Advances in machine learning algorithms and the abundance of data available on the internet have contributed to the development of powerful AI engines that can mimic or imitate the cognitive functions of the human mind.
So how do AI engines work?
The detail is in the algorithms which have made it possible to train large, sophisticated models on large amounts of data. Machine learning is a branch of artificial intelligence that involves training computers to learn from data and make predictions or decisions without being explicitly programmed. One of the key components of machine learning is the algorithm, which is a set of instructions that the computer follows to learn from the data.
- Deep learning algorithms: These are a set of algorithms that are modelled after the structure of the human brain and are particularly well-suited for tasks such as image and speech recognition. They have been used to train large neural networks with billions of parameters, which have achieved state-of-the-art performance on a wide range of tasks.
- Transfer learning: This is a technique that allows a machine learning model trained on one task to be fine-tuned or adapted to a different but related task, using a smaller amount of data. This has made it possible to train models on large amounts of data and then fine-tune them for specific tasks with much less data.
- Generative models: Generative models: These are a set of algorithms that can learn to generate new data that is similar to the data they were trained on. They allow the models to train on vast amounts of data to generate similar content in the future.
- Ensemble methods: This is a method which uses multiple models to combine their outputs and make a better prediction, for example a Random Forest algorithm. These methods have been shown to achieve better performance than a single model by combining multiple models' predictions.
- Data augmentation: This is a technique that allows the artificial increase the size of the training dataset by applying various random transformations and distortions to the images in the dataset. This allows the model to learn from different variations of the same image, making the model more robust and less prone to overfitting.
So what is Chat-GPT?
ChatGPT is an interactive chatbot built on OpenAI’s GPT-3 large language model. You can ask it for inspiration for your college essay, get it to write poetry, create marketing content, write computer code, and much more. The list is seemingly endless. If you haven’t tried it then sign-up here, it’s free for now but this will almost certainly change.
What other AI Chat bots exist?
We’ve been checking out other emerging AI chatbots and here are some of the most interesting that we think you should play around with:
- Chai. Need a friend? Create your own personal bot with chai.ai.
- Character.ai is bringing to life the science-fiction dream of open-ended conversations and collaborations with computers.
- Maya is aimed at the business sector and is an AI human that helps to find answers within data faster, better, and more accurately.
- Gemsouls claims to allow you to meet, befriend, and create virtual characters.
- Quickchat is a technology to build AI Assistants that talk like a Human that you can add to any website.