What is ChatGPT

OpenAI introduced a long-form question-answering AI called ChatGPT that answers complex questions conversationally.

It’s a revolutionary technology because it’s trained to learn what humans mean when they ask a question.

Many users are awed at its ability to provide human-quality responses, inspiring the feeling that it may eventually have the power to disrupt how humans interact with computers and change how information is retrieved.

What Is ChatGPT?

ChatGPT is a large language model chatbot developed by OpenAI based on GPT-3.5. It has a remarkable ability to interact in conversational dialogue form and provide responses that can appear surprisingly human.

Large language models perform the task of predicting the next word in a series of words.

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.

Who Built ChatGPT?

ChatGPT was created by San Francisco-based artificial intelligence company OpenAI. OpenAI Inc. is the non-profit parent company of the for-profit OpenAI LP.

OpenAI is famous for its well-known DALL·E, a deep-learning model that generates images from text instructions called prompts.

The CEO is Sam Altman, who previously was president of Y Combinator.

Microsoft is a partner and investor in the amount of $1 billion dollars. They jointly developed the Azure AI Platform.

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.

A March 2022 research paper titled Training Language Models to Follow Instructions with Human Feedback explains why this is a breakthrough approach:

• This work is motivated by our aim to increase the positive impact of large language models by training them to do what a given set of humans want them to do.
• By default, language models optimize the next word prediction objective, which is only a proxy for what we want these models to do.
• Our results indicate that our techniques hold promise for making language models more helpful, truthful, and harmless.
• Making language models bigger does not inherently make them better at following a user’s intent.
• For example, large language models can generate outputs that are untruthful, toxic, or simply not helpful to the user.
• In other words, these models are not aligned with their users.

The engineers who built ChatGPT hired contractors (called labelers) to rate the outputs of the two systems, GPT-3 and the new InstructGPT (a “sibling model” of ChatGPT).

Based on the ratings, the researchers came to the following conclusions:

Labelers significantly prefer InstructGPT outputs over outputs from GPT-3.

InstructGPT models show improvements in truthfulness over GPT-3.

InstructGPT shows small improvements in toxicity over GPT-3, but not bias.

The research paper concludes that the results for InstructGPT were positive. Still, it also noted that there was room for improvement.

Overall, our results indicate that fine-tuning large language models using human preferences significantly improves their behavior on a wide range of tasks, though much work remains to be done to improve their safety and reliability.

What sets ChatGPT apart from a simple chatbot is that it was specifically trained to understand the human intent in a question and provide helpful, truthful, and harmless answers.

Because of that training, ChatGPT may challenge certain questions and discard parts of the question that don’t make sense.

Another research paper related to ChatGPT shows how they trained the AI to predict what humans preferred.

The researchers noticed that the metrics used to rate the outputs of natural language processing AI resulted in machines that scored well on the metrics, but didn’t align with what humans expected.

The following is how the researchers explained the problem:

Many machine learning applications optimize simple metrics which are only rough proxies for what the designer intends. This can lead to problems, such as YouTube recommendations promoting click-bait.

So the solution they designed was to create an AI that could output answers optimized to what humans preferred.

To do that, they trained the AI using datasets of human comparisons between different answers so that the machine became better at predicting what humans judged to be satisfactory answers.

The paper shares that training was done by summarizing Reddit posts and also tested on summarizing news.

The research paper from February 2022 is called Learning to Summarize from Human Feedback.

The researchers write:

• In this work, we show that it is possible to significantly improve summary quality by training a model to optimize for human preferences.
• We collect a large, high-quality dataset of human comparisons between summaries, train a model to predict the human-preferred summary, and use that model as a reward function to fine-tune a summarization policy using reinforcement learning.

What are the Limitations of ChatGPT?

• Limitations on Toxic Response

ChatGPT is specifically programmed not to provide toxic or harmful responses. So it will avoid answering those kinds of questions.

• Quality of Answers Depends on Quality of Directions

An important limitation of ChatGPT is that the quality of the output depends on the quality of the input. In other words, expert directions (prompts) generate better answers.

Answers Are Not Always Correct

Another limitation is that because it is trained to provide answers that feel right to humans, the answers can trick humans that the output is correct.

Many users discovered that ChatGPT can provide incorrect answers, including some that are wildly incorrect.

The moderators at the coding Q&A website Stack Overflow may have discovered an unintended consequence of answers that feel right to humans.

Stack Overflow was flooded with user responses generated from ChatGPT that appeared to be correct, but a great many were wrong answers.

The thousands of answers overwhelmed the volunteer moderator team, prompting the administrators to enact a ban against any users who post answers generated from ChatGPT.

Will Language Models Replace Google Search?

Google itself has already created an AI chatbot that is called LaMDA. The performance of Google’s chatbot was so close to a human conversation that a Google engineer claimed that LaMDA was sentient.

Given how these large language models can answer so many questions, is it far-fetched that a company like OpenAI, Google, or Microsoft would one day replace traditional search with an AI chatbot?

Some on Twitter are already declaring that ChatGPT will be the next Google.

The scenario that a question-and-answer chatbot may one day replace Google is frightening to those who make a living as search marketing professionals.

It has sparked discussions in online search marketing communities, like the popular Facebook SEOSignals Lab where someone asked if searches might move away from search engines and towards chatbots.

Having tested ChatGPT, I have to agree that the fear of search being replaced with a chatbot is not unfounded.

The technology still has a long way to go, but it’s possible to envision a hybrid search and chatbot future for search.

But the current implementation of ChatGPT seems to be a tool that, at some point, will require the purchase of credits to use.

How Can ChatGPT Be Used?

ChatGPT can write code, poems, songs, and even short stories in the style of a specific author.

The expertise in following directions elevates ChatGPT from an information source to a tool that can be asked to accomplish a task.

This makes it useful for writing an essay on virtually any topic.

ChatGPT can function as a tool for generating outlines for articles or even entire novels.

It will provide a response for virtually any task that can be answered with written text.

Conclusion

As previously mentioned, ChatGPT is envisioned as a tool that the public will eventually have to pay to use.

Over a million users have registered to use ChatGPT within the first five days since it was opened to the public.