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Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration Apple Machine Learning Research

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​A recent line of work shows that notions of multigroup fairness imply surprisingly strong notions of omniprediction: loss minimization guarantees that apply not just for a specific loss function, but for any loss belonging to a large family of losses. While prior work has derived… Read More »Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration Apple Machine Learning Research

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding Apple Machine Learning Research

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​This paper was accepted at the UniReps Workshop at NeurIPS 2023. The landscape of publicly available vision foundation models (VFMs), such as CLIP and Segment Anything Model (SAM), is expanding rapidly. VFMs are endowed with distinct capabilities stemming from their pre-training objectives. For instance, CLIP… Read More »SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding Apple Machine Learning Research

Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs Apple Machine Learning Research

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​Recent work in Natural Language Processing and Computer Vision has been using textual information – e.g., entity names and descriptions – available in knowledge graphs to ground neural models to high-quality structured data. However, when it comes to non-English languages, the quantity and quality of… Read More »Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs Apple Machine Learning Research

What Algorithms can Transformers Learn? A Study in Length Generalization Apple Machine Learning Research

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​This paper was accepted at the MATH workshop at NeurIPS 2023. Large language models exhibit surprising emergent generalization properties, yet also struggle on many simple reasoning tasks such as arithmetic and parity. This raises the question of if and when Transformer models can learn the… Read More »What Algorithms can Transformers Learn? A Study in Length Generalization Apple Machine Learning Research

Understanding the Concept of GPT-4V(ision): The New Artificial Intelligence Trend Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​ OpenAI has been at the forefront of the latest advancements in AI, with its highly competent models like GPT and DALLE. When released, GPT-3 was a one-of-its-kind model with great language processing capabilities such as text summarization, sentence completion, and many others. The release… Read More »Understanding the Concept of GPT-4V(ision): The New Artificial Intelligence Trend Asif Razzaq Artificial Intelligence Category – MarkTechPost

This AI Research from MIT and Meta AI Unveils an Innovative and Affordable Controller for Advanced Real-Time In-Hand Object Reorientation in Robotics Adnan Hassan Artificial Intelligence Category – MarkTechPost

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​ Researchers from MIT and Meta AI have developed an object reorientation controller that can utilize a single depth camera to reorient diverse shapes of objects in real-time. The challenge addressed by this development is the need for a versatile and efficient object manipulation system… Read More »This AI Research from MIT and Meta AI Unveils an Innovative and Affordable Controller for Advanced Real-Time In-Hand Object Reorientation in Robotics Adnan Hassan Artificial Intelligence Category – MarkTechPost

Schedule Amazon SageMaker notebook jobs and manage multi-step notebook workflows using APIs Anchit Gupta AWS Machine Learning Blog

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​ Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. Amazon SageMaker notebook jobs allow data scientists to run their notebooks on demand or on a schedule with a few clicks in SageMaker… Read More »Schedule Amazon SageMaker notebook jobs and manage multi-step notebook workflows using APIs Anchit Gupta AWS Machine Learning Blog

Announcing new tools and capabilities to enable responsible AI innovation Peter Hallinan AWS Machine Learning Blog

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​ The rapid growth of generative AI brings promising new innovation, and at the same time raises new challenges. These challenges include some that were common before generative AI, such as bias and explainability, and new ones unique to foundation models (FMs), including hallucination and… Read More »Announcing new tools and capabilities to enable responsible AI innovation Peter Hallinan AWS Machine Learning Blog

Half-precision Inference Doubles On-Device Inference Performance noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog

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​ Posted by Marat Dukhan and Frank Barchard, Software Engineers CPUs deliver the widest reach for ML inference and remain the default target for TensorFlow Lite. Consequently, improving CPU inference performance is a top priority, and we are excited to announce that we doubled floating-point… Read More »Half-precision Inference Doubles On-Device Inference Performance noreply@blogger.com (TensorFlow Blog) The TensorFlow Blog

Introducing the AWS Generative AI Innovation Center’s Custom Model Program for Anthropic Claude Sri Elaprolu AWS Machine Learning Blog

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​ Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of… Read More »Introducing the AWS Generative AI Innovation Center’s Custom Model Program for Anthropic Claude Sri Elaprolu AWS Machine Learning Blog