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Meet Prompt Diffusion: An AI Framework For Enabling In-Context Learning In Diffusion-Based Generative Models Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

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​ 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

Google I/O 2023: What’s new in TensorFlow and Keras? noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog

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​ 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

The ‘Finding Neurons in a Haystack’ Initiative at MIT, Harvard, and Northeastern University Employs Sparse Probing Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

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​ 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

Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data Apple Machine Learning Research

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​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

Generalization on the Unseen, Logic Reasoning and Degree Curriculum Apple Machine Learning Research

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​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

Operationalize ML models built in Amazon SageMaker Canvas to production using the Amazon SageMaker Model Registry Janisha Anand AWS Machine Learning Blog

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​ You can now register machine learning (ML) models built in Amazon SageMaker Canvas with a single click to the Amazon SageMaker Model Registry, enabling you to operationalize ML models in production. Canvas is a visual interface that enables business analysts to generate accurate ML… Read More »Operationalize ML models built in Amazon SageMaker Canvas to production using the Amazon SageMaker Model Registry Janisha Anand AWS Machine Learning Blog

Don’t Miss Out on the Ultimate Conversational AI Workshop Stefan Kojouharov Chatbots Life – Medium

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​ We are excited to announce our upcoming Conversational AI workshop, designed to help professionals like you learn how to design and develop chatbots, and gain certification in Conversational AI Design, NLU, or ChatGPT. This three-day workshop will feature top industry speakers in Conversational AI, Voice,… Read More »Don’t Miss Out on the Ultimate Conversational AI Workshop Stefan Kojouharov Chatbots Life – Medium

Amazon SageMaker with TensorBoard: An overview of a hosted TensorBoard experience Baichuan Sun AWS Machine Learning Blog

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​ Today, data scientists who are training deep learning models need to identify and remediate model training issues to meet accuracy targets for production deployment, and require a way to utilize standard tools for debugging model training. Among the data scientist community, TensorBoard is a… Read More »Amazon SageMaker with TensorBoard: An overview of a hosted TensorBoard experience Baichuan Sun AWS Machine Learning Blog