In the world of technological advancements, AI is no longer a thing of science fiction movies, it’s now a reality that is shaping our world in ways we never thought possible. From self-driving cars to virtual personal assistants, AI is changing the way we live and work. And the best part? You don’t have to be a tech giant to take advantage of it!
Thanks to the power of the open source, you can now access a wide range of AI tools, libraries, and frameworks without breaking the bank. Open-source AI solutions are not only cost-effective, but they also offer a level of flexibility and customization that proprietary options simply can’t match. And let’s not forget the community aspect, where developers from all over the world contribute to making AI solutions better and more accessible. So, whether you’re a tech enthusiast, a startup founder, or a seasoned developer, there’s never been a better time to dive into the world of AI and open-source AI solutions.
Image Source: here
Types of AI
When it comes to AI, there are two main types: extractive and generative. Extractive AI is all about extracting information from data. This is the type of AI that powers search engines, sentiment analysis, and text summarization. It’s all about taking existing data and making sense of it. It’s like mining for gold, but instead of digging through dirt, you’re digging through data.
Both extractive and generative AI have their own set of strengths and use cases. Extractive AI is great for understanding and making sense of large amounts of data, while generative AI is great for creating new content and generating new ideas. They are both important and powerful tools in the AI toolbox, and both are essential in the advancement of AI.
| Extractive AI | Generative AI |
| Extractive AI is all about extracting information from data. | Generative AI generates new information, rather than just extracting it from existing data. |
| Extractive AI is used for tasks such as search engines, sentiment analysis, text summarization, etc. | Generative AI is used for tasks such as text generation, image generation, language translation, etc. |
| Extractive AI can be thought of as “mining for gold” in data. | Generative AI can be thought of as a “goldsmith” creating something new from raw materials. |
| Extractive AI is great for understanding and making sense of large amounts of data. | Generative AI is great for creating new content and generating new ideas. |
Read our detailed article on extractive AI vs Generative AI here.
Open source solutions
Open-source AI is like the wild west of AI development, it’s a place where developers and researchers come together and create something truly amazing. With open-source AI, developers have access to a wide range of tools, libraries, and frameworks that they can use to build their own AI models. They can also contribute to the community by sharing their work and making it available for others to use.
Open-source AI also enables collaboration and sharing of knowledge, which is crucial for the development of generative AI models. With a community of developers working together, the development of generative AI models becomes more efficient, and the models themselves become more accurate and sophisticated but with a condition that the workflow of the collaboration goes as intended.
Pluaris: Extractive AI
Pluaris is an AI platform that specializes in extractive AI using NLP techniques, it is highly accurate and efficient, making it a powerful tool for extracting insights from textual data, and a great example of how open-source AI can be used to extract insights from data, making it easier for developers and organizations to make sense of unstructured text data.
- Pluaris is a platform that specializes in extractive AI.
- It uses natural language processing (NLP) techniques to extract insights and knowledge from unstructured textual data.
- It can be used to extract entities, concepts, relationships, and sentiments from text data, making it ideal for tasks such as text summarization, sentiment analysis, and information retrieval.
- Pluaris is built on top of state-of-the-art NLP models, making it highly accurate and efficient.
- The platform is also highly customizable and can be fine-tuned for specific use cases, such as industry-specific language or domain-specific terminology.
- It is a perfect tool for organizations that deal with a large amount of unstructured text data and want to extract insights from it.
Image source: here
Pluaris works on end-to-end problem solving and so you can not only understand your data in a better way, you can share and collaborate with your team on the same.
Just imagine the countless use cases that a tool like Pluaris has. It can fit into any work process that involves dealing with data. Any professional setting that is under the load of working with a high amount of data on a day-to-day basis will find Pluaris to be a sigh of relief.
CONCLUSION
Each use case of AI can be solved using multiple AI technologies. It’s about finding the right type of AI and methods to get the best fitting output. Pluaris is an extractive AI solution that mainly focuses on B2B use cases. It can fit various industry use cases and learn industry-specific resources to extract key information from them. Know more about the tool and the use cases here.
