Web3 AI is becoming a niche, with Web3 companies flocking to AI due to its amazing benefits: data analysis and automation, improved user experience, and security.
1. Data analysis and automation
Web3 companies generate and store vast amounts of data on blockchain networks. AI is critical for extracting data insights, helping these companies monitor network performance and make data-driven decisions. The convergence of Web3 AI has given rise to powerful analytics, which can detect risks and anomalies in real-time, bolstering Web3 platform integrity.
Web3 AI streamlines complex processes. AI-driven automation and smart contracts can handle transactions and verify user identities autonomously, improving efficiency and reducing the need for middlemen. This reduces operational expenses and saves time.
2. Improved user experience
Web3 AI is characterized by decentralized, blockchain-based platforms. The niche enables more user-centric and better experiences. Web3 AI companies can offer more efficient and personalized services. AI-driven algorithms can tailor interactions, content, and recommendations, improving user engagement and satisfaction with Web3 applications.
3. Security
Security is a major concern in Web3, because solid protection is required for decentralized systems. Web3 AI enhances cybersecurity by identifying and mitigating risks, but this process isn’t a simple one. Web3 AI company Aizel Network recently joined peaq to alleviate it and improve security.
Aizel is building a DePIN for running secure, private, and verifiable machine learning models leveraging a variety of technologies to give people more insight into what’s happening under the hood of various AI-powered apps and services. In the longer run, the Web3 AI integration may pave the way for more AI use in critical industries which need utmost transparency and verifiability for their models.
The risks of AI’s growth
As the AI industry continues to bask in the public spotlight, some of its key flaws prompt uncertainty about just how far the boom could go. Security researchers are already exploring various ways of tampering with models and their outputs, which may lead to dramatic consequences in real-world scenarios, from a self-driving car causing an accident to an institutional-grade trading bot crashing an entire economy.
Aizel is building a DePIN for making Web3 AI computations trustless and verifiable. It makes every inference — the processing of a specific input by a trained model — more transparent by combining it with a cryptographically-secured set of metadata. The metadata can include the specific model used to produce the output and any other variables, such as the amount of electricity the process had consumed.
More secure and transparent Web3 AI apps
Aizel taps multi-party computation and trusted execution environments (secure CPU and memory areas) to protect the outputs from tampering. As a result, the user always knows what model produced the output to a desired query, making for more secure and transparent Web3 AI applications — without the kind of scaling constraints that comes with using zero knowledge computation for trustless Web3 AI.
Tapping the home of DePIN as its layer-1 backbone, Aizel will leverage the peaq SDK to make its network compatible with peaq. As part of the integration, it will deploy the smart contracts powering its core logic, including uploading Web3 AI models and user inputs, on peaq. Finally, it will set up a cross-chain module, further connecting its network with peaq, and issue a certain percentage of its token supply natively on the home of DePIN.
Jeremy, co-founder of Aizel Network, commented:
Most of today’s AIs run as closed-off black boxes offering the users little to no insight into what model they are actually interacting with. Aizel unlocks verifiable AI for everyone — and peaq’s powerful fundamentals, Modular DePIN Functions, and a vibrant DePIN ecosystem make it the perfect home for that.
Till Wendler, co-founder of peaq, added:
To live up to its full potential and unlock new use cases, AI needs transparency and verifiability. Web3 AI company Aizel taps the Web3 stack to make that happen, and we’re excited to see it tap peaq as its layer-1 backbone for this important mission.
The future of Web3 AI
Cutting-edge technologies like AI and Web3 are adopted based on an S-shaped trajectory, also known as the S-curve theory. At first, growth is slow. It gets very fast in the middle phase, and when maturity or saturation is reached, it slows down again.
AI has entered the stage of early maturity, while Web3 is still in the early stages of the S-curve. It is gaining traction thanks to the partial merge with AI and the promise of trustless ecosystems and a decentralized internet. However, it still faces challenges related to infrastructure development and regulation. Initially, technologies following the S-curve face limited adoption, but they go mainstream eventually.
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