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Released in 2020, AlphaFold leverages deep learning algorithms to accurately predict the 3D structure of proteins from their amino acid sequences, outperforming traditional methods by a significant margin.
We perform a k-nearestneighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. According to the information provided in the summary, GPT-3 from 2020 had 175B (175 billion) parameters, while GPT-2 from 2019 had 1.5B (1.5 Compared to GPT-2, how many more parameters does GPT-3 have?
For a given frame, our features are inspired by the 2020 Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ): we construct an image for each time step with the defensive players at the rows and offensive players at the columns. He is broadly interested in Deep Learning and NaturalLanguageProcessing.
Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-NearestNeighbor (k-NN) search in Amazon OpenSearch Service ), among others.
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