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LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
As originally proposed by Google, [12] each CoT prompt included a few Q&A examples. This made it a few-shot prompting technique. However, according to researchers at Google and the University of Tokyo , simply appending the words "Let's think step-by-step", [ 23 ] has also proven effective, which makes CoT a zero-shot prompting technique.
Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)
One-shot learning is an object categorization problem, found mostly in computer vision. Whereas most machine learning -based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.
Frank Livoti Jr. said his father, Frank Livoti Sr., instantly recognized the significance of the intricate lighter and spent decades trying to locate its owner, whose initials “P.L. Shipley ...
China's Ministry of Commerce adds 28 U.S. entities to export control list to "safeguard national security and interests."
The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. [1]
Donald Trump said he will work to immediately reverse President Biden's action to protect 625 million acres from offshore oil and gas drilling.