Task optimized gpt agents.

AI assistans are not (yet) magic buttons that do all the work while we can go and ask more salary from our bosses. As much as we'd love to believe that these digital marvels possess by default an otherworldly ability to effortlessly handle all our tasks, the reality is far from it. While AI assistants have undoubtedly made significant strides in last year, they still require a fair amount of tailoring to perform optimally for specific tasks.

Innofactor GPT Agents offer a unique approach to enhancing productivity by incorporating human involvement in the loop. Unlike traditional AI assistants, our platform recognizes the importance of deep task-specific tailoring and the need for human oversight. With our system, you can supercharge your individual tasks while still having the guidance and expertise of a human counterpart. Our promise is to provide AI assistants that are not only optimized for your specific job tasks but can also be tailored to your needs at the source code level. So, addition to generic AI assistants say hello to task-optimized, human-inclusive productivity boosters.

What is the real difference between generic AI assistants and Innofactor GPT Agents?

Usually generic AI assistants use the language model as a reasoning engine which talks to itself in order to create a plan what it should do and then executes each step in it's plan. That is very good approach in some cases but we have to remember that language models are creating their answers based on probabilities. If a generic AI assistant is asked to run a process that takes 5 individual step to run (e.g. fetch data from data base, use some tools to analyze the data, etc.), each step is executed correctly with some probability. For example let's say that each step is ran correctly with 90% success rate. Then if we count the planning phase as a one extra step the probability that the end result is correct is 90% ^ 6 = 53%. In other words, we get satisfying answer with the little more often than with the toss of the coin.

In building our AI assistant platform, we have come to realize that deep task-specific tailoring is crucial for its proper functioning. Unlike generic AI assistants, our platform focuses on optimizing the success rate for each individual step in a longer process. This is achieved by reducing the language model's capability for creating generic answers and instead channeling its power to follow a specific pre-determined information flow. In fact, we have even designed the platform to allow for customization at the source code level, enabling users to force the AI assistant to follow their desired information flow if necessary. So, even though one-size-fits-all solutions are powerful- with our platform, you can chat with task-optimized AI assistants that are tailored to your specific job needs. It's like having a personal assistant, but with the added benefit of being able to optimize it to your liking right down to the source code.

Lastly, while we are also developing a powerful generic assistant, we view it as just one tool in achieving optimal results. Our model involves utilizing this AI assistant as an orchestrator for process execution, while relying on task-optimized agents to handle the actual task-specific executions. You can think it as a highly capable middle manager that is assisting you with a working agents in your daily tasks while keeping you in the loop as a top dog.

Innofactor GPT Agents

Platform for deep tailored AI agents for spesific work tasks. Project in Innofactor Oy.