Posted by Kendra Byrne, Senior Product Manager, and Jie Tan, Staff Research Scientist, Robotics at Google (This is Part 6 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Within our lifetimes,… Read More »Google Research, 2022 & beyond: Robotics Google AI Google AI Blog
Amazon Kendra is an intelligent search service powered by machine learning (ML). It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for. In some… Read More »Building AI chatbots using Amazon Lex and Amazon Kendra for filtering query results based on user context Rohit Satyanarayana AWS Machine Learning Blog
We’re excited to announce that Amazon Personalize now lets you measure how your personalized recommendations can help you achieve your business goals. After specifying the metrics that you want to track, you can identify which campaigns and recommenders are most impactful and understand the… Read More »Measure the Business Impact of Amazon Personalize Recommendations Anna Gruebler AWS Machine Learning Blog
Posted by Mathieu Guillame-Bert, Richard Stotz, Luiz GUStavo Martins Two years ago, we open sourced the experimental version of TensorFlow Decision Forests and Yggdrasil Decision Forests, a pair of libraries to train and use decision forest models such as Random Forests and Gradient Boosted… Read More »Updates: TensorFlow Decision Forests is production ready noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog
A deep learning model in its simplest form are layers of perceptrons connected in tandem. Without any activation functions, they are just matrix multiplications with limited power, regardless how many of them. Activation is the magic why neural network can be an approximation to… Read More »Using Activation Functions in Deep Learning Models Adrian Tam MachineLearningMastery.com
Everybody knows about ChatGPT. And everybody knows about ChatGPT’s propensity to “make up” facts and details when it needs to, a phenomenon that’s come to be called “hallucination.” And everyone has seen arguments that this will bring about the end of civilization as we… Read More »AI Hallucinations: A Provocation Mike Loukides AI & ML – Radar
RAID, or Redundant Array of Independent Disks, is a technology that helps protect against the loss of data in case one disk fails by providing redundancy through multiple disks. While there are many different types of RAID configurations available, it’s important to understand which… Read More »A Guide to Using RAID for Database Servers Seb Programmathically
This post is co-written by Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, DeepRacer SME at Accenture. With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to… Read More »Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK Zdenko Estok AWS Machine Learning Blog
This paper was accepted at the Workshops on Data Science with Human in the Loop at EMNLP 2022 Identifying and integrating missing facts is a crucial task for knowledge graph completion to ensure robustness towards downstream applications such as question answering. Adding new facts to… Read More »Improving Human Annotation Effectiveness for Fact Collection by Identifying the Most Relevant Answers Apple Machine Learning Research
Table of Contents Building a Dataset for Triplet Loss with Keras and TensorFlow Labeled Faces in the Wild Dataset Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Creating Our Configuration File Creating Our Data Pipeline Preprocessing Faces: Detection and Cropping… Read More »Building a Dataset for Triplet Loss with Keras and TensorFlow Shivam Chandhok PyImageSearch