AI, Web3 and Alpha Trend: Shaping the way organizations do business
The evolution of data creation, storage, and perception
As we find ourselves in 2023, a year full of buzz around Artificial Intelligence (AI) and Web 3.0, it’s worthwhile reflecting on the internet’s history and evolution and its role in shaping how we create, store, and perceive data. While the contemporary AI emergence may seem like a recent phenomenon, its genesis dates to the 1950s. At this time, the concept of AI models was built on rule-based logic and symbolic reasoning, mostly done in written format, since the internet was still a research concept. As the internet emerged — the first version of a digital library access-based model known as Web 1.0 — it shaped how data was stored. In the 80s and 90s, as more text-based digital files emerged, AI models were built on this text data, allowing the formation of natural language processing and machine learning models to recognize patterns and trends.
As the internet grew and more data files emerged, including text and image data, the early 2000s allowed patterns to predict outcomes through decision trees and neural networks. The evolution of the internet, otherwise known as Web 2.0, marked a shift from static web pages to dynamic and interactive content that yielded more data for research, with images, audio, and video becoming integral parts of the internet’s fabric.
Between 2010 and 2020, the increase in computational power and real-time event capture down to nanosecond precision allowed for the emergence of big data. This data was stored in large data warehouses and shaped how we analyze it and guide behavior based on it. Deep learning and cognitive neural network modeling emerged, allowing us to make a significant leap from detective AI (identifying trends) to predictive AI (forecasting outcomes). This period also marked a new internet evolution — Web 3.0 — unlocking new data storage and ownership methods using decentralized and distributed networks such as blockchain.
While the excitement around AI and Web 3.0 surged mainly after the 2020s, these technologies have quietly matured over time. The convergence of the two is now driving the creation of digital files or NFTs, optimization of storage on blockchain, and improvement in transactions through smart contracts, creating more secure, faster, and beneficial outcomes.
Data and AI as the building block of Alpha Trend
Our Alpha Trend journey was built on a long-term 40+ years of expertise in leveraging big data and AI modeling to detect and predict outcomes. The same team behind Alpha Trend built another startup previously, leveraging social media image and text data to detect and predict trends in the retail industry. In early 2021, we saw an opportunity to build the same models on a new type of data prone to social volatility: the valuation of digital assets — cryptocurrencies and non-fungible tokens. The Web 3.0 evolution allowed us to analyze assets and have visibility — through blockchain and smart contracts — on wallets holding those assets and trends in ownership transfer. This was the first version of our product known as Alpha Intel.
Introduction of Web3 infrastructure
While we had initial success in how we analyzed data, we observed a bigger problem in the adoption phase of these assets, recognizing that we were slightly early to wide market adoption with our predictive models. Based on an intake request by one of our large customers, we built infrastructure around creating digital wallets and launching digital assets known as our AlphaLaunch technology. AlphaLaunch consists of two aspects: 1) an admin portal, allowing organizations to set up custodial accounts and launch blockchain-based programs, and 2) a digital storefront, allowing end-customers of those organizations to set up digital wallets, use credit or debit cards for transactions, and to purchase blockchain programs with one button click easily.
With our AlphaIntel and AlphaLaunch technology, we can serve any organization, regardless of where they are on their Web3 journey.
The role generative AI plays in the construction of assets
Access to generative AI technologies marked a significant turning point for our journey, as it allowed us to scale the efforts of digital collectible creation for our customers. Generative AI allowed us to integrate additional offerings to create large digital asset collections as cover art for loyalty memberships and digital collectible applications. Our generative AI models can craft unique digital assets, tokens, and NFT images that resonate with users, tapping into the growing market for collectibles and engagement programs and helping organizations easily capture the benefits of web3 technology.
Final Thoughts
At Alpha Trend, we proudly lead the evolution of business operations using Web3 and AI applications, empowering organizations to understand better and engage with their audiences through secure blockchain data storage and predictive insights. Our journey from data detection to generative innovation reflects technology’s evolution, and we’re actively shaping the future, revolutionizing data, loyalty, and customer engagement in the Web3 world. If you are exploring whether this fits your organization or want to improve how you manage your web3 programs, give us a shout today and see if we can help.
