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The best scientist of the face, Tomas Wolf’s hugs, says the current AI systems are less likely to make scientific discoveries, some leading laboratories hope.
Talker Fortune In the Viva technology in Paris, a large language models (LLS) indicate an effective ability to find answers to the questions, it is a short thing when the monster is seen as a more complex part of the real scientific progress.
“In science, asking questions, it is a difficult part, he does not find the answer,” he said. “The frequent response is very clear after questioning, but the tough part is really asking questions and the models are very bad to ask big questions.”
Wolf said he came to the conclusion after reading an anthropic CEO Dario amodani a widespread blog post Loving grace machines. Thus, Amodei has been accelerating the AI scientifically for several years in the world’s 21st century.
Wolf started to doubt the idealistic vision of Amodei, which inspires the piece first, but after the second reading.
“The EU intends to solve cancer and solve mental health problems – this is going to bring peace to the world, but then I realized that there is something very wrong about it, and I do not believe it.”
The problem for the worm is not a lack of knowledge, but the ability to challenge our existing knowledge. AI models are likely to predict the sustainability, for example, the next word in a sentence and today’s models are in imitation of man’s thinking and falls into the short part of any real original thought.
“Models are trying to predict only the most likely things.” “But in almost all discovery or art events, not the most likely artwork you want to see, but the most interesting.”
Deepmind’s Alphago defeated the world champions in 2016, using a stage of a stage in the AI history, Wolf claimed to invent such a complex game of a great game. In science, it is the equivalent of inventing the game This is to ask this really original questions.
The monster first offered this idea in a blog postmatch Einstein ai modelwas published earlier this year. “To create a Einstein in a data center, we simply do not need a system that knows all the answers, but we do not need a system that can ask anyone who does not want or unwilling.”
Instead, it is models that behave like “yes-men on servers” what we do
