Home Artificial Intelligence Artificial Intelligence News Time handling by Quantum and Classical computers

Time handling by Quantum and Classical computers

Audio version of the article

As humans, we take time for granted. We’re born into an innate understanding of the passage of events because it’s essential to our survival. But AI suffers from no such congenital condition. Robots do not understand the concept of time.

State of the art AI systems only understand time as an implicit construct (we program it to output time relevant to a clock) or as an explicit representation of mathematics (we use the time it takes to perform certain calculations to instruct its understanding of the passage of events). But an AI has no way of understanding the concept of time itself as we do.

Time doesn’t exist in our classical reality in a physical, tangible form. We can check our watch or look at the sun or try and remember how long it’s been since we last ate, but those are all just measurements. The actual passage of time, in the physics sense, is less proven.

In fact, scientists have proven that time’s arrow – a bedrock concept related to the classical view of time – doesn’t really work on quantum computers. Classical physics suffers from a concept called causal asymmetry. Basically, if you throw a bunch of confetti in the air and take a picture when each piece is at its apex, it’ll be easier for a classical computer to determine what happens next (where the confetti is going) than what happened before (what direction the confetti would travel in going backwards through time).

Quantum computers can perform both calculations with equal ease, thus indicating they do not suffer causal asymmetry. Time’s arrow is only relevant to classical systems – of which the human mind appears to be, though our brains are almost certainly quantum constructs.

Where things get most interesting is if you consider the addition of artificial intelligence into the mix. As mentioned previously, AI doesn’t have a classical or quantum understanding of time: time is irrelevant to a machine.

But experts such as Gary Marcus and Ernest Davis believe an understanding of time is essential to the future of AI, especially as it relates to “human-level” artificial general intelligence (AGI). The duo penned an op-ed for the New York Times where they stated:

In particular, we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets — often using an approach known as deep learning — and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality.

While the statement is intended as a sweeping indictment on relying on bare bones deep learning systems and brute force to achieve AGI, it serves as a bit of a litmus test as to where the computer science community is at when it comes to AI .

Currently, we’re building classical AI systems with the hopes they’ll one day be robust enough to mimic the human mind. This is a technology endeavor, meaning computer experts are continuously pushing the limits of what modern hardware and software can do.

The problem with this approach is that it’s creating a copy of a copy. Quantum physics tells us that, at the very least, our understanding of time is likely different from what might be the ultimate universal reality.

How close can robots ever come to imitating humans if they, like us, only think in classical terms? Perhaps a better question is: what happens when AI learns to think in quantum terms while us humans are still stuck with our classical interpretation of reality?

This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed.

Source link

- Advertisment -

Most Popular

Data Analytics vs. Machine Learning

Technological advancements have changed the way we perform a lot of tasks. Today, we have powerful devices that have made our work quite easier....

Nanotechnology: What is it and how does it improve CBD?

There is just about any kind of CBD product you can think of - there are edibles (with vegan options because why not?), oil...

Make Your Own Virtual Zoom Background | Beginner Python Coding Tutorial 

A lot of video calling software like Zoom and Google Hangouts now let users use a virtual background behind them. In this project, we'll...

The Evolution in Data Science Jobs

AutoML is poised to turn developers into data scientists — and vice versa. Here’s how AutoML will radically change data science for the better. In...

Understanding the Difference between Blockchain and Relational database

What is a blockchain database? If we consider all that we have learned about blockchains so far, we can say that blockchains are quite sophisticated and complex....

Understanding the Future of Money

Five years ago, Bitcoin and its cousins in cryptocurrency seemed so unimportant that central banks could hardly be bothered to sneer at them. Now...
- Advertisment -