ChatGPT has in itself started a revolution. But China seems to use it differently.

Just four months have gone since ChatGPT was introduced by Microsoft-backed OpenAI.

Tech businesses are scrambling to incorporate the AI-powered bot into their goods and apps as a result of the considerable excitement that it has created among its users. The article focusses upon China and what it is doing with ChatGPT. Is the country selling ChatGPT logins to black Market?

Most users have been astounded by how clever the AI-powered chatbot sounds; some have even compared it to Google after hearing how well it can offer straightforward solutions to challenging issues. One nation appears to have been overlooked, and that is China, at a time when users all over the world are in awe of its potential.

Although being accessible elsewhere in the globe, the developers of ChatGPT have not made their AI chatbot available in the Asian nation. The tech-savvy fans, however, have continued to use it. These programs are essentially sub-programs on the platform like “ChatGPT Online,” which provides customers with a limited number of free inquiries before charging for time with a chatbot. These middlemen query ChatGPT users on their behalf and reply with the results. Yet, a lot of Chinese internet firms have cracked down on logins obtained illegally.

In contrast to WeChat, which also limits related services, the article claims that Taobao has prohibited terms like OpenAI and ChatGPT.Many significant Chinese IT businesses are attempting to introduce their own ChatGPT-like products, despite the fact that OpenAI has not made any announcements on the launch of ChatGPT in China.On February 7, Baidu declared that the Ernie bot, or “Wen Xin Yi Yan” in Chinese, would be released in March for internal testing.

Ernie 3.0-Titan, a sizable language model that Baidu has been creating since 2019, will serve as the foundation for the bot.

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Generative AIoT applications beyond ChatGPT that you need to know right now in 2023

On November 30, 2022, OpenAI released ChatGPT. The chatbot, which is based on the large language model GPT3 went viral and set records for the fastest-growing consumer application in history, with 100 million active users in just two months.

Surprisingly, many people are unaware that the technology underlying ChatGPT is not new. The transformer architecture is based on a 2017 Google research paper titled “Attention Is All You Need.” As of early March 2023, the paper had been cited over 67,000 times and can be considered a source of generative AI innovation.

In this article, we have explained the IoT using generative AI and 3 generative AIoT applications beyond ChatGPT.

So, why has OpenAI’s ChatGPT become so popular even though it is neither new nor unique?

The answer is ChatGPT’s ease of use and accessibility, as it was the first cutting-edge large language model made freely available to anyone with internet access.

Key Use Cases of Generative AI

Generative AI can have an impact on connected devices, typical IoT use cases, and IoT technology in general as a market research company focusing on IoT and IoT-related topics. Our findings were published in the Generative AI Trend Report. The report discusses the technology in general, examines the competitive landscape, and then delves into generative AI use cases related to IoT scenarios. Here are three of the nine use cases we identified at the crossroads of generative AI and IoT:

3 Generative AI Applications for IoT

Here are the top 3 generative applications for IoT

Application #1: Code generation for IoT

Large language models can be used to create, complete, or combine software code based on code snippets or natural language descriptions, and they can be applied to a wide range of domains, tasks, and programming languages. With such capabilities, these models can help both professional and inexperienced developers build innovative applications. Many IDEs already support generative AI. Although it is already used by software developers, many believe that generative AI will not replace developers anytime soon. Consider it another tool in the toolbox for code generation, similar to the no-code/low-code tools that have recently been added to the general software development toolbox.

Application #2: Robot control

Generative AI may have an impact on how autonomous (IoT) devices, such as robots, are controlled. Generative AI can generate control logic and commands for robots by capturing motion data from animals or humans. Instead of deterministically programming movements for each leg of a robot dog, for example, generative AI models can be used to generate individual part movements and make the robot dog walk complex, interconnected steps. Furthermore, generative AI models can assist robots in understanding their surroundings and connecting so-called horizon goals with more intermediate steps to achieve the goals (e.g., filling a glass with juice). Robots can then generate intermediate tasks without requiring human intervention to reach the higher horizon task.

Application #3: Social IoT devices

Today’s IoT-connected devices enable users to access data via an API. Typically, these provide predefined sets of information, such as usage, battery, and asset health. However, generative AI has the potential to make device communication “more social” in three ways:

Allowing the device to respond to complex questions posed by the user.

Allowing the end user to communicate with the device to change settings.

Allowing the devices to generate answers using generative AI. The below example helps you understand how a large language model can be used to guide a stuck robot after it has been given unclear instructions.

Example

Amazon created the DialFRED framework to allow robots to ask questions when they are unsure. The questionnaire model is fine-tuned through reinforcement learning to ask the right types of questions at the right time to benefit task completion. The framework includes an “oracle” that generates answers to generated questions automatically using ground-truth metadata from the simulation environment. As a result, DialFRED offers an interactive Q&A framework for training embodied dialogue agents. ​

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The ChatGPT successor GPT-4 launched by Open AI, its latest model for image and text understanding

The San Francisco-based tech organization guarantees that GPT-4 is the most recent achievement in its work to increase profound learning. GPT-4 has been profoundly expected since the outcome of ChatGPT. ChatGPT can imitate other writing styles and respond to questions in a manner that is comparable to that of a human.

With numerous new features, GPT-4 is a larger model that outperforms ChatGPT’s GPT-3.5. GPT-4 is more astute and more imaginative than ChatGPT and presently it can deal with additional words, acknowledge pictures as contributions to produce subtitles, and that’s only the tip of the iceberg!

GPT-4 can comprehend both text and images. It can caption, understand, and identify objects in relatively complicated images. Additionally, OpenAI is introducing “system” messages, a brand-new API feature that enables developers to specify a specific style and task by providing clear instructions. It has performed well in low-resource languages and has been tested on a variety of benchmarks, including simulated human exams.

Still ‘Flawed’, Even Though More Creative?

Similar to its predecessors, GPT-4 carries several limitations and potential dangers. OpenAI acknowledges that it still has biases, the potential to produce misleading data, and the potential for error. It might “hallucinate” the facts, not be able to solve difficult problems like humans, and believe false statements to be true. Additionally, the model only has a limited understanding of events that occurred after September 2021, which may result in straightforward erroneous reasoning.

Despite these drawbacks and dangers, OpenAI has enhanced the model’s safety and dependability. To improve its capacity to reject dangerous requests, the company has collaborated with experts to conduct an adversarial test of the model and gathered additional data.

However, it is still possible to produce content that violates usage rules, so use language model outputs with caution, especially in high-stakes situations.

How Does It Work?

The most recent and cutting-edge language model, GPT-4, has already been implemented by Microsoft’s Bing search engine and some third-party applications. Be My Eyes is testing its ability to process visual inputs by implementing a new Virtual Volunteer feature to respond to questions about images sent to it. GPT-4 has also begun to be used in a variety of ways by other businesses.

It has been incorporated into a brand-new tier of language learning subscriptions by Duolingo, and Stripe uses it to scan business websites, improve user experience, and combat fraud. Morgan Stanley likewise utilizes GPT-4 to coordinate its tremendous information base and recover pertinent data for its monetary examiners.

In addition to these early adopters, Khan Academy is conducting a limited pilot program to investigate the potential of GPT-4. The AI model is also being used by the Icelandic government to keep its language.

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