What is ChatGPT And How Can You Use It?

This is what ChatGPT is and why it may be the most important tool since modern search engines

ChatGPT, a long-form question-answering AI from OpenAI, is capable of conversing and resolving challenging queries.

Its ability to train itself to understand what questions from people mean makes it a groundbreaking piece of technology.

Many users are in awe of its capacity to deliver responses that are on par with those of humans, giving rise to the notion that it may one day have the ability to transform how people interact with computers and how information is found.

What Is ChatGPT?

On the basis of GPT-3.5, OpenAI created the big language model chatbot known as ChatGPT. It is remarkably capable of engaging in conversational conversations and responding in a way that sometimes seems shockingly human.

Predicting the following word in a string of words is a task carried out by large language models.

ChatGPT learns to obey instructions and produces responses that are acceptable to humans using Reinforcement Learning with Human Feedback (RLHF), an additional training layer.

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.

Large Language Models

ChatGPT is a large language model (LLM). Large Language Models (LLMs) are trained with massive amounts of data to accurately predict what word comes next in a sentence.

It was discovered that increasing the amount of data increased the ability of the language models to do more.

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.”

Similar to autocomplete, but on a mind-boggling size, LLMs predict the next word in a string of words in a sentence as well as the following sentences.

They are able to produce paragraphs and full pages of text thanks to this skill.

But LLMs have a drawback in that they frequently fail to comprehend precisely what a person wants.

And with the aforementioned Reinforcement Learning with Human Feedback (RLHF) training, ChatGPT advances the state of the art in this area.

How Was ChatGPT Trained?

To assist ChatGPT learn dialogue and develop a human manner of response, GPT-3.5 was trained on enormous volumes of code-related data and knowledge from the internet, including sources like Reddit debates.

In order to teach the AI what people anticipate when they ask a question, Reinforcement Learning with Human Feedback was also used to train ChatGPT. This method of training the LLM is novel since it goes beyond only teaching it to anticipate 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.

As a result of that instruction, ChatGPT may challenge particular questions and ignore any unclear portions of the inquiry.

Another study pertaining to ChatGPT demonstrates how they programmed the AI to anticipate human preferences.

The researchers discovered that the metrics used to evaluate the outputs of natural language processing AI produced machines that performed well on the metrics but didn’t match what people would have anticipated.

The researchers provided the following explanation of the issue:

“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.”

The idea they came up with was to develop an AI that could produce replies that were tailored to human preferences.

In order to achieve this, they trained the AI utilising datasets of human comparisons of various replies in order to improve the machine’s prediction of what humans would deem 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 drawback is that because it is programmed to give responses that feel natural to people, the answers may lead people to believe that the output is accurate.

Many users observed that ChatGPT sometimes gives false information, including those that are radically false.

It’s possible that responses that seem reasonable to people have an unintended effect, as was observed by the moderators at the coding Q&A website Stack Overflow.

Stack Overflow was overwhelmed with user responses coming from ChatGPT that seemed to be the right answers, but there were actually a lot of them.

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.

The flood of ChatGPT answers resulted in a post entitled: Temporary policy: ChatGPT is banned:

“This is a temporary policy intended to slow down the influx of answers and other content created with ChatGPT.

…The primary problem is that while the answers which ChatGPT produces have a high rate of being incorrect, they typically “look like” they “might” be good…”

The experience of Stack Overflow moderators with wrong ChatGPT answers that look right is something that OpenAI, the makers of ChatGPT, are aware of and warned about in their announcement of the new technology.

OpenAI Explains Limitations of ChatGPT

The OpenAI announcement offered this caveat:

“ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers.

Fixing this issue is challenging, as:

(1) during RL training, there’s currently no source of truth;

(2) training the model to be more cautious causes it to decline questions that it can answer correctly; and

(3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows.”

Is ChatGPT Free To Use?

Currently, during the “research preview” period, ChatGPT usage is free.

Users can currently test out the chatbot and give feedback on the responses so that the AI can improve at responding to inquiries and learn from its errors.

According to the official statement, OpenAI is happy to hear input regarding the errors:

“While we’ve made efforts to make the model refuse inappropriate requests, it will sometimes respond to harmful instructions or exhibit biased behavior.

We’re using the Moderation API to warn or block certain types of unsafe content, but we expect it to have some false negatives and positives for now.

We’re eager to collect user feedback to aid our ongoing work to improve this system.”

There is currently a contest with a prize of $500 in ChatGPT credits to encourage the public to rate the responses.

“Users are encouraged to provide feedback on problematic model outputs through the UI, as well as on false positives/negatives from the external content filter which is also part of the interface.

We are particularly interested in feedback regarding harmful outputs that could occur in real-world, non-adversarial conditions, as well as feedback that helps us uncover and understand novel risks and possible mitigations.

You can choose to enter the ChatGPT Feedback Contest3 for a chance to win up to $500 in API credits.

Entries can be submitted via the feedback form that is linked in the ChatGPT interface.”

The currently ongoing contest ends at 11:59 p.m. PST on December 31, 2022.

Will Language Models Replace Google Search?

LaMDA is an AI chatbot that Google has already developed. An engineer at Google asserted that LaMDA was sentient since the performance of the chatbot was so similar to a human discussion.

Is it unlikely that a business like OpenAI, Google, or Microsoft will eventually replace conventional search with an AI chatbot given how these massive language models can respond to so many queries?

On Twitter, some people have already predicted that ChatGPT will overtake Google.

For those who make their job as search marketing experts, the possibility that a question-and-answer chatbot would eventually replace Google is terrifying.

It has spurred debates in online communities for search marketing, such as the well-known Facebook SEOSignals Lab, where someone questioned whether or not search queries may shift away from search engines and toward chatbots.

After using ChatGPT, I have to admit that the worry over chatbots taking the role of search engines is not unwarranted.

Although there is a long way to go in terms of technology, it is conceivable to picture a search future that combines chatbots with hybrid search.

But it appears that ChatGPT as it is now implemented will eventually need users to spend credits in order to utilise it.

How Can ChatGPT Be Used?

ChatGPT is capable of crafting text in the form of short stories, poems, songs, and even code.

ChatGPT is transformed from a source of information to a tool that may be used to complete a task thanks to its proficiency in following instructions.

It can therefore be used to write an essay on just about any subject.

ChatGPT can be used as a tool to create article or even book-length outlines.

Almost any assignment that can be answered with written word will have a response from it.

Conclusion

As was already mentioned, it is planned for the public to eventually pay to utilise ChatGPT.

Within the first five days of ChatGPT’s public launch, more than a million users had registered to utilise it.

What is ChatGPT And How Can You Use It?

What are the Limitations of ChatGPT?

Limitations on Toxic Response

Quality of Answers Depends on Quality of Directions

Answers Are Not Always Correct

OpenAI Explains Limitations of ChatGPT

Is ChatGPT Free To Use?

Will Language Models Replace Google Search?

How Can ChatGPT Be Used?

Conclusion

Aley

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