SFBigAnalytics_20200825: Bootstrapping meaning with embodied language learning
NLP models like GPT-3,word2vec, and transformers have been making huge leaps and bounds in machine learning and textual understanding. Cracks in these models are starting to appear thought and many research scientists are worried that we have reached the limits of what these models can do. While these models show seemingly amazing abilities to understand what we are saying, we will show that these models actually understanding nothing. They have no frame of reference to our world. While there are many debated pieces as to what scientist believe are missing to take AI to the next level, we will talk about one very key point: embodiment. AIs cannot understand things the way we do without having some way to interact with the world. Words like rough and heavy obtain their meaning from the physical world around us, not from parsing billions of lines of text. We will go through a tour of why grounding meaning is key and recent developments.
Speaker : Jason Toy ( CloudApp)
Jason Toy is startup generalist focused on technology, operations, and growth. Occasional angel investor and advisor. Currently COO at CloudApp, a remote communications platform. He has spent a lot of time working with machine learning and artificial intelligence in both production environments and research. Current area of research is embodied cognition and sensorimotor representations in the brain.