Getting up to Speed with AI – Developer Perspective

Been a minute since my last post but the AI firehose is now more manageable. The thing that I have learned with AI is that the toolset is diverse with multiple vendors and options. Plus these tools are being updated at a breakneck pace. with the new git version on a weekly basis.

Here are the toolset and vendors I have used and this is just the summary level.
– OpenAI
– Langchain
– LLMA index
– Pinecone
– Hugging Face
– Google CoLab
– Jupyter Notebooks
– mini Conda
– Git Co-Pilot

Will go into more detail in future posts that will be more frequent. The main lesson learned is when people post videos on Youtube with an accompanying git repo. The version of the libraries they use may be out of date by the time you access them. You have to understand the libraries and options. Copy, Paste, and run won’t cut it.

I will say this if you are using Python, notebooks are the best way to experiment with a new library and concept. And is awesome that co-pilot works in notebooks.