LLM Integration
What are LLMs?
At its core, Large Language Models consists of a large neural network with multiple layers of self-attention mechanisms. During the training process, the model learns to predict the likelihood of a word given its surrounding context in a sentence. This enables it to understand and generate coherent text based on the patterns and structures it has observed in the training data.
When a user interacts with LLMs, they provide a prompt or a question. The model then processes the input by encoding it into a numerical representation. This encoding is fed into the neural network, which performs a series of computations to generate a response. The response is generated word by word, with each word being sampled based on the probabilities assigned by the model.
To make the responses more relevant and informative, LLMs benefit from a technique called "prompt engineering." By carefully crafting the initial prompt or providing system-level instructions, users can guide the model's behavior and specify the desired output. This helps in achieving more controlled and tailored responses.
LLMs are typically trained on a diverse range of topics, allowing it to provide information, engage in conversation, and assist with various tasks. However, it's important to note that while LLMs can produce impressive and coherent responses, it may also generate incorrect or nonsensical answers, often referred to as "hallucinations" . Users should exercise critical thinking and verify the information independently when needed.
Overall, LLMs represents a significant advancement in natural language processing and has the potential to assist users in generating human-like text and engaging in interactive conversations.
GPT is a large language model developed by OpenAI that uses a deep learning technique called the Transformer architecture. It is trained on a vast amount of text data from the internet, allowing it to generate human-like responses to a wide range of prompts and questions.
Viabl.ai LLM integration Build Tools can leverage the power of LLM at both design time and run time:
Viabl.ai LLM Design-time Build Tools
The following Build Tools can be used to accelerate development at design-time:
Viabl.ai LLM Runtime Build Tools
Viabl.ai enables the developer to leverage the powerof LLMs to extract and infer answers to Questions from a body of free text such as an email or an technical report. Cruicially, it also allows the developer to build the nexessary "guard rails" to minimise the impact of any "hallucinations" by adding decision logic to validate the responses before they are used to make decisions.
The following Build Tools leverage the power of LLM during decision inference (run-time):
