Artificial Intelligence vs. Machine Learning: Battle of Advanced Technologies

Artificial Intelligence (AI) and Machine Learning (ML) are two terms that may sound similar but have different meanings yet are often used interchangeably. Both these technologies have turned out to be a boon for the Internet of Things (IoT) industry.

So, what's the difference between AI and ML? And which one is better for IoT?

Understanding AI and ML

Artificial Intelligence involves the creation of computer-controlled machines that can perform tasks that typically require human intelligence, such as visual recognition, language translation, decision-making, and learning. In contrast, Machine Learning focuses on the design of algorithms that can learn from data and make predictions without human intervention.

In simple terms, AI can be seen as a more extensive concept that includes several subsets like Natural Language Processing, Robotics, and Computer Vision. ML, on the other hand, is one of the subsets that falls under the umbrella of AI.

A Battle of Statistics

When it comes to IoT, both AI and ML encounter significant applications. A recent study by Gartner suggests that investment in IoT will reach $1.5 trillion by 2025. AI and ML technologies are estimated to make up a considerable share of this investment.

A report by ResearchAndMarkets estimates that the market for AI in IoT is projected to exceed $16 billion by 2025, with an expected Compound Annual Growth Rate (CAGR) of 26.6% during the forecast period (2020-2025).

The report further mentions that the market for ML in IoT is also set to witness substantial growth. It is anticipated to reach $10.6 billion by 2025, growing at a CAGR of 28.4% during the forecast period (2020-2025).

Which One is Better for IoT?

AI and ML are both relevant in IoT contexts. AI can help advance predictive maintenance, identify anomalies and optimize overall systems, while enabling efficient decision-making.

ML, on the other hand, can train machines to recognize patterns, learn from the gathered data, and adapt to changing environments. ML can be applied to various use cases such as smart homes, connected cars, and health monitoring among others.

In conclusion, it's difficult to say which technology is better suited for IoT, as both AI and ML have unique advantages and are applicable in different ways. Their application depends on the specific needs of the IoT use case.

References

• Gartner. (2019). Gartner Says the Internet of Things Installed Base Is Forecast to Grow to 20.4 Billion Units in 2020. [Press release].
• ResearchAndMarkets. (2020). Global Artificial Intelligence (AI) in IoT Market opportunities, growth drivers, Trends, and Forecasts to 2025. Report.