“We believe LaMDA’s natural conversation capabilities have the potential to make information and computing radically more accessible and easier to use.” (From 2021)
made T-NLG, and OpenAI made GPT-3. Engineers often assess these models by the number of parameters, a measurement of connections between artificial neurons in a deep learning system. BERT included hundreds of millions of parameters, and GPT-3 has 175 billion. In January, Google released a 1-trillion-parameter language model. At Google’s I/O event, Raghavan called MUM 1,000 times more powerful than BERT based on the number of parameters.
Such a model doesn’t exist. In fact the authors say it may require the creation of artificial general intelligence or advances in fields like information retrieval and machine learning. Among other things, they want the new approach to supply authoritative answers from a diversity of perspectives, clearly reveal its sources, and operate without bias.
Blumenthal, who has been consulting for businesses on search strategies for 20 years, notes that Google search results have evolved from a list of links served up by PageRank to include ads, knowledge panels, maps, videos, andThat shift has led to the rise of what some call zero-click searches, instances where people no longer click through to a website to finish a web search. This gives Google the ability to capture ad revenue without users leaving Google to visit the rest of the web.
, a startup based in Birmingham, Alabama, uses GPT-3 to, among other things, generate SEO metatags for websites. CEO Shegun Otulana says the company doesn't see Google's recent moves “as a threat, but as further progress for the whole AI space. It confirms we are moving in the right direction.”
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