What are machine learning modes? Explain each one in detail. Machine learning is an integral part of the world of artificial intelligence and has opened up new possibilities for businesses, industries, and society as a whole. Machine learning models are algorithms that enable computers… Read More »Machine Learning Models Narender Kumar Spark By {Examples}
Image generation has come a long way in the last year. The saga began with the release of Stable Diffusion, and its success has attracted the attention of researchers from different domains to advance it even further. It is now possible to generate photo-realistic… Read More »Divide, Train, and Generate: Patch Diffusion is an AI Approach to Make Training Diffusion Models Faster and More Data-Efficient Ekrem Çetinkaya Artificial Intelligence Category – MarkTechPost
Explain the difference between linear regression and polynomial regression. Regression analysis is a statistical tool that is used to examine the relationship between a dependent variable and one or more independent variables. Linear regression is one of the most widely used regression techniques that… Read More »Difference Between Linear Regression and Polynomial Regression Narender Kumar Spark By {Examples}
Explain the difference between Linear Regression and Logistic Regression. Regression analysis is a popular statistical technique that is used to model and analyze the relationship between one or more independent variables and a dependent variable. Regression models are widely used in various fields, including… Read More »Difference Between Linear Regression and Logistic Regression Narender Kumar Spark By {Examples}
State-of-the-art large language models (LLMs), including BERT, GPT-2, BART, T5, GPT-3, and GPT-4, have been developed as a result of recent advances in machine learning, notably in the area of natural language processing (NLP). These models have been effectively used for various tasks, including… Read More »Meet Prompt Diffusion: An AI Framework For Enabling In-Context Learning In Diffusion-Based Generative Models Aneesh Tickoo Artificial Intelligence Category – MarkTechPost
Posted by Lauren Usui and Joe Fernandez Artificial intelligence is a topic of kitchen table conversations around the world today, and as AI becomes more accessible for users and developers, we want to make it easier and more useful for everyone. This year at… Read More »AI and Machine Learning @ I/O Recap noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog
Posted by Ayush Jain, Carlos Araya, and Mani Varadarajan for the TensorFlow team Welcome to TensorFlow and Keras at Google I/O! The world of machine learning is changing, faster than ever. The rise of Large Language Models (LLMs) is sparking the imagination of developers… Read More »Google I/O 2023: What’s new in TensorFlow and Keras? noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog
It is common to think of neural networks as adaptable “feature extractors” that learn by progressively refining appropriate representations from initial raw inputs. So, the question arises: what characteristics are being represented, and in what way? To better understand how high-level, human-interpretable features are… Read More »The ‘Finding Neurons in a Haystack’ Initiative at MIT, Harvard, and Northeastern University Employs Sparse Probing Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost
Self-training has been shown to be helpful in addressing data scarcity for many domains, including vision, speech, and language. Specifically, self-training, or pseudo-labeling, labels unsupervised data and adds that to the training pool. In this work, we investigate and use pseudo-labeling for a recently proposed… Read More »Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data Apple Machine Learning Research
This paper considers the learning of logical (Boolean) functions with focus on the generalization on the unseen (GOTU) setting, a strong case of out-of-distribution generalization. This is motivated by the fact that the rich combinatorial nature of data in certain reasoning tasks (e.g., arithmetic/logic) makes… Read More »Generalization on the Unseen, Logic Reasoning and Degree Curriculum Apple Machine Learning Research