Artificial Intelligence #89

Hey, in this issue: state of AI Report 2021; a new language model, 3x bigger than GPT-3; deep neural networks for tabular data; a paper explained; building NLP models with retrieval; a new link to an old model could crack the mystery of deep learning; and more.

The sponsors of this issue are SeMI's Weaviate and Scale AI.

• State of AI Report 2021 is out
• [ArXiv] Deep neural networks and tabular data: a survey
• Colorizing Klimt’s vanished paintings with artificial intelligence and Klimt experts
• FLAN: more generalizable language models with instruction fine-tuning
• [Sponsored] Weaviate – an open-source, cloud-native, modular, vector search engine

If you work in ML, you might like Weaviate, an OSS vector search engine that allows you to search through your embeddings at scale in mere milliseconds. You can import your own embeddings or generate them using various state-of-the-art models. Get started with the Weaviate docs here or on Github.

• Building scalable, explainable, and adaptive NLP models with retrieval
• Microsoft and Nvidia introduced a natural language generation model that has 3x more parameters than GPT-3 (Microsoft, Nvidia)
• [Sponsored] Now On-Demand: TransformX Virtual Conference. Watch 60+ Sessions From the World's Top Experts on AI & ML
• [Paper Explained] Grokking: Generalization beyond Overfitting on small algorithmic datasets
• A new link to an old model could crack the mystery of deep learning

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Have a nice weekend! See you next week. — Andriy