When OpenAI’s ChatGPT came out in November 2022, it was a huge hit on the internet right away. Now, Google has said that it will have an AI-powered chatbot. When a user asks for something, generative AI makes that thing by using data from its machine learning model. The content is automatically made to answer questions.
People started looking for ways to use content made by AI for business, education, and their own needs when OpenAI released ChatGPT. AI experts, on the other hand, warned that information from the wrong data sources can make things confusing. There are both good and bad things about coming up with your own content.
Microsoft is already a leader in the AI industry, and its latest AI project makes it even more so. The latest AI chatbot feature for Microsoft Bing just came out, and it can now be used on iOS, Android, Edge, Skype, and other devices and operating systems.
By adding this cutting-edge feature, customers will be able to talk to Microsoft’s AI chatbot in a more natural way and have a more exciting and immersive experience. There are important differences between the two, even though they do some of the same things.
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What is ChatGPT?
ChatGPT is a chatbot that uses machine learning and AI to answer questions in a conversational way. OpenAI released ChatGPT on November 30, 2022. Sam Altman, the CEO of OpenAI, says that ChatGPT had a million users in just five days.
ChatGPT uses the GPT-3 language model, which learns from text written by people on the Internet. ChatGPT uses this language model to figure out how to answer user questions. Some of the most popular things that ChatGPT’s AI makes are:
- code on paper;
- product descriptions;
- blog posts;
- email sets up;
- The main points are taken from transcripts, meetings, and podcasts;
- Simple ways to explain things that are hard to understand;
- law briefs;
- translations;
- jokes or memes; and
- social media posts.
Teachers and professors were worried that ChatGPT was helping students write convincing essays, and they wanted to know what they could do to stop students from cheating. OpenAI replied that it would put out a new AI text classifier in January 2023.
Also Read: Check Our List of Top 10 Best Open Ai Apps in 2023!
What is Bing?
Bing AI mobile is now available for everyone to use. Microsoft’s new Bing, which uses AI, has been in the news for a while, and now it will be available on smartphones. Who wouldn’t want to carry around in their pocket an AI-powered chatbot?
Users of the Edge and Bing apps for Android and iOS can now chat with the chatbot. So what about the other things? People who don’t have access yet will be able to try out new Bing’s other AI features and get on the waiting list more easily through the mobile Bing app.
Bing AI is one of the best AI search engines, and its chatbot has become a popular replacement for ChatGPT. Google Bard AI wasn’t reliable, and ChatGPT didn’t have a mobile app, but Bing AI mobile could be a game-changer in the business of generative AI.
How Are Bing Chat and ChatGPT Different From Each Other?
There is a reason why Bing seems more intelligent. Microsoft’s new, next-generation OpenAI large language model was used to train Bing Chat. This model is more advanced than ChatGPT and works with Bing search as well. This mixed model is called “Prometheus” inside the company.
Even though Microsoft hasn’t said for sure, there are hints that the model used for training is GPT-4. First of all, the date of GPT-4’s release is getting close to being suspicious. GPT-4 is the long-awaited sequel to GPT-3.
Open AI CEO Sam Altman has been saying that the model’s release is still “up in the air,” but a report from The New York Times said that the model should be released in the first half of this year. People say that the model behind Bing Chat has less latency than ChatGPT. This means that it is either GPT-4 or a different version of it.
Also, it’s clear that Sydney (former name of Bing Chat) has nothing in common with ChatGPT. She sounds more like a GPT family model, whose answers are more natural and instinctive. Sydney tends to repeat herself when a conversation goes on for a long time, just like GPT models do.
At least for the question to create a workout and meal plan for a person for the next three months, who is 5’8″ tall and weigh 125 pounds and want to gain 30 pounds of muscle. Microsoft’s improved Bing seems to give better advice than ChatGPT.
When this question is asked, ChatGPT shows a bulleted list of a workout and meal plan that, if followed, should help a person gain 30 pounds of muscle in 90 days. Some of the tips are to lift weights for 45–60 minutes, four or five times a week, do cardio for 20–30 minutes, two or three times a week, and eat a dinner that is high in protein, healthy fats, and complex carbs. One dish is salmon with quinoa and vegetables. A turkey burger with sweet potato fries is another option.
Bing, on the other hand, says that gaining 30 pounds in three months might not be possible and could be dangerous. Bing said that it might take a lot of genetic potential, steroids, or both to gain that much muscle mass. It also had a link to a related article on Healthline. Bing suggests that you change your goals to something more realistic, like gaining 10-15 pounds of muscle in 3 months.
Also Read: Microsoft Bing ChatGPT: Integration of Bing and ChatGPT
A Brief History of Chatbots
Over time, chatbots have changed a lot. Some people may be surprised to learn that these chatbots have been around since the 1960s. Eliza was the first thing like it. Joseph Weizenbaum made it between 1964 and 1966 at the MIT Computer Science and Artificial Intelligence Laboratory.
It was made on purpose to show how shallow a conversation can be between a person and a machine. The chatbot mimicked a conversation between a patient and a psychiatrist by looking for keywords and pattern matching.
This was the first time that NLP, or natural language processing, was used in a computer program. As the Internet became more popular in the 1990s, NLP and ML were used to make chatbots smarter. This helped them understand what the users were saying and come up with responses that seemed more human.
For example, Richard Wallace’s chatbot ALICE which stood for Artificial Linguistic Internet Computer Entity and was based on Eliza was one of the first to use ML algorithms to find answers. When messaging apps came along, many people started using chatbots to help with customer service and support.
Siri, which was released by Apple in 2011, is one of the best-known chatbots of our time. Most people thought it was a chatbot that used rules to respond to what users said, even though it wasn’t a conversational bot.
Chatbots like Cortana, Google Assistant, and Alexa were made to help people or to use simple voice commands to control connected systems. Even though these models and newer ones like ChatGPT have some things in common, the technologies and algorithms they use are very different.
But Siri and ChatGPT are different in one way: they use different algorithms. Siri and ChatGPT both use AI/ML and NLP, but Siri uses recurrent neural networks or LSTM while ChatGPT uses the generative pretrained transformer (GPT) algorithm (Long short-term memory).
This means you have to make layers that look like memory. Simply put, assistants like Siri should be able to understand what a person says, process it, and reply in a natural way. This is called “Natural Language Understanding,” or NLU. It is a part of natural language processing (NLP) that uses algorithms for machine learning.
On the other hand, ChatGPT is not a helper. It has learned from a lot of text data and tries to write like a person. LLM models like ChatGPT can’t talk to the outside world yet, but they can be used for a wide range of tasks. On the other hand, personal assistants like Siri can only be used for one thing. The other part of NLP is Natural Language Generation (NLG).
NLG models, as their name suggests, turn structured or unstructured text data into easy-to-understand text. These are made to be much more flexible and capable of making a wider range of things. With ChatGPT and Google Bard, LLMs have made the writing part even better.
Because they can process language, they can understand and respond to a much wider range of inputs and make much more complex and varied outputs. Right now, these models are the best examples of artificial intelligence (AI).
Recent advances in AI, especially in transformer-based architectures, have made it possible for machines to not only understand language but also write text that looks like it was written by a human.
Also Read: Microsoft Bing ChatGPT: Integration of Bing and ChatGPT
Conclusion
AI’s future in marketing is still changing and adapting as quickly as it did when it first began. In addition to making content, it is now used for customer service, email optimization, product recommendations, and social media posts. Other AIs can also create content. There are also new companies that are working on their own projects, like ChatSonic, Jasper AI, OpenAssistant, and Wordtune. The app Ernie Bot from the Chinese search engine Baidu will also use AI.
