WHY AI IN WEB 3??

The Evolution and Impact of Artificial Intelligence

Artificial Intelligence (AI) is exactly what its name suggests: intelligence demonstrated by machines. However, while we are surrounded by examples of intelligence in everyday life, AI doesn’t always reflect the same level of cognitive ability. A classic example of this is the calculator. Is it intelligent? Yes, in a limited way. But can we truly call it AI?

This question leads us to a fundamental query: how do we recognize intelligence in machines? Alan Turing, a pioneer in computer science, proposed a test to help answer this question. In what became known as the "Turing Test," AI is compared to a human being in a side-by-side evaluation. Both the AI and the human are asked a series of questions, much like how you interact with ChatGPT. If you cannot distinguish the AI's responses from the human's, then the AI has reached a level of intelligence. If the difference is clear, then the AI still falls short.

This is the reason why we don’t typically refer to calculators as AI. We all understand that calculators are computers, but they don’t yet pass the test of genuine intelligence.

The Role of AI in Modern Times

Moving into today’s world, we must ask: why do we need AI? What purpose does it serve? How does AI even come into existence? Does it simply appear, or is it created?

The answer is simple—AI can be made, and relatively easily, too. For instance, think of Microsoft Excel. Those seemingly mundane Excel sheets have far more value than many realize. In fact, I’m currently building my own AI and feeding it data. But what exactly is data? In one word: information.

To better understand how AI learns, let’s draw a parallel with human children. Every child is born with the potential for intelligence, but they have little to no information about the world at birth. They rely on their parents and environment to teach them, to feed them information. This is quite similar to how we train AI. It starts as a blank slate, much like a newborn, and requires data—massive amounts of data—to become "intelligent." Hence, we use datasets, Excel sheets, or complex algorithms to input this knowledge.

This process, however, is not without its challenges. Building a functional AI model requires vast amounts of data. We’re talking about datasets containing millions, if not billions, of rows. A fully developed AI should understand a wide range of subjects: physics, mathematics, language, science, and even culturally relevant information, like knowledge of global leaders. The more data you feed your AI, the more it learns and improves.

The Power and Risks of Data

As AI systems continue to evolve, there is a growing concern about their potential to "take over." Consider the sheer amount of data collected by platforms like Google Chrome over the years—it's staggering. In fact, your YouTube account likely knows more about your preferences than you do. Even in "incognito mode," our data isn’t entirely safe; it’s still being tracked and, potentially, stolen.

This poses a serious problem, as AI is turning into a competition between billion-dollar companies that are vying for control over your data. They collect it for fun and profit, while also using it to refine their AI models. Though AI can be helpful—automating day-to-day tasks like turning on your air conditioning—it also raises significant privacy concerns.

Every year, trillions of dollars’ worth of stolen data are sold on the dark web. It’s highly likely that someone, somewhere, has your information and is profiting from it. This is a real threat to privacy, which is why we need solutions like Web3 AI.

Web3 AI: A Solution to Privacy Concerns

Web3 AI presents a promising solution to some of these privacy issues. Unlike traditional platforms that rely on email addresses, Web3 AI only requires a wallet address, minimizing the amount of personal data collected. By removing the need for identifying information, Web3 AI reduces the risk of creating patterns or profiles about individuals.

However, Web3 AI has its own challenges, one of which is overfitting. Overfitting occurs when there isn’t enough data to train the model properly, leading to inaccuracies and biased results.

The Future of AI: Where Are We Heading?

At present, AI is still relatively limited. We are in the era of Artificial Narrow Intelligence (ANI), where AI systems are designed to perform specific tasks. There are higher levels of AI—Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI)—and when we reach the ASI stage, job losses may become inevitable as machines surpass human capabilities.

AI is often compared to a diamond mine; it is a resource that the world is eager to explore and exploit. Mastering AI will undoubtedly be a valuable skill in the global economy, with the potential to transform industries and society as a whole.