't play Call of Duty with it. Rao claims that ditching the GPU heritage made room for optimizations like super-fast data interconnections allowing a bunch of Nervanas to act together like one giant chip. They also do away with the caches that hold data the processor might need to work on next. "In neural networks... you know ahead of time where the data's coming from, what operation you're going to apply to that data, and where the output is going to," says Rao.
AI in video games is very different from the AI that these chips would be using. The AI in video games sucks for three reasons:
1. If the AI were too good, players would quit because it is too hard. Certain games specifically are designed to be extremely hard, but this isn't the norm. In a first person shooter, this would be the equivalent of fighting against an aimbot. (Aimbots are a great example of AI - they're designed to be perfect or to use information that the player doesn't normally have.) It becomes a game balance and design decision to make the AI imperfect.
2. Complex AI can be very computationally intensive. There's a tradeoff in the speed of calculations between "good enough" and "perfect" in some algorithms. When you're dealing with a lot of variables in a complex game that a good AI might use, it takes a lot of processor cycles to calculate how to respond to you to make it more difficult for you. Take for example Civilization that takes far longer between turns at the end of the scenario than it does at the beginning of the scenario because there are more variables to consider.
3. Given 1 and 2, the easiest method to implement a balanced AI is to cheat - give the computer advantages that the players don't have or to hardcode certain behaviors. Those behaviors can be easy for humans to learn and beat, even when the computer is cheating.
The processors in this article are talking about new chips that are designed to calculate the math for a certain type of complex calculation by making assumptions about the type of calculation being done and taking some shortcuts with the drawback that they can't perform other calculations as fast.