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The Limits of Retrieval Augmentation, 8 AI Research Labs Worth Exploring, and Supercharging LLMs…

ODSC - Open Data Science

The Limits of Retrieval Augmentation, 8 AI Research Labs Worth Exploring, and Supercharging LLMs with LangChain Is RAG All You Need? Industry, Opinion, Career Advice What Dagster Believes About Data Platforms The beliefs that organizations adopt about the way their data platforms should function influence their outcomes.

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Marlos C. Machado, Adjunct Professor at the University of Alberta, Amii Fellow, CIFAR AI Chair – Interview Series

Unite.AI

He was a researcher at DeepMind from 2021 to 2023 and at Google Brain from 2019 to 2021, during which time he made major contributions to reinforcement learning, in particular the application of deep reinforcement learning to control Loon’s stratospheric balloons. The reason this matters is because it allows discovery of new behavior.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah. Thanks for having me.

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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. This approach greatly enhances their domain- or task-specific performance, and could open new worlds of capabilities for organizations spanning many industries. Find out in the guide below.

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74 Summaries of Machine Learning and NLP Research

Marek Rei

Below you will find short summaries of a number of different research papers published in the areas of Machine Learning and Natural Language Processing in the past couple of years (2017-2019). The model achieves new state-of-the-art on several VQA datasets. They cover a wide range of different topics, authors and venues. Here we go.

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Multi-Modal Methods: Image Captioning (From Translation to Attention)

ML Review

If you enjoy our work, then please feel free to follow, share and clap for our team. 2017)[ 51 ] Introduction to Image Captioning Suppose that we asked you to caption an image; that is to describe the image using a sentence. Thanks for reading! Note : Cropped from the full image which provides more failure examples. Source: Lu et al.

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Harness large language models in fake news detection

AWS Machine Learning Blog

Fake news, defined as news that conveys or incorporates false, fabricated, or deliberately misleading information, has been around as early as the emergence of the printing press. Early examples include advanced social bots and automated accounts that supercharge the initial stage of spreading fake news.