Database Q&A 2023-06-28
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Automorphic

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Language model and NLP improvements.
Generated by ChatGPT

Automorphic is a tool called Conduit that enables the infusion of knowledge into language models. It overcomes the limitations of prompt stuffing by allowing fine-tuning of language models, training adapters for behavior or knowledge, and combining them dynamically.

This tool facilitates rapid iteration on models by incorporating human-in-the-loop feedback and streamlining model deployment.Conduit improves language models by continuously updating them based on user feedback and manual labeling.

It ensures high performance and deployment efficiency by enabling quick loading and stacking of fine-tuned adapters. Compatibility with the OpenAI API allows users to seamlessly integrate Conduit into their existing codebase.The Automorphic Hub serves as a platform where publicly shared models trained and enhanced using Automorphic are made available for inference.

The hub provides access to these models, allowing users to leverage them for their own applications.Another tool offered by Automorphic is TREX, which converts unstructured data into a structured format of the user's choice, such as JSON, XML, YAML, or any other format defined by a regular expression or context-free grammar.

TREX offers a highly customizable alternative to OpenAI's functions.Aegis is a firewall tool provided by Automorphic to protect language models and users from adversarial attacks.

It defends against prompt injections, prompt and personal identifiable information (PII) leakage, and toxic language. Aegis continuously learns from usage to enhance its detection capabilities over time.

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Automorphic was manually vetted by our editorial team and was first featured on September 2nd 2023.
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Pros and Cons

Pros

Fine-tunes language models
Combines models dynamically
Allows rapid model iteration
Incorporates human feedback
Streamlined model deployment
Continuous model updates
Enables quick adapter loading
Stacks fine-tuned adapters
Publicly shared models hub
Converts unstructured data
Supports JSON, XML, YAML
Supports other formats via regex/context-free grammar
Detects adversarial attacks
Prevents PII leakage
Filters toxic language
Learns from usage
Protects against prompt injections
Adapts to new threats over time
Compatible with existing codebase
100% predictable output
User-customized structuring of unstructured data
Provides data protection
Automates data structuring
Shares enhanced models publicly
Generates valid json objects
Supports customized grammars

Cons

Requires manual feedback
Adapts slow to initial feedback
Complex setup for TREX
No multi-language support
Limited information on Aegis mechanism
No clarity on update frequency

Q&A

What is Automorphic?
What is Conduit and how does it improve language models?
How does Conduit enable quick loading and stacking of fine-tuned adapters?
Can Conduit be integrated easily into my already existing codebase?
What is the purpose of the Automorphic Hub?
Can I access models from other users on the Automorphic Hub?
What is TREX and what advantages does it offer over OpenAI's functions?
Can TREX convert unstructured data into JSON or XML?
What is Aegis and how does it protect language models and users?
Does Aegis have the capability to detect toxic language and PII leakage?
How does Aegis improve its detection capabilities over time?
What is meant by 'infusing knowledge into language models'?
How does Conduit incorporate human-in-the-loop feedback?
How can Automorphic update models based on user feedback or manual labelling?
How compatible is Automorphic with OpenAI API?
What formats can TREX convert the unstructured data into?
Is Automorphic a secure platform?
How does Aegis protect against adversarial attacks?
Can Automorphic overcome limitations of prompt stuffing?
How do language models and users benefit from Automorphic's continuous learning and updating features?

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