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Description
AWS Inferentia accelerators, engineered by AWS, aim to provide exceptional performance while minimizing costs for deep learning (DL) inference tasks. The initial generation of AWS Inferentia accelerators supports Amazon Elastic Compute Cloud (Amazon EC2) Inf1 instances, boasting up to 2.3 times greater throughput and a 70% reduction in cost per inference compared to similar GPU-based Amazon EC2 instances. Numerous companies, such as Airbnb, Snap, Sprinklr, Money Forward, and Amazon Alexa, have embraced Inf1 instances and experienced significant advantages in both performance and cost. Each first-generation Inferentia accelerator is equipped with 8 GB of DDR4 memory along with a substantial amount of on-chip memory. The subsequent Inferentia2 model enhances capabilities by providing 32 GB of HBM2e memory per accelerator, quadrupling the total memory and decoupling the memory bandwidth, which is ten times greater than its predecessor. This evolution in technology not only optimizes the processing power but also significantly improves the efficiency of deep learning applications across various sectors.
Description
Enhance the efficiency of your deep learning projects and reduce the time it takes to realize value through AI model training and inference. As technology continues to improve in areas like computation, algorithms, and data accessibility, more businesses are embracing deep learning to derive and expand insights in fields such as speech recognition, natural language processing, and image classification. This powerful technology is capable of analyzing text, images, audio, and video on a large scale, allowing for the generation of patterns used in recommendation systems, sentiment analysis, financial risk assessments, and anomaly detection. The significant computational resources needed to handle neural networks stem from their complexity, including multiple layers and substantial training data requirements. Additionally, organizations face challenges in demonstrating the effectiveness of deep learning initiatives that are executed in isolation, which can hinder broader adoption and integration. The shift towards more collaborative approaches may help mitigate these issues and enhance the overall impact of deep learning strategies within companies.
API Access
Has API
API Access
Has API
Integrations
AUSIS
AWS Parallel Computing Service
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
IBM Intelligent Video Analytics
WithoutBG
Integrations
AUSIS
AWS Parallel Computing Service
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
IBM Intelligent Video Analytics
WithoutBG
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/machine-learning/inferentia/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/deep-learning-platform
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Infrastructure-as-a-Service (IaaS)
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization