No! ChatGPT did not write this for me!
The banking, finance, and insurance sectors have been abuzz with artificial intelligence (AI) and machine learning (ML) for a while now. It created too much noise in the market after Chris Stone’s LinkedIn post spread like wildfire about how OpenAI ChatGPT wrote his LinkedIn posts for a week.
What is ChatGPT?
ChatGPT is an advanced AI chatbot trained by OpenAI which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT relies on the powerful GPT-3.5 technology. GPT stands for Generative Pre-Trained Transformer, a complex neural network based on the revolutionary Attention concept.
With the help of the huge amounts of information it is trained on, ChatGPT is able to deliver responses that are remarkably human-like. The capacity of ChatGPT to record context from users’ earlier statements in a thread and use it to inform responses later in the conversation is another feature that sets it apart.
ChatGPT Tutorial | Chat GPT Explained | What is Chat GPT ? | Edureka
ChatGPT Tutorial | Chat GPT Explained | What is Chat GPT ? | Edureka
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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.
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.
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Who Built ChatGPT?
The artificial intelligence company OpenAI, headquartered in San Francisco, developed ChatGPT. The for-profit OpenAI LP is a subsidiary of OpenAI Inc., a nonprofit organisation. The well-known DALLE deep learning model from OpenAI, which creates images from text prompts, is well-known.
The researchers and engineers at OpenAI are exploring ways to increase the transparency of this deep learning model and are attempting to be as open and honest as they can about the model’s capabilities, limitations, and potential for abuse. In order to remove bias in their training data, OpenAI data scientists are constantly reviewing user comments and have implemented the “humans in the loop” (HITL) method. Engineers at OpenAI are always keeping an eye on the model’s outputs and user prompts in ChatGPT to make sure it is being applied responsibly.
ChatGPT vs Other Tools
- OPT:
The Open Pretrained Transformer, or OPT, is Meta’s take on the GPT. The OPT has a number of intriguing properties that make it a competitive alternative to GPT. OPT and the GPT model, for instance, have accuracy levels that are rather comparable when it comes to Zero-Shot NLP evaluation. Google LAMDA:
Google is worried about ChatGPT. People could rely on ChatGPT instead of using the web’s first search engine to find the answers to their most pressing queries. LAMDA, like ChatGPT, is based on Transformer, a neural network architecture created by Google Research and made available for use in 2017. The Transformer architecture generates a model that can be trained to read multiple words (a phrase or paragraph, for example), pay attention to how those words relate to one another, and then predict what words it believes will come next.
BLOOM:
It was established to loosen Big Tech’s grip on Large Models. Over the past few years, tech companies have been conducting research employing huge amounts of computing power that are inaccessible to normal academics and organisations. Independent researchers find it difficult to verify and refute the Big Tech Companies’ results as a result.
Here is a list of Chinese tech companies that have recently made announcements on AI technology:
- BAIDU: Baidu Inc said on Feb. 7 it would complete internal testing of a ChatGPT-style project called “Ernie Bot” in March.
- ALIBABA: On February 8, Alibaba Group announced that it is creating and testing a ChatGPT-like technology internally. Large language models and generative AI, according to the e-commerce behemoth, have been areas of attention since Damo Academy, its research institute, was established in 2017.
Limitations of ChatGPT
As a language model, ChatGPT will invariably give incorrect responses. Sometimes this chatbot appears to be quite certain of its responses, even when they are incorrect, which could be dangerous.
ChatGPT’s training data is constrained, as is the case with many AI models. Both a lack of training data and bias in the data might have a negative impact on the model’s output.
The chatbot’s responses might be inaccurate in several factual areas. For instance, it may create fictional historical figures and publications that don’t exist or incorrectly answer some maths questions. The understanding of ChatGPT is still restricted to 2021 data, although it might advance over time.
However, it is anticipated that ChatGPT will pave the way for considerably more sophisticated AI systems in the future. The potential of GPT-3 has already sparked interest in OpenAI’s upcoming LLM model, GPT-4.
Delve into the nuances of Generative AI vs Large Language Models (LLM) in our comprehensive comparison guide – discover which technology aligns best with your project needs.
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