@Geroge,

Hello George,

It’s fantastic that you’re interested in AI at 83! A great starting point is to explore online courses on platforms like Coursera, edX, or Khan Academy. They offer beginner-friendly AI courses.

Considering your background with A/S 400, IBM, and Linux, you might find Python programming language useful for AI. There are many online resources to learn Python. Once comfortable, explore AI concepts and tools.

Feel free to join AI communities, like those on Reddit or forums, for discussions and insights. Books like “Artificial Intelligence: A New Synthesis” by Nils J. Nilsson or “Artificial Intelligence: Foundations of Computational Agents” could be good reads.

Best wishes on your AI journey!

Count me crazy but, at 83, I have become interested in AI. The question is, “where to start?”

In addition to the A/S 400, I am an MS Early Adopter and my go-to OS has been Linux since 2002 (Fedora and now Ubuntu).

What is the best into to AI at this point? Anyone have a suggestion?

George

People need to analyze data and not make a master’s degree in how to use it! There is no AI open source data mining software, software being, commercial or open source features only generative INs that are hard to use due to one can’t guess proper hyperparameters. There are more possibilities than winning the toughest lotto in the world.

It’s all pre-90s when those base algorithms were developed. All you can get is pieces that u have to code all together by yourself, and then you have to code also what these pieces would do manually and the interconnections between them.

That’s why you need a master’s degree in coding, mathematics, statistics, and databases. There are also huge drawbacks to how this kind of software handles data inputs (no continuous workflows, not user-friendly, error rich, most of them don’t even take rows into account only columns (but data in rows are also equally relevant as in columns (cross-importance), some even winning on named 1st columns meta names and so on …), poor tuts, not exactly clear how data in the matrix are treated and so on… software is still crap and poorly coded and answers on all those questions one has to empirically finds out by himself just to find out how this isn’t supposed to work.

So in the end results are devastating useless waste of nerves and time. Try to get promised accuracy on non-linear datasets with various IN shapes near or above 70% for results to be of some use.

You can only dream getting it on more than 90% as posted all over the net. It’s all lie. I’m in this field for 1 year now and I can only say leave it be if u don’t need it professionally. AI not for end users.

@Antony

Thanks for sharing your thoughts with us, we will covering more commonly used AI technologies out there.