Three months before ChatGPT debuted in November, Facebook’s parent company Meta released a similar chatbot. But unlike the phenomenon that ChatGPT instantly became, with more than a million users in its first 5 days, Meta’s BlenderBot was boring, said Meta’s chief artificial intelligence scientist, Yann LeCun. “The reason it was boring was because it was made safe”, LeCun said last week at a forum hosted by AI consulting company Collective[i]. He blamed the tepid public response on Meta being “overly careful about content moderation”, like directing the chatbot to change the subject if a user asked about religion. ChatGPT, on the other hand, will converse about the concept of falsehoods in the Quran, write a prayer for a rabbi to deliver to Congress and compare God to a flyswatter.
…The technology underlying ChatGPT isn’t necessarily better than what Google and Meta have developed, said Mark Riedl, professor of computing at Georgia Tech and an expert on machine learning. But OpenAI’s practice of releasing its language models for public use has given it a real advantage.
“For the last two years they’ve been using a crowd of humans to provide feedback to GPT”, said Riedl, such as giving a “thumbs down” for an inappropriate or unsatisfactory answer, a process called “reinforcement learning from human feedback.”
…In the past year or so, top AI researchers from Google have left to launch start-ups around large language models, including Character.AI, Cohere, Adept, Inflection.AI and Inworld AI, in addition to search start-ups using similar models to develop a chat interface, such as Neeva, run by former Google executive Sridhar Ramaswamy.
Character.AI founder Noam Shazeer, who helped invent the transformer and other core machine learning architecture, said the flywheel effect of user data has been invaluable. The first time he applied user feedback to Character.AI, which allows anyone to generate chatbots based on short descriptions of real people or imaginary figures, engagement rose by more than 30%.