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What is Taylor AI?

Creating open source language models requires a significant investment of both time and expertise. Taylor AI empowers your engineering team to focus on delivering true business value rather than getting entangled in complex libraries and the establishment of training frameworks. Partnering with external LLM providers can often lead to the exposure of sensitive organizational data, as many of these providers retain the right to retrain models with your information, introducing potential risks. With Taylor AI, you retain ownership and complete control over your models, avoiding these pitfalls. Move away from the traditional pay-per-token pricing structure; with Taylor AI, you only pay for the training of the model itself, granting you the freedom to deploy and interact with your AI models as often as you wish. New open-source models are introduced monthly, and Taylor AI keeps you informed about the latest releases, relieving you of that responsibility. By opting for Taylor AI, you ensure a competitive edge and access to state-of-the-art models for your training needs. As the owner of your model, you have the flexibility to deploy it in line with your organization's specific compliance and security standards, ensuring all requirements are met. This level of autonomy fosters greater innovation and adaptability within your projects, making it easier to pivot as necessary. Furthermore, it allows your team to focus their creative energies on developing groundbreaking solutions rather than managing operational complexities.

What is OpenVINO?

The Intel® Distribution of OpenVINO™ toolkit is an open-source resource for AI development that accelerates inference across a variety of Intel hardware. Designed to optimize AI workflows, this toolkit empowers developers to create sophisticated deep learning models for uses in computer vision, generative AI, and large language models. It comes with built-in model optimization features that ensure high throughput and low latency while reducing model size without compromising accuracy. OpenVINO™ stands out as an excellent option for developers looking to deploy AI solutions in multiple environments, from edge devices to cloud systems, thus promising both scalability and optimal performance on Intel architectures. Its adaptable design not only accommodates numerous AI applications but also enhances the overall efficiency of modern AI development projects. This flexibility makes it an essential tool for those aiming to advance their AI initiatives.

Media

Media

Integrations Supported

Caffe
Cameralyze
EndoAim
Falcon-40B
Falcon-7B
Hugging Face
Intel Geti
Intel Open Edge Platform
Keras
LaunchX
Llama 2
Nero AI
Nutanix Karbon Platform Services
ONNX
PaddlePaddle
PyTorch
StarCoder
TensorFlow

Integrations Supported

Caffe
Cameralyze
EndoAim
Falcon-40B
Falcon-7B
Hugging Face
Intel Geti
Intel Open Edge Platform
Keras
LaunchX
Llama 2
Nero AI
Nutanix Karbon Platform Services
ONNX
PaddlePaddle
PyTorch
StarCoder
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Taylor AI

Company Website

www.trytaylor.ai/

Company Facts

Organization Name

Intel

Date Founded

1968

Company Location

United States

Company Website

www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html

Categories and Features

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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