ChatGPT — A large language model AI Chatbot
ChatGPT (Chat Generative Pre-trained Transformer) — a large language model chatbot launched by OpenAI in November 2022. Large language models perform the task of predicting the next word in a series of words. ChatGPT answers complex questions conversationally. The language model can answer questions, and assist you with tasks such as composing emails, essays, and code.
It has been fine-tuned (an approach to transfer learning) using both supervised and reinforcement learning techniques. Reinforcement Learning with Human Feedback (RLHF) is an additional layer of training that uses human feedback to help ChatGPT learn the ability to follow directions and generate responses that are satisfactory to humans.
OpenAI was founded by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman, and its CEO is Sam Altman.
According to Stanford University:
“GPT-3 has 175 billion parameters and was trained on 570 gigabytes of text. For comparison, its predecessor, GPT-2, was over 100 times smaller at 1.5 billion parameters.
This increase in scale drastically changes the behavior of the model — GPT-3 is able to perform tasks it was not explicitly trained on, like translating sentences from English to French, with few to no training examples.
This behavior was mostly absent in GPT-2. Furthermore, for some tasks, GPT-3 outperforms models that were explicitly trained to solve those tasks, although in other tasks it falls short.”
LLMs predict the next word in a series of words in a sentence and the next sentences — kind of like autocomplete, but at a mind-bending scale.
This ability allows them to write paragraphs and entire pages of content.
But LLMs are limited in that they don’t always understand exactly what a human wants.
And that’s where ChatGPT improves on state of the art, with the aforementioned Reinforcement Learning with Human Feedback (RLHF) training.
How was ChatGPT Trained?
GPT-3.5 was trained on massive amounts of data about code and information from the internet, including sources like Reddit discussions, to help ChatGPT learn dialogue and attain a human style of responding.
ChatGPT was also trained using human feedback (a technique called Reinforcement Learning with Human Feedback) so that the AI learned what humans expected when they asked a question. Training the LLM this way is revolutionary because it goes beyond simply training the LLM to predict the next word.
Alternatives to ChatGPT:
BLOOM
BigScience
BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. As such, it is able to output coherent text in 46 languages and 13 programming languages that is hardly distinguishable from text written by humans. BLOOM can also be instructed to perform text tasks it hasn’t been explicitly trained for, by casting them as text generation tasks.
Bard
Bard is an upcoming AI chatbot from Google that can answer questions and write content like a human would. Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence and creativity of our large language models. It draws on information from the web to provide fresh, high-quality responses.
OPT — 175B
Meta
Meta AI is sharing Open Pretrained Transformer (OPT-175B), the first 175-billion-parameter language model to be made available to the broader AI research community. A language model is a probability distribution over sequences of words. It predicts the next word based on all the previous words. OPT, a language model with 175 billion parameters trained on publicly available data sets, to allow for more community engagement in understanding this foundational new technology.
