Insights From Hack Seasons Singapore: Speakers Share How AI Can Accelerate Web3 Development
At the beginning of October, the Hack Seasons Conference was held in Singapore, bringing collectively main professionals to look at the most recent developments in AI, Web3, blockchain, and cryptocurrency. One of the day’s most notable panels, titled “AI: The Logic and Intelligence Layer Web3 Needs?,” centered on how AI-driven analytics can improve on-chain exercise, creating sooner, smarter, and extra adaptive ecosystems. The dialogue, moderated by Igor Lessio, CEO of AIFlow, featured distinguished figures together with Will Carter, CTO of Lamina1; Lane Retting, Head of Research at Near Foundation; Dillon Chen, Founder and CEO of Common; and Aaron Ramirez, AI Software Engineer at Flipside.
The dialogue started with an acknowledgment that Web2 and Web3 differ within the velocity of improvement, prompting the query of what at present prevents Web3 from reaching the identical tempo as Web2.
Panelists agreed that Web3 is transferring slower than Web2, however emphasised that this isn’t essentially a disadvantage—it’s, in some ways, a function. Unlike Web2, Web3 prioritizes safety and finality. Building in Web3 requires cautious implementation of guardrails to make sure that decentralization is preserved and that reliance on opaque programs, resembling black-box massive language fashions, doesn’t introduce new dangers. Web3 builders should remedy distinctive challenges that Web2 doesn’t even encounter.
The panel additional highlighted that human programs in Web3 carefully mirror technical programs. In a centralized Web2 software, builders can depend on a central database or oracle to attain high throughput, quick transactions, and scale—however this comes at the price of centralization. By distinction, utilizing a blockchain in Web3 is slower and costlier, however it offers immutability and different core decentralized options. The slower tempo additionally extends to the social layer, the place decentralized governance processes and community-driven decision-making contribute to raised long-term outcomes, even when they sluggish improvement. AI brokers, the panel famous, can assist mitigate a few of these inefficiencies by automating repetitive duties or supporting governance, successfully accelerating sure features of decentralized processes.
Another level raised was that improvements in cryptocurrency area usually stay invisible to finish customers. Mechanisms resembling consensus protocols and social governance layers function behind the scenes, very like developments within the open-source AI neighborhood, which could be months behind the most recent cutting-edge analysis.
A recurring theme was safety. Unlike Web2, the place velocity usually takes priority over safety, Web3’s major focus is safety and reliability, which naturally slows product launch cycles. Panelists urged that Web3 groups can leverage AI instruments strategically to streamline improvement and speed up launches with out compromising security, thereby combining the advantages of decentralization with extra environment friendly manufacturing.
Balancing Decentralization And AI: Privacy, Transparency, And Multi-Agent Systems In Web3
The dialog shifted to the subject of decentralization, a core precept of Web3, and the way it intersects with AI, which regularly represents centralized intelligence. Panelists explored methods for sustaining decentralization of intelligence whereas leveraging AI applied sciences.
Privacy in AI fashions stays a problem, significantly when programs function remotely. In follow, most builders prioritize efficiency over privateness for a lot of purposes. On-device AI presents one method to protect person knowledge for restricted use circumstances, however units like smartphones can solely run fashions of restricted dimension, making a trade-off between efficiency, functionality, and privateness. The panel famous that most people usually prioritizes comfort over privateness, choosing platforms which will exploit person knowledge, citing examples resembling WhatsApp and TikTok. However, smaller, focused instruments—resembling onboarding purposes—can profit from native AI frameworks that translate technical knowledge into user-friendly, intent-based interactions. Despite these options, AI fashions stay largely opaque black containers, and extra clear alternate options are wanted.
Speakers emphasised the significance of open and verifiable mannequin coaching, together with cryptographic proofs that guarantee AI pipelines and on-device inference processes are reliable. They admitted that two years in the past they’d been overly optimistic concerning the public’s concern for privateness and verifiability. Today, whereas mass consciousness stays restricted, there are market segments that prioritize privateness, representing a major alternative in a probably trillion-dollar market.
Beyond privateness, panelists mentioned present limitations of AI fashions, noting that even superior programs like ChatGPT can produce inconsistent outputs for a similar queries. User expertise, multi-agent programs, and decision-making processes are key areas requiring enchancment. On belief, the panel underscored the necessity for corporations to offer transparency concerning the knowledge AI brokers use.
Looking forward, the dialogue urged that reliance on a single AI supplier is dangerous. Diversifying throughout a number of suppliers, together with open-source fashions, is advisable. Several rising corporations are creating AI merchandise that retailer no person knowledge and make the most of open-source fashions, creating the potential for elevated competitors and extra decentralized, privacy-focused AI options over the subsequent 5 years.
Concluding the dialogue, panelists mirrored on how person expertise (UX) has developed, noting a transparent shift towards chat-based interfaces. They emphasised that the subsequent main wave in client DeFi will probably be formed by experiences just like ChatGPT, the place customers can entry info in fractions of a second. They additional highlighted that this evolution would require rethinking operational approaches to completely embrace this new, streamlined UX, significantly as most interactions now happen on cell units.
The panel famous that customers are more and more conditioned to anticipate quick responses, making each velocity and accuracy essential. At the identical time, they confused the significance of person literacy, mentioning that folks nonetheless want to know how massive language fashions (LLMs) work, together with their limitations, and that outputs ought to all the time be verified.
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