💫 ATTUNE - VECTOR LEVEL 1 CLOSED 💫 Attune just closed Vector Level 1. Earlier method: 79% on one task, one arm. Fine-tuned pi0.5 sat at 87%. Vector made it harder. Two arms. Sixteen tasks. One demonstration. Weights stayed frozen. Crown started at 49%. Finished at 87.9%. Beat the specialist on the harder exam. Behind on the easy job. Ahead on the hard one. That is the growth curve. Level 2 is open. robotensor.ai/blog/attune-ve… $TAO $SOL $COIN $HOOD $BTC $ETH $RNDR $FET $AKT $VIRTUAL $AI16Z #Bittensor #dTAO #PhysicalAI #Robotics #EmbodiedAI #DePIN #AI #Crypto #OpenSource #Subnet58

💫 ENGY - MERGE MINING LIVE 💫 PRL merge mining is live on engy’s 5090s. Engy has already experimented with and deployed PRL merge mining across its full 5090 fleet. This is the quiet compounding move. The same GPUs that serve inference now generate additional revenue in the gaps between jobs, and utilization is holding near 100%. Hardware that was already paid for and powered is now working closer to full capacity, turning idle cycles into a second revenue stream without extra power draw or new boxes. Inference remains the priority. The team is still tuning the setup to protect peak-hour performance. That discipline is the point. Mining is additive precisely because it does not degrade the core service customers are already paying for. The fleet stays full. The primary business stays clean. The next step is visibility. The dashboard will be updated to show mining-side revenue alongside the inference numbers. Once that lands, both streams become measurable, and the utilization story stops being a claim and becomes a number the market can track. This is operational leverage in real time. The hardware is running. The software is deployed. Utilization is already near the ceiling. The remaining work is refinement and reporting, not invention. Dual revenue on the same fleet is how margins expand without waiting for the next capacity cycle. Read the signals. $TAO $SOL $AI $LLM $HOOD #Bittensor #TAO #AI #LLM #MiniMax #DecentralizedAI #SN53 #Engy #BlueTAO #RobinhoodChain #Inference #Crypto #Web3 #Solana #MergeMining #PRL

💫 REAX SN92 - ANTSEED LISTING 💫 Decision Models just listed on Antseed - an open marketplace for AI inference. Their specialized decision models (including the EU tier) and Auto Router are now available alongside 700+ other models. The Auto Router automatically picks the best option per request for strong quality at lower cost. More distribution for REAX-powered decision models as the open inference market grows. #TAO #Bittensor #AI #DecisionModels #REAX #SN92 #Crypto #OpenSourceAI $TAO $SOL #Solana $COIN #Coinbase $HOOD #Robinhood #RobinhoodChain xitter.cf/decisionmodels_/status…

💫 REAX SN92 - ENGINE 6X FASTER 💫 REAX just shared another update on the engine track - and the speed numbers keep improving. What is the engine track? It’s a permanent competition on Subnet 92 where people compete to make the REAX inference engine itself faster. The goal is to serve the same decision models with higher throughput and lower latency on the same hardware, while keeping the answers essentially identical. Better engines mean the whole network can handle more requests, cheaper and quicker. Florian said he has been further improving the baseline (the reference engine). On some models it is now 6× as fast as normal inference. This lines up with the earlier teaser where their optimized engine ran the 27B decision model about 6× faster than the reference server on the same GPU (~32 vs 5.7 decisions per second on one RTX PRO 6000), with practically the same answers. In plain terms: they’re not just hosting models - they’re actively making the engine that runs them significantly faster. For decision models, where speed and cost matter more than raw size, that is one of the most important levers. Early, but the core technology is moving in the right direction. #TAO #Bittensor #AI #DecisionModels #REAX #SN92 #Crypto #OpenSourceAI $TAO $SOL #Solana $COIN #Coinbase $HOOD #Robinhood #RobinhoodChain

💫REAX - COMP & ENGINE UPDATE💫 REAX just tightened the specialist competition rules - and gave a strong engine teaser. What are the specialist competitions? REAX has rotating tracks where miners compete to build better specialized decision models for real use cases (for example, routing, scoring, or classification tasks). The best model on each track becomes the “champion” and earns a share of the emissions until someone clearly beats it. The idea is to keep improving the models that customers can actually use, not just host the base ones. From Tue 20 Oct 18:00 UTC, models that are extremely close to the current champion can no longer win on small calibration tweaks. They now need to get more items correct and lead by a clear margin. Near-copies of the winner no longer take the crown. Previous champion keeps earning during the short approval window (up to 48h). What is the engine track? It’s a permanent competition on REAX where people compete to make the REAX inference engine itself faster. The goal is to serve the same decision models with higher throughput and lower latency on the same hardware, while keeping the answers essentially identical. Winners get a share of the emissions for improving the speed of the whole network. It’s separate from the model-quality competitions - this one is pure speed and efficiency. Engine track target open is Tue 20 Oct 18:00 UTC (or next day if final checks run long). Florian also shared that their optimized REAX engine is now running the 27B decision model ~6× faster than the reference server on the same GPU (~32 vs 5.7 decisions/sec on one RTX PRO 6000), with almost identical answers. They’re closing the obvious copy path on the model tracks, keeping rewards flowing fairly, and showing real speed gains on the inference side. Early, but the rules are hardening and the engine is moving. Read the signal. #TAO #Bittensor #AI #DecisionModels #REAX #SN92 #Crypto #OpenSourceAI $TAO $SOL #Solana $COIN #Coinbase $HOOD #Robinhood #RobinhoodChain

💫REAX SN92 - COMPETITION UPDATE💫 REAX just shared a clear status update on its model competitions - and it’s the kind of detail you want to see this early. The DF track has a new approved champion (UID 40) that will start getting paid from the next weight sets. The RA track is still deciding between a couple of strong contenders (decision expected later today). At the same time they’re rolling out Eval v3: 20% of the test items will now be private real-world data, with a penalty if a model is clearly weaker on them. They’re also tightening the rules so that a near-tie has to actually win by a meaningful margin instead of just being close. Why the temporary human checks? The subnet is only days/weeks old. Scoring rules for specialized decision models are easy to game at the start, so they’re manually reviewing champions for now to keep things fair while the system hardens. Florian was explicit that full automation and machine-led scoring is the goal - this is temporary oversight, not the end state. In plain terms: they’re raising the bar, closing obvious exploits, and starting to reward real performance instead of pure benchmark gaming. That’s exactly what you want to see when a new competition mechanism is still forming. Early, but the direction looks right. Read the signal. #TAO #Bittensor #AI #DecisionModels #REAX #SN92 #Crypto #OpenSourceAI $TAO $SOL #Solana $COIN #Coinbase $HOOD #Robinhood #RobinhoodChain

💫 REAX’s JEV Models: Fast Decision-Making for the Machines of Tomorrow 💫 The new Tesla Roadster Elon Musk showed can drive up a wall, flip in the air, hover, and land using thrusters (see the demo:). The hard part is not just the power - it is making the right decisions, in the right order, at the right moment. That is where REAX’s JEV models fit. What are JEV models? Most AI writes long answers. JEV models do something simpler and faster. You give them a snapshot of the situation and a short list of possible choices. They instantly return the best option plus how confident they are. They do not write paragraphs - they just decide. REAX is an open network (Bittensor subnet 92) that hosts and checks these models. Specialized engines make the answers even quicker, so they can run many times per second at low cost. How this would work in practice on the Roadster Think of the car as having two brains working together. The fast brain (ordinary software) This handles millisecond-level control: firing thrusters to stay level while flipping, adjusting suction fans, or correcting a wobble. It works like a plane’s autopilot or a car’s stability control - very fast, predictable, and focused only on staying stable and safe. Decision models are not used here because these reactions must happen with almost no delay. The smart brain (REAX JEV model) Every few tenths of a second, the car sends the model a clean summary of the situation: position, speed, remaining thruster pressure, nearby obstacles or wind, and the requested stunt (for example, “full flip then land”). The model answers a few simple questions in parallel, such as: • Of these next moves (full flip, half flip, abort and land early), which is best right now? • How confident are you that this path is still safe? • Continue the stunt or switch to a safer landing? It replies almost instantly with the best choice and a confidence score. What happens next • High confidence → the car proceeds; the fast brain carries out the precise thruster and steering adjustments. • Medium confidence → the car makes a smaller adjustment and checks again a moment later. • Low confidence → the car immediately falls back to a pre-programmed safe behavior (abort and land upright). In everyday terms, the fast brain is like your reflexes when catching a ball. The smart brain is the quick judgment that decides whether to try the catch or step aside. Both are needed, and they work at different speeds. This hybrid pattern already appears in research demos with drones and simulated cars. Broader future uses The same idea applies to everyday autonomous vehicles (lane changes, yielding, emergency stops), robots and drones, edge devices inside vehicles, AI agents handling frequent simple choices, and specialized models that improve over time on the open REAX network. Why it matters These models are fast, cheap, and open. Answers can be verified by the network rather than simply trusted. They do not replace rigorous safety engineering or regulation - especially for vehicles that leave the ground - but they offer a practical way to add real-time higher-level intelligence on top of precise low-level control. The Roadster demo shows how dramatically vehicles can move when thrusters and clever control are combined. Adding fast decision models could let those same machines understand high-level requests, weigh options in real time, and act with calibrated confidence. That combination is one plausible path for the machines of the next decade. Food for thought. #Tesla #Roadster #ElonMusk #SpaceX #FlyingCar #AI #DecisionModels #REAX #Bittensor #TAO #AutonomousVehicles #Robotics #EdgeAI #FutureOfTransport $SOL #Solana $COIN #Coinbase $HOOD #Robinhood #RobinhoodChain $TAO xitter.cf/elonmusk/status/211091…

💫 ENGY – ACCELERATED GROWTH 💫 The public card shows the month. Early October sat near 12 billion tokens a day. From 10 October the total began to climb. On 15 October it closed at 70.3 billion. GLM-5.3-flash alone was 53.5 billion. Today is already projected above 96 billion. That is not a one-day print. It is a step-up that has held and widened. The growth is concentrated in the longest jobs on the cheapest of the three main models. DeepSeek stayed large. Kimi continued to step between roughly 2.3–4.6 billion with no lift in its floor. The volume is landing where the work is longest and the price is lowest. Ning said the team has been fixing client issues day and night, making the service more reliable, and that the distribution pipeline is starting to kick in. The timing matches. The doors that were already open - the direct endpoint, AntSeed, Requesty, BlueTAO, the internal Bittensor routes - are now feeding more of the longer jobs. Those jobs are staying. The floor is higher because the service is more stable. A rough blended rate puts the flash model near $0.21 per million tokens and Kimi near $3.90. On 15 October the flash lane alone was tens of thousands of dollars before cache effects. The high-price lane was larger in revenue than its share of tokens. The desk is processing far more volume than it was two weeks ago. Revenue per token is lower because the mix has shifted toward the longer, cheaper jobs. That is the normal shape when reliability improves and the existing channels start delivering scale. The constraint remains capacity. The doors are open. The longer jobs are landing and staying. The high-price lane is still there. When the mix shifts toward it, or when the next models land, the revenue chart will not need the token chart to double again. It will move because the work that is already arriving is higher-priced. The month is the evidence. The acceleration is real. The pipeline is feeding it. Read the signal. $TAO $SOL $AI $LLM $HOOD $COIN #Bittensor #TAO #AI #LLM #MiniMax #DecentralizedAI #SN53 #Engy #BlueTAO #RobinhoodChain #Coinbase #Inference #Crypto #Web3 #Solana #Base

💫 ENGY SN53 – RELIABILITY IS KEY 💫 The public card cannot see the keys. The owner just described the mechanism. Asked what is behind the recent token climb, Ning said there is no magic. The team has been fixing client issues day and night, making the service more reliable. Now the distribution pipeline is starting to kick in. That is a different read from pure testing. The floor is holding because the service is more stable, and more traffic is finding its way through the doors that are already open. The doors are public. The direct endpoint at api.engy.ai. AntSeed’s Gateway Console, where Engy is now serving. Requesty. BlueTAO. Inside Bittensor, Albedo is routing a large share of its judging calls through the desk. The referral program is live. Ning did not list them. The record shows they are there. The numbers match the shape. Yesterday closed at 70.3 billion tokens. GLM-5.3-flash alone was 53.5 billion. Today is already at 47.5 billion by 11:05 UTC, projected to 95.7 billion. The blue bars are the growth. Those are the longest jobs. When that model takes a larger share, total tokens rise even if request counts do not. On the Kimi step-up, Ning said it is all mixed up, mostly organic. The lane is still stepping between the quiet band and the high band. He is not treating the recent prints as a clean new client switch. The baseline has not yet lifted. On Pareton’s optimisations, he said yes, they are helping, and the leverage will be larger once they finish K3. No ETA yet. If Kimi gets the same treatment the other models have had, the steps we have been watching could sit on a higher floor rather than just turning on and off. The useful part is the pipeline line. If the existing channels are starting to feed the desk on their own, the recent token climb does not need a new signed client every day to stay elevated. Reliability is the part Ning is saying is now paying off. The constraint remains capacity and how cleanly the longer jobs land. Read the signal. $TAO $SOL $AI $LLM $HOOD $COIN #Bittensor #TAO #AI #LLM #MiniMax #DecentralizedAI #SN53 #Engy #BlueTAO #RobinhoodChain #Coinbase #Inference #Crypto #Web3 #Solana #Base