ecosystem.Ai 2024 Roadmap
In this blog post, we'll explore our roadmap for the ecosystem.Ai platform in 2024-2025.
Introduction
We are excited to share our roadmap for the ecosystem.Ai platform in 2024-2025. Our goal is to continue to provide cutting-edge AI solutions to our customers and partners. We are committed to delivering new features and enhancements that will help you achieve your business goals and drive innovation in your industry.
Real-time Scoring
One of the key features we are working on is real-time scoring. This will allow you to get instant feedback on your models and make quick decisions based on the latest data. Real-time scoring will help you optimize your models and improve the accuracy of your predictions.
Dynamic Interactions
Recommenders that can adapt to user behavior in real-time are another area of focus for us. We are working on dynamic interactions that will allow you to personalize your recommendations based on user preferences and behavior. This will help you engage your users more effectively and drive better results.
Generative Models
We are also exploring the use of generative models to create new content and generate new ideas. Generative models can help you generate text, images, and other types of content that can be used in a variety of applications. We are excited to see how generative models can be used to drive innovation and creativity in your projects.
Focus Areas:
- Chat to SQL: We are working on a new feature that will allow you to convert chat conversations into SQL queries. This will help you extract valuable insights from your conversations and make data-driven decisions based on the information you gather. Chat to SQL will help you streamline your workflow and improve the efficiency of your data analysis process.
- Various Vector Stores: We are exploring the use of various vector stores to store and retrieve embeddings for your models. Vector stores can help you manage and query large amounts of data efficiently and improve the performance of your models. We are excited to see how vector stores can be used to enhance the capabilities of your models and drive better results.
- Fact-Injection for Real-time: We are working on a new feature that will allow you to inject facts into your models in real-time. This will help you update your models with the latest information and improve the accuracy of your predictions. Fact-injection for real-time will help you keep your models up-to-date and ensure that you are making decisions based on the most current data.