What is web 3.0?
What is Web 3.0?
How will it glance?
How will it impact our stamina?
It is the advanced next third-generation Internet Technology, leaning on machine learning (ML), Artificial Intelligence (AI), and Blockchain to facilitate real-time human communication.
Tim Berners-Lee, the architect of the World Wide Web, initially guided Web 3.0 as the Semantic Web to build a more liberated, intelligent, and open internet.
WEB 3.0 MEANING
If we expand on the definition simply, websites and apps will process data in a human-like mode using Machine Learning (ML), big data, and Decentralized Ledger Technology (DLT), among other technologies. Data will be decentralized, which is a significant headway over the existing epoch of the internet (Web 2.0), where data is primarily kept in centralized depositories.
Besides, data will be able to transmit with individuals and machines. However, programs must understand information theoretically and culturally for this to happen. With this in mind, Web 3.0’s two pillars are the Semantic Web and Artificial Intelligence (AI).
KEY COMPONENTS OF WEB 3.0
- Artificial Intelligence
- Semantic Web
- 3D Graphics
WEB 3.0, CRYPTOCURRENCY AND BLOCKCHAIN
Since Web 3.0 grids will be established on decentralized protocols — the basic building blocks of blockchain and cryptocurrency technology — we may anticipate a vital intersection and symbiotic association between these three technologies and other industries. They will be seamlessly blended, interoperable, and automated via smart contracts. They will be utilized to power everything from microtransactions in Africa to censorship-resistant P2P data file storage and sharing via applications like Filecoin to alter how businesses conduct and operate their operations fundamentally. The current outbreak of DeFi protocols is only the beginning.
POSSIBLE AND PITFALLS OF WEB 3.0
Web 3.0 holds the potential to supply users with significantly more utility than the social media, streaming, and online retail applications that make up the majority of Web 2.0 applications used by consumers. Semantic Web, artificial intelligence, and machine learning capabilities at the heart of Web 3.0 have the potential to expand applications in new domains and improve user interaction significantly.
Web 3.0’s defining factors, such as decentralization and permissionless techniques, will significantly boost consumer control over personal data. This may aid minimize data extraction—information about web users acquired without their agreement or compensation—and mitigate the network influences that have allowed technology corporations to achieve near-monopoly status via exploitative advertising and marketing activities.
WEB 1.0, 2.0, 3.0
- Home Pages
- Web Forms
- Page Views
- Britannica Online
- Company Focus
- Owning Content
- Banner Advertising
- Blogs / Wikis
- XML / RSS
- Web Applications
- Cost Per Click
- Community Focus
- Sharing Content
- Interactive Advertising
- Read, Write and share personalized content.
- Live-streams / Waves
- RDF / RDFS / OWL
- Smart Applications
- User Engagement
- The Semantic Web
- Individual Focus
- Consolidating Content
- User Behavior
- Behavioral Advertising
WHAT ARE WEB 3.0 EXAMPLES?
For its part, Apple’s Siri relies on advanced speech recognition and artificial intelligence to accomplish tasks like:
“I’m starving; where can I get some lasagna?” Or
Schedule an appointment for 10.00 am tomorrow,
For better understanding, we may compare Wolfram Alpha vs Google in search results for “England vs Australia.”
Cricket matches between England and Australia appear to be the most prevalent search topic on Google. It’s important to note that neither “cricket” nor “matches” are typed in our search bars.
Wolfram Alpha treats the search as a comparison between two countries and provides geographic, historical data, organized statistics, demographic and linguistic data for comparative analysis.
Beyond all, classic tools (Web 1.0 and 2.0) do a “word by word like” search comparing the text concerning what is posted on the network. In other words, it often introduces information bias based on what is most abundant; resulting in not delivering what is most applicable to the user at the time.