Toronto Chatbots

At Toronto Chatbots, we are excited to become the go to service for developing custom, highly functional chatbots in Toronto and beyond. We specialize in developing Custom GPTs and providing Amazon Q integration. Chatbots can be applied to a multitude of uses including content creation and data analysis as well as industries such as digital marketing, finance and legal. These chatbots are trained on your data so in effect, you are talking to your data which can save a great amount of time with impressive results. Common types of data that can be imported into your chatbot include PDFs, news articles, books, computer code, emails, chat logs, spreadsheets, URLs, images and many more. Reach out to us now for a free consultation.

Amazon Q

Amazon Q allows business owners to access companies' content and data which enables a fast and easy way to get relevant answers to important questions, solve problems and generate content. This is a great option for people who are already part of the Amazon ecosystem. Amazon Q can be easily and securely connected to commonly used systems and tools. Pricing for hosting is very reasonable.

Custom GPTs

Since its inception two years ago, ChatGPT has taken the world by storm. The application reached 100 million users in just two months. To create a custom GPT you need a Plus plan which is also reasonably priced. One of the common misconceptions is that GPT knows everything. This is not the case and which is why it is important to train it on your own data. Custom GPTs can be private or public.

How it Works

Custom GPTs and Amazon Q are custom trained large language models (LLM). LLMs are deep learning models that use neural networks to process large amounts of data. Neural networks mimic how the human brain works. One of the key innovations that enable LLMs is the self-attention mechanism which determines which parts of text are more important and where to focus the models attention. LLMs use a statistical process to determine the next word in a sequence. Another discovery that enables LLMs is word embeddings. Basically, each word is assigned an embedding which is a list of approximately one thousand numbers. Similar words will have similar embeddings.