This episode is a Bittensor catch-up rather than a subnet interview, with Siam back from three weeks in California and Mark writing from Spain. The main focus is the pace of recent BitTensor “upgrades,” especially Root Reborn, validator baskets, deregistration mechanics, conviction, chain buys, and the looming arrival of shorting. Both remain strongly bullish on Bittensor, but argue that the ecosystem is becoming difficult for investors, subnet owners, and potential new teams to navigate because rules are changing quickly and often without enough notice, roadmap clarity, or explanation. Mark frames his recent article as a call for better process rather than a complaint: the issue is not that changes are bad, but that constant changes create fatigue, uncertainty, and make it harder for serious teams and institutional capital to commit.

A major theme is whether price alone is the right mechanism for deciding which subnets survive. They argue current deregistration can become a popularity contest, while real businesses, especially enterprise or research-focused subnets, often need 6–24 months to generate meaningful revenue. They compare this to startups like Tesla, Apple, Anthropic, or enterprise software companies, where patient capital is required before results arrive. Siam also highlights that markets inside Bittensor are still inefficient: tweets, Telegram comments, and short-term narratives can move subnet prices far more than fundamentals. They discuss how Root Reborn and chain buys may create new investment metas, but sudden future changes could instantly break those strategies, which is exactly why clearer process matters.

They also debate conviction and whether it actually protects investors from rug pulls. Both are sceptical, with Siam calling it “virtue signalling” and Mark arguing it may restrict good teams from using alpha to fund growth while not necessarily stopping bad actors. They also warn that conviction plus shorting could increase the power of deep-pocketed players to influence, pressure, or even attack subnets. The closing message is that Bittensor still has huge talent and potential, but the network’s incentive mechanism needs refinement so value, talent, capital, and long-term builders are better aligned. They finish by reinforcing that they are not bearish or moaning; they are pushing for improvements because they believe Bittensor can become much bigger if the ecosystem becomes easier to understand, invest in, and build within.

In this episode, Mark and Siam discuss why they now view Const’s rapid protocol changes more positively: although constant changes can make institutional investors nervous, they argue Const is in “founder beast mode,” trying to fix Bittensor’s core mechanics before the network scales. They focus heavily on “Root Reborn,” especially the distinction between emissions and injections: miner/validator/subnet-owner emissions are not what’s changing; the new formula affects liquidity-pool injections, rewarding subnets with stronger root proportion, stronger EMA price, and lower miner burn. They frame this as a way to stop zombie subnets, reduce gaming, and reward teams that are actually producing value.

They also cover the new “naughty list” / injection-eligibility list, arguing it is less a punishment list and more a forcing function for subnets to prove their incentive mechanisms work. New subnet registrations now start with injections off by default, meaning teams need to be ready from day one rather than buying a slot and sitting on it. Mark and Siam debate whether this kills the secondary subnet-slot market, why new subnets may now have a better setup than buying old slots, and how the “Goldilocks subnet” might be a new project with high root prop, high starting price, low burn, real product-market fit, and revenue/buyback capacity from launch. They briefly touch on conviction, impending shorting, and then plug DSV’s upcoming “Inside Bittensor” event in London, where they’ll reveal DSV’s first subnet, Subnet 69.

This session starts with Mark and Siam briefly addressing the decision to pivot away from “Handshake”: it didn’t gain the traction they hoped, the team’s focus drifted toward building trading/mining “skills” that didn’t feel like a scalable revenue path, and they chose to “rip the band-aid off” rather than keep a zombie project alive. They argue that in AI (especially on Bittensor) things change fast, so it’s better to redeploy talented builders quickly, even if that decision attracts criticism.

The main segment features Subnet 103 “Djinn,” led by Harry Crane (stats professor with deep prediction markets/sports betting background) and Iosef Gerstein (finance + scientific startups). Djinn’s core idea is a “genius–idiot network”: profitable bettors (“geniuses”) have an edge but get limited/banned by sportsbooks, while the mass of recreational bettors (“idiots,” i.e., accounts that can still place bets) can execute. Djinn is building a trustless, privacy-preserving information exchange to connect the two—geniuses sell time-sensitive betting signals, buyers execute them wherever they have access (Bet365, Polymarket, etc.), and the protocol uses Bittensor miners/validators for verification and obfuscation (including decoys) so neither Djinn nor outsiders can easily steal signals. Revenue is expected to come from transaction fees (they discuss ~0.5% as a working idea), with buybacks/utility mechanisms considered to support alpha; they’re currently moving from fake-money testing to low-stakes real-money testing and say they’ll launch only when they’re confident it’s safe.

This episode, Mark discloses that DSV is already invested in today’s subnet, but they’ll still ask the awkward questions. They bring on Koyuki (“special k”) from San Francisco, who shares her background in AI (web2 + web3), how she joined the Bittensor Foundation/OTF as Head of AI, and then dives into her slides on Subnet 78, Vocence.

Koyuki pitches Vosens as a decentralized “voice intelligence layer” on Bittensor, targeting the rapidly growing voice AI market and competing with incumbents like ElevenLabs by being more open, cheaper, and driven by Bittensor incentives. She shows that Vocence already has a live studio product (TTS/STT, voice cloning/design, text-to-music, API) and outlines how miners submit models that validators score across nine dimensions (script accuracy and naturalness weighted highest), with winning models becoming the new baseline for inference. On revenue, she describes a credit-based SaaS model (consumer + API, with enterprise as the big upside), plans for buybacks into a treasury, and an emissions burn condition if no model clears a defined improvement threshold. The discussion then focuses on the “Turing test” problem for voice agents—latency, filler words, interruptions, and overlapping speech—and Koyuki claims a new “style trajectory TTS” approach will make agents sound truly human soon. Siam offers a $5,000 wager that Vocence can produce a voice agent he can’t detect as AI by the end of the month, and Koyuki accepts, with some talk about testing via a phone-call scenario and adversarial off-script questions. They wrap by noting the prior Vocence slot issues/deregistration risk and arguing this time is different due to stronger leadership, a live product, faster shipping, and early traction.

In this episode, Bob from Subnet 48 (quantum compute) gives a grounded overview of quantum computing: huge long-term promise (materials, batteries, drug simulation), but today’s machines are still “NISQ” (noisy, intermediate-scale, not error-corrected at useful scale). Subnet 48’s pitch is essentially “Airbnb for quantum computers”—miners run real quantum workloads, users submit quantum circuits, and the network executes them cheaper than traditional access. Bob shows OpenQuantum.com as the front-end marketplace, listing multiple hardware providers (IonQ, Rigetti, IQM, AQT) with current machines in the ~20–50 qubit range, and explains that most jobs on OpenQuantum are being executed via Subnet 48.

The conversation then veers into the big scary question: quantum risk to crypto. Bob distinguishes SHA-256 (mining) from elliptic curve cryptography (ownership/signing) and argues the nearer-term threat isn’t quantum “mining Bitcoin faster,” but breaking signature security unless chains migrate to post-quantum schemes. He mentions industry roadmaps and research suggesting timelines could be tighter than people assume, and plugs Subnet 63 (Enigma)—a prize-driven subnet designed to incentivize public breakthroughs in cryptography rather than vague claims.

In this Revenue Search episode, the hosts sit down with Aldo from Subnet 55 (NIOME / “Neural Intelligence in Omics”)—a project tackling one of the messiest problems in biotech: how to make genomic/biodata usable for research and AI without turning it into a privacy and cybersecurity nightmare. Aldo walks through why the status quo is broken, pointing to repeated breaches and misuse across the industry (from direct-to-consumer testing firms to major institutions), and makes the case that “compliance” doesn’t equal “security” when hackers are actively targeting sensitive health data.

NIOME’s approach is twofold. First, through the wider genomes.io ecosystem, individuals can store their DNA data in encrypted “vaults” where the user remains the owner and controls access—rather than handing away rights to hospitals or platforms. Second, the subnet’s core mission is to generate synthetic genomic / biodata at scale—so pharma, biotech, and researchers can train models and run analyses without exposing raw identifiable datasets. The roadmap is built around a structured series of predictive challenges (starting with cystic fibrosis / CFTR), with commercial interest already forming around bespoke challenges, licensing outputs, and data brokerage partnerships (e.g., bringing external datasets into the synthetic pipeline and sharing revenue when that data is used). The big idea: make biodata safe, precise, and scalable and use Bittensor’s open, inspectable “under-the-hood” model development to build trust versus black-box approaches.

This episode brings the long-awaited sequel with Jake (Investing 88) and Alex (Trusted Stake). They recap how the two teams teamed up to build Subnet 118 / HODL, a joint venture focused on making subnet investing less painful by reducing slippage, improving liquidity, and smoothing out the constant rotation/volatility that comes from trading directly against shallow alpha pools.

The core product is the HODL Exchange: a secondary-market style, automated escrow/order-book layer that lets users buy and sell TAO ↔ alpha with far less price impact than the native AMM pools. Instead of “one big swap” causing huge slippage, orders can be partially filled over time by counterparties (including incentivised market makers / IMMs) who earn subnet emissions for providing fill volume, plus there’s a private-order option for direct counterparties. The plan is to introduce a dynamic fee model that charges a small share of the slippage saved (e.g., taking ~15% of the saved slippage so users still keep ~85% of the benefit), with fees after OPEX used for buybacks. They also discuss how this matters even more if the subnet cap rises and liquidity gets thinner across more subnets.

Revenue Search returns with the usual chaos and banter, then introduces Josh and the launch of Green Compute—a new Bittensor compute subnet designed specifically for enterprise-grade inference workloads. Josh shares his background building and selling GPU infrastructure in the UK since 2017, and explains that Green Compute plugs into an already-profitable compute business with existing customers, contracts, and deployment experience—so the subnet isn’t starting from zero.

The core thesis: bring data centers to constrained renewable energy. Across the UK (and beyond), farms and renewable sites often generate power the grid can’t accept—so it’s wasted. Green Compute turns that stranded power (solar, wind, hydro, and especially anaerobic digestion / biogas) into usable AI compute, offering site owners far higher returns than exporting electricity back to the grid. Unlike “spot” compute markets, Green Compute is aiming at longer-term, high-volume enterprise deals that require symmetry (large clusters of identical GPUs, networking, CPUs/RAM/storage) plus real human support (sales + engineers) and predictable uptime—things many existing marketplaces struggle to guarantee.

They also touch on tokenomics and onboarding: compute can be bought with fiat, but the goal is to push real-world customers toward paying via subnet alpha over time (creating buy pressure). Mining is gated by standards (e.g., high-bandwidth connectivity and matching hardware) to meet enterprise requirements, with a process for miners to apply and be verified—including the “green” power source. The team plans to update naming/branding and community channels shortly, with more details and access via the Green Compute website.

Revenue Search returns with the usual banter (and a bit of tech lag) before welcoming Bitrecs (Subnet 122)—a small, doxxed team building an LLM-powered product recommendation engine for e-commerce, starting with Shopify. Dimitri (CEO), Max (CTO) and Arsham (CRO) explain how their widget boosts store performance by generating smarter “you might also like” suggestions, then cleaning messy LLM outputs with a consensus/ranking layer. They show live examples on real stores, including a unique feature: explanations (“reasoning”) displayed to end-users for why each recommendation was chosen.

They also introduce Bitrecs V2, which separates the product into a fast Web2 inference layer (serving real-time recommendations) and a Bittensor “intelligence” layer where miners compete in a winner-take-all prompt-template (“artifact”) evolution game. Bitrecs shares business traction (~130 customers), metrics (avg ~$32/month ARPU, ~$75 CAC, ~1% lift so far with a goal of 2–5%+), and a clear growth plan: deploy a six-figure marketing budget, aim for ~1,000 stores, ship a self-serve API for non-Shopify/enterprise use, and (once trust + lift improve) transition toward performance-based billing / revenue share so stores pay only on measurable uplift.

Revenue Search is back after the Bittensor San Francisco event, and this episode is a first: a dual-subnet session with Yanez (SN54) and BitMind (SN34). Jose and Ken announce a partnership aimed at tackling the rapidly growing threat of deepfake-driven identity fraud—the kind of attacks that can bypass KYC, liveness checks, and even enable high-value social engineering scams.

In short: Yanez produces high-fidelity, well-annotated synthetic identity/face data and attack vectors, and BitMind uses that to train and improve face-focused deepfake detection models via their subnet. They’ll take the combined “data + detection” stack to enterprise customers (financial institutions and identity providers), typically via licensing/usage-based deals, with both teams reinforcing that real-world revenue supports their subnets (including alpha buybacks into treasury) while keeping flexibility for future DeFi/treasury use.