Training Value Functions via Classification for Scalable Deep Reinforcement Learning: Study by Google DeepMind Researchers and Others Mohammad Asjad Artificial Intelligence Category – MarkTechPost

[[{“value”:” Value functions are a core component of deep reinforcement learning (RL). Value functions, implemented with neural networks, undergo training via mean squared error regression to align with bootstrapped target values. However, upscaling value-based RL methods utilizing regression for extensive networks, like high-capacity Transformers, has… Read More »Training Value Functions via Classification for Scalable Deep Reinforcement Learning: Study by Google DeepMind Researchers and Others Mohammad Asjad Artificial Intelligence Category – MarkTechPost

This AI Paper from UCSD and ByteDance Proposes a Novel Machine Learning Framework for Filtering Image-Text Data by Leveraging Fine-Tuned Multimodal Language Models (MLMs) Adnan Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:” In artificial intelligence, the synergy between visual and textual data plays a pivotal role in evolving models capable of understanding and generating content that bridges the gap between these two modalities. Vision-Language Models (VLMs), which leverage vast datasets of paired images and text, are… Read More »This AI Paper from UCSD and ByteDance Proposes a Novel Machine Learning Framework for Filtering Image-Text Data by Leveraging Fine-Tuned Multimodal Language Models (MLMs) Adnan Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:”This paper was accepted at The 5th AAAI Workshop on Privacy-Preserving Artificial Intelligence. Personalized recommendations form an important part of today’s internet ecosystem, helping artists and creators to reach interested users, and helping users to discover new and engaging content. However, many users today are… Read More »Randomized Algorithms for Precise Measurement of Differentially-private, Personalized Apple Machine Learning Research

[[{“value”:” Developing large language models (LLMs) in artificial intelligence, such as OpenAI’s GPT series, marks a transformative era, bringing profound impacts across various sectors. These sophisticated models have become cornerstones for generating contextually rich and coherent text outputs, facilitating applications from automated content creation to… Read More »Enhancing Tool Usage in Large Language Models: The Path to Precision with Simulated Trial and Error Nikhil Artificial Intelligence Category – MarkTechPost

[[{“value”:” Large Language Models (LLMs) have increasingly been fine-tuned to align with user preferences and instructions across various generative tasks. This alignment is crucial for information retrieval systems to cater to diverse user search intentions and preferences effectively. Current retrieval systems often need to improve… Read More »INSTRUCTIR: A Novel Machine Learning Benchmark for Evaluating Instruction Following in Information Retrieval Mohammad Arshad Artificial Intelligence Category – MarkTechPost

The 96th Academy Awards are officially in the books and the ceremonies went without a hitch for the second year Continue reading The 96th Academy Awards are officially in the books and the ceremonies went without a hitch for the second yearContinue reading Read More Fun, Media… Read More »Grading our 2024 Oscars Machine Learning Predictions atakancetinsoy The Official Blog of BigML.com

[[{“value”:” The ability of Large Language Models (LLMs) to solve tasks related to Natural Language Processing (NLP) and Natural Language Generation (NLG) using few-shot reasoning has led to an increase in their popularity. However, more research is still needed on the subject of LLMs’ comprehension… Read More »This AI Paper from Microsoft Proposes a Machine Learning Benchmark to Compare Various Input Designs and Study the Structural Understanding Capabilities of LLMs on Tables Tanya Malhotra Artificial Intelligence Category – MarkTechPost

[[{“value”:” The surge in deploying Large Language Models (LLMs) such as GPT-3, OPT, and BLOOM across various digital interfaces, including chatbots and text summarization tools, has brought the critical need for optimizing their serving infrastructure to the forefront. LLMs are notorious for their huge sizes… Read More »DéjàVu: A Machine Learning System for Efficient and Fault-Tolerant LLM Serving System Adnan Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:” In artificial intelligence, large language models (LLMs) are a beacon of innovation, ushering in an era where autonomous agents can perform complex tasks with unprecedented precision. These models, including renowned examples like GPT-4, enable agents to plan and execute actions within diverse environments, from… Read More »Exploration-Based Trajectory Optimization: Harnessing Success and Failure for Enhanced Autonomous Agent Learning Sana Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:”Posted by Zilong Wang, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team People use tables every day to organize and interpret complex information in a structured, easily accessible format. Due to the ubiquity of such tables, reasoning over tabular data has long been… Read More »Chain-of-table: Evolving tables in the reasoning chain for table understanding Google AI Google AI Blog