Imbue’s Approach to AI
At Imbue, our primary focus is on building custom, reasoning AI agents. We believe that in order for AI to be truly effective, it must have the ability to reason. Reasoning allows agents to handle uncertainty and adapt to different situations, making them more versatile in the real world. Our goal is to develop AI agents that can make decisions and deal with complexities in a way that is comparable to human reasoning.
Training Models for Reasoning
To achieve our goal of building reasoning AI agents, we use large language models (LLMs) that are specifically optimized for reasoning. These models allow us to train agents that have a strong foundation in reasoning abilities. Reasoning is the core blocker to developing AI agents that work well, and by focusing on this aspect, we can ensure that our agents are capable of handling complex tasks.
The Power of Reasoning
Reasoning is crucial for AI agents because it allows them to handle uncertainty and adapt their approaches. In the real world, things are not always black and white, and having the ability to reason allows agents to navigate these uncertainties. Additionally, reasoning enables agents to gather new information, make decisions, and deal with complex problems that may arise. By imbuing our AI agents with reasoning capabilities, we empower them to be more effective and versatile.
Imbue’s Full Stack Approach
At Imbue, we take a full stack approach to AI development. This means that we focus on all aspects of the AI development process, from training foundation models to building robust tools and infrastructure. By taking this comprehensive approach, we ensure that our AI agents are built on a strong foundation and have the necessary tools and resources to function effectively.
Imbue’s Focus on Coding Agents
One of our primary focuses at Imbue is developing AI agents for everyday tasks, such as writing code and analyzing policies. We believe that coding is a key area where reasoning can be applied effectively, and we use coding as a test-bed for evaluating the effectiveness of our models. By developing agents that can code, we not only improve their reasoning abilities but also provide practical tools that can be used in various industries.
Unpacking the Black Box
One area where Imbue differentiates itself is in our focus on making models explain their reasoning and provide references. This focus on explainability is important for transparency and trust in AI systems. As AI becomes increasingly powerful, it becomes crucial to understand what is happening inside the “black box” of deep learning models. By unpacking this black box and making models explain their reasoning, we aim to improve user experience and build trust in AI systems.
Explainability and Trust
We believe that understanding what is happening inside deep learning models is essential for building trust in AI systems. By making models explain their reasoning and providing references, we can provide users with a better understanding of how AI systems work. This focus on explainability is not only important for building trust but also for improving the user experience. When users can truly understand what is going on with AI systems, they can have more confidence in using them.
Imbue’s Open Business Model
Imbue takes an open approach to building applications on our models. We believe that it is important to empower businesses and individuals to use our models in a way that best suits their needs. We are open to building applications directly on our models or enabling others to build on top of them. By taking this open approach, we aim to create a diverse ecosystem where different companies can provide different models for different needs.
Our vision at Imbue is to create a personalized, customizable AI ecosystem. We want to enable users to be in control of their own AI tools and have the ability to customize them to their specific needs. Just like personal computers revolutionized the way we use technology, we believe that democratizing AI and allowing users to have their own custom software will unlock vast potential and change the way we interact with AI.
Imbue’s Progress and Future Plans
In our first year since coming out of stealth, we have made significant progress in training models and experimenting with agents internally. We are continuously pushing the boundaries of reasoning models and striving to understand how these models work and how they can be used effectively. Our future plans involve further developing our reasoning models and expanding the applications for our AI agents. We are committed to building AI tools that are reliable, robust, and capable of helping users accomplish their goals.