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Hex-LLM: A New LLM Serving Framework Designed for Efficiently Serving Open LLMs on Google Cloud TPUs Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” In the rapidly evolving world of artificial intelligence, large language models (LLMs) have become essential tools for a variety of applications, ranging from natural language understanding to content generation. While the capabilities of these models continue to expand, efficiently serving and deploying them remains… Read More »Hex-LLM: A New LLM Serving Framework Designed for Efficiently Serving Open LLMs on Google Cloud TPUs Asif Razzaq Artificial Intelligence Category – MarkTechPost

Evaluating the Planning Capabilities of Large Language Models: Feasibility, Optimality, and Generalizability in OpenAI’s o1 Model Tanya Malhotra Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” New developments in Large Language Models (LLMs) have shown how well these models perform sophisticated reasoning tasks like coding, language comprehension, and math problem-solving. However, there is less information about how effectively these models work in terms of planning, especially in situations where a… Read More »Evaluating the Planning Capabilities of Large Language Models: Feasibility, Optimality, and Generalizability in OpenAI’s o1 Model Tanya Malhotra Artificial Intelligence Category – MarkTechPost

Contrastive Localized Language-Image Pre-Training Apple Machine Learning Research

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​Contrastive Language-Image Pre-training (CLIP) has been a celebrated method for training vision encoders to generate image/text representations facilitating various applications. Recently, CLIP has been widely adopted as the vision backbone of multimodal large language models (MLLMs) to connect image inputs for language interactions. The success… Read More »Contrastive Localized Language-Image Pre-Training Apple Machine Learning Research

When is Multicalibration Post-Processing Necessary? Apple Machine Learning Research

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​Calibration is a well-studied property of predictors which guarantees meaningful uncertainty estimates. Multicalibration is a related notion — originating in algorithmic fairness — which requires predictors to be simultaneously calibrated over a potentially complex and overlapping collection of protected subpopulations (such as groups defined by… Read More »When is Multicalibration Post-Processing Necessary? Apple Machine Learning Research

On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization Apple Machine Learning Research

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​Reinforcement Learning from Human Feedback (RLHF) is an effective approach for aligning language models to human preferences. Central to RLHF is learning a reward function for scoring human preferences. Two main approaches for learning a reward model are 1) training an explicit reward model as… Read More »On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization Apple Machine Learning Research

Efficient Pre-training of Llama 3-like model architectures using torchtitan on Amazon SageMaker Roy Allela AWS Machine Learning Blog

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​[[{“value”:” This post is co-written with Less Wright and Wei Feng from Meta Pre-training large language models (LLMs) is the first step in developing powerful AI systems that can understand and generate human-like text. By exposing models to vast amounts of diverse data, pre-training lays the… Read More »Efficient Pre-training of Llama 3-like model architectures using torchtitan on Amazon SageMaker Roy Allela AWS Machine Learning Blog

Researchers at Stanford University Introduce Tutor CoPilot: A Human-AI Collaborative System that Significantly Improves Real-Time Tutoring Quality for Students Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Integrating Artificial Intelligence (AI) tools in education has shown great potential to enhance teaching methods and learning experiences, especially where access to experienced educators is limited. One prominent AI-based approach is using Language Models (LMs) to support tutors in real time. Such systems can… Read More »Researchers at Stanford University Introduce Tutor CoPilot: A Human-AI Collaborative System that Significantly Improves Real-Time Tutoring Quality for Students Asif Razzaq Artificial Intelligence Category – MarkTechPost

NVIDIA AI Summit Highlights Game-Changing Energy Efficiency and AI-Driven Innovation Brian Caulfield – Archives Page 1 | NVIDIA Blog

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​[[{“value”:” Accelerated computing is sustainable computing, Bob Pette, NVIDIA’s vice president and general manager of enterprise platforms, explained in a keynote at the NVIDIA AI Summit on Tuesday in Washington, D.C. NVIDIA’s accelerated computing isn’t just efficient. It’s critical to the next wave of industrial,… Read More »NVIDIA AI Summit Highlights Game-Changing Energy Efficiency and AI-Driven Innovation Brian Caulfield – Archives Page 1 | NVIDIA Blog

Time series forecasting with Amazon SageMaker AutoML Davide Gallitelli AWS Machine Learning Blog

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​[[{“value”:” Time series forecasting is a critical component in various industries for making informed decisions by predicting future values of time-dependent data. A time series is a sequence of data points recorded at regular time intervals, such as daily sales revenue, hourly temperature readings, or… Read More »Time series forecasting with Amazon SageMaker AutoML Davide Gallitelli AWS Machine Learning Blog