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Acoustic Model Fusion for End-to-end Speech Recognition

Machine Learning Research at Apple

Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted its accuracy to a new level. Despite this simpler system architecture, fusing a separate LM, trained exclusively on text corpora, into the E2E system has proven to be beneficial.

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9 Careers You Could Go into With a Data Science Degree

Smart Data Collective

Working as a machine learning scientist, you would research new data approaches and algorithms that can be used in adaptive systems, utilizing supervised, unsupervised, and deep learning methods. Business Intelligence Developer. Applications Architect.

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Rad AI reduces real-time inference latency by 50% using Amazon SageMaker

AWS Machine Learning Blog

Let’s transition to exploring solutions and architectural strategies. Approaches to researcher productivity To translate our strategic planning into action, we developed approaches focused on refining our processes and system architectures. He has a passion for continuous innovation and using data to drive business outcomes.

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Build a dynamic, role-based AI agent using Amazon Bedrock inline agents

AWS Machine Learning Blog

To understand how this dynamic role-based functionality works under the hood, lets examine the following system architecture diagram. As shown in preceding architecture diagram, the system works as follows: The end-user logs in and is identified as either a manager or an employee.

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Embedded AI Integration with MATLAB and Simulink

Pickl AI

Simulink provides blocks specifically designed for AI functions, allowing you to incorporate Machine Learning or deep learning models seamlessly. Training : Train your model using MATLAB’s built-in functions or toolboxes like the Deep Learning Toolbox. Model Selection : Choose appropriate algorithms (e.g.,

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Google Research, 2022 & beyond: Robotics

Google Research AI blog

Further improvements are gained by utilizing a novel structured dynamical systems architecture and combining RL with trajectory optimization , supported by novel solvers. We improved the efficiency of RL approaches by incorporating prior information, including predictive information , adversarial motion priors , and guide policies.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

In this post, we describe our design and implementation of the solution, best practices, and the key components of the system architecture. Amazon Rekognition makes it easy to add image and video analysis into our applications, using proven, highly scalable, deep learning technology.

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