Day 1 of learning Blockchain Research Before diving deep into anything, you have to understand the basics. Today, I focused on the foundations of blockchain technology ; nodes, transactions, mempool, Layer 1s, Layer 2s, and more. To solidify my understanding, I compared three major blockchains. Here’s what I found: Bitcoin → Digital Money Core feature: * Proof of Work (PoW) Miners secure the network Limitations: * Extremely secure, but not very user-friendly * Slow transaction speed Possible solution: Layer 2 solutions like the Lightning Network can make transactions faster and cheaper. Ethereum → World Computer Core features * Proof of Stake (PoS) * Smart contracts Limitations * Scalability issues * High gas fees can push away everyday users Possible solution: * Layer 2 rollups, which spread the cost of transactions and significantly reduce fees. Solana → Onboarding & Speed Core features: * Very fast * Cheap fees * Developer-friendly Limitations: Network instability during periods of extremely high activity Each blockchain is designed with different goals and trade-offs in mind. There’s no “perfect” chain only different design choices. I’ll be sharing what I learn daily. Stick with me. Thanks 🙏 @faysalOfWeb3

Anthropic told the world Mythos is too dangerous to release. They found a 27 year old bug in OpenBSD in hours. A flaw in FFmpeg that survived 5 million automated tests. Thousands of vulnerabilities across every major operating system. Then they locked it down, kept it for themselves and 40 enterprise partners. The UK's AI Safety Institute confirmed that Mythos can execute multi-stage attacks on enterprise networks autonomously. First model to solve a 32-step attack chain that takes humans 20 hours. Expert-level CTFs: 73% success rate. Two years ago the best models couldn't do beginner. This sounds like a security story. It is not. Anthropic filed for IPO on June 1. The model was "accidentally" leaked in March. Formally announced April 7. Then locked behind a $100 million usage credit program for banks and tech giants. Now the narrative is "we're the responsible stewards of technology too powerful for the public." Alex Stamos put it plainly. We have about six months before open-weight models catch up. Then every ransomware actor has this capability. The bottleneck everyone's missing: In the old world, finding vulnerabilities was the hard part. Humans spent years looking for one good bug. In the new world, Mythos finds thousands. The hard part becomes triage. Prioritization. Patching without breaking production. Knowing which 3 of 3,000 findings are about to become an incident. Palo Alto's CEO said Mythos has a 30% false positive rate. That sounds like a problem for attackers. It is actually a fatal problem for defenders. Attackers need one working exploit. Defenders need to process 10,000 alerts and pick the three that matter. The model finds the bugs. The platform manages the response. Anthropic is telling a fable about responsibility. The real story is about who controls what happens between the finding and the fix. The system is the product. The model is just the sensor.

If you're still in crypto you must be very loyal in relationships

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This is exactly why we’re building a subnet scouting CLI. The tool will let you run checks on any subnet before registering: • registration cost • hardware requirements • validator reward logic • miner/owner concentration • emissions distribution • repo activity • setup complexity • capital or latency requirements • “can I actually mine this on my current setup?” Because the expensive part is not always registration. Sometimes the real cost is hidden in the game the validator is rewarding. A subnet can look cheap from the outside, then you inspect the code and realize it needs inventory, collateral, low-latency execution, or an edge you don’t have. The goal is simple: before spending TAO, know whether you have a realistic path to earning. Cheap registration ≠ cheap mining. github.com/Jeffrey978/subnet…

"Client: I've sent the payment." We've all heard those words before. Then comes the waiting. This story isn't about crypto. It's about time. And what happens when money finally starts moving at the speed of the internet. #SuiNetwork @SuiNetwork @SuiNetworkNG @Nefarii

One subnet is turning real estate into an intelligence market. Not another chatbot. Not another wrapper. @zipcodenetwork is taking property valuations, collateral checks, appraisal models, and real estate data — then putting them inside Bittensor’s incentive layer. 1,461 models. 114 in the latest eval. Top score: 0.942. All-time high: 0.985. 14.9 TAO emitted daily to compete on real estate intelligence. This is the part people keep missing about $TAO. It is not just decentralized AI. It is markets for intelligence. Training markets. Inference markets. Data markets. And now collateral markets. If Zipcode works, real estate does not just get tokenized. It gets priced, verified, and underwritten by an open network. Shorter quote version: One subnet. 1,461 appraisal models. Real estate data. Collateral checks. Property valuation. On-chain lending rails. @zipcodenetwork is showing why $TAO is bigger than “AI apps.” Bittensor is turning intelligence itself into market infrastructure.

Subnet Scout progress today We pushed Subnet Scout from a basic ranking script into a more practical Bittensor mining research CLI. What changed: 1. Live Taostats integration - Pulls live subnet data - Reads registration cost, active miners, validators, max neurons, flow data, and identities - Uses Taostats API instead of relying on stale notes 2. dTAO pool data - Added dTAO pool endpoint support - Better subnet names/symbols - Better market context where available 3. Cache fallback - Taostats can rate-limit with 429 - Now the CLI saves live data locally - If API fails, it falls back to cached data instead of breaking 4. Fixed unit bug - Some Taostats values come in rao - Registration cost like 500000 was showing wrongly - Fixed it so it displays correctly as 0.0005 TAO 5. Flow tracking - Added 1-day, 7-day, and 30-day TAO flow fields - Changed the table from useless missing 24h% to Flow1d - Makes it easier to see where capital is moving 6. Cleaner scoring - Better placeholder detection - Names like unknown, pending, parked, and deprecated are treated as risky - Helps avoid chasing fake/low-quality leads 7. New leads command - This is the practical shortlist command - Filters for subnets that are more realistic for VPS/CPU-style mining - Shows: • subnet • registration cost • miners • validators • 1d flow • score • why it is a lead • next action 8. JSON output - Added: python -m subnet_scout.scout leads --json Useful later for automation, dashboards, bots, or alerts. 9. New deep command - Added: python -m subnet_scout.scout deep 124 It gives: • subnet inspect view • registration cost • miner/validator count • flow • website • GitHub • summary • due diligence checklist • next commands to run 10. Deep JSON output - Added: python -m subnet_scout.scout deep 124 --json Useful for future automated subnet reports. 11. GitHub repo setup • Created a clean repo export . • Added SSH deploy key • Pushed updates to: github.com/Jeffrey978/subnet… SN124 Swarm ( @SwarmSubnet ) showed as the strongest current lead Main result Subnet Scout now does more than “rank subnets.” It gives a practical workflow: python -m subnet_scout.scout leads python -m subnet_scout.scout deep 124 So instead of guessing, we can now scan → shortlist → inspect → decide what to research next.

Zipcode launches today, June 1st. Real estate is massive, but access is still messy for most people. Watching how this one develops.

Zipcode.network is now LIVE. Decentralized intelligence and capital, under one roof. One Network One Mission… Enable Real World Financial Services, onchain. Welcome to the future of finance.

65% of data-center training efficiency on Orion-100B is the part people should pay attention to. Distributed training usually breaks on coordination: latency, bandwidth, unreliable nodes, and verification. Macrocosmos is showing that Bittensor can turn underused global compute into coordinated training capacity. If this keeps scaling, decentralized AI moves from “GPU marketplace” to actual model production.

Locking public stake means less liquid founder overhang, stronger long-term alignment, and a cleaner signal to the market: “I’m not here to dump volatility. I’m here to build through it.” Most founders market conviction. Very few restrict their own optionality to prove it. $TAO

The real highlight of @proofoftalk will not be hype. It will be exposure. For the first time in a more serious setting, Bittensor gets pushed in front of people outside its own native bubble, and that matters more than most people think. Inside the ecosystem, it is easy to believe the story. - You see the subnets. - You understand the emissions. - You follow the builders. - You know why decentralized intelligence is interesting. But none of that guarantees the story survives contact with outsiders And that is the real test A dedicated Bittensor track at Proof of Talk is important because it forces the ecosystem to explain itself to people who are not already emotionally invested. Not miners. Not subnet holders. Not timeline loyalists. People who want to know: Is this infrastructure or just narrative? Are these subnets real businesses or just clever token wrappers? Is decentralized intelligence actually producing something useful, or is it still mostly internal excitement talking to itself

Bittensor | $TAO This emissions-blocking update is one of the more important governance moves in Bittensor right now. Not because it is perfect. Because it shows the network is starting to separate useful subnet activity from extractive subnet activity. According to Taostats, Bittensor will now block emissions from subnets that: burn 100% miner emissions have no plan to go live self-mine fake activity are dead or abandoned exploit TaoFlow That matters because emissions are not just “rewards.” They are the economic signal of the network. If emissions keep flowing to dead subnets, fake activity, or teams with no intention of going live, then the system rewards extraction instead of production. And that weakens the entire subnet market. The real promise of Bittensor is not that every subnet deserves emissions forever. The promise is that useful digital commodities can compete for capital, miners, validators, and attention. That only works if low-quality or exploitative subnets are not allowed to drain the system while real builders compete for the same emissions. This is why the cleanup phase matters. It forces every subnet to answer simple questions: Are you live? Are miners doing real work? Is the incentive mechanism honest? Is value flowing to contributors, or being captured by insiders? Can the subnet justify the emissions it receives? That is the right pressure. Short term, some people will call this harsh or centralized. And maybe they have a point. But Taostats also framed it as temporary while conviction and governance mature. That distinction matters. The endgame should not be manual intervention forever. The endgame should be better governance, stronger market signals, and a network where emissions naturally move toward subnets producing real value. For now, this looks like a necessary filter. Bittensor is moving from “launch a subnet and farm attention” toward something more serious: prove useful work, or lose emissions. That is how subnet quality improves.

Bittensor | $TAO This is a necessary cleanup phase. If emissions are meant to reward useful work, then dead subnets, fake self-mining, TaoFlow exploits and “no plan to go live” projects should not keep draining value. Temporary or not, this pushes the network in the right direction: less noise, stronger subnets, better incentives.

Congrats to the SN60 team. This is exactly the kind of progress Bittensor needs more of: measurable agent improvement, faster vulnerability detection, and real security use cases. The strongest subnets won’t just sound interesting. They’ll keep proving useful work in public.

Found a Medium-severity vulnerability in Zebra, @zcash's Rust full-node implementation, and reported it through the Zcash Bounty Program for a $37,500 bounty. Already patched and shipped in v4.5.0 — disclosure below. github.com/ZcashFoundation/z… @ZcashCommGrants Had some duplicates too. Feels good 😁

Spent today building a small Python tool for Bittensor subnet discovery. The problem is simple: There are too many subnets to track manually, and for small miners, the important question is not “which subnet is trending?” It’s: Which subnet is actually worth researching? So I built Subnet Scout. It looks at things like: ▫️ registration cost ▫️ miner count ▫️ validator activity ▫️ docs/GitHub availability ▫️ early vs crowded subnets ▫️ suspicious “cheap but dead” signals ▫️ possible CPU/VPS-friendly opportunities The goal is not to blindly tell me where to mine. The goal is to reduce noise and surface better questions. For example: A subnet with low registration cost and 1 miner might be early. Or it might be closed, dead, or impossible to mine without private docs. That difference matters. Bittensor discovery is still messy, but tools like this can make it easier for small miners to find real opportunities before they become obvious. Still rough, but it works. Next step: better docs detection, daily snapshots, and a proper watchlist.

AdTAO(SN21) is interesting because the problem is real. Google Ads is full of noisy data, attribution gaps, and campaigns where it’s hard to know what actually caused results. If SN21 can use Bittensor incentives to improve prediction around ad outcomes, that’s not just a subnet narrative. * That’s a market people already spend billions trying to solve.

Chutes generates more revenue than $RENDER $AKT $FIL And this is just ONE Bittensor $TAO subnet Sheesh 😮‍💨 Undervalued.