A report issued by Globaldata, a global consulting and data analysis company, predicts that China will become a leading country in metaverse tech during 2023. The firm believes that the development of other technologies like artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and 6G will allow China to configure itself as a metaverse hub.

China to Lead Metaverse Industry in 2023

While the interest in the metaverse seems to be waning at a worldwide level, China is still pushing to become a leader in the industry. According to a recent report prepared by Globaldata, a consulting firm, China is positioning itself to surpass the West when it comes to metaverse tech, as the country will keep investing in technologies related to this field.

The report states the importance that China gives to these accessory technologies will allow it to become a center for the metaverse. It states:

The growing emphasis on VR, AR, AI, and 6G aims to outpace advances in the West and position China as a global hub for the metaverse.

Furthermore, Globaldata believes that there are signs that indicate that China will continue to invest in virtual reality and artificial intelligence with the objective of promoting the economic development of the nation. Several Chinese provinces and cities have already presented plans to become metaverse tech hubs, including Shanghai and Zhejiang among them.

Where Will the Metaverse Go?

While the metaverse is commonly associated with software and hardware dedicated to the consumers, the report proposes the Chinese metaverse is likely to focus more on the industry and the benefits that it can reap from including metaverse tech in its processes.

The Chinese Ministry of Industry and IT recently released a report on the application of VR and metaverse tech into industrial processes, showing how these can be mixed efficiently. Globaldata predicts the metaverse will be more appreciated than other technologies due to the possibilities it presents. On this, it explains:

Chinese investments in metaverse-related technology will highlight the value of the metaverse compared to existing one-off experiences such as social media, gaming, or ecommerce.

However, even with estimations that put the metaverse sector value at $376 billion by 2025, 2023 is described as a year in which investments in the metaverse will suffer a cool-down phase, product of the “cooling interest, economic obstacles, and the immaturity of enabling technologies.”

What do you think about the prediction that puts China over the western world when it comes to metaverse investments? Tell us in the comment section below.

Image Credits: Shutterstock, Pixabay, Wiki Commons

Artificial Intelligence in Voice Cloning is an interesting way to use the technology

Artificial Intelligence has rapidly made its way, you name it and Artificial Intelligence (AI) is everywhere.

The article mentions how can AI be used in Voice Cloning.

AI can easily copy a voice by understanding the patterns of vocal cord vibration that result in particular sounds. Then, new, comparable sounds that can imitate the original voice are produced using these patterns. Artificial intelligence (AI) is used in voice cloning technology to imitate a person’s voice. Neural Networks can help a lot in AI Voice Cloning.

With the aid of this technology, it is possible to duplicate someone’s voice or produce a new voice that is similar to the original. Creating artificial voices for digital assistants, making voiceovers for movies and video games, and developing new voices for communication devices are just a few of the many uses for voice cloning.

Although several methods can be used for voice cloning, in my opinion, neural networks are the finest.

Why Neural Networks, You Ask?

Because it is just like a brain like a human brain, which has millions and billions of neurons that receive the signal from various senses, assist the brain in decoding them, and then assist in assisting the body in reacting following the signals, similarly, Neural Network is an artificial brain, which has millions and billions of neurons, which assist in decoding the signals and assisting the machine in reacting.

Neural networks come in three main categories:

Synthetic neural networks (ANNs), Recurrent neural systems (RNNs), and Convolutional neural systems (CNNs).

The simplest kind of neural network is an ANN. A hidden layer, an output layer, and an input layer make up each of them. The hidden layer handles the calculations, the input layer takes in the inputs, and the output layer generates the outputs. RNNs are akin to ANNs, but they also contain extra layers that let them interpret data sequences. As a result, they excel at tasks like speech recognition, and machine translations are built with image processing in mind.

Some convolutional layers, an output layer, and an input layer are all present.

The output layer creates the results after the convolutional layer’s extract features from the images.

Hence AI Has reached a point where it can be used for many purposes.

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