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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Businesses now have numerous options to efficiently train their deep learning and machine learning models without breaking the bank. AI accelerators cater to various scenarios, providing solutions that range from economical inference to robust training capabilities. Getting started is straightforward, thanks to an array of services designed for both development and deployment purposes. Custom-built ASICs known as Tensor Processing Units (TPUs) are specifically designed to train and run deep neural networks with enhanced efficiency. With these tools, organizations can develop and implement more powerful and precise models at a lower cost, achieving faster speeds and greater scalability. A diverse selection of NVIDIA GPUs is available to facilitate cost-effective inference or to enhance training capabilities, whether by scaling up or by expanding out. Furthermore, by utilizing RAPIDS and Spark alongside GPUs, users can execute deep learning tasks with remarkable efficiency. Google Cloud allows users to run GPU workloads while benefiting from top-tier storage, networking, and data analytics technologies that improve overall performance. Additionally, when initiating a VM instance on Compute Engine, users can leverage CPU platforms, which offer a variety of Intel and AMD processors to suit different computational needs. This comprehensive approach empowers businesses to harness the full potential of AI while managing costs effectively.

Description

Accelerate the building, training, and deployment of models at scale through a fully managed infrastructure that provides essential tools and streamlined workflows. Launch personalized AI and LLMs on any infrastructure in mere seconds, effortlessly scaling inference as required. Tackle your most intensive tasks with batch job scheduling, ensuring you only pay for what you use on a per-second basis. Reduce costs effectively by utilizing GPU resources, spot instances, and a built-in automatic failover mechanism. Simplify complex infrastructure configurations by deploying with just a single command using YAML. Adjust to demand by automatically increasing worker capacity during peak traffic periods and reducing it to zero when not in use. Release advanced models via persistent endpoints within a serverless architecture, maximizing resource efficiency. Keep a close eye on system performance and inference metrics in real-time, tracking aspects like worker numbers, GPU usage, latency, and throughput. Additionally, carry out A/B testing with ease by distributing traffic across various models for thorough evaluation, ensuring your deployments are continually optimized for performance.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform Yes 
Cloudbrink Yes 
Evoltsoft Yes 
Flywheel Yes 
Galileo Yes 
Gemma 2 No 
Google Cloud VMware Engine Yes 
Hostinger Horizons Yes 
Jupyter Notebook No 
Knovos Discovery Yes 
LangChain No 
Llama 3.1 No 
Mixtral 8x7B No 
MultiTV Yes 
Phonexa Yes 
Pinecone No 
PromptX Yes 
Rayven Yes 
UMH Yes 
Visual Studio Code No 

Integrations

Google Cloud Platform Yes 
Cloudbrink No 
Evoltsoft No 
Flywheel No 
Galileo No 
Gemma 2 Yes 
Google Cloud VMware Engine No 
Hostinger Horizons No 
Jupyter Notebook Yes 
Knovos Discovery No 
LangChain Yes 
Llama 3.1 Yes 
Mixtral 8x7B Yes 
MultiTV No 
Phonexa No 
Pinecone Yes 
PromptX No 
Rayven No 
UMH No 
Visual Studio Code Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

$100 + compute/month
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/ai-infrastructure

Vendor Details

Company Name

VESSL AI

Founded

2020

Country

United States

Website

vessl.ai/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Infrastructure-as-a-Service (IaaS)

Analytics / Reporting No 
Configuration Management No 
Data Migration No 
Data Security No 
Load Balancing No 
Log Access No 
Network Monitoring No 
Performance Monitoring No 
SLA Monitoring No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives