Bittensor (TAO)

$TAO / $USD - Update $288 needs to hold now on TAO to remain bullish short term. Otherwise this will open up the shorts down to $270 https://t.co/nllZdKj9cG

Grayscale decentralized AI fund $TAO 👀 https://t.co/j3eTHggY9R

$TAO #SN67 - @Tenex_SN67 announcing & executing ✅

🚀 TAO marks a new key impulse $TAO surpasses $300 before its first halving, strengthening bullish sentiment around @Bittensor. 📰 Full article: https://t.co/p5zupNikv8

This is probably the most meaningful and well-articulated discussion about the TAO Flow model I’ve seen so far. Many of the points raised by @badenglishtea were already addressed in detail in the reply section by @const_reborn, so I won’t rehash each one individually. But after going through both the original post and Const’s response, there are a few broader reflections I would like to share. First, no model is perfect. The previous design had shortcomings and this one does too. That’s the nature of evolving systems. Bittensor has always operated on a framework of intelligence meritocracy, just as Bitcoin operates on a mathematical/computational meritocracy. Both systems produce scenarios that can feel unfair but that is simply part of the competitive landscape. If I cannot afford high-end hardware, I won’t mine BTC efficiently. And if a subnet cannot meaningfully contribute toward the problem it claims to solve, it’s unrealistic to expect strong demand or meaningful capital inflow (and less emissions as a consequence). I fully understand where @badenglishtea is coming from. New models introduce new challenges but they also resolve previous forms of imbalance. Ultimately, speculation, market-making, and attempts to game Flow may exist at the margins but none of that changes the fundamental reality that subnets that solve real problems win regardless of emissions mechanics. We already have clear examples: - @webuildscore has demonstrated real-world value with their vision models and now has multiple paying clients across industries. - @bitmind is tackling what may become one of the most critical problems of the AI era which is distinguishing authentic content from AI-generated content. If they succeed, that alone represents a billion-dollar market. I could also talk about @chutes_ai, @TargonCompute, @sportstensor and many other fantastic SNs that already found their PMF and are poised to generate revenue as a business regardless of $TAO emissions. Every subnet has its own thesis. Those that execute well will naturally break out of the web3 bubble and grow into sustainable businesses (the original vision behind Bittensor). I also understand the concern that established subnets benefited from emissions in the past, while newer subnets may face steeper initial hurdles under Flow. But with a capped number of subnets and growing interest around TAO, the same supply of opportunities will be met by increasing demand, attention, and capital. In many ways this mirrors the early-stage startup environment. Additionally, teams can also seek outside funding if their idea is strong but they need runway before emissions align with their value. At the end of the day, while the Flow model may feel demanding for some TAO players, capital and attention will always follow those who build solutions with real-world impact. As @jameswoodmanv brilliantly said, “whether that TAO is staked to SN4 or SN62 shouldn’t actually matter. If you see other subnet owners as colleagues, you should be just as happy to see TAO flowing to their pools as to yours.” If a subnet doesn’t thrive, that should not be attributed to emissions design or governance mechanics. It’s because it didn’t reach product-market fit in a highly competitive ecosystem. Ultimately, the subnets that succeed will be those focused on solutions, not obstacles. And if this model causes some subnets to fail faster, then it will also accelerate the emergence of others that ultimately will win.

this is why I love crypto and crypto twitter. public objection raised. public response given. whether or not you agree with what is said, you should be thankful it is said in the open. #bittensor $TAO $dTAO

. @inference_labs Inference Labs' Bittensor Subnet 2 demonstrated that incentives increase proof speed. The inference network injects energy into corporate autonomy. It combines not only trust but also economic efficiency and cryptography. DeAI https://t.co/bACO918zgE

Staking into $TAO subnets is taking a position on a small neural economy before it industrializes. Some subnets will 3× in performance. Some will 30× in adoption. A few might create entirely new markets the same way early DeFi protocols did. Your stake is a conviction call on which intelligence nodes become indispensable infrastructure. The upside isn’t only emissions… It’s owning a slice of the next intelligence rails.