Future Artificial Intelligence Development Trends

Data centres (cloud), communication terminals (mobile phones), and specialised application goods (self-driving cars, head-mounted AR/VR, drones, robots) are the three main market segments that AI chips fall under. There are now eight new tendencies in the future development of AI.

Trend 1:

AI applications have significant potential in several sectors' vertical fields.

The market for AI has enormous potential across numerous economic sectors, including retail, manufacturing, transportation and automation, and agriculture. The market is primarily driven by the rising number of applications of artificial intelligence technology across a range of end-user industries, particularly to enhance consumer services.

Of course, the development of IT infrastructure, the acceptance of smartphones, and the popularity of innovative wearable technology all impact the growth of the artificial intelligence industry. A significant portion of the AI market, specifically the natural language processing (NLP) application sector, comprises these.

Several initiatives benefit from developing natural language processing technologies, including automobile infotainment and entertainment systems, AI robots, and AI-enabled smartphones.

Trend 2:

AI is being incorporated into the healthcare sector to sustain its rapid expansion.

Big data and artificial intelligence are widely used in the healthcare sector, which helps to accurately enhance disease detection, address the human imbalance between patients and medical staff, lower medical expenses, and foster cross-industry collaboration.

Clinical studies, extensive medical planning, medical counselling, promotion, and sales development are additional areas where AI is extensively used. From 2016 to 2022, the use of artificial intelligence in the healthcare sector is predicted to increase, with a compound annual growth rate of 52.68%, from US$667.1 million in 2016 to US$7.9888 billion in 2022. AI will replace the screen with the following UI/UX interface

Trend 3:

User interfaces have historically been used with screens or keyboards, dating back to the days of PCs and mobile phones. People can readily communicate with computing systems without a net as intelligent speakers (SmartSpeaker), virtual/augmented reality (VR/AR), and self-driving automobile systems rapidly reach the human living environment.

It indicates that in the future, the user interface and user experience will replace the screen as artificial intelligence improves technology's intuitiveness and ease of use through natural language processing and machine learning.

Artificial intelligence can perform increasingly complicated jobs in the technical interface and have a significant role in the business's back end. Using visual graphics in self-driving cars and real-time translation using artificial neural networks, for instance, artificial intelligence makes interfaces more user-friendly and sophisticated while setting a high bar for future interactions.

Trend 4:

AI computer cores must be integrated into upcoming mobile phone chips.

Future mobile phone chips will undoubtedly feature integrated AI processing cores because the standard ARM architecture processor can now not conduct a significant number of picture calculations quickly enough.

Similar to how Apple followed up by introducing 3D sensing technology to the iPhone, handsets from the Android camp will do the same thing the following year.

Trend 5:

Successful software and hardware fusion is the key to AI chips.

A semiconductor and an algorithm make up the brain of an AI chip. AI hardware's primary requirements are faster instruction cycles and reduced power consumption, including GPU, DSP, ASIC, FPGA, and neuron chips. Deep learning algorithms must be paired with AI hardware, and the secret to a successful pairing is cutting-edge packaging technology.

In general, FPGA is more energy-efficient and faster than GPU. Thus, the choice of AI hardware relies on the demands of the product manufacturers.

Infrared lens, floodlight sensing component, distance sensor, ambient light sensor, front-end camera, point Array projectors, speakers, and microphones are just a few of the up to eight pieces that Apple's FaceID facial recognition system integrates for analysis. Apple emphasizes that the user's biometric information, such as fingerprints or face recognition, is encrypted and stored inside the iPhone, making it difficult to steal.

Trend 6:

The ultimate objective of AI is autonomous learning.

Machine learning, deep learning, and independent learning are all steps in the AI "brain" becoming smarter. It is still in the machine learning and deep learning stages right now. Four significant issues must be resolved for autonomous learning to occur.

Creating an AI platform for autonomous machines is the first step. Creating a virtual environment that enables autonomous machines to learn independently is also necessary. This environment must adhere to the laws of physics and have the same impact, pressure, and effects as the real world. Next, integrate the AI "brain" into the frame of the autonomous machine and then build the virtual world portal (VR).

The autonomous machine processor Xavier, which NVIDIA currently has available, is geared toward the popularization and commercialization of autonomous machines.

Trend 7:

Combining CPU and GPU (or other processors) is the best architecture.

In the future, several super-performance processors will be needed in specialized industries. Still, the CPU is a universal component for many devices that may be used in any circumstance.

Therefore, combining the CPU with GPU (or other processors) is the best architecture.

For instance, NVIDIA unveiled the CUDA computing architecture, which blends general-purpose ASICs with specialized function ASICs to enable programmers to build a variety of algorithms.

Trend 8:

AI's eyes are becoming AR's, which are essential and complementary.

Future AI will require AR, and future AR will require AI. AR is comparable to AI's eyes. The virtual environment produced for robot learning is virtual reality in and of itself. More other technologies are required if people want to train the robot in the virtual world.

As we look ahead, it's clear that the semiconductor industry is poised for a new wave of success. This time, it will be fueled by exciting new technologies like artificial intelligence, the Internet of Things, virtual reality, and augmented reality. These innovations will transform our lives and work for 30 years and beyond.

Being a part of this industry at this time is thrilling, and I'm looking forward to what lies ahead! Chips used in product applications are still in high demand. Thanks to its considerable market advantages in semiconductors.