I Asked an A.I. How to Learn A.I.

(Image created by A.I. DALL-E)

I've been spending a great deal of my time learning all I can about Artificial Intelligence which is the reason why I ask an A.I. to help with the process.

What I asked: Design steps on how to learn about A.I.

The Output:

1. Begin by researching the basics of A.I. and familiarizing yourself with the key concepts and terminology. Make sure to understand the different types of A.I. and the goals and objectives of each.

2. Take online courses or tutorials that teach the fundamentals of A.I. such as machine learning, deep learning, natural language processing and robotics.

3. Read books and articles from experts in the field of A.I. to gain a deeper understanding of the topic.

4. Follow blogs and forums about A.I. to stay up-to-date on the latest developments.

5. Participate in hackathons and coding competitions that involve A.I.

6. Experiment with A.I. by creating projects or building applications.

7. Network with other A.I. professionals and attend conferences to learn more.

Crazy uh?

Will the novelty of A.I. wear off?

A.I. is in its infancy and is already gathering a lot of attention but will it last?  I don't see A.I. as a novelty as much as the next step in our evolution. The future of such things as online searches is found in A.I. - some companies, behind those online searches, may already be using some form of A.I. 

The day will come where A.I. will be widely available via our phone or via a drone that would follow us around to help in our daily activities (For gamers: Think of "Ghost" in the "Destiny" video game).

The issue with A.I. currently is that we can't always trust the data that it produces. There's always a little something that we need to double check or fix. You can't currently, for example, use A.I. to build software without first knowing about software as the output that it produces needs to be refined in order to work properly. The key word here, however, is "Output" - the A.I. is producing "Something" which is better than "Nothing" and can be used with a little tweaking or help inspire new things.

A day will come, with enough data/time, where all of the issues will be fixed and every output will be as good as the experts.