LLM Fine Tuning
Are concerns about security and privacy keeping you from tapping the potential of Large Language Models (LLMs) to aggressively and painlessly maximize productivity? If so, we can fine tune one or more LLMs for your organization that is custom-built, inherently secure, and exclusively yours.
What is LLM fine tuning?
LLM fine-tuning leverages custom, private data to tailor an AI model specific to your needs, building on the strengths of an existing large language model using supervised, reinforced learning algorithms to improve LLM outputs for a particular set of use cases. At Atigro, we use generated and real-life training data to customize the core of the LLM for your specific workflows, such as construction logistics and document processing.
Fine tuning LLMs for private access and secure usage.
Businesses are sometimes hesitant to use LLMs due to concerns about data leaks and unauthorized access. They fear that:
- Company data sent to an external platform may be exposed if the provider’s systems are compromised
- Providers will have their sensitive information and use it for their own benefit
- The lack of strict usage control could allow unauthorized people to access their data
To protect against these threats, our system keeps your data completely and securely contained on a dedicated private server, making the risk of exposure nearly zero. We eliminate any possibility of data leakage and loss of control at all stages of the AI solutions and integration process.
- Our LLM engine does not depend on external updates or information sharing.
- Only those you authorize can access it.
- None of your data, inputs, or outputs are shared with the LLM providers.
Privately hosted LLMs also overcome these issues found with cloud-based LLMS:
- Bandwidth limitations
- Abrupt updates which change outcomes without warning
- Uncontrolled system update downtimes,
- Token limitations,
- Data size limitations
Fine tuning LLMs for maximum productivity.
Currently available LLMs, without fine tuning, have a limited ability to increase productivity because their answers are often factually incorrect or incomplete (hallucinations). The time spent vetting and correcting the output negates the time saved using AI. What’s more, the errors may go undetected and be untraceable after the fact.
If you have information from multiple sources that needs to be processed in unique ways, your employees will be hindered in their work if the burden is on them to retrieve, calculate, and process it.
Imagine how much more efficient your business will be when your talent doesn’t need to waste time:
- Validating responses
- Formatting output
- Checking for errors
- Checking for missing information
- Interpreting search results
- Searching databases
- Determining next steps
For businesses with unstructured systems and complex information, a custom LLM is the quickest possible path to increased productivity and cost-savings.
