Skip to main content
  1. Contributor Content

The decentralized future of Web3 apps

By , Content Contributor
A laptop is open with code on the screen.
Bybit

Technology and internet applications are fundamentally changing, and Web3 apps are leading the way. These apps are often fundamentally changing how users can use digital services. Web3 apps utilize blockchain technology. Blockchain can offer a more secure option for users, allowing them to better control their online stored data and even interactions.

Unlike previous app versions, Web3 apps function on a peer-to-peer network. Traditional applications are often centralized, being controlled by one corporation, government, or other various entities. In contrast, Web3 apps are decentralized, taking out the middle man while providing extra security and privacy.

Recommended Videos

It is the underlying architecture of these two app types that sets them apart from one another. In utilizing blockchain, Web3 apps keep transactions public and open, so users have additional control. This also helps to prove transparency and build trust with a new audience. Without the need for human interaction, Web3 apps also use smart contracts that automate transactions based on predefined conditions. This, overall, serves to help avoid fraud or error. Options for Web3 apps include financial services, gaming, supply chain management, and even more secure social media.

Related: 
Best new movies to stream on Netflix, Hulu, Prime Video, HBO Max, and more

The world of finance is seeing the largest increase in Web3 app development. Users often refer to this as DeFi or decentralized finance. This unique option provides various financial instruments without banks or brokers, potentially revolutionizing how users handle their finances online. One such exchange is Uniswap, which lets its users trade their cryptocurrencies without using a single central authority. Web3 users can even find a decentralized lender. This could allow them to borrow funds outside of a traditional lending company.

But Web3 is moving into more spaces than just financial. It is quickly being seen amongst creative industries as well. Non-fungible tokens (NFTs) are creating waves in the art and entertainment spaces, allowing creators to utilize digital ownership and monetize in a way that was previously impossible. Markets including OpenSea allow artists to sell and trade or purchase digital assets quickly and securely.

Social media is another area in which Web3 is making its mark. Decentralized social platforms like Mastodon or Peepeth offer an alternative to traditional social networks by ensuring users retain ownership of their content and personal data. These platforms do not rely on advertising revenue. The benefit is that this reduces the incentive to mine user data, offering a more private and user-centric experience.

Despite the promise and potential of Web3 apps, there are significant challenges. Scalability remains a primary concern, as blockchain networks, like those used by many Web3 apps, can become congested as they grow. This leads to slower transactions and higher costs. Furthermore, the user experience in Web3 apps often needs to catch up to that of more mature Web2 applications, posing a barrier to widespread adoption.

Security is another critical area. Many users value Web3 apps for their extra security options. Because they use blockchain technology similar to ETH to USD LP, however, there is a possibility they could become targets for a new wave of cyberattacks. This becomes increasingly concerning, considering that blockchain transactions are irreversible and cannot easily be changed if a cyberattack occurs.

Despite these challenges, the future of Web3 looks promising. Technological advancements and growing public and private interest indicate that Web3 apps may become more prevalent. However, ongoing innovation, combined with thoughtful regulation and user education, will be essential for this potential to be fully realized.

Digital Trends partners with external contributors. All contributor content is reviewed by the Digital Trends editorial staff.
Chris Gallagher
Chris Gallagher
Chris Gallagher is a New York native with a business degree from Sacred Heart University, now thriving as a professional…
Will the future of data entry be entirely controlled by AI? Long-time industry expert weighs in

There’s no doubt that artificial intelligence is changing the world. AI’s potential to automate many tasks that are being done by humans is unparalleled, and it is expected to contribute $15.7 trillion to the global economy by 2030. With such a wide-reaching impact, some roles will inevitably be made redundant by businesses adopting AI into their operations. Some experts believe that data entry is one of these jobs, due to being composed mostly of simple, repetitive tasks.

Many businesses are turning to AI because of increased speed and cost savings, and it allows the business to allocate its human resources to other tasks. However, AI is not a silver bullet that can perform all needed tasks without the need for human intervention. Alan Bandell, Founder and CEO of Axion Data Services, an industry leader in providing data entry outsourcing services to companies all over the US, believes that the future of data entry will be intertwined with and majorly transformed by AI, but it won’t make human expertise obsolete.

Read more
“AI Alone Cannot Save Disjointed Data Systems,” says Coginiti Founder

Artificial Intelligence has grabbed the attention of every business around the globe, driven by visions of automation and smarter decision-making. This has fueled a race to integrate AI into their operations. And yet, as per Gartner’s latest update, at least 30% of AI initiatives will be abandoned this year.
Why? “It’s not because AI doesn’t work,” states Rick Hall, founder of Coginiti. “It’s because most companies haven’t done the foundational work. They expect AI to clean up their mess, but it can’t. Companies need to clean up their own data before inviting AI in.”
 
Hall believes AI is still in the early phases of a decade-long transformation, one that will redefine nearly every business operation. But for that transformation to succeed, organizations must first tackle three persistent problems: poor alignment to business goals, bad data, and failed integration.
 
Companies often rush to implement AI without understanding how it will actually improve their business. “They start with the technology, not the outcome,” Hall states. “They can’t articulate what success looks like.” Without a clear hypothesis of what AI will do and the value it will drive, the initiative flounders.
 
Messy, redundant, and poorly labeled data is one of the most common obstacles to AI success. One of Coginiti’s clients, for example, had been using a cloud-based sales system for years. They wanted to deploy AI to optimize their sales pipeline. But their sales opportunity record had ballooned to 250 columns with four different fields just for purchase orders.
“Over time, processes change, people add fields, create nicknames, and now AI has no idea which one to use,” Hall explains. “You’re asking an algorithm to make sense of something even your sales team doesn’t fully understand.” Without clearly named, clean, and integrated data, no AI can deliver value.

Even when an AI model is successfully trained in a pilot program, many businesses struggle to scale it. That’s because they haven’t built clear bridges between their test environments and real-world operations. “You might have something that works in isolation, but integrating it into your existing systems, your workflows, your infrastructure, that’s where everything breaks down,” Hall says.
 
To solve these problems, Coginiti helps organizations build a digital twin, a virtual representation of how the business actually works. A digital twin isn’t just a model or a dashboard; it’s a semantic representation that maps your business processes, data, and systems in a structured, meaningful way.
 
“When you have a digital twin integrated into your system,” Hall says, “you can simulate change. You can say: ‘If we improve this process, we’ll see this benefit.’ It aligns your AI efforts to business value from the beginning.”
 
The digital twin acts as a translator between your messy, physical reality and a logical business model that AI can understand. It defines your data layer clearly and exposes it to AI tools in a way that is consistent and scalable.
 
A digital twin starts with understanding how your business actually runs. What are the key value chains? What are the metrics for improvement? This means data will be well-defined, consistently named, and logically organized. “The semantic model is the heart of a digital twin,” Hall says. “It’s what allows AI to interface with your business meaningfully.”
 
A true digital twin links clean, logical models to real-world data across systems: CRMs, ERPs, call centers, data warehouses, and more. A digital twin further pulls from across departments and platforms, ensuring a single, unified source of truth. With the integration in place, businesses can use AI agents to model changes, test new processes, and develop rapid pilots that can easily be deployed in production.
 
Ultimately, AI is not a magic bullet. It’s a powerful tool, but only as powerful as the foundation it rests on. “Think of AI as a new room in your house. If the blueprint is vague and the bricks are cracked, even the best architect can’t build a stable structure,” Hall compares. “The companies that invest in doing this the right way today will be tomorrow’s leaders.” Coginiti can help you with the transformation. 

Read more
Shaping Enterprise resilience through cybersecurity and software quality

The lines between software quality and cybersecurity are starting to blur in the online world. Companies can’t afford to think of them as separate issues anymore. A bug in the code can just as easily become an open door for hackers, and security gaps often trace back to how the software was built. According to Cybersecurity Ventures, cybercrime is expected to cost the world $10.5 trillion annually by 2025, highlighting the significant risks for companies, governments, and national defense systems. Cybersecurity today involves protecting private data, safeguarding critical infrastructure, maintaining public trust, and supporting the stability of economies. Gopinath Kathiresan is working to bridge these critical areas. As a seasoned quality engineering expert, he’s helping businesses build safer, stronger systems.

The Business Imperative: Quality and Security as Two Sides of the Same Coin
With more than 15 years working at the forefront of software quality and automation, Kathiresan understands that getting software ‘right’ is not just about avoiding bugs; it’s also about maintaining trust. Currently, each mistake incurs hundreds of thousands of dollars in the digital economy. Customers do not just want perfection—they expect it. When something goes wrong, they will not just lose users; they will lose their reputation and earnings as well.

Read more