Pat, The difference between traditional programming and AI is that, in traditional programming approach, we manually set all parameters and actions by imaging all possibilities. In AI, the machine “learns”  parameters by finding the patterns in datasets (numerical data, images). Here the parameters refer to the coefficients or weights which determine a “model”. A Model is for us to make predictions after it has been well trained with datasets. It is common for non-AI professionals to think anything with automatic functions (such as automations, robots) is AI. Right now, we have formed many branches in AI such as Supervised Learning, Unsupervised Learning, Reinforcement Learning, but the core concept is always machine learning. Without machine learning for various models, this is NO concepts of AI. We need to make sure what we are doing.

The latest Commercial robots can leverage cloud to train their models, and then download the models to robots for inference. Those robots are AI enabled. I’m not sure if K12 schools afford the cost of working with cloud, but big companies such as Google may provide the solutions. You may want to do more research. In summary, the core concept of AI is machine learning.

Sent from my iPhone

> On Sep 22, 2019, at 2:13 PM, Pat Langley <patrick.w.langley@gmail.com> wrote:
>
> Frank,
>
>> First of all, if a robot does not have a learning process using datasets,
>> the robot is not related to AI! Some robots may be preloaded with
>> some pre-trained “models”, so that you can train the robots easily,
>> but you should read what models they have. If the whole document
>> does not talk about training or learning, although they use Python
>> programs, that robot has no value in teaching AI. The traditional
>> robots many schools have been using are NOT related to AI.
>
> Although machine learning is an important element of AI, one can
> definitely build AI systems without it and one can certainly teach
> many core ideas about AI without discussing learning. I encourage
> you to look at some classic AI textbooks to see what I mean.
>
> Best wishes,
> Pat Langley