What is generative AI?
Generative AI is a branch of artificial intelligence that leverages machine learning models to create new content, designs, or predictions based on the patterns it recognizes from input data.
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Training a Model
Training a model involves teaching a machine learning algorithm to recognize patterns and improve predictions using a large dataset.
Input a Prompt
Inputting a prompt guides the language model by providing a starting point or specific instructions, shaping its output for more accurate and tailored responses.
Generated Content
AI-generated content is created using advanced algorithms and data analysis, producing contextually relevant and human-like writing efficiently and at scale.
Clarifai is helping companies explore and use Generative AI, a significant shift in what is possible with artificial intelligence
Harnessing Generative AI for Innovation
Clarifai is helping companies explore and utilize Generative AI, a significant shift in what is possible with artificial intelligence
Data Augmentation
Use Generative AI models to auto-generate synthetic datasets.
This is particularly useful when data is scarce, or companies must protect privacy. Synthetic data can be used for training other machine learning models.
Content Creation
Reduce the time and resources spent on content creation.
Create various types of engaging content, from written articles to music to graphic designs.
Personalization
Personalize content for individual users based on their preferences and behavior.
Improve the user experience and increase customer loyalty with personalized email content and recommendations.
Product Design
AI algorithms generate various design options based on certain prompts.
This allows for a much faster design process and enables companies to explore a wider range of potential designs.
How Clarifai helps
Start building with a broad repository of Foundation Models in language and vision
Clarifai's platform integrates the latest in AI, including models from OpenAI, Cohere and Anthropic. We also make available dozens of open-source foundation models like GPT-Neo, RoBERTa, BERT, Stable Diffusion, and we are always adding more.
Use Language Chains
LLMs in language chains streamline complex tasks, efficiently processing extensive information and enhancing functionality in data analysis, content generation, and natural language understanding.
- Stuffing Chains
- Map-Reduce Chain
- Refine Chain
Stuffing Chains
- The Stuffing Chain is a type of LLM chain that manages large volumes of information by segmenting documents and employing semantic search techniques to retrieve relevant information based on a query. The retrieved information is then 'stuffed' into the LLM context for generating a response.
- Although there may be increased complexity and potential loss of contextual coherency, the Stuffing Chain enables the consolidation of multiple documents and comprehensive information processing.
Map-Reduce Chain
- The Map-Reduce chain is an LLM chain that iterates over a list of documents, generating individual outputs for each document, and then aggregating these outputs for a final result. It excels in tasks that require parallel processing of documents.
- While challenges arise in output aggregation and potential redundancy, the Map-Reduce chain offers advantages such as scalability, parallel processing capabilities, and enhanced information extraction.
Refine Chain
- The Refine chain in LLMs uses iterative refinement, continuously improving accuracy by utilizing previous outputs as input for subsequent iterations. Although it may require more resources and longer processing times, this approach enhances the overall accuracy and quality of the final result.
- The Refine chain balances increased resource usage and longer processing times with continuous improvement and heightened accuracy in the final output, making it ideal for tasks requiring crucial result refinement and fine-tuning.
Find a Generative AI Module or
Create your own
Create applications right within the Clarifai platform for your own use cases. Build from one of our templates or start your own from scratch.
- PDF Data Import Module
- Synthetic Data Generation Module
- Compare LLMs Module
PDF Data Import Module
- LLMs face input length limitations when handling large documents. To overcome this, the document can be split into sections, creating numerical representations for each section in a 'vector database' that can be queried based on user input, effectively leveraging LLM capabilities with large documents.
- This process improves accuracy, prevents false generation of data, and enhances accessibility of information in large documents, enabling efficient utilization of LLMs for handling extensive textual content.
Synthetic Data Generation Module
- Large Language Models (LLMs) have the ability to generate synthetic data, which can mimic real-world datasets, making them valuable for testing and training purposes while preserving privacy.
- By comprehending the underlying patterns in the training data, LLMs can produce diverse data examples, contributing to enhanced model robustness and performance.
Compare LLMs Module
- Comparing LLMs is highly valuable as it empowers users to assess the strengths and weaknesses of each model for specific tasks, enabling informed decision-making when selecting the most suitable model.
- Additionally, LLM comparisons offer insights into performance and accuracy variations across different models, identifying areas that may require improvement. Furthermore, this tool facilitates benchmarking new models against existing ones, supporting the ongoing development and refinement of LLMs.
Unlock the Power of Creativity: Harnessing the Potential of Generative AI Tools
Unlock the Power of Creativity
Harnessing the Potential of Generative AI Tools
Vector Store
Vector search is a search engine technology that uses numerical representations of unstructured data to efficiently retrieve relevant text, images, and videos, surpassing traditional keyword search methods. Unlike keyword search, vector search can find similar content even without exact search term matches, enhancing its utility in searching for specific unstructured data.
Prompt library
Provide pre-defined input phrases or questions, serving as starting points that guide content generation. This results in more focused, contextual, and quality outputs aligned with the desired output themes. With a wide array of prompts, the AI can better generalize and adapt to user needs, leading to more robust and flexible applications.
Vector Store
Vector search is a search engine technology that uses numerical representations of unstructured data to efficiently retrieve relevant text, images, and videos, surpassing traditional keyword search methods. Unlike keyword search, vector search can find similar content even without exact search term matches, enhancing its utility in searching for specific unstructured data.
Prompt library
Provide pre-defined input phrases or questions, serving as starting points that guide content generation. This results in more focused, contextual, and quality outputs aligned with the desired output themes. With a wide array of prompts, the AI can better generalize and adapt to user needs, leading to more robust and flexible applications.
Together with our patented AI platform, Clarifai provides a solution including data preparation, model development, and operationalization so you build and deploy models at scale.
Resources
AI Glossary
For over 4 years now we’ve expand upon the terms to help continue to advance the knowledge of AI.
Developer Docs
Clarifai offers an end-to-end platform for the complete AI lifecycle. No matter the amount of content, you are second away of using AI.
IDC Report
Clarifai named a leader in IDC MarketScape Computer Vision Software Platform 2022 vendor assessment.
AI Glossary
For over 4 years now we’ve expand upon the terms to help continue to advance the knowledge of AI.
Developer Docs
Clarifai offers an end-to-end platform for the complete AI lifecycle. No matter the amount of content, you are second away of using AI.
IDC Report
Clarifai named a leader in IDC MarketScape Computer Vision Software Platform 2022 vendor assessment.