Travis Millott: Tao Templar, Bittensor Subnets, Dynamic Tao, Mining, Crypto Education | Ep. 44

This episode of the Ventura Labs podcast features Travis Millott (Tao Templar) demystifying Bittensor's permissionless market dynamics, exploring its potential beyond AI, and offering crucial insights for navigating its evolving ecosystem for investors and researchers.

Introducing Travis Millott (Tao Templar) and His Crypto Journey

• Travis Millott, known in the community as Tao Templar, shares his background as a software developer for 15 years with an interest in cryptocurrency since 2013.
• He discovered Bittensor about a year ago through "Siam Kid's" trading course, initially intrigued by the "AI plus crypto" concept, but soon realized its potential was "way, way bigger than that."
• Travis describes himself as completely engrossed in the Bittensor ecosystem, to the point where it has "completely engulfed my life."
• His previous hobbies included gaming and playing soccer with his kids, which he now does less of due to his focus on Bittensor.

The Genesis of Tao Templar: Visualizing Bittensor

• Travis explains that he has difficulty visualizing images mentally (a condition sometimes referred to as aphantasia). This led him to create visual aids to understand Bittensor.
• He couldn't find existing videos that clearly explained Bittensor's interconnected components.
• "Basically I drew it out to because my brain isn't capable of it so that I could see what the interconnectedness of all the parts," Travis states, explaining the origin of his whiteboard videos.
• The Tao Templar channel began as a personal project to help himself visualize how miners, validators, subnet owners, and stakers interact within the Bittensor system, eventually sharing it with friends and then a wider audience.
• The name "Tao Templar" was chosen due to his deep passion for Bittensor, likening it to an almost "religious conviction," and his fondness for alliteration.

Early Learning and Understanding Bittensor

• Travis's initial approach to learning Bittensor involved watching all available interviews and online discussions, rather than diving deep into math-heavy whitepapers.
• He found the Bittensor whitepaper difficult to understand due to its advanced mathematical concepts.
• He actively engaged with the community on Discord, asking questions to build his understanding.

Defining Bittensor: Beyond AI

• Travis describes Bittensor as a "crowdsourcing network for any digital information," comparing it to a "gig economy plus crowdsourcing plus crypto."
• He initially likens it to a commodities market where any commodity (a raw material or primary agricultural product that can be bought and sold, or in a digital context, a standardized unit of data or computation) can be traded.
• While acknowledging Bittensor is "built for AI and it works very well for AI," Travis emphasizes it's not limited to AI.
  • He offers a speculative example of a brick-and-mortar store running on Bittensor, with validators acting as managers checking employee performance and miners being actual people or robots.
• Strategic Implication: Investors and researchers should consider Bittensor's broader utility beyond AI, as its core mechanism can incentivize various forms of digital work and information exchange, potentially opening up unforeseen markets.

Bittensor as an Incentive Layer and Free Market

• Travis strongly agrees with classifying Bittensor as an "incentive layer," stating, "incentives is like how we all interact in a developed economy."
• He draws parallels between Bittensor and free trade, asserting that Bittensor is "the closest thing in the world to a free market."
  • The key distinction from traditional markets like the stock market is Bittensor's permissionless nature.
  • Travis explains, "anyone can compete, anybody can get involved. There's no gatekeepers... anybody can register a bit tensor subnet... There's no one that you need to ask permission from."
• This means legal barriers are largely removed, replaced by economic barriers related to Tao (the native cryptocurrency of the Bittensor network, used for staking, governance, and accessing services) ownership.
• Actionable Insight: The permissionless nature of Bittensor fosters rapid innovation and competition. Investors should look for subnets that leverage this to attract talent and create value efficiently, unhindered by traditional gatekeeping.

Navigating Subnet Politics and Controversies: The LolaCost Example

• Travis acknowledges past concerns about "backroom deals" or "cabals" (a secret political clique or faction) within Bittensor, particularly before Dynamic Tao (a mechanism that adjusts Tao emissions to subnets based on their perceived value and performance, creating a more competitive market for rewards).
• He discusses the "LolaCost" subnet (Subnet 28) incident, where a subnet was registered purely as a meme, rewarding miners for holding its token.
  • The "F validator" (Opentensor Foundation validator) intervened by acquiring over 50% of the validator weight and changing the subnet's code to incentivize selling the token, effectively crashing it.
• Travis initially disagreed with shutting down a meme subnet but came to appreciate that the F validator acted "through their power of holding a lot of stake in the network," not through their developer privileges.
  • "They did what anybody else could have done, which I mean like to me that's really cool," he notes, highlighting the use of existing market mechanisms.
• This was achieved through child keying, where other validators delegate their stake to a lead validator, consolidating voting power.
• Strategic Consideration: This incident demonstrates that even in a decentralized system, significant stake can influence subnet outcomes. Researchers should analyze stake distribution and potential for such coordinated actions on various subnets.

Survivorship Bias in Prediction Subnets

• Travis expresses concerns about survivorship bias in prediction subnets. Survivorship bias is a cognitive bias that occurs when focusing on the "survivors" of a particular process and inadvertently ignoring those that did not survive due to their lack of visibility.
• He questions the reliability of statistics from prediction subnets if they don't account for miners who performed poorly and were deregistered.
  • "My concern there is that if we're not counting the miners that dropped out of the network, how can we be confident that copying all of the trades is actually a profitable strategy?"
• Drawing on his decade of experience with data analysis, Travis emphasizes his skepticism towards presented statistics without a deep understanding of the underlying data and methodology.
• Actionable Insight: Investors should critically evaluate performance data from prediction subnets, questioning whether it accounts for deregistered (failed) miners. A lack of transparency here could indicate misleading performance metrics. Travis advises caution and deeper due diligence for these types of subnets.

Evaluating and Investing in Niche Subnets

• Travis acknowledges the difficulty in evaluating subnets in highly specialized fields requiring deep machine learning expertise.
• He personally tries to increase his knowledge but avoids investing in areas he doesn't understand well enough, particularly prediction subnets due to data concerns.
• He contrasts this with subnets like Bitcast (a subnet focused on video content, which he mines), where the output and functionality are more transparent and verifiable.
• Strategic Implication: Investors should prioritize understanding the core mechanics and value proposition of a subnet. If direct expertise is lacking, focusing on transparency, team responsiveness, and community validation becomes crucial.

Dynamic Tao and Investment Caution

• Travis mentions developing trading bots and strategies for Dynamic Tao, a system where subnets compete for Tao emissions based on their market-perceived value, allowing for subnet-specific tokens to be traded.
• However, he advises caution for casual investors: "I think it's probably safe to just kind of stay out of dynamic towel right now. If you're just like a casual investor."
• He has heard stories of significant losses and emphasizes that "it's a market. You can lose everything still."
• Travis himself takes a cautious approach, investing less than 5% of his portfolio in Dynamic Tao assets, highlighting the preciousness and increasing difficulty of mining raw Tao.
• The increasing competition for mining Tao, he argues, inherently drives its value up.
• Actionable Insight: Dynamic Tao introduces new opportunities but also significant volatility and risk. Investors should approach with caution, thorough research, and potentially limit exposure, especially if unfamiliar with the specific subnet dynamics.

The Role and Characteristics of Subnet Owners

• Travis defines a subnet owner as responsible for ensuring the incentive mechanism of their subnet is "flawless." This is crucial for maximizing the value of what miners produce.
• He sees them as "stewards of the incentive mechanism" and also responsible for attracting mining talent.
• Good subnet owners are responsive, helpful to new miners and validators, and provide clear documentation, such as setup guides.
  • "They need to be a proper business owner at this point basically, otherwise they're just going to lose out on emissions."
• Conversely, bad subnet owners are unresponsive and unhelpful, which was more common before Dynamic Tao enforced productivity.
• Strategic Consideration: The quality and engagement of a subnet owner are critical indicators of a subnet's potential success. Investors should assess the owner's communication, support for their community, and ability to refine the incentive mechanism.

Bittensor's Current Weaknesses and Path to Improvement

• Travis identifies two main weaknesses in Bittensor:
  1. Education: The complexity of Bittensor makes it hard to understand. His videos aim to address this.
  2. Decentralization of the Substrate Chain: The underlying blockchain infrastructure of Bittensor is still relatively centralized, which he views as his "biggest worry."
     • Substrate is a modular framework for building blockchains, used by Bittensor. Decentralizing its core operational nodes is seen as a key step.
• He believes decentralizing the substrate chain should happen "before the power structures understand what's happening."
• However, he is optimistic that even if powerful entities become aware, Bittensor's open-source nature means the code can be copied to launch a new, unstoppable decentralized chain.
• Travis praises the Opentensor Foundation (F) for their intelligent design decisions and rapid iteration, acknowledging the high level of expertise required.
• He also notes that features like EVM (Ethereum Virtual Machine) compatibility, which allows for smart contract functionality similar to Ethereum (e.g., potentially NFTs - Non-Fungible Tokens), are already possible but not yet fully built out on Bittensor.
• Actionable Insight: The decentralization of the substrate chain is a critical milestone for Bittensor's long-term resilience and censorship resistance. Investors and researchers should monitor progress in this area closely.

Future Impact: Reshaping Work and Disrupting Power Structures

• Travis foresees Bittensor significantly changing how people work, with individuals choosing to mine on subnets aligned with their skill sets as the technical barrier to entry lowers.
  • "Bittensor almost becomes like a job board."
• He believes Bittensor will have a "massive impact on the power structures in the world," including governments and large corporations, by disrupting them.
  • "It's going to disrupt a lot of the power structures in the world."
• He anticipates these traditional power structures will likely remain "oblivious until it's too late" due to Bittensor's complexity and crypto's sometimes negative connotations.

The Value of Hyper-Specialization

• Travis highlights Bittensor's ability to enable hyper-specialization, where the best global talent in niche areas can be compensated according to the value they provide, free from traditional corporate overhead and social navigation.
• He contrasts this with traditional work environments where social skills and navigating company politics can be barriers, especially for neurodivergent individuals.
• "Bittensor, what that allows you to do is just completely separate all that and just evaluate somebody on their productivity."
• This opens up the talent pool significantly, allowing individuals to contribute and be rewarded based purely on their expertise and output.
• Strategic Implication: Bittensor's model for hyper-specialization could unlock significant value by efficiently matching niche expertise with demand, a trend researchers should study for its economic and social impacts.

The Realities of Mining on Bittensor

• Travis candidly shares his own early mining experiences: "I tried mining a couple subnets before making the course and I was I made a little bit of towel but like basically nothing."
• He emphasizes that mining is "very competitive, very difficult," with many unexpected challenges.
• His mining course was created to share the process he learned for setting up a new miner, addressing the lack of information at the time.
• He views inter-subnet competition as generally positive, leading to better overall outcomes for the Bittensor ecosystem.

Thoughts on Subnet Sales and Cold Key Swaps

• Travis expresses uncertainty about the practice of selling subnets via cold key swaps (transferring ownership of a subnet by transferring the private key that controls it).
• He notes a potential issue: if a subnet is bought, the new owner can accumulate its tokens, which might feel unfair compared to subnets like Bitcast where mining rewards were distributed from day one without a "pre-mine" for the owner.
  • A pre-mine refers to a situation where a significant portion of a cryptocurrency's or token's supply is allocated to developers, founders, or early investors before it becomes publicly available or minable.
• He likens buying a subnet to buying a used car, with potential "known issues" like an effective pre-mine.
• He speculates about a "magic" reset mechanism where a subnet could be reset, cashing out existing holders and starting token emissions from zero, but acknowledges liquidity challenges.
  • Grant suggests a hypothetical reset: liquidating the pool, distributing to holders, and resetting emissions. Travis worries this would force-sell and crash the token price.
• Strategic Consideration: The evolving market for subnet ownership and transfers presents both opportunities and risks. Investors should be aware of the history and token distribution of any acquired subnet.

Excitement for Bittensor's Unpredictable Future

• Travis is not excited about specific subnets but rather the overall market dynamic of Bittensor.
  • "I just love the market dynamic of selecting the best miners and the best subnet owners and the best subnets, the best validators. I love that all of that comes together and the magic that comes out of that is that you you don't know what is coming."
• He shares an analogy of a private security firm solving a crime problem in an apartment building with a simple, inexpensive, and non-obvious solution (posting signs about undercover police), illustrating how open marketplaces for ideas can generate unexpected and highly effective solutions.
• This, for him, is the most exciting part of Bittensor: its potential to foster novel solutions that individuals might never conceive of alone.

Advice for Newcomers to Bittensor

• For those trying to understand Bittensor, Travis recommends his Tao Templar YouTube channel, specifically the "learn bit tensor tow" playlist.
• He designed this playlist to introduce concepts in a logical order for beginners, aiming to provide what he wished he had when starting.
• He also mentions learntensor.org as a resource for those who prefer reading.
• Actionable Step: New investors and researchers should leverage educational resources like Tao Templar's channel to build a foundational understanding of Bittensor's complex mechanics before engaging deeply.

Conclusion: Bittensor's Unfolding Potential as a Permissionless Innovation Engine

This episode underscores Bittensor's profound potential as a permissionless, free-market incentive layer capable of fostering unpredictable and disruptive innovations beyond just AI. Investors and researchers should monitor its progress in decentralization and the emergent strategies within its dynamic subnet ecosystem to identify transformative opportunities.