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No Pricing

February 3, 2024
Features
Self-Improving Models
Fast Loading and Stacking of Fine-Tuned Adapters
Best For
Data Scientist
Research Scientist
AI Developer
Use Cases
Model Security
Public Model Sharing

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What is Automorphic?

Automorphic is a powerful tool for enhancing language models. It enables users to infuse knowledge into models with just 10 samples, allowing for improved model performance. The tool also provides self-improving models, fast loading and stacking of fine-tuned adapters, and compatibility with the OpenAI API. Additionally, Automorphic includes a firewall feature called Aegis, which enhances model security by detecting prompt injections, prompt and PII leakage, toxic language, and more. Overall, Automorphic works by offering a suite of solutions to enhance and secure language models, making it a valuable tool for AI developers and researchers.

Automorphic Features

  • Infuse Knowledge with Minimal Samples

    Enhance language models by infusing knowledge with just 10 samples.

  • Self-Improving Models

    Continuously improve language models with self-improvement capabilities.

  • Fast Loading and Stacking of Fine-Tuned Adapters

    Easily load and stack fine-tuned adapters to quickly enhance language models.

  • Openai API Compatibility

    Seamlessly integrate with the popular OpenAI API for enhanced functionality.

  • Automorphic Hub for Publicly Shared Models

    Collaborate and share language models with the AI community through the Automorphic Hub.

Automorphic Use Cases

  • Language Model Enhancement

    Automorphic can be used to infuse knowledge into language models with just 10 samples, improving model performance and compatibility with the OpenAI API.

  • Model Security

    The Aegis firewall feature in Automorphic helps detect and prevent prompt injections, prompt and PII leakage, and toxic language, enhancing the security of language models.

  • Public Model Sharing

    With the Automorphic Hub, users can share language models publicly, facilitating collaborative model development and knowledge sharing within the AI community.

Related Tasks

  • Knowledge Infusion

    Infusing knowledge into language models using minimal samples.

  • Model Improvement

    Continuously improving language models through self-improvement capabilities.

  • Adapter Loading and Stacking

    Loading and stacking fine-tuned adapters for faster model customization.

  • API Integration

    Ensuring compatibility with the OpenAI API for seamless integration.

  • Prompt Detection

    Detecting and preventing prompt injections to ensure model accuracy.

  • PII Leakage Detection

    Identifying and preventing the leakage of personally identifiable information (PII) in model outputs.

  • Toxic Language Filtering

    Detecting and filtering out toxic language to maintain model safety.

  • Public Model Sharing

    Sharing language models with the community through the Automorphic Hub.

  • Model Security Enhancement

    Enhancing the security of language models through the Aegis firewall feature.

  • Collaborative Model Development

    Facilitating collaboration and knowledge sharing within the AI community through the Automorphic Hub.

  • AI Engineer

    Utilizes Automorphic to enhance and fine-tune language models for various applications.

  • Data Scientist

    Uses Automorphic to analyze and improve the performance of language models in data-driven projects.

  • Research Scientist

    Incorporates Automorphic to enhance language models and conduct experiments for research purposes.

  • AI Developer

    Develops and deploys language models using Automorphic for various AI applications.

  • Natural Language Processing NLP Engineer

    Leverages Automorphic to improve the understanding and generation of natural language by models.

  • Machine Learning Engineer

    Utilizes Automorphic to enhance language models' performance and optimize their functionality.

  • Content Creator

    Utilizes Automorphic's language generation capabilities to automate and enhance the process of content creation.

  • AI Consultant

    Advises clients on leveraging Automorphic to enhance their language models and improve AI-powered solutions.

  • Ethical AI Researcher

    Explores and evaluates the ethical implications of language models enhanced by tools like Automorphic.

  • AI Product Manager

    Oversees the integration of Automorphic in language models to enhance their performance and align them with user needs and goals.

Automorphic FAQs

What are the key features of Automorphic?

- Automorphic offers features such as infusing knowledge into language models with minimal samples, self-improving models, fast loading and stacking of fine-tuned adapters, OpenAI API compatibility, and an Automorphic Hub for publicly shared models.

How does Automorphic enhance language models?

- Automorphic enhances language models by allowing the infusion of knowledge with just 10 samples, enabling self-improvement, and providing fast loading and stacking of fine-tuned adapters.

What is the Aegis feature in Automorphic?

- Aegis is a firewall for models provided by Automorphic, which can detect prompt injections, prompt and PII leakage, toxic language, and more, enhancing the security of language models.

Can Automorphic be used for public model sharing?

- Yes, Automorphic provides an Automorphic Hub for publicly shared models, allowing for collaborative model development and knowledge sharing within the AI community.

Is Automorphic compatible with the OpenAI API?

- Yes, Automorphic is compatible with the OpenAI API, enabling seamless integration with this popular AI platform.

How does Automorphic ensure model security?

- Automorphic ensures model security through its Aegis feature, which can detect and prevent prompt injections, prompt and PII leakage, and toxic language, thereby enhancing the security of language models.

What are the benefits of using Automorphic for language models?

- The benefits of using Automorphic include the ability to enhance language models with minimal samples, improve model performance, ensure model security, and facilitate collaborative model sharing through the Automorphic Hub.

Can Automorphic be used for fine-tuning language models?

- Yes, Automorphic supports fast loading and stacking of fine-tuned adapters, allowing for efficient fine-tuning of language models.

Is Automorphic suitable for AI developers and researchers?

- Yes, Automorphic is designed to cater to the needs of AI developers and researchers by providing tools for model enhancement, security, and collaborative sharing.

Is Automorphic currently under review or flagged for any issues?

- Yes, there are indications that Automorphic is currently under review due to concerns about its practices. It is advisable to exercise caution when using this tool until the review is concluded.

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