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Every relevant Silicon Valley CEO (Jensen, Elon, Sam, Satya, Dell, etc, etc, with the only exception being Dario) Fund Manager/VC (Gerstner, Baker, Andreesen, Gurley, Sacks, Chamath, etc, etc) is full throated endorsing open source AI as a key strategic technology for America that must be fostered/cultivated rather than cut off by regulation.
How does an investor express a trade that benefits from this? The obvious one is Bittensor.
Bittensor is an open, permissionless, decentralized ecosystem designed to fund and coordinate open source compute protocols, pre/post-training, AI apps/businesses, AI research, etc (think: open source AI startups)
Bittensor’s TAO token is a liquid index designed to capture the value these open source AI start ups are creating. It’s a hard money asset with the exact same tokenomics as Bitcoin. It currently trades at 2B mcap.
This is the trade of the decade sitting in plain sight.
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
The world needs both frontier closed models and frontier open models.
images.nvidia.com/pdf/Open-W…
sun runner retweeted
Here's a very crude simplified chutes roadmap/plan, for near term:
- move the most unprofitable things off of the subnet, including today's announcement of some (not all) additional inference options (not paid via emissions)
- this allows us to scale the things we want and need to avoid capacity issues/better direct incentive - this includes models we use to build data pipelines and relationships to other teams/networks/etc
- add options that are completely revenue positive (hourly pricing/rentals/simple docker based jobs/etc), TEE, private, secure, priced above cost, more extensive version of private chutes we have today basically
- expand the hourly compute offerings to also include CPU only (e.g. to run agents, web browsers, sandboxes, non-GPU work of any kind)
- use some of the incentive for ideally non-datacenter based model training and serving
- build a non-extractable product on chutes from the models we build, via dynamic edge nodes, possibly from the epigenesis work (smaller faster cheaper faster than lora customizations from the sparse sections of pretrained model, participant supplied)
- models and pipeline etc. will be open source, the customization and ensemble thereof will live only in chutes, inc. the continuously evolving set of served variations/RL/etc.
We'd like, to the extent we can, attract participants who want to build and have no obligation to pay datacenters or any particular hardware vendor, to keep the value inside the subnet at all times by attacking sell pressure at the source (DC commitments, chip purchases, etc).
We will continue to have secure TEE inference and GPUs; not elimating anything wholesale, just focusing more on a commodity that doesn't have to flow out to DCs and single hardware vendors.
NVIDIA reportedly has 75% profit margins, revenue for the sake of revenue fueling GPU reselling goes straight to one place, basically. Fine, I guess, but I'd rather work together as individuals with whatever hardware we can bring, to a reasonable degree.
sun runner retweeted
The world doesn't have a shortage of compute. It has a problem connecting it.
We've built the infrastructure to change that.
The future is liquid.
Replying to @Yuchenj_UW
I think we’re going to see a lot of stranded compute in partially complete data centers
sun runner retweeted
For those wondering the connection - suggest you read this several times:
What happens when intelligence becomes commoditized?
open.substack.com/pub/90days…
For those wondering the connection - suggest you read this several times:
What happens when intelligence becomes commoditized?
open.substack.com/pub/90days…
sun runner retweeted
👀
🚨 $TAO | GRAYSCALE - NEW SEC FILING
On October 23, 2026, Grayscale filed Amendment No. 2 to its S-1 registration statement for the Grayscale Bittensor Trust.
This is more than a simple ETF rumor.
Key developments:
• Grayscale intends to rename the trust Grayscale Bittensor ETF upon registration effectiveness and NYSE Arca listing.
• The proposed ETF would hold actual $TAO, providing traditional investors with exposure to Bittensor without directly managing tokens.
• The structure involves institutional infrastructure including BitGo, Coinbase Custody, BNY Mellon and Coinbase Prime.
• Staking is contemplated, subject to regulatory and operational conditions.
Why does this matter?
Bittensor is progressively building bridges between decentralized AI and traditional financial markets.
An ETF could expand access to $TAO, attract new categories of investors and potentially create additional demand for the underlying asset.
But let's be clear: this is NOT an ETF approval, and no launch date has been confirmed.
The regulatory process is progressing. What happens next matters.
@DCGco , could you provide more clarity on the remaining regulatory steps, the potential timeline and the conditions for enabling staking?
The Bittensor community would certainly appreciate an update.
Source: SEC Form S-1/A, filed October 23, 2026.
#Bittensor #TAO #GTAO #ETF
Source: sec.gov/Archives/edgar/data/…
sun runner retweeted
A question we often hear from teams evaluating the IOTA SDK: if I train this again, do I get the same model?
We ran 7 independent 16B pretraining runs, ~140 GPUs each. Between them, 585 worker crashes, preemptions and rejoins. The loss curves are almost identical.
Reproducibility is what turns a result into science instead of a one-off. It's also what makes a training run worth paying for.
Most distributed training projects overfit to a single experiment: one model, one recipe, one demo run. The IOTA SDK is general purpose, fault-tolerant and reproducible.
iota.macrocosmos.ai/sdk
sun runner retweeted
As frontier labs subsidies going down, majority of companies will be forced to pivot to open weight models that will be 70-80% cheaper for 95% of the performance
Inference is like energy, study Jevon paradox.
Use @engyai
Replying to @Kimi_Moonshot
On Terminal-Bench 4.0, which evaluates coding agents on realistic, resource-constrained terminal tasks using strict task-specific tests, K3.1 Pro scores 65.7%, ahead of GPT-6 Astra (58.2%) and narrowly behind Claude Opus 5.5 (66.4%).
What is the TAM for inference providers that serve frontier-grade intelligence (Kimi K3.1 Pro) at the lowest possible cost in a private fashion?
This quoted post is unavailable.
The future of enterprise AI is local / decentralized
sun runner retweeted
For those who left TAO and/or were once curious about it and moved on to other things, now is probably a good time to re underwrite.
NFA.
bittensor:native
its been a good week being a citizen of the Bittensor network state. here's everything that happened this week
• @lium_io now hosts $30M in GPUs (91% utilization), including 225 B300s. At a $21M run rate
• @affine_io dropped a video model thats ~10x cheaper than the base model with virtually no drop in output quality after 3 days of model optimization
• @engyai hits a new ATH, with 370B tokens processed this week
• @say_gm_ had its highest traffic week, crossing $1M in total volume since July
• @cacheon_ai adds Meta's Muse Spark Open Kernel challenge to their mining competition
• Ingot released Ingot-I quantized Qwen 27B into FP8 better than Alibaba's own quantization in just 1 week
• @trishoolai released HaloGuard EU, an API product that enables companies to be in compliance with the EU's AI act. It's 200x cheaper than Jev
• @yugosai announces their subnet pivot to an intelligent model router
• @metanova_labs subnet-derived compounds underwent wet lab testing and compared favorably with reference compounds including approved drugs
• More subnets entering the buyback game this week with @VantaTrading @ $102K, @Bitcast_network @ $93K, @almnc_ai @ $45K, and @_redteam_ @ $30K.
• eTAO upgrade was implemented into the chain, giving subnet owners control over how they set their emissions. Huge quality of life improvment
sun runner retweeted
A lot of people don't like TAO because they keep updating the protocol, sometimes new features, sometimes tweaks to existing features. But AI is an arms race; you have to move fast or you'll get left behind. Consequently, the speed that the protocol improves at, is one reason why I like Bittensor so much.
sun runner retweeted
Replying to @Fiskantes
Bitcoin mines for SHA256 hashing power.
Bittensor mines for all the elements of intelligence (be it compute, inference, pre-training, post-training/RL, synthetic data, applied AI, etc), and it tokenizes them.
Pearl mines for MatMul hashing power.
Suppose “Bitcoin of AI” is in the eye of the beholder.
Replying to @Evan_ss6
Ok, I just put together a proper effort post here, so hopefully you read it, but the TL;DR is that TAO hits all the notes you mentioned above. You want a coin that's essential to an AI business, where that business generates real-world value and that value drives back to the coin itself. That's Bittensor.
I am going to assume you don't know much about Bittensor beyond the "AI Bitcoin" moniker and start with a brief origin story, since I think it's important and helps illuminate where "AI Bitcoin" came from. The interesting thing about Bitcoin for the Bittensor story is that it figured out how to use a token to bootstrap a decentralized compute network, owned by nobody and accessible to everyone, that to this day is the largest computing network on Earth. Bittensor's founders are AI researchers. They knew how important compute was going to be for building AI, and they set out to build the same thing for intelligence: a decentralized intelligence network, owned by nobody and accessible to everyone. Just as Bitcoin could coordinate a disparate group of people to fight centralized control of money, perhaps a new primitive, Bittensor, could be designed to fight the coming centralized control of intelligence.
So they abstracted the Bitcoin incentive system (i.e., spend energy securing the network by solving SHA-256 hashes, get paid in BTC) so it could be applied to a whole new set of problems, all aimed at one goal: mining for intelligence. Mining SHA-256 today on Bitcoin is incredibly difficult, but as a system it's simple and objective. Mining for intelligence is orders of magnitude more complex. It's subjective, so it has to be scored on a gradient (study: Yuma Consensus), and there are multiple components that all need to be mined (compute, data, algorithms, etc.). That's where subnets come in. Each one tackles a piece of the problem.
(1) Outside revenue + value to the tokens:
It took years and a lot of iteration, but Bittensor is now doing exactly what it set out to do. It's mining intelligence.
Compute/inference: ~5 subnets are coordinating GPUs around the world to serve raw compute and inference into the open market. Customers range from retail to enterprise, with the crypto abstracted away entirely. Estimates vary, but I put this group at ~$40-50MM aggregate ARR and scaling fast (for context, think ~200% QoQ and ~50% MoM growth).
Training: two subnets are doing SOTA decentralized pre-training right now (SN3 and SN9). SN9 just wrapped up a 100B-parameter run with the highest MFU reported for a distributed pipeline-parallel run. SN3's current run is a 110B-parameter model, the largest decentralized pre-train ever attempted. These teams are past proof of concept and working on scale. And SN120 Affine is post-training Chinese OSS models at SOTA levels.
Applied AI: a whole set of subnets incentivize miners to build verticalized models that power real products. Score for computer vision. RedTeam and Bitsec for cybersecurity. Minos for genomics. Yanez for identity and fraud. Trishool for alignment. Vidaio for video compression. I'm missing plenty more. These are real products being used in the wild by enterprises. I'd put this category at $10-20MM ARR, also scaling quickly.
For context, 12 months ago I'd have said ARR across the entire network was under $5MM. The TAMs here are massive, and the blue-chip subnets are exiting the pre-revenue stage and entering the scaling-revenue stage right now.
Critically, these teams are taking that revenue and buying/burning their tokens. Not because they're altruistic. Because the network makes it the only rational move. Two reasons for this:
(1) A subnet pays its miners in its own token, a fixed number of tokens per block. So the only way to grow the supply side (more GPUs, better models, more output) is for the token to go up. If you're a compute subnet and want more capacity, you take your revenue, cover miner COGS plus some margin, and buy your token. Buy pressure on your token becomes a derivative of your compute bill. The token is the production budget.
(2) And the chain runs the same game one level up. Subnets compete against one another in a fight for daily $TAO emissions, and the scoreboard is the price of each subnet's alpha token (a clever way to let the broader market instruct the protocol on how to allocate its resources). The winners get a bigger share, and for mature subnets that TAO goes straight into buying their own token off the pool. Fall too far in the ranks and you not only lose out on emissions, you risk being deregistered.
So you might astutely point out that revenues < emissions today. That is true, but the trend is our friend. Bittensor is essentially running the Uber playbook, which I would argue a cryptocurrency is tailor-made to do. Use the token, rather than VC funding, to bootstrap supply before the demand exists. Once supply is there, demand scales and the flywheel kicks in: demand up → revenue up → buy+burns → alpha price up → miner rewards up → more/better supply → repeat. The early alpha buyers were the pre-revenue seed/Series A investors. Now we're entering the revenue/scaling era.
Although revenue isn't yet covering emissions, as discussed above, it is growing. Meanwhile, the supply side is in its first halving cycle. TAO had its first halving last December, alpha halvings are coming in 2027/28, and the subsidy shrinks on schedule as revenue takes over. I am not speculating here either - a couple of subnets already bring in more from customers than they pay out to miners.
Important to mention: to buy and burn its alpha token, a team has to buy TAO first and stake it into the pool that pairs TAO against its token. Every alpha burned leaves TAO behind in the pool. ~2M TAO already sits in those pools, and every subnet token can only trade against TAO. So subnet revenue = TAO buy pressure, mechanically. Speculative investing in subnets = TAO buy pressure. Subnet/miner/validator registrations = TAO buy pressure. Taken to its logical end... TAO is literally an index of all 128 subnets, or in other words, an index of 128 AI startups building on crypto rails.
(2) It's cypherpunk:
TAO also represents the right ethos for crypto x AI. It leverages a novel crypto primitive to bootstrap networks that coalesce edge compute and edge talent from around the world, coordinate them to produce the real inputs to intelligence (compute, data, algos, etc.), and serve them to anyone, anywhere. A network that serves open, permissionless, decentralized, uncensored intelligence. A true alternative to centralized labs and governments. And because it harnesses the world's edge compute and talent, it can scale in ways the fiat companies just can't.
(3) You're still early:
The top 3 compute subnets are ~$100MM market caps. The next two are $30-60MM. Promising subnets in other categories are sitting at $10-20MM. There are 128 subnets today and there'll be 256+ down the road. Maybe many more in the future. Bad teams get deregistered and new ones take their place. As the ecosystem grows, so do miner and owner rewards, which pulls in more teams and better talent. There will be fantastic teams launching subnets a year from now that you can buy at $5-10MM or less.
CT isn't woke to this. 99% have not bridged over to the native Bittensor chain to participate in this ecosystem. Cross-chain bridges are only just going live. In my mind, this screams opportunity.
And that's before you get to TAO itself, the L1/index/launchpad under all of it, sitting at ~$3B. That's comically low. Its 1:1 comp is ETH at ~$327B. 100x with size is viable here.
Will follow up with some longer-form sources to check out.
Great explainer on Gamma Tokens from @markjeffrey
Bittensor mines for intelligence and then tokenizes it.
Tokenized Intelligence.
Bittensor Gamma tokens:
It's like 'Sign In With Google' for ALL subnet products.
No signup / onboarding. No KYC. No credit cards. No API keys.
Any agent with a $TAO wallet can ALREADY access all 128 subnets. The wallet IS the API key.
Standardized payment rails + access.
































