3 Trends in Artificial Intelligence to Watch in 2024

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Localized AI: The technology will make AI faster and more efficient and useful.

Investor’s Business Daily recently provided one of the better definitions of artificial intelligence that I’ve seen. Specifically, it noted that “AI uses computer algorithms to replicate the human ability to learn and make predictions,” while adding that the technology “needs computing power to find patterns and make inferences from large quantities of data.”

By enabling computers to progressively learn, AI is going to make them so much more powerful and helpful to humans. In my opinion, the technology will be a game changer for many sectors, including autos, healthcare, and retailers. Meanwhile, AI, which is now provided to consumers by computers located in far-away data centers, will be utilized directly by our own devices, radically changing how it affects our lives.

Here are three AI trends to watch in 2024.

In my view, we’ll really start to see AI radically change the auto sector next year. Specifically, autonomous vehicles are going to start proliferating in 2024, although the most rapid advances will likely take place in China and in the U.S. trucking sector.

In China, as I noted in a previous column, Xpeng (NASDAQ:XPEV) has developed an AI-based autonomous navigation system called City Navigation Guided Pilot (NGP). And “in May, Xpeng reported that NGP was able to drive by itself as well as ‘a novice driver,'” while its capabilities will only improve going forward.

The technology is already being utilized by drivers in five Chinese cities and is slated to be rolled out in an additional 20 cities by the end of this month. By the end of this year, it will be available in another 30 cities. What’s more, the company also recently unveiled its “AI Valet Driver,” which learns how to autonomously navigates routes after a human drives them one time.

AI is already transforming healthcare, and that trend will only intensify next year. On Oct. 10, for example, Microsoft (NASDAQ:MSFT) unveiled a data analytics tool that’s tailor-made for healthcare entities. The product integrates information from many different sources and enables organizations “to build and run AI models, as well as derive insights” from them.

The software giant also introduced Azure AI Health Insights which it described as “a cognitive service that provides prebuilt models that perform analysis and provide inferences that can be reviewed and used by clinicians and researchers to facilitate patient care.” The most impressive tool within Azure AI Health Insights, called Radiology Insights, provides healthcare providers with treatment recommendations and assesses their decisions, helping to prevent errors.

In general, AI will also enable more “personalized medicine,” better testing for diseases and improved robotic surgery. And as I’ve pointed out in multiple, previous columns, AI is going to enable the drug discovery process to become much faster and more effective.

Among the companies that are using AI to improve the drug discover process are Schrodinger (NASDAQ:SDGR) and Exscientia (NASDAQ:EXAI).

At this point, most of the AI utilized by both individuals and companies is provided by far-away data centers. Starting next year, though, we should start to see devices that will enable us to utilize AI on our own.

As Intel (NASDAQ:INTC) CEO Pat Gelsinger recently explained, “As the world moves towards more AI-integrated applications, there’s a market shift towards local inferencing. ” He added that “We are bringing AI to where the data is being generated and used rather than forcing it into the cloud.”

According to TechTarget, localized AI, more commonly referred to as Edge AI, is faster, cheaper, and more secure. Additionally, it enables AI to be utilized to perform more tasks, such as “speech recognition, fingerprint detection, face-ID security, fraud detection and autonomous driving systems.”

Intel and Qualcomm (NASDAQ:QCOM) are among the companies developing the chips that will enable Edge AI. Localization will certainly be one of the most important AI trends in 2024.

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