How tokenized real world assets can help crypto investors beat volatility

You probably wont know them by name.

Researchers at Stanford’s Center for Research on Foundation Models (CRFM) have unveiled an artificial intelligence (AI) model that works much like the famous ChatGPT but cost them only $600 to train.The company has spent millions of dollars training them and making sure that they provided responses to human queries in the way another human would respond.

How tokenized real world assets can help crypto investors beat volatility

and used an Application Programming Interface (API) to use 175 human-written instruction/output pairs to generate more in the same style and format.But what if someone does not really care what the chatbot says and about whom and wants it to work without filters? There are Open AI’s user terms that prevent users from building competing AI and LLaMA access available only for researchers.The researchers go on to state that their process wasn’t really optimized and they could have gotten better results.

How tokenized real world assets can help crypto investors beat volatility

the language model has some capabilities that are equipped with but nowhere close to the levels that we have seen with ChatGPT.The researchers said that they hadn’t optimized their process and future models could be trained for lesser.

How tokenized real world assets can help crypto investors beat volatility

But researchers at Stanford seem to have done it at a modest budget that could allow AI companies to be spun out of garages.

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