Last Updated on May 3, 2023 As neural networks become increasingly popular in the field of machine learning, it is important to understand the role that activation functions play in their implementation. In this article, you’ll explore the concept of activation functions that are… Read More »Activation Functions in PyTorch Muhammad Asad Iqbal Khan MachineLearningMastery.com
NVIDIA today introduced a wave of cutting-edge AI research that will enable developers and artists to bring their ideas to life — whether still or moving, in 2D or 3D, hyperrealistic or fantastical. Around 20 NVIDIA Research papers advancing generative AI and neural graphics… Read More »Latest NVIDIA Graphics Research Advances Generative AI’s Next Frontier Aaron Lefohn – Archives Page 1 | NVIDIA Blog
Posted by Jeremy Wortz, ML specialist, Google Cloud & Jordan Totten, Machine Learning Specialist Cross posted from Google Cloud AI & Machine Learning In a previous blog, we outlined three approaches for implementing recommendation systems on Google Cloud, including (1) a fully managed solution… Read More »Scaling deep retrieval with TensorFlow Recommenders and Vertex AI Matching Engine noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog
Machine learning (ML) helps organizations generate revenue, reduce costs, mitigate risk, drive efficiencies, and improve quality by optimizing core business functions across multiple business units such as marketing, manufacturing, operations, sales, finance, and customer service. With AWS ML, organizations can accelerate the value creation… Read More »Bring your own ML model into Amazon SageMaker Canvas and generate accurate predictions Aman Sharma AWS Machine Learning Blog
*=Equal Contributors There exists a correlation between geospatial activity temporal patterns and type of land use. A novel self-supervised approach is proposed to survey landscape based on activity time series, where time series signal is transformed to frequency domain and compressed into embeddings by a… Read More »Self-Supervised Temporal Analysis of Spatiotemporal Data Apple Machine Learning Research
Today, we announce the availability of sample notebooks that demonstrate question answering tasks using a Retrieval Augmented Generation (RAG)-based approach with large language models (LLMs) in Amazon SageMaker JumpStart. Text generation using RAG with LLMs enables you to generate domain-specific text outputs by supplying… Read More »Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart Xin Huang AWS Machine Learning Blog
Researchers from the University of California, Berkeley, have developed a system called FastrLap that uses machine learning to teach autonomous vehicles to drive aggressively at high speeds. The system is designed to help self-driving cars navigate a racetrack quickly and efficiently while taking risks… Read More »UC Berkeley Researchers Propose FastRLAP: A System for Learning High-Speed Driving via Deep RL (Reinforcement Learning) and Autonomous Practicing Niharika Singh Artificial Intelligence Category – MarkTechPost
Teaching LLM from scratch is challenging because of the extensive time required to understand why fine-tuned models fail; iteration cycles for fine-tuning on small datasets are typically measured in months. In contrast, the tuning iterations for a prompt take place in seconds, but after… Read More »Meet Lamini AI: A Revolutionary LLM Engine Empowering Developers to Train ChatGPT-level Language Models with Ease Tanushree Shenwai Artificial Intelligence Category – MarkTechPost
Stability AI has partnered with its AI research lab DeepFloyd to introduce the research version of its latest technology, called DeepFloyd IF. This text-to-image cascaded pixel diffusion model is designed to generate high-quality images from text inputs. The model is available on a non-commercial,… Read More »Stability AI Launches DeepFloyd IF: A High-Performance Text-to-Image Model with Advanced Integration Capabilities Niharika Singh Artificial Intelligence Category – MarkTechPost
The $group stage in MongoDB is used for grouping documents based on a specified key(s) in aggregation. The $group stage takes one or more fields as input and returns a new set of documents that have been grouped based on those fields. In this… Read More »MongoDB $group (aggregation) Usage with Examples AQSA Spark By {Examples}