I'm looking at the AI timeline and I came across Neuro-Symbolic AI (being symbolic AI used in combination with deep learning) and Transformer AI (which I understand as neural networks that take context into account).
If I look at Wikipedia then I'll find that GTP-3 is a form of Neuro-Symbolic AI, but its name is clearly a giveaway for Transformer AI (Generative Pre-trained Transformer-3).
So I'm left wondering; what exactly is the different between these two?
There is a big difference between Neurosymbolic AI and transformer AI. Neurosymbolic AI is more rule-based and logical, while transformer AI is more creative and can learn from data.
Neurosymbolic AI tends to focus on using artificial neural networks to approximate symbolic reasoning, while transformer AI focuses on using transformer networks to learn language representations.
Neurosymbolic AI utilizes both symbolic and sub-symbolic representations of knowledge, while transformer AI primarily uses a symbolic representation. In addition, Neurosymbolic AI often incorporates techniques from artificial neural networks and machine learning, while transformer AI focuses more on learning from data through self-attention.
