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Symbolica hopes to head off the AI arms race by betting on symbolic models
In February, Demis Hassabis, the CEO of Google's DeepMind AI research lab, warned that throwing increasing amounts of compute at the types of AI
Symbolic AI solves tasks by defining symbol-manipulating rule sets dedicated to particular jobs, such as editing lines of text in word processor software. Morgan rebutted by saying that current training methods soon won’t be able to meet the needs of companies that wish to harness AI for their purposes, making any promising alternatives worth investing in. “Public perception around AI models is still very much that ”scale is all you need.’ Thinking symbolically is absolutely necessary to makes progress in the field — structured and explainable outputs with formal reasoning capabilities will be required to meet demands.”
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