Web3 is a broad term for an imagined third generation of the internet in which decentralization has led to a more equitable distribution of the internet’s power and benefits. Some large tech firms will no longer be able to control the core features of the web.
Users will have complete control over their information, privacy will be protected, censorship will be nonexistent, and rewards will be distributed fairly in a decentralized system.
The current paradigm places a premium on web centralization, which has been instrumental in the rise of AI. Now, with all this talk about Web3, what exactly is AI’s place in the future of a decentralized society? And how should we go about untangling AI’s centralization tendencies?
Let’s explore this blog and know how Artificial Intelligence in web3 can bring new changes to this technology era.
* What is Web3?
To understand Web3, it makes sense to understand what came before.
- Web 1: The original Internet, or Web 1, debuted in the late 1990s and was made up of a network of linked websites. The websites were not interactive. Reading and publishing content was only possible.
- Web 2: The current iteration of the World Wide Web, or “Web2,” is the one most people are familiar with. In web2, businesses willing to offer their services in exchange for access to your private information have taken over the internet.
- Web3: Web3 is the third generation of the World Wide Web, the decentralized web that promises to connect people and devices worldwide without centralized intermediaries.
The decentralized web is driven by a network of interconnected individuals, unlike the traditional web, which depends on centralized authorities like governments and corporations to provide content and services.
This peer-to-peer network allows for direct interactions between users without intermediaries.
* Prominent Characteristics of Web3
- Decentralization: Web3 would allow information to be stored in multiple locations across a network. This would enable users to have greater control over the vast databases.
- Permissionless and trustless: Web3 is decentralized and based on open-source software, making it possible to share and access information without permission or trust in a centralized authority. Web3 apps that run on blockchains are called dApps.
- Artificial intelligence (AI) and machine learning: Using Semantic Web principles and natural language processing, Web3 will implement AI and machine learning to give computers human-level data comprehension.
Connectivity: Information and content are more connected with web3 and are accessible by multiple applications.
* What is AI?
The term “artificial intelligence” (AI) refers to the process by which computers can mimic human intelligence. Some examples of AI are expert systems, natural language processing (NLP), speech recognition, and computer vision.
The hardware and software used to create and train machine learning algorithms are the foundations upon which artificial intelligence rests. AI systems generally work by ingestion of large amounts of labeled data.
They look for regularities in the information and extrapolate from that to anticipate potential outcomes. A chatbot, for instance, can be taught how to engage in natural-sounding conversation with humans by being exposed to actual textual exchanges between humans.
An image recognition tool can also learn how to recognize objects in images by being exposed to millions of images. AI programming is focused on three cognitive skills: reasoning, learning, and self-correction.
* Distinctive Forms of Artificial Intelligence
1. Weak AI or Narrow AI
- Narrow AI is a type of AI that can perform a dedicated task with intelligence.
- The most common and currently available AI is Narrow AI in Artificial Intelligence.
- Narrow AI cannot perform beyond its field or limitations, as it is only trained for one specific task. Because of this, it is also known as “weak AI.” When stretched too far, narrow AI can fail in unexpected ways.
- Apple Siri is a good example of Narrow AI, but it operates with a limited pre-defined range of functions.
- Narrow AI also includes IBM’s Watson supercomputer because it employs an Expert system approach in addition to Machine learning and natural language processing.
- Playing chess, making product recommendations on an online store, autonomous vehicles, speech recognition, and image recognition are all examples of Narrow AI.
2. Strong AI or General AI
- Strong artificial intelligence allows systems to mimic human performance on various tasks.
- Compared to older systems, these newer ones are more intricate and difficult to understand.
- These programs are designed to operate independently of human input.
- Strong AI can be seen in applications such as driverless cars and surgical suites.
* Layers of Web 3 Intelligence
1. Adaptive Blockchains
Blockchain concentrates on creating computing components for the decentralized functioning of financial transactions. These components, like oracles, consensus mechanisms, node applications, virtual machines, and distributed ledgers, perform a crucial role.
Traditional software infrastructure components, such as data storage and communication, are catching up quickly. The next blockchains’ core and sidechains will include machine learning features. It is possible to design a scalable consensus protocol by using transaction prediction.
2. Smart Protocols
The Web 3 stack, including smart contracts and protocols, will begin incorporating ML features soon. It looks like DeFi is the standard bearer for this movement. The next generation of DeFi AMMs and lending protocols will soon include smarter logic based on ML models.
For example, we can conceive of a lending protocol that employs some smart score to ensure that loans from all kinds of wallets are equally distributed.
3. Superior dApps
Web3 development solutions that allow for the rapid addition of ML-driven features are likely to include decentralized applications (dApps). There is already evidence of this trend in NFTs, which will only increase.
Next-generation NFTs will move from static images to artifacts with intelligent behavior. These NFTs can modify their actions depending on the owner’s emotional state.
* Why Artificial Intelligence in web3?
In web3, we are expanding AI’s abilities to benefit everyone, not just the rich. Each AI model is honed with the creator’s unique experiences, interests, and insights.
In web3, creators fully control their data, AI models, and digital assets.
As a result of AI’s proliferation in web3, a new creator economy is emerging in which communities can finance both the artists they admire and the AIs that improve their daily lives. Creators now have the opportunity to build a sustainable business around their creativity, and the community can benefit from this success.
* Final Words
Future technologies will likely include improvements to ArtificiaI Intelligence in web3. Over the past decade, the rapid advancement of ML technology and research has resulted in an overwhelming amount of ML platforms, frameworks, and APIs that can provide intelligent capabilities to web3 solutions. Already, we are seeing some instances of intelligence in web3 apps. We can say that web3 is brilliant, but this intelligence is not uniformly distributed.