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Transforming Catalyst Research: Meet CatBERTa, A Transformer-Based AI Model Designed For Energy Prediction Using Textual Inputs Tanya Malhotra Artificial Intelligence Category – MarkTechPost

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​ Chemical catalyst research is a dynamic field where new and long-lasting solutions are always sought after. The foundation of contemporary industry, catalysts speed up chemical reactions without being consumed in the process, powering everything from the generation of greener energy to the creation of… Read More »Transforming Catalyst Research: Meet CatBERTa, A Transformer-Based AI Model Designed For Energy Prediction Using Textual Inputs Tanya Malhotra Artificial Intelligence Category – MarkTechPost

A novel computational fluid dynamics framework for turbulent flow research Google AI Google AI Blog

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​Posted by Shantanu Shahane, Software Engineer, and Matthias Ihme, Research Scientist, Athena Team Turbulence is ubiquitous in environmental and engineering fluid flows, and is encountered routinely in everyday life. A better understanding of these turbulent processes could provide valuable insights across a variety of research… Read More »A novel computational fluid dynamics framework for turbulent flow research Google AI Google AI Blog

Optimize equipment performance with historical data, Ray, and Amazon SageMaker Walt Mayfield AWS Machine Learning Blog

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​ Efficient control policies enable industrial companies to increase their profitability by maximizing productivity while reducing unscheduled downtime and energy consumption. Finding optimal control policies is a complex task because physical systems, such as chemical reactors and wind turbines, are often hard to model and… Read More »Optimize equipment performance with historical data, Ray, and Amazon SageMaker Walt Mayfield AWS Machine Learning Blog

Best practices and design patterns for building machine learning workflows with Amazon SageMaker Pipelines Pinak Panigrahi AWS Machine Learning Blog

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​ Amazon SageMaker Pipelines is a fully managed AWS service for building and orchestrating machine learning (ML) workflows. SageMaker Pipelines offers ML application developers the ability to orchestrate different steps of the ML workflow, including data loading, data transformation, training, tuning, and deployment. You can… Read More »Best practices and design patterns for building machine learning workflows with Amazon SageMaker Pipelines Pinak Panigrahi AWS Machine Learning Blog

Make ChatGPT See Again: This AI Approach Explores Link-Context Learning to Enable Multimodal Learning Ekrem Çetinkaya Artificial Intelligence Category – MarkTechPost

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​ Language models have revolutionized the way we communicate with computers by their ability to generate coherent and contextually relevant text. Large Language Models (LLMs) have been at the forefront of this progress, trained on massive amounts of text data to learn the patterns and… Read More »Make ChatGPT See Again: This AI Approach Explores Link-Context Learning to Enable Multimodal Learning Ekrem Çetinkaya Artificial Intelligence Category – MarkTechPost

Testing Spark locally with EmbeddedKafka: Streamlining Spark Streaming Tests  sailaja Spark By {Examples}

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​ While Spark is commonly associated with processing large batches of data through massive daily jobs, the reality is that data often enters our systems continuously. To process this data in batch mode, aggregation and processing delays are usually required. However, this can be inefficient… Read More »Testing Spark locally with EmbeddedKafka: Streamlining Spark Streaming Tests  sailaja Spark By {Examples}

Meet LLaSM: An End-to-End Trained Large Multi-Modal Speech-Language Model with Cross-Modal Conversational Abilities Capable of Following Speech-and-Language Instructions Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

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​ Speech carries more information than writing since it takes semantic and paralinguistic information like tone. Additionally, speaking is a more practical and organic approach for people to communicate with AI. Consequently, following speech-and-language guidelines while creating a general-purpose assistant is essential. However, most big… Read More »Meet LLaSM: An End-to-End Trained Large Multi-Modal Speech-Language Model with Cross-Modal Conversational Abilities Capable of Following Speech-and-Language Instructions Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

Google Research Explores: Can AI Feedback Replace Human Input for Effective Reinforcement Learning in Large Language Models? Janhavi Lande Artificial Intelligence Category – MarkTechPost

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​ Human feedback is essential to improve and optimize machine learning models. In recent years, reinforcement learning from human feedback (RLHF) has proven extremely effective in aligning large language models (LLMs) with human preferences, but a significant challenge lies in collecting high-quality human preference labels.… Read More »Google Research Explores: Can AI Feedback Replace Human Input for Effective Reinforcement Learning in Large Language Models? Janhavi Lande Artificial Intelligence Category – MarkTechPost