Ethereum Classic ($ETC ) is the original Ethereum blockchain that preserves the principle of blockchain immutability. It supports smart contracts and decentralized applications while maintaining its independent ecosystem. Continued adoption of decentralized applications could strengthen ETC's long-term value.
Holoworld AI ($HOLO ) is an AI-powered Web3 platform focused on creating interactive digital characters and immersive virtual experiences. It combines artificial intelligence with blockchain ownership and creator tools. Growing interest in AI entertainment could support HOLO's long-term growth.
Boundless ($ZKC ) is a zero-knowledge infrastructure project that leverages cryptographic proofs to improve blockchain scalability, privacy, and verifiable computation. It enables developers to build efficient and secure decentralized applications. Increased adoption of zero-knowledge technology could strengthen ZKC's long-term potential.
SAPIEN ($SAPIEN ) is a decentralized AI project focused on building human-verified data networks for training artificial intelligence models. It rewards contributors for high-quality data while supporting transparent AI development. Rising demand for AI data infrastructure could support SAPIEN's ecosystem.
Sign ($SIGN ) is a blockchain infrastructure project focused on decentralized identity, credential verification, and on-chain attestations. It enables individuals and organizations to verify information securely without relying on centralized authorities. Growing adoption of decentralized identity solutions could strengthen SIGN's long-term ecosystem.
Vanar ($VANRY ) is a Layer-1 blockchain built for AI, gaming, entertainment, and real-world asset applications. It focuses on scalability, low transaction costs, and developer-friendly infrastructure. Continued ecosystem expansion could support VANRY's long-term growth.
Plasma ($XPL ) is a blockchain infrastructure project designed to improve scalability, transaction throughput, and interoperability for decentralized applications. It aims to provide high-performance infrastructure for the next generation of Web3 services. Continued development could strengthen XPL's long-term potential.
Dusk ($DUSK ) is a privacy-focused Layer-1 blockchain built for regulated financial applications, tokenized securities, and compliant decentralized finance. It combines confidentiality with regulatory compatibility. Growing institutional blockchain adoption could enhance DUSK's long-term value.
DeepBook ($DEEP ) is the native token of the DeepBook decentralized order book ecosystem on the Sui blockchain. It supports governance, incentives, and liquidity while enabling efficient on-chain trading. Growth of the Sui ecosystem could strengthen DEEP's long-term outlook.
I’ve been spending some time trying to understand how exchanges handle liquidation losses once an Insurance Fund is no longer enough. The deeper I looked into GRVT, the more I realized the answer isn’t as simple as I first thought.
From what I understand, the Insurance Fund is the first line of defense. But if it falls into negative equity because of unprofitable liquidations, GRVT temporarily applies a Socialized Loss Haircut to withdrawals until the fund is restored.
What I find interesting is that timing can completely change the outcome.
If I need to withdraw while the deficit is active, I could receive less because of the haircut. If I decide to wait and the Insurance Fund recovers through future liquidations or additional capital, I may avoid that reduction altogether.
I can see why GRVT chose this approach. It helps protect the platform from making the deficit even worse during periods of stress. At the same time, it makes me wonder whether the burden is being shared in the most balanced way.
I don't think there's an obvious right or wrong answer. Part of me sees it as a practical way to protect solvency, while another part feels that the people who happen to need liquidity first end up carrying more of the impact.
It left me thinking about a simple question: when an Insurance Fund isn't enough, should the cost be shared across everyone with exposure, or is it more reasonable for withdrawals during the recovery period to absorb the deficit first?
Newton Protocol NEWT The Trust Layer for Autonomous AI
I spend a lot of time reading about AI and crypto, and honestly, most projects start sounding the same after a while. Everyone talks about smarter models, faster execution, or the next big breakthrough. But the question I keep coming back to is much simples: Can I actually trust AI to act on my behalf? That question is what made me spend more time looking into Newton Protocol (NEWT). The more I read, the more I felt the project isn't trying to build the smartest AI. It's trying to build the rules that AI should follow. To me, that's a much more important problem to solve. If AI is going to manage wallets, execute trades, or interact with smart contracts, it shouldn't have unlimited freedom. I want to know exactly what it's allowed to do, what it's not allowed to do, and whether those actions can be verified afterward. That's the direction Newton Protocol seems to be taking by building a secure authorization layer for AI agents on-chain. Something else that stood out to me is how much attention the team gives to security. Features like Trusted Execution Environments (TEEs) and zero-knowledge proofs might sound technical, but the idea behind them is actually pretty simple. They help make sure AI agents can carry out tasks securely while giving users confidence that the process hasn't been tampered with. I also don't think this is only about automated trading, even though that's one of the obvious use cases. If AI keeps becoming part of Web3, it could eventually help with portfolio management, payments, treasury operations, and many other on-chain activities. None of that works at scale unless people trust the system first, and I think Newton Protocol understands that. Another part I find interesting is the growing ecosystem around the project. Developers can publish AI models through the protocol, while operators provide the infrastructure needed to run them. Since operators have economic incentives tied to their behavior, the network encourages reliability instead of simply asking users to trust whoever is running an AI agent. Recent updates also show the team thinking beyond today's market. Their work around identity verification, policy-based permissions, and secure execution makes me feel they're building for a future where AI isn't just experimenting with blockchain—it becomes a normal part of how people interact with it. I'm not saying Newton Protocol will solve every challenge in AI or become the biggest project in the space. No one can know that. But I do think it's asking the right questions at the right time. For me, the future of AI in crypto won't be decided by which model is the smartest. It'll probably be decided by which protocol makes automation feel safe enough for people to actually use. Right now, that's the reason Newton Protocol continues to hold my attention, and I'm genuinely interested to see where the project goes next. @NewtonProtocol #Newt $NEWT
@NewtonProtocol I've been reading more about Newton Protocol, and what keeps me interested isn't the AI narrative itself. It's the idea that automation shouldn't run without clear rules.
The more I think about it, the more I feel that fast execution isn't the biggest challenge. It's making sure AI knows what it's allowed to do before it touches real assets.
That's what I find interesting about Newton Protocol. Instead of only focusing on automation, it's building around authorization with things like policy rules, spending limits, identity-aware permissions, verifiable credentials, and zero-knowledge proofs.
I don't know how the space will evolve, but I do think trust will matter just as much as intelligence. If AI is going to play a bigger role in onchain finance, projects like Newton Protocol that focus on accountability are worth paying attention to
iShares MSCI South Korea ETF ($EWYB ) is a tokenized ETF providing exposure to major South Korean companies across technology, manufacturing, finance, and consumer sectors. It offers diversified access to one of Asia's largest and most advanced economies.
Tesla ($TSLAB ) is a tokenized stock tracking Tesla, a global leader in electric vehicles, energy storage, robotics, and AI technologies. Long-term growth depends on EV adoption, autonomous driving, and continued innovation across its technology businesses.
Strategy ($MSTRB ) is a tokenized stock representing Strategy (formerly MicroStrategy), a company known for its large Bitcoin holdings alongside its enterprise software business. Its performance is often closely linked to Bitcoin's market movements.
NVIDIA ($NVDAB ) is a tokenized stock representing NVIDIA, a global leader in AI processors, GPUs, and accelerated computing. Strong demand for artificial intelligence, gaming, and data center technologies continues to support NVIDIA's long-term growth potential.
SpaceX ($SPCXB ) is a tokenized stock that tracks the value of SpaceX, the private aerospace company behind Falcon rockets and the Starlink satellite network. It gives traders blockchain-based exposure to one of the world's leading space technology companies. Future commercial expansion could support long-term interest.
SanDisk ($SNDKB ) is a tokenized stock representing SanDisk, a global leader in flash memory, SSDs, and digital storage solutions. Rising demand from AI, cloud computing, and consumer electronics could support the company's long-term growth and investor interest.
Micron Technology ($MUB ) is a tokenized stock tracking Micron, a major producer of DRAM and NAND memory chips. The company's products are essential for AI, data centers, cloud infrastructure, and advanced computing. Continued growth in semiconductor demand could strengthen its long-term outlook.
Circle Internet Group ($CRCLB ) is a tokenized stock linked to Circle, the company behind the USDC stablecoin and blockchain payment infrastructure. As regulated digital payments and stablecoin adoption expand, Circle could benefit from increasing institutional and enterprise demand.