codenlearn

This is exactly what I was working on last week. You have beaten me to it. Amazing work now time for me to find a new project.

Doesn't Language itself encode multimodal experiences? Let's take this case write when we write text, we have the skill and opportunity to encode the visual, tactile, and other sensory experiences into words. and the fact is llm's trained on massive text corpora are indirectly learning from human multimodal experiences translated into language. This might be less direct than firsthand sensory experience, but potentially more efficient by leveraging human-curated information. Text can describe simulations of physical environments. Models might learn physical dynamics through textual descriptions of physics, video game logs, scientific papers, etc. A sufficiently comprehensive text corpus might contain enough information to develop reasonable physical intuition without direct sensory experience.

As I'm typing this there is one reality that I'm understanding, the quality and completeness of the data fundamentally determines how well an AI system will work. and with just text this is hard to achieve and a multi modal experience is a must.

thank you for explaining in very simple terms where I could understand

the one thing that is handy and missing here is creating and pushing tags.

I wrote my first calculator app 11 years ago using shunting yard algorithm. It’s a wonderful algorithm, hats off to Dijsktra for coming up with a simple and elegant algorithm.

The jespen analysis is amazing, thank you for sharing it.

Thank you, this is an amazing resource.

Thank you for posting the link.

This behavior is happening in the default model (GPT-3.5). I edited the question as well.