Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

Generative AI refers to AI techniques that learn a representation of artifacts from data, and use it to generate brand-new, unique artifacts that resemble but don't repeat the original data.

According to Gartner, before long, GenAI will greatly impact product development, customer experience, employee productivity and innovation. We predict that:

By 2025, 70% of enterprises will identify the sustainable and ethical use of AI among their top concerns.

By 2025, 35% of large organizations will have a chief AI officer who reports to the CEO or COO.

By 2025, the use of synthetic data will reduce the volume of real data needed for machine learning by 70%.

By 2025, 30% of outbound marketing messages from large organizations will be synthetically generated. That’s up from less than 2% in 2022.

Through 2026, despite all the advancements in AI, the impact on global jobs will be neutral — there will not be a net decrease or increase.

By 2030, AI could reduce global CO2 emissions by 5 to 15% and consume up to 3.5% of the world’s electricity.

By 2030, decisions made by AI agents without human oversight will cause $100 billion in losses from asset damage.

By 2033, AI solutions will result in more than half a billion net-new human jobs.

Source: Gartner

1. Reactive Machines AI

Reactive machines are AI systems that have no memory and are task specific, meaning that an input always delivers the same output. Machine learning models tend to be reactive machines because they take customer data, such as purchase or search history, and use it to deliver recommendations to the same customers.

2. Limited Memory AI

The next type of AI in its evolution is limited memory. This algorithm imitates the way our brains’ neurons work together, meaning that it gets smarter as it receives more data to train on. Deep learning improves image recognition and other types of reinforcement learning.

3. Theory of Mind AI

The first two types of AI, reactive machines and limited memory, are types that currently exist. Theory of mind and self-awareness are AI types that will be built in the future. As such, there aren’t any real world examples yet.

4. Self-Awareness AI

The grand finale for the evolution of AI would be to design systems that have a sense of self, a conscious understanding of their existence. This type of AI does not exist yet.

Source: Coursera