Viso.ai

MARCH 7, 2023

Autoencoders are a powerful tool used in machine learning for feature extraction, data compression, and image reconstruction. Explanation and Definition of Autoencoders Autoencoders are neural networks that can learn to compress and reconstruct input data, such as images, using a hidden layer of neurons.

Computer Vision 52

Computer Vision Neural Network Convolutional Neural Networks Machine Learning 52

Mlearning.ai

JULY 3, 2023

Despite not having done any serious photography for some years now, I too was caught up with the rest of the world when image generative AI models such as DALL-E , Midjourney or Stable Diffusion were released. Hallucinating Images by Denoising Noise Stable Diffusion does not create images out of thin air (this is AI, not magic!).

Generative AI 52

Generative AI Auto-complete Auto-classification AI 52

Pickl AI

AUGUST 3, 2023

For example, mean squared error (MSE) is often used for regression problems, while cross-entropy loss is common for classification tasks. Iterative Training: The training process iterates over the entire training dataset multiple times (epochs). SOMs have been used in data clustering, data compression, and anomaly detection.

Deep Learning 52

Deep Learning Machine Learning Algorithm Neural Network 52

TensorFlow

MAY 2, 2023

In this blog, we dive deep into option (3) and demonstrate how to build a playlist recommendation system by implementing an end-to-end candidate retrieval workflow from scratch with Vertex AI. Figure 3: Figure 3: A reference architecture for two-tower training and deployment on Vertex AI. relevance, recall).

Neural Network 52

Neural Network AI AI Metadata 52

AssemblyAI

JUNE 27, 2023

Over the past decade, we've witnessed significant advancements in AI-powered audio generation techniques, including music and speech synthesis. This blog post is part of a series on generative AI. Until very recently, however, these improvements were still far from the outstanding progress observed in image and text generation.

Generative AI 298

Generative AI AI AI BERT 298

Mlearning.ai

JANUARY 17, 2024

Each section of this story comprises a discussion of the topic plus a curated list of resources, sometimes containing sites with more lists of resources: 20+: What is Generative AI? 95x: Generative AI history 600+: Key Technological Concepts 2,350+: Models & Mediums — Text, Image, Video, Sound, Code, etc.

Generative AI 98

Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

Lexalytics

APRIL 5, 2021

These were exciting times: the Dartmouth AI conference had been held in 1956, with its promise of solving AI through symbolic methods. Rosenblatt wasn’t the only one at that time with a learning procedure in the guise of a neural model: Bernard Widrow and Marcian Hoff introduced the Adeline [ 8 ], shown here. So it goes.)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52