The Snips SDK enables you to create your own AI assistant, while keeping user data safe. Snips is Private by Design.
Source: Snips | AI Voice Platform
Since Snips can run fully on-device, your user data doesn’t have to be sent to a server. This means better protection of your user data against hacking and surveillance, and lower compliance costs with HIPAA and GDPR regulations
Machines won’t become intelligent unless they incorporate certain features of the human brain. Here are three of them
Source: What Intelligent Machines Need to Learn From the Neocortex – IEEE Spectrum
The only example of intelligence, of the ability to learn from the world, to plan and to execute, is the brain. Therefore, we must understand the principles underlying human intelligence and use them to guide us in the development of truly intelligent machines.
These three fundamental attributes of the neocortex—learning by rewiring, sparse distributed representations, and sensorimotor integration—will be cornerstones of machine intelligence. Future thinking machines can ignore many aspects of biology, but not these three. Undoubtedly, there will be other discoveries about neurobiology that reveal other aspects of cognition that will need to be incorporated into such machines in the future, but we can get started with what we know today.
From the earliest days of AI, critics dismissed the idea of trying to emulate human brains, often with the refrain that “airplanes don’t flap their wings.” In reality, Wilbur and Orville Wright studied birds in detail. … the Wright brothers studied birds and then chose which elements of bird flight were essential for human flight and which could be ignored. That’s what we’ll do to build thinking machines.
Machines can now see into the future, and we ignore them at our peril.
in our galaxy, technology is the Force. Increasingly, it’s computers that train our intuition. It’s computers that help us perceive beyond our senses.
You can avoid bad futures because you can actually see them. … It’s an entirely new kind of vision. We don’t often think of computation that way, as a visual aid, because it’s somewhat difficult to describe what it helps us see. Where telescopes and microscopes show us the very far and the very small, the computer shows us the very much, all at once. It makes time available to the mind and eye. Computation, in that sense, is a kind of compacting of imagination: It helps us generate and explore a zillion scenarios and digest them into a representation that’s easy to play around with.
This is going to start happening everywhere. We’ll use computers to explore possible futures, and over time we’ll learn how to see those futures for ourselves, almost to feel them, to the point where it’ll seem to those not in the know that we have command of an arcane force.
Source: Why Luke Skywalker Was Wrong to Use the Force – The Atlantic
Google and others offer wrong answers with matter-of-fact authority.
The reasonable desire for speed has to be tempered by higher-order concerns of fact and accuracy.
the more Google and other answer machines become the authorities of record, the more their imperfect understanding of the world becomes accepted as fact. Designers of all data-driven systems have a responsibility to ask hard questions about proper thresholds of data confidence—and how to communicate ambiguous or tainted information.
How can we make systems that are not only smart enough to know when they’re not smart enough… but smart enough to say so and signal that human judgment has to come into play?
Source: Systems Smart Enough To Know When They’re Not Smart Enough | Big Medium
A list of useful books for game AI programming.
Source: The AI Programmer’s Bookshelf