AI & digital money. And I like elephants a little bit 🐘

Joined December 2022
AlphaRidge puts research, screening, and automation in one place instead of five tabs and three subscriptions. A trader finds a setup on the screener, turns it into a rule, and the rule keeps running and alerting even with the browser closed. @alpharidge_ai maps a few ways the workflow actually closes: > Screening on news: Sort the whole market by 7-day sentiment, event clusters, and impact scores instead of just price and volume. > From idea to rule: Paste a TradingView Pine script into RidgeScript, test it, then arm alerts to Discord, Telegram, or email. > AI that shows its work: The analyst writes screens and marks up charts, then surfaces the exact platform data it used so you can check it. The neat part is the news layer. Miners on SN45 turn hundreds of thousands of articles a day into screenable sentiment and events, so the screener can look at what is being said, not just what already happened. Paper trading is free today. Live brokerage execution is still rolling out. The AI cites its sources, but you still have to confirm before anything is placed.
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Just pulled a Flareon from a Pokémon Gacha pack on @rarible 🔥 My childhood cards are still at my mom’s place, on the other side of the planet. So it's a bit of a hassle for me to go through the cards to see if there might be any little treasures among them. Not to mention trading the cards. But trading via Rarible means no shipping, no meetups & not worrying about damages. My Flareon here is safely vaulted and easy to sell online. That's actually pretty cool.
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Danny Herrmann retweeted
I saw that @heydittoai walked through Ditto v2 at Exploit Summit, including the bit where an agent switches platforms and keeps the context. Their own write-up uses a case that is basically one sentence: point the new agent at the old one and tell it to mind meld. No rebuild. To give you some more context on this, a normal chat remembers you only inside that app. Claude does not know what you told Cursor, and a new agent starts from zero. But if the spec changed in Telegram, or you moved from one coding agent to another, Ditto v2 keeps one memory under the tools and waits for a yes before it sends or edits anything risky. So the flow would look something like this: ▸ You say it once, in Claude, Cursor, Codex or Grok, and the others can already use it. ▸ Telegram and Slack sit next to the docs and the code, so the agent can search the decision, not just the repo. ▸ A workflow or browser agent runs the job, and the step that could do damage waits for your approval. Depending on the tool, you stay in that chat or leave with the memory exported. This ties back to what I wrote before: the models got good at answering, but you are still the switchboard between them. That’s the part Ditto v2 is building for, even when the handoff is a single sentence. What other agent handoffs should I look into?
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SayGM (SN28) might be the best AI altcoin that noone is talking about 💎 This $TAO subnet has rapidly become a blue chip in the Bittensor ecoystem Why? First of all, their new desktop app allows anyone to access Claude, ChatGPT, Gemini, and Llama for up to 70% cheaper and privately Currently at $5M ARR and growing 🤑 Secondly, their new growth marketing affiliate program "Proof of Customer affiliate pool" is turning heads: - @say_gm_ pays people who refer new developers that actually spend money on its AI gateway - You can earn up to $1 worth of SayGM Subnet 28 alpha for every $1 your referrals spend during their first 30 days Example: you refer a developer who spends $1,000 -> you could earn up to $1,000 worth of SN28 alpha - The rewards do not come from SayGM's normal business revenue or marketing budget. They come from a pool funded by Subnet 28 emissions So now they have an amazing product and an effective growth strategy Sky is the limit here 🚀
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This one hits different for me I’ve seen Shell stations since I was a kid. Now a Bittensor subnet is actually deploying physical AI at them I’m holding the token too, so it feels personal. Most of what we see here stays on screens. Seeing something from this ecosystem show up at a place I’ve known my whole life is a different kind of progress. Still early but it matters to me bittensor:native
ladies and gentlemen. @manakoai is officially working with @Shell. deploying physical ai to better their fuel retail operations. lfgooooooo🔥👊🚀
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bittensor:native to $5,000 is easy peasy
How far will $TAO go? ‣ $500 ‣ $1,000 ‣ $1,500 ‣ $2,000 ‣ $2,500 (10x from the current price of $259)
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TEN bittensor:native
$TAO or $NEAR? 🤔 Are you choosing 10 $TAO or 100 $NEAR right now? 👀 Price, ⬜️ $TAO : $278 🟩 $NEAR : $5.25 Market Cap, ⬜️ $TAO : $3.15B 🟩 $NEAR : $6.88B #aicrypto #crypto #tao #near
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For $899, you can't even call an emergency service 😂
Your wealth is digital. The device you manage it with should be built for that. Meet Ledger Atom™: the security of industry leading hardware, the convenience of your everyday apps, plus control over your AI tools, and a rapidly expanding platform of apps, all in one quantum ready device. Agents propose. You approve. Your Ledger signer enforces.
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Fast and Furious is never ending now 🫣
We got Flying Car before GTA 6 bro Whatever Tesla is up to, they’re very close if not there already Can’t wait for Jason Statham to use this in one of his movies
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Interesting one. Giving the actual data collection devices their own on-chain identities makes the footage more verifiable instead of just trusting whoever submitted it. Robotics data is already getting valuable enough that people will try to fake it, so tying recordings back to specific hardware feels practical. Curious to see if the financing side actually gets used once more devices are out there or if this mostly stays as an identity layer for now. bittensor:native
We’re bringing @peaq’s machine identity infrastructure to OpenRoboto Shift. Our first 30 OR-S1 data collectors now use peaqOS Pro, each with its own decentralized identity (DID) on @solana.
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Danny Herrmann retweeted
With eTAO on the horizon, it's finally time. Talking Targon 001 with @const_reborn drops tomorrow.
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Mainnet was expected but the interesting part is they're bringing an already running network with real providers instead of starting from zero The Capacity Reserve idea makes sense to me using excess emissions to actually fund capacity instead of just letting it sit or get dumped. At least it shows some longer-term thinking Still early though. Permissionless is cool on paper but in privacy stuff trust and real usage take time. Execution from here is what will matter bittensor:native
UR is live on mainnet on SN25! - Our 100k+ network providers are being transitioned to Bittensor miners - Our validator is active, setting weights and verifying traffic - It's permissionless for anyone to become a miner or validator - Launch of Network Capacity Reserve (more info below) After many weeks of hard work and countless hours spent to get here, we are proud of this milestone and appreciate all your patience on the journey The job is far from complete but this is a big step forward by moving our infrastructure onchain. The core mission is very important to us and it's critical we build with intention, while properly testing these new changes UR is building the privacy network for everyone and we are excited to be building this alongside the Bittensor community Together we will help empower people across the world to have privacy online
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Danny Herrmann retweeted
Perturb (@perturbaix – Bittensor Subnet 26) runs a live adversarial testing network where miners compete to find the smallest image change that flips what an AI model sees. Validators then confirm two things: the model’s answer actually changed and the change stays small enough that a human would not notice it. The strongest attacks earn bittensor:native. Copied work earns nothing. Companies receive a robustness score, a heatmap of weak spots, verified attack examples for retraining, and an on-chain certificate of the testing. Image-model testing is live today. Text and multimodal attacks are on the roadmap. This is the practical way to harden models against the kinds of tiny physical changes that have already fooled real systems. Full breakdown in the video below (Angle 1) 👇 #PerturbVideo
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In 2018, researchers showed that a few black-and-white stickers could make an AI image classifier mistake a stop sign for a 45 mph speed limit sign That’s the kind of vulnerability @perturbaix is built to uncover Running on Bittensor SN26, PerturbAI turns adversarial testing into a competitive process where miners search for the smallest changes that fool image models But finding an attack isn’t enough Validators verify that the model’s prediction actually changes and that the perturbation remains imperceptible to humans Miners earn bittensor:native for successful attacks, while verified examples can help improve the models being tested This creates an ongoing incentive to discover weaknesses that conventional testing might miss, rather than relying solely on one-off audits The interesting part of SN26 is how it separates attack discovery from verification. Finding vulnerabilities takes creativity and computation, while validating them follows measurable criteria PerturbAI turns that process into a continuous competition where better attacks produce useful training data
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One thing I find interesting about AlphaRidge is that you don’t have to start from scratch if you already use TradingView Pine scripts You can bring an existing script into RidgeScript, compile it and use it across charts, a screener covering ~4,500 US stocks + crypto and even build strategies or automations around it The team behind Bittensor SN45 built @alpharidge_ai, with SN45 powering its news and events engine Customers are already paying for it The real value is connecting the whole workflow in one place instead of jumping between tools bittensor:native
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bittensor:native had babies 🍼 From staking 🤭
I had forgotten about this old Ledger wallet, so I opened it up to check if it was safe. To my surprise, I discovered I had stored a lot of $TAO inside, the only generational opportunity since Bitcoin.
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$78k buyback in the next 7 days, roughly 280 bittensor:native worth 🔥 That’s real buying pressure in my view
We've not forgotten about this. We'll be buying back the remaining $78k in the next 7 days as promised.
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SN65 just shipped its first release-ready model and it's 40% smaller than the base while keeping the full 32k context That's the part that matters because a smaller model with the same usable context is something people can actually deploy Now I want to see the case study numbers and what the consumer product looks like. That's where this proves itself
TPN Labs produced its first release-ready model. The model (TPN005) is the outcome of an optimization process that reduced the size of the Ministral-3-8B base model by ~40%, while keeping its full 32k context. This was the first round scored entirely on Fluid Bench, and it marks the first successful TPN upgrade. So, what now? We are happy with this result. This was Fluid Bench's first iteration, which paved the way for even better models to be produced by Subnet 65, with many more patches and upgrades to be implemented along the way. Subnet produced models will become highly relevant once we release TPN's upcoming consumer facing product. To close Competition 5 on a high note, we'll release a case study with all the numbers shortly.
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The next Wall Street fits in your wallet ethereum:0xfaba6f8e4a5e8ab82f62fe7c39859fa577269be3
A generational shift is underway. Tokenization is changing who gets to participate in the world’s leading financial markets. The next Wall Street fits in your wallet.
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bittensor:native to $3000 🔥 No explanation needed 🤫
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