Depin: Decentralized Physical Infrastructure Network
While depin projects in theory try to provide real tools to crypto, there are few who really solve problems in real life have a sensible business model capable of disturbing existing businesses and cannot be easily falsified. Most are simply solutions in search of a problem. A remarkable exception is a floating -track network called Wingbits. Why? Because it solves a web2 problem by solving it with web3inchitaments. For anyone who has ever traced a flight like BA117 from London to New York, you may have used sites like Flightaware or Flight Tradar.
Figure 1: Wingbits Flight Tracking Map
Source: Wingbits – Transforming Flight Tracking.
Flight-tracking companies generate millions in revenue by selling flight data to carriers and to buyers as financial analysts who monitor private jet movements for mergers and acquisitions. These companies also earn revenue from ads and subscriptions on their platforms. However, their capital costs do not include significant infrastructure and hardware expenses. This is because aviation monitoring technology, called ADS-B recipients, is a hardware that requires antennas and Raspberry Pi’s, purchased and configured by aviation enthusiasts. These enthusiasts expect a little in return and often just receive a free subscription to their favorite floating tracking platform.
The main problem is that enthusiasts are not incentive to maximize the quality of data for these networks. Without marginal incentives, ADS-B recipients are often poorly located-for example in lounge rum corners or over-consumption in densely populated urban areas, leading to weak coverage in rural areas.
Figure 2: (LHS) Traditional ADS-B receiver, (RHS) Wingbits mines
Source: Wingbits – Transforming Flight Tracking.
Wingbits revolutionize flight tracking by incenting enthusiasts to create stations strategically, based on height, while using a system similar to Uber’s hexagonal hierarchical spatial index. This approach ensures optimized coverage, higher quality data and most importantly, fair rewards for contributors to the network. They obtained coverage of 75% of the largest network with only 1/11. The number of wingbits stations. This high level of efficiency combined with an expected roll -out of 4,000+ stations is expected to surpass traditional flight tracking networks with a significant margin that provides data for better quality to end customers.
The next family dinner interview explaining this concept will easily come, as we can now point to a real use of use, driven by cryptoincitaments that everyday people can understand.
Crypto x AI
Similar to market cycles, the demand for calculated experiences is tops and troughs. GPUs can be expensive and supply restrictions make them even more. It is not a new concept to unlock the inactive calculation on consumer units, but to solve the synchronization challenge across multiple devices. Exo Labs is a groundbreaking project that achieves breakthroughs in edge -computing that allows users to run models on everyday consumer quality units, such as household mac books. This means that sensitive data remains under your control, reducing risks associated with cloud -based storage or treatment.
Figure 3: A 9-layer model is divided into 3 cuts each running on a separate unit
Source: Transparent Benchmarks – 12 days with Exo, Exo Labs.
Exo Labs has developed a new software infrastructure called Pipeline Parallel Inference, which allows you to detect a large language model (LLM) in “SKRER” so that different devices can run separate parts of the model while it remains connected to the same network. This approach provides various benefits such as reduced latency, improved safety, cost -effectiveness and most importantly confidentiality benefits.
Investigation of privacy further reveals Bagel AI, a project that has developed Zlora (Zero-Knowledge Low-Rank adaptation), a privacy conservation approach to fine-tuning LLMs. This innovation enables the creation of specialized models for industries such as legal services, healthcare and financing, which allows sensitive data to be used for reinforcement learning without risking confidential information leaks.
While Privacy Preservation is a hot topic, a greater challenge for most LLMs is the hallucination problem, a response generated by AI that contains false or misleading information presented as a fact. A portfolio manager once told me, “Wisdom lies in synthesizing competing views to reveal the nuanced truth between two extremes.” Blocksense is a project that has developed a proprietary approach called the ZKSchellingcoin consensus. This method aims to overlay subjective truths from several sources – say, different LLMs – to reach a single, common truth. For example, imagine running the same inquiry across chatgpt, claude, well and llama. If a model gives the wrong output, it is statistically unlikely that all four models will generate the same false result compared to each other.
Figure 4: Overview of ZKSchellingCoin -Consensus
Source: Blocksense Network – ZK -Rollup for programmable oracles.
The ZKSchellingcoin consensus could also be used to add verifiable to AI -Inference. How can we, for example, confirm that an AI agent correctly brought USDC into the highest displacement vault at the time of execution? Trust in AI would be significantly strengthened with a further verification layer. If we can solve this without compromising costs or latency, it can lead to a major breakthrough in the real world.
The journey from hype to reality in depin and AI shows that real innovation lies in solving problems in the real world with practical and effective solutions. Projects such as Wingbits and EXO Labs prove how blockchain and AI can create meaningful influence-What is revolutionizing flight tracking with strategic incentives or locking consumer devices for safe and cost-effective computing. With progress like Zlora to privacy with AI and ZKSchellingcoin for verifiable truth, these new technologies are ready to tackle critical challenges and pave the way for a more decentralized, effective and trusting future.
