Remove 2020 Remove Artificial Intelligence Remove Supervised Learning
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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. Generative AI often operates in unsupervised or semi-supervised learning settings, generating new data points based on patterns learned from existing data.

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Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup

KDnuggets

Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020. It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different.

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Avery Smith’s 90-Day Blueprint: Fast-Track to Landing a Data Job

Towards AI

Louis-François Bouchard in What is Artificial Intelligence Introduction to self-supervised learning·4 min read·May 27, 2020 80 … Read the full blog for free on Medium. Author(s): Louis-François Bouchard Originally published on Towards AI. Join thousands of data leaders on the AI newsletter.

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How generative AI delivers value to insurance companies and their customers

IBM Journey to AI blog

Foundation models are pre-trained on unlabeled datasets and leverage self-supervised learning using neural network s. Foundation models are becoming an essential ingredient of new AI-based workflows, and IBM Watson® products have been using foundation models since 2020.

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Meet the winners of the Video Similarity Challenge!

DrivenData Labs

Self-supervision: As in the Image Similarity Challenge , all winning solutions used self-supervised learning and image augmentation (or models trained using these techniques) as the backbone of their solutions. His research interest is deep metric learning and computer vision.

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Foundation models: a guide

Snorkel AI

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning?

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Create and fine-tune sentence transformers for enhanced classification accuracy

AWS Machine Learning Blog

For this demonstration, we use a public Amazon product dataset called Amazon Product Dataset 2020 from a kaggle competition. It is a multi-task, multi-lingual, multi-locale, and multi-modal BERT-based encoder-only model trained on text and structured data input.