Episode Summary
Executive Summary: The episode centered on NEAR’s rising role as both a crypto asset and an AI infrastructure bet, alongside Bitwise’s new NEAR ETF (ticker NRR). Sal argued NEAR is undervalued because of real usage, revenue-generating intents, and the AI/private inference roadmap, while Hunter explained Bitwise’s long-standing hands-on involvement, staking/validator operations, and how the ETF makes NEAR easier for mainstream investors to access.
Main Topics: Bitwise launches the NEAR ETF (NRR): Hunter introduces Bitwise’s new NEAR ETF and frames it as a new access point for investors to gain exposure to NEAR while Bitwise deepens its support for the ecosystem through research, validators, and infrastructure participation. NEAR Intents and value accrual: Sal explains how NEAR Intents facilitates swaps and other transactions, generates fees from volume, and routes net revenue into buybacks rather than burns, creating a demand sink and long-term value capture mechanism for the token. NEAR as an AI + crypto convergence play: Both guests emphasize NEAR’s positioning at the intersection of AI and crypto, especially through private inference, agentic workflows, and the belief that AI adoption expands NEAR’s addressable market and relevance. Institutional framing and mainstream investor education: Hunter describes how Bitwise explains NEAR to clients in familiar terms—growth, utility, revenue, ecosystem health, and AI exposure—rather than using crypto-native ranking metrics like CoinMarketCap. Fragmentation as a thesis for the future of AI and blockchains: The conversation argues that the future will likely involve many models, agents, chains, and stablecoins rather than one winner-take-all system, making NEAR’s interoperability and privacy focus strategically useful. Privacy, confidentiality, and enterprise demand: The guests discuss increasing consumer and enterprise concern about privacy, arguing that verifiable confidential computing and no-telemetry guarantees may become standard requirements for AI workloads. Market validation and momentum: Sal notes that price appreciation and ecosystem attention have validated the project, while Hunter reports strong early ETF inflows and trading volume as evidence of market demand.
Key Arguments: Bitwise’s involvement with NEAR is not opportunistic; it has been building research, staking, validator, and infrastructure exposure for a long time, reflecting genuine conviction in the protocol. NEAR Intents creates economic value by processing user transactions, charging take rates, and converting activity into protocol revenue and buybacks, which strengthens token value accrual. NEAR should be evaluated not only as a blockchain but as an AI infrastructure platform with exposure to a broader technology stack, especially privacy-preserving inference and agentic systems. Mainstream investors do not think in coin-ranking terms; they respond better to narratives around AI, revenue, utility, ecosystem health, and portfolio construction. The future likely involves multiple AI models and multiple blockchains, so NEAR’s role as a simplifying interoperability layer becomes more valuable in a fragmented world. Privacy is becoming more important for both consumers and enterprises, making NEAR’s confidential-computing approach increasingly relevant as AI adoption grows. ETF access can broaden the investor base for NEAR by making exposure simpler and by matching the maturity of the crypto market with familiar public-market investment vehicles.
Data Points: NEAR price at the time referenced: about $5, after previously being around $1.30 - Sal and David discuss how NEAR’s market price has risen since the previous interview. NEAR Intents volume processed: more than $32 billion - Sal cites cumulative volume processed by NEAR Intents. Tokenized equity support on NEAR Intents: 400 tokenized equity products - Sal says the system recently expanded to swaps involving tokenized equity instruments. ETF early inflows: roughly $50 million in the first three days - Hunter says the ETF saw strong first-week demand, with tweets referencing investor conviction. ETF daily inflows: over $10 million per day - Hunter describes early days of NRR trading as extremely strong. ETF daily volume: $10 million to $20 million per day - Hunter gives trading-volume ranges during the first few days of the ETF. Bitwise AUM: about $16 billion - Hunter uses Bitwise’s scale to explain client access and ecosystem involvement. Bitwise team size: about 150 people - Hunter notes the firm is sizable but cannot do everything across crypto ecosystems. Validator position on NEAR: 4th largest validator - Hunter says Bitwise is operating as a staking/validator provider on NEAR. Current inflation proposal: reduce inflation from 2.5% to 1.6% over two years - Sal references a governance proposal discussing NEAR’s emission schedule.
Pivotal Quotes: "I think near is two to four X underpriced at current human level of adoption." — Sal: Sal’s original thesis, recalled by David, about NEAR’s valuation relative to current usage. "We’ve moved on from the CoinMarketCap era." — Hunter: Hunter explains that investors now think in terms of utility, revenue, and themes like AI rather than token rankings. "It’s not just for me, it’s to the entire ecosystem, the entire developer community." — Sal: Sal describes the ecosystem-wide validation that followed NEAR’s stronger market performance.
Implications: NEAR is being positioned as both a productive crypto asset and an AI infrastructure bet. If usage, buybacks, privacy, and ETF access continue to scale, NEAR could attract a broader institutional audience and gain stronger token value capture.