Deep Learning and System Architecture

Acoustic Model Fusion for End-to-end Speech Recognition

Machine Learning Research at Apple

JANUARY 28, 2024

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.

System Architecture

System Architecture Deep Learning Deep Learning

9 Careers You Could Go into With a Data Science Degree

Smart Data Collective

JUNE 10, 2022

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.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

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

AWS Machine Learning Blog

NOVEMBER 26, 2024

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.

ML

ML ML AI AI

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

AWS Machine Learning Blog

MARCH 5, 2025

It requires checking many systems and teams, many of which might be failing, because theyre interdependent. Developers need to reason about the system architecture, form hypotheses, and follow the chain of components until they have located the one that is the culprit.

AWS

AWS AI AI Machine Learning

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

AWS Machine Learning Blog

FEBRUARY 13, 2025

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.

AI

AI AWS AI ML

Embedded AI Integration with MATLAB and Simulink

Pickl AI

NOVEMBER 12, 2024

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.,

AI

AI AI Deep Learning Deep Learning

Google Research, 2022 & beyond: Robotics

Google Research AI blog

FEBRUARY 14, 2023

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.

Algorithm

Algorithm System Architecture Deep Learning Deep Learning

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

AWS Machine Learning Blog

FEBRUARY 24, 2023

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.

ML

ML ML AWS Data Pipeline

Why AI Has Become the Top Developer Skill of 2023

ODSC - Open Data Science

JULY 18, 2023

The way Tabnine works is that it uses deep learning algorithms to provide intelligent code suggestions as developers write code. It’s not simple to autocomplete, as Tabnine is able to offer highly accurate and context-aware suggestions based on the current code context and patterns learned from a vast corpus of code.

AI

AI AI Deep Learning Deep Learning

Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud.

Clustering

Clustering AWS ML ML

A Guide to LLMOps: Large Language Model Operations

Heartbeat

JANUARY 9, 2024

Deployment : The adapted LLM is integrated into this stage's planned application or system architecture. This includes establishing the appropriate infrastructure, creating communication APIs or interfaces, and assuring compatibility with current systems. We pay our contributors, and we don't sell ads.

Natural Language Processing

Natural Language Processing Machine Learning Machine Learning Artificial Intelligence

Introducing Our New Punctuation Restoration and Truecasing Models

AssemblyAI

NOVEMBER 8, 2023

This aligns with the scaling laws observed in other areas of deep learning, such as Automatic Speech Recognition and Large Language Models research. New Models The development of our latest models for Punctuation Restoration and Truecasing marks a significant evolution from the previous system.

System Architecture

System Architecture Deep Learning Deep Learning AI

Data Intelligence empowers informed decisions

Pickl AI

DECEMBER 4, 2023

Machine Learning Engineer Designs and develops algorithms that enable computers to learn from and make predictions or decisions based on data. 10,00000 Deep learning, programming (e.g., Data Architect Designs and creates data systems and structures for optimal organisation and retrieval of information.

Data Analysis

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence

LLMOps: What It Is, Why It Matters, and How to Implement It

The MLOps Blog

MARCH 12, 2024

Observability tools: Use platforms that offer comprehensive observability into LLM performance, including functional logs (prompt-completion pairs) and operational metrics (system health, usage statistics). Caption : RAG system architecture.

Database

Database Machine Learning Machine Learning AI

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

Flipboard

JANUARY 15, 2025

System architecture for GNN-based network traffic prediction In this section, we propose a system architecture for enhancing operational safety within a complex network, such as the ones we discussed earlier. Specifically, we employ GraphStorm within an AWS environment to build, train, and deploy graph models.

AWS

AWS Machine Learning Machine Learning System Architecture

Data Science Current

Acoustic Model Fusion for End-to-end Speech Recognition

9 Careers You Could Go into With a Data Science Degree

Trending Sources

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

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

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

Embedded AI Integration with MATLAB and Simulink

Google Research, 2022 & beyond: Robotics

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

Why AI Has Become the Top Developer Skill of 2023

Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

A Guide to LLMOps: Large Language Model Operations

Introducing Our New Punctuation Restoration and Truecasing Models

Data Intelligence empowers informed decisions

LLMOps: What It Is, Why It Matters, and How to Implement It

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

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