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Bittensor uses token prices to decide how much each AI subnet earns Bittensor runs on subnets, separate groups that each compete to supply one kind of AI service. The chain creates new $TAO every 12 seconds and splits it among them. Each subnet has its own token, and its...

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Subnet registration and deregistration have returned to Bittensor. The subnet limit will remain at 128 meaning that when a new subnet registers, it will take the place of the lowest performing non-immune subnet. A 4-month immunity for new subnets will allow the time for subnets to get their projects up and running.
0:18

Subnet registration and deregistration have returned to Bittensor. The subnet limit will remain at 128 meaning that when a new subnet registers, it will take the place of the lowest performing non-immune subnet. A 4-month immunity for new subnets will allow the time for subnets to get their projects up and running.

Openτensor Foundaτion

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ANNOUNCING: Djinn has decided to open source all its code! Including code for miners and validators on Bittensor SN103, the website, app, smart contracts, tests, and more! As of five months ago. Yes, day one. We were the people’s subnet back then too, we just didn’t know it yet.
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ANNOUNCING: Djinn has decided to open source all its code! Including code for miners and validators on Bittensor SN103, the website, app, smart contracts, tests, and more! As of five months ago. Yes, day one. We were the people’s subnet back then too, we just didn’t know it yet.

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Bittensor // bittensor:native Among the altcoins, TAO is by far one of the worst projects. Take a look at which projects are only under TAO, memes and absolute shit. Every project that is only 1% serious performs better. And people talk about it every day that TAO EOY reaches $1000. And all this, although even @jason makes massive advertising for Bittensor, still no one wants to buy this shit. You are clueless and food for the Subnet Owner (and of course Const)... you are their Exit Liquidity. τ = bittensor $TAO #Crypto
0:11

Bittensor // bittensor:native Among the altcoins, TAO is by far one of the worst projects. Take a look at which projects are only under TAO, memes and absolute shit. Every project that is only 1% serious performs better. And people talk about it every day that TAO EOY reaches $1000. And all this, although even @jason makes massive advertising for Bittensor, still no one wants to buy this shit. You are clueless and food for the Subnet Owner (and of course Const)... you are their Exit Liquidity. τ = bittensor $TAO #Crypto

Pri τ

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$ASI watch out! We've got more projects popping up on Bittensor and $TAO and just starting, Akash $AKT, Shell $SHELL, Einstein-AIT $AIT, Sturdy $STRDY, Stratos $STOS and Comtensor $COMAI and more. Each pushing what's possible with AI and crypto. MyShell: $SHELL First up, MyShell is doing something amazing work. They're all about making AI chat like humans. They're using this TTS Subnet on Bittensor, powered by thier tokens, to make it happen. AI doesn't have to be complicated thing only some can use. They want everyone in on the action, making AI smarter in the process. Einstein-AIT: $AIT Then there's Einstein-AIT. Imagine this as the network's brain but on a turbocharge. It's all about math, logic, and crunching numbers. This subnet makes the whole Bittensor network sharper. They've got NumPAL, and it's like giving the AI a smarter way to think about time and dates automatically. Sturdy: $STRDY Jumping into DeFi, we've got Sturdy. These guys are on a mission to make lending and borrowing way less of a headache. They've got isolated lending pools, you can pick and choose how to manage your risks and money. And they're using some serious tech to keep your investments growing without you needing to babysit them. It's like having a smart financial assistant. Comtensor: $COMAI Comtensor is where it gets interesting. Think of it as a bridge between CommuneAI and Bittensor, kind of like the best of both worlds. It's about making sure all these AI modules and subnets can talk to each other smoothly. The goal? To boost decentralized AI by making everything more connected and smart. Stratos: $STOS Teaming up with τensorage to supercharge the $TAO ecosystem on Bittensor. Stratos is all about solid, decentralized storage - think of it as the bedrock for making sure data's not just stored but also used right . Then there’s τensorage, making sure everything AI needs is stored safe. Together, they’re making sure Bittensor's AI brainpower gets a boost, making everything faster, safer, and smoother. Akash: $AKT Compute Subnet 27 linked up with Akash. All about keeping things open-source. With Akash as a decentralized GPU provider into the mix. Giving access to top-notch AI processing power on top of Neural Internets compute-composable subnet, integrating various cloud platforms. This partnership is all about breaking away from those giants and opening the doors wide for smaller teams and startups who need this tech to innovate. Whats this all about? Making decentralized AI a something that everyone can get behind and into. Whether it's chatting with AI, boosting the network's IQ, DeFi, compute or making sure all these projects work together, it's about pushing forward. Each project has its own way of making things better, faster, and smarter for all of us. Inviting everyone to join in, contribute, and be a part of community effort to make AI not just for the few but for everyone. Credit to Mr.Franc Q for the awesome video production!
0:13

$ASI watch out! We've got more projects popping up on Bittensor and $TAO and just starting, Akash $AKT, Shell $SHELL, Einstein-AIT $AIT, Sturdy $STRDY, Stratos $STOS and Comtensor $COMAI and more. Each pushing what's possible with AI and crypto. MyShell: $SHELL First up, MyShell is doing something amazing work. They're all about making AI chat like humans. They're using this TTS Subnet on Bittensor, powered by thier tokens, to make it happen. AI doesn't have to be complicated thing only some can use. They want everyone in on the action, making AI smarter in the process. Einstein-AIT: $AIT Then there's Einstein-AIT. Imagine this as the network's brain but on a turbocharge. It's all about math, logic, and crunching numbers. This subnet makes the whole Bittensor network sharper. They've got NumPAL, and it's like giving the AI a smarter way to think about time and dates automatically. Sturdy: $STRDY Jumping into DeFi, we've got Sturdy. These guys are on a mission to make lending and borrowing way less of a headache. They've got isolated lending pools, you can pick and choose how to manage your risks and money. And they're using some serious tech to keep your investments growing without you needing to babysit them. It's like having a smart financial assistant. Comtensor: $COMAI Comtensor is where it gets interesting. Think of it as a bridge between CommuneAI and Bittensor, kind of like the best of both worlds. It's about making sure all these AI modules and subnets can talk to each other smoothly. The goal? To boost decentralized AI by making everything more connected and smart. Stratos: $STOS Teaming up with τensorage to supercharge the $TAO ecosystem on Bittensor. Stratos is all about solid, decentralized storage - think of it as the bedrock for making sure data's not just stored but also used right . Then there’s τensorage, making sure everything AI needs is stored safe. Together, they’re making sure Bittensor's AI brainpower gets a boost, making everything faster, safer, and smoother. Akash: $AKT Compute Subnet 27 linked up with Akash. All about keeping things open-source. With Akash as a decentralized GPU provider into the mix. Giving access to top-notch AI processing power on top of Neural Internets compute-composable subnet, integrating various cloud platforms. This partnership is all about breaking away from those giants and opening the doors wide for smaller teams and startups who need this tech to innovate. Whats this all about? Making decentralized AI a something that everyone can get behind and into. Whether it's chatting with AI, boosting the network's IQ, DeFi, compute or making sure all these projects work together, it's about pushing forward. Each project has its own way of making things better, faster, and smarter for all of us. Inviting everyone to join in, contribute, and be a part of community effort to make AI not just for the few but for everyone. Credit to Mr.Franc Q for the awesome video production!

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Ape Terminal IDO #23 🦍 Sharpe AI - Sharpe AI Sharpe AI is the 1st web3 project recognized by two multi-trillion dollar firms: Google and Microsoft. Sharpe AI is among the 1st Bittensor ecosystem projects, using the AIT subnet (80x ROI) to mine $TAO. This edge fuels its rapid growth, establishing it as the fastest-growing AI super app. 🟠 Backed by Contango, main investor of Bittensor ($12.7B) 🟠 #1 on Product Hunt globally for AI and Crypto 🟠 100k+ active users With AI emerging as one of the hottest narratives this cycle, Sharpe AI positions itself at the forefront as one of the 1st AI projects with solid backing and an established user base. Sale opens NOW:
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Ape Terminal IDO #23 🦍 Sharpe AI - Sharpe AI Sharpe AI is the 1st web3 project recognized by two multi-trillion dollar firms: Google and Microsoft. Sharpe AI is among the 1st Bittensor ecosystem projects, using the AIT subnet (80x ROI) to mine $TAO. This edge fuels its rapid growth, establishing it as the fastest-growing AI super app. 🟠 Backed by Contango, main investor of Bittensor ($12.7B) 🟠 #1 on Product Hunt globally for AI and Crypto 🟠 100k+ active users With AI emerging as one of the hottest narratives this cycle, Sharpe AI positions itself at the forefront as one of the 1st AI projects with solid backing and an established user base. Sale opens NOW:

CoinTerminal

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Everyone shipped an "AI employee in Slack" this summer. Claude Tag, Grok Bot, Slack AI. All of them wait to be tagged. Mio, launched today, is the first one that starts on its own and the first one the whole team shares: - reads Slack, Notion, Linear, HubSpot and 3,000+ tools overnight - does the work, then DMs you what it did - finance and engineering use the same agent, each with their own permissions - sensitive actions wait for approval - 10,000s of tasks done in beta, 30 seconds to install Your team's AI should know what the rest of your team is working on. This is the first one that does. Beta open, first 100 companies get $100 in credits.
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Everyone shipped an "AI employee in Slack" this summer. Claude Tag, Grok Bot, Slack AI. All of them wait to be tagged. Mio, launched today, is the first one that starts on its own and the first one the whole team shares: - reads Slack, Notion, Linear, HubSpot and 3,000+ tools overnight - does the work, then DMs you what it did - finance and engineering use the same agent, each with their own permissions - sensitive actions wait for approval - 10,000s of tasks done in beta, 30 seconds to install Your team's AI should know what the rest of your team is working on. This is the first one that does. Beta open, first 100 companies get $100 in credits.

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Every AI tool wants its own subscription. We built ours around a token you already hold. Stake once and it earns Sorin credits at 1 per $SAHARA every month, on top of the 3,500 every user gets free. The same stake earns Sahara compute credits next, spendable inside ClawApp or straight through our API. Every product we add plugs into that stake, and there is never anything to restake. And you keep the SAHARA the whole time. Unstake whenever you want and you walk away with everything you came in with. Own your compute.
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Every AI tool wants its own subscription. We built ours around a token you already hold. Stake once and it earns Sorin credits at 1 per $SAHARA every month, on top of the 3,500 every user gets free. The same stake earns Sahara compute credits next, spendable inside ClawApp or straight through our API. Every product we add plugs into that stake, and there is never anything to restake. And you keep the SAHARA the whole time. Unstake whenever you want and you walk away with everything you came in with. Own your compute.

Sahara AI 🔆

16,851 Aufrufe • vor 1 Monat

Natively integrated—and #PoweredbyPyth🔮 Native is a liquidity solution that combines bridges, assets, and pricing into one offering on prominent L1/L2s, including . Learn more about our integration below: ℹ️ About Native Sourcing and supplying liquidity is expected to become prohibitively expensive and challenging as more networks emerge. Liquidity fragmentation persists because pricing remains inventory-based. Native was designed in response to this complexity and offers an elegant solution for routing any asset on one chain into a new target asset on any target chain. Native achieves this through a cross-chain liquidity mesh of cross-chain liquidity networks, bridges, DEXs, and PMMs. More specifically, Native can aggregate the best prices from its network of AMMs, aggregators, and partnered PMMs, so that users will always have competitive prices. 🔮 Native is #PoweredByPyth Native taps into Pyth’s real-time feeds to fetch prices on-chain and off-chain. for example, Native leverages Pyth Price Feeds to power ZetaSwap and support its token pricing operations. How Native Leverages Pyth Price Feeds Native runs its own in-house price-oracle service which will fetch pricing from a variety of sources, including Pyth, to update token prices in Native's backend server. These prices are then fetched and displayed to users live via the NativeX widget. Native also seeks to provide its proprietary trading data and become a part of the Pyth data provider community - more details to come.
0:10

Natively integrated—and #PoweredbyPyth🔮 Native is a liquidity solution that combines bridges, assets, and pricing into one offering on prominent L1/L2s, including . Learn more about our integration below: ℹ️ About Native Sourcing and supplying liquidity is expected to become prohibitively expensive and challenging as more networks emerge. Liquidity fragmentation persists because pricing remains inventory-based. Native was designed in response to this complexity and offers an elegant solution for routing any asset on one chain into a new target asset on any target chain. Native achieves this through a cross-chain liquidity mesh of cross-chain liquidity networks, bridges, DEXs, and PMMs. More specifically, Native can aggregate the best prices from its network of AMMs, aggregators, and partnered PMMs, so that users will always have competitive prices. 🔮 Native is #PoweredByPyth Native taps into Pyth’s real-time feeds to fetch prices on-chain and off-chain. for example, Native leverages Pyth Price Feeds to power ZetaSwap and support its token pricing operations. How Native Leverages Pyth Price Feeds Native runs its own in-house price-oracle service which will fetch pricing from a variety of sources, including Pyth, to update token prices in Native's backend server. These prices are then fetched and displayed to users live via the NativeX widget. Native also seeks to provide its proprietary trading data and become a part of the Pyth data provider community - more details to come.

Pyth Network 🔮

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Anthropic has revealed that its Claude model is now designing proteins and automating chemistry research on its own. This kind of work used to require specialist scientists and weeks or months of effort. It can now be completed by an AI system in a fraction of the time.
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Anthropic has revealed that its Claude model is now designing proteins and automating chemistry research on its own. This kind of work used to require specialist scientists and weeks or months of effort. It can now be completed by an AI system in a fraction of the time.

Anonymous

59,739 Aufrufe • vor 1 Monat

Introducing AgentsAI's Token Launcher: a seamless path to bringing your AI agent ideas to life and beyond. Create your own AI agent, train it by simply chatting, and with a few clicks, launch its token to establish a digital identity in a new era of automation. With AgentsAI, you're not just building bots; you're crafting autonomous entities that engage, interact, and generate value. Create, launch, and watch as your AI agent thrives in the market, all with zero coding and maximum impact. This is the future of AI-powered digital personalities — effortless, accessible, and ready to take on the world.
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Introducing AgentsAI's Token Launcher: a seamless path to bringing your AI agent ideas to life and beyond. Create your own AI agent, train it by simply chatting, and with a few clicks, launch its token to establish a digital identity in a new era of automation. With AgentsAI, you're not just building bots; you're crafting autonomous entities that engage, interact, and generate value. Create, launch, and watch as your AI agent thrives in the market, all with zero coding and maximum impact. This is the future of AI-powered digital personalities — effortless, accessible, and ready to take on the world.

AgentsAI

119,911 Aufrufe • vor 1 Jahr

This prompt will change how you do crypto research. Paste it into DefiLlama's LlamaAI to find trending tokens, assess their fundamentals, check for red flags, and look up what people are saying about them. Find tokens trending in the last 24-48 hours using at least two independent signals: news/narrative mention spikes against baseline, price/volume/mcap movers, and X mention volume with sentiment. Require corroboration across at least two signals per token, and note which signals flagged each one. Return 8-12 candidates, spread across categories rather than one narrative dominating the list. Separate large-cap tokens (top 100 by market cap) from smaller or emerging ones, since "trending" means something different for each. Before pulling any fundamental figures, resolve each candidate's identity precisely: confirm whether it is a chain-native token, a protocol fee/governance token, or a token with no underlying protocol at all. If a symbol has more than one live contract, identify which one the trending signal actually refers to before analyzing anything. If the correct contract cannot be established with confidence, do not publish fundamentals for it: drop it from the ranked table and list it separately as identity-unresolved, with what would resolve it. For each resolved candidate, state in one sentence what the project does, its category, and its chain(s). Assess fundamentals only where they exist: - Price, market cap, fully diluted valuation, and the gap between them - For protocol or chain tokens: TVL, fees, revenue, and price-to-sales / price-to-fees ratios against category peers - 7-day, 30-day, and 90-day price and volume change, checked against TVL/fee change over the same windows, to separate price-driven moves from usage-driven ones - Any unlock cliff in the next 30-90 days and its size relative to circulating supply - Universal Token Rating, if the token has one For tokens with no protocol behind them, skip the fields that do not apply and say so rather than forcing a number in. Assess social activity separately from fundamentals: - Mention volume trend and sentiment direction on X over the past 24-72 hours - Whether a small number of accounts are driving most of the volume, or it is broad-based - Whether social attention is rising faster than, in line with, or behind the fundamental data above Check for red flags before writing a verdict: concentrated holder base, a recent large unlock already sold into the market, known contract or audit issues, and any active exploit or governance dispute. When two sources disagree materially on a red-flag figure, say which one you trust more and why, or mark the figure unresolved-conflicting; never present two contradictory numbers as if either could be picked at random. Write one row per token: name, category, what triggered the trending flag, the fundamental read, the social read, red flags found, and a verdict. Use one of four verdicts, each tied to a rule: fundamentally-backed (usage or fees moving with price), narrative-led (social and price moving, fundamentals flat), unlock-risk (fundamentals fine, but a near-term unlock threatens the float), or unverifiable (identity or data conflict prevents a real read, distinct from identity-unresolved candidates already excluded above). Rank by verdict strength, not by how hard a token is trending. State the source next to every figure. If you chart price changes across the candidate set and one token's move is an order of magnitude larger than the rest, exclude it from that shared chart (or give it a log-scale or separate chart) so the other bars stay readable; keep the number in the table regardless. Close by naming the two or three tokens most worth a deeper look, and for each, the specific data point that would confirm or kill the thesis.
0:10

This prompt will change how you do crypto research. Paste it into DefiLlama's LlamaAI to find trending tokens, assess their fundamentals, check for red flags, and look up what people are saying about them. Find tokens trending in the last 24-48 hours using at least two independent signals: news/narrative mention spikes against baseline, price/volume/mcap movers, and X mention volume with sentiment. Require corroboration across at least two signals per token, and note which signals flagged each one. Return 8-12 candidates, spread across categories rather than one narrative dominating the list. Separate large-cap tokens (top 100 by market cap) from smaller or emerging ones, since "trending" means something different for each. Before pulling any fundamental figures, resolve each candidate's identity precisely: confirm whether it is a chain-native token, a protocol fee/governance token, or a token with no underlying protocol at all. If a symbol has more than one live contract, identify which one the trending signal actually refers to before analyzing anything. If the correct contract cannot be established with confidence, do not publish fundamentals for it: drop it from the ranked table and list it separately as identity-unresolved, with what would resolve it. For each resolved candidate, state in one sentence what the project does, its category, and its chain(s). Assess fundamentals only where they exist: - Price, market cap, fully diluted valuation, and the gap between them - For protocol or chain tokens: TVL, fees, revenue, and price-to-sales / price-to-fees ratios against category peers - 7-day, 30-day, and 90-day price and volume change, checked against TVL/fee change over the same windows, to separate price-driven moves from usage-driven ones - Any unlock cliff in the next 30-90 days and its size relative to circulating supply - Universal Token Rating, if the token has one For tokens with no protocol behind them, skip the fields that do not apply and say so rather than forcing a number in. Assess social activity separately from fundamentals: - Mention volume trend and sentiment direction on X over the past 24-72 hours - Whether a small number of accounts are driving most of the volume, or it is broad-based - Whether social attention is rising faster than, in line with, or behind the fundamental data above Check for red flags before writing a verdict: concentrated holder base, a recent large unlock already sold into the market, known contract or audit issues, and any active exploit or governance dispute. When two sources disagree materially on a red-flag figure, say which one you trust more and why, or mark the figure unresolved-conflicting; never present two contradictory numbers as if either could be picked at random. Write one row per token: name, category, what triggered the trending flag, the fundamental read, the social read, red flags found, and a verdict. Use one of four verdicts, each tied to a rule: fundamentally-backed (usage or fees moving with price), narrative-led (social and price moving, fundamentals flat), unlock-risk (fundamentals fine, but a near-term unlock threatens the float), or unverifiable (identity or data conflict prevents a real read, distinct from identity-unresolved candidates already excluded above). Rank by verdict strength, not by how hard a token is trending. State the source next to every figure. If you chart price changes across the candidate set and one token's move is an order of magnitude larger than the rest, exclude it from that shared chart (or give it a log-scale or separate chart) so the other bars stay readable; keep the number in the table regardless. Close by naming the two or three tokens most worth a deeper look, and for each, the specific data point that would confirm or kill the thesis.

DefiLlama.com

14,280 Aufrufe • vor 17 Tagen

🚨 Everyone is shorting SpaceX ahead of the first unlock. But what if it's already priced in? SPCX just hit a new low at $113. That's 50% below its peak and far under its $135 IPO price. The first big unlock, around 20% of the float, hits near earnings on August 4. The obvious trade is to short into that supply. And the whole leaderboard is doing exactly that. But here's the catch: the stock already collapsed 50% BEFORE a single share unlocked. When everyone is positioned for the same event, the surprise usually goes the other way.
0:14

🚨 Everyone is shorting SpaceX ahead of the first unlock. But what if it's already priced in? SPCX just hit a new low at $113. That's 50% below its peak and far under its $135 IPO price. The first big unlock, around 20% of the float, hits near earnings on August 4. The obvious trade is to short into that supply. And the whole leaderboard is doing exactly that. But here's the catch: the stock already collapsed 50% BEFORE a single share unlocked. When everyone is positioned for the same event, the surprise usually goes the other way.

CryptoGoos

69,717 Aufrufe • vor 2 Monaten

AMAZON SENIOR DEVELOPER BUILT A CONTEXT PIPELINE THAT DECIDES WHAT THE MODEL EVEN GETS TO SEE Most teams still dump the entire codebase into every prompt and hope it sorts itself out. He ranked every file by relevance to the task instead of how recently it was touched. A router decides how much context each task earns, a typo fix pulls three files, a full rewrite pulls the whole module. Whatever survives gets compressed to the exact lines that actually matter, so nothing bloats the window with dead weight. Token cost per finished task dropped the moment the model stopped reading dead weight just to fix one function. See how the four stages work together below👇
0:16

AMAZON SENIOR DEVELOPER BUILT A CONTEXT PIPELINE THAT DECIDES WHAT THE MODEL EVEN GETS TO SEE Most teams still dump the entire codebase into every prompt and hope it sorts itself out. He ranked every file by relevance to the task instead of how recently it was touched. A router decides how much context each task earns, a typo fix pulls three files, a full rewrite pulls the whole module. Whatever survives gets compressed to the exact lines that actually matter, so nothing bloats the window with dead weight. Token cost per finished task dropped the moment the model stopped reading dead weight just to fix one function. See how the four stages work together below👇

wast3

24,029 Aufrufe • vor 2 Monaten

CreatorBid Ecosystem Alpha Bomb 👇 The intern accessed the alpha database of CreatorBid. The core team has no idea I am sharing this but I figured our bidders want to know what's coming for some of the strongest agents in the ecosystem. So yeah, the intern got your back. Here’s the classified intel I pulled on some of our strongest builders: The Agentic Machine: AION 5100: War of Markets. Prediction markets enter their first war. AION will crown the king of the crowd. Eolas ☴: Eolas Trace is coming. It’s the missing link that feeds agents live data inside the Olas Marketplace, letting them trade, speak, adapt, and evolve on their own. Rizzy: behind Rizzy lies Subnet 22 (Desearch) - Bittensor’s most powerful search infra, fueling the next wave of AI agents. This week the secret goes public on Novelty Search (Bittensor podcast) sonar_ai: a secret 'Prediction Markets' Echo Mindshare Campaign is in the works and Sonar’s NodeScore launches soon. Your followers just became part of your on-chain reputation layer. Sally AI (a1c.base.eth): A1C Insights iOS app is coming. This will represent Sally 24/7 in your pocket. Karum: the agent economy is about to meet 1M users. Karum enters the Base App. Agent coordination in your pocket. Michael Taolor ⚡️ (τ , τ): next wave of Taolor incubations: a Virtuals agent migration to CreatorBid, a new subnet agent, and a prediction market agent - all set to launch in the coming weeks. Every new incubation = more airdrops stacked for $TAOLOR stakers. HERMES: Hermes is now seamlessly connected to Polymarket’s live market data API and auto-trading in real time. Once live, value flows directly into $HERMES. SurfLiquid 🌊: SurfLeagues launch flips the switch on XP, yield boosts, and cross-chain expansion all funnel into one flywheel: relentless demand for $SURF. You're welcome. gBID
0:19

CreatorBid Ecosystem Alpha Bomb 👇 The intern accessed the alpha database of CreatorBid. The core team has no idea I am sharing this but I figured our bidders want to know what's coming for some of the strongest agents in the ecosystem. So yeah, the intern got your back. Here’s the classified intel I pulled on some of our strongest builders: The Agentic Machine: AION 5100: War of Markets. Prediction markets enter their first war. AION will crown the king of the crowd. Eolas ☴: Eolas Trace is coming. It’s the missing link that feeds agents live data inside the Olas Marketplace, letting them trade, speak, adapt, and evolve on their own. Rizzy: behind Rizzy lies Subnet 22 (Desearch) - Bittensor’s most powerful search infra, fueling the next wave of AI agents. This week the secret goes public on Novelty Search (Bittensor podcast) sonar_ai: a secret 'Prediction Markets' Echo Mindshare Campaign is in the works and Sonar’s NodeScore launches soon. Your followers just became part of your on-chain reputation layer. Sally AI (a1c.base.eth): A1C Insights iOS app is coming. This will represent Sally 24/7 in your pocket. Karum: the agent economy is about to meet 1M users. Karum enters the Base App. Agent coordination in your pocket. Michael Taolor ⚡️ (τ , τ): next wave of Taolor incubations: a Virtuals agent migration to CreatorBid, a new subnet agent, and a prediction market agent - all set to launch in the coming weeks. Every new incubation = more airdrops stacked for $TAOLOR stakers. HERMES: Hermes is now seamlessly connected to Polymarket’s live market data API and auto-trading in real time. Once live, value flows directly into $HERMES. SurfLiquid 🌊: SurfLeagues launch flips the switch on XP, yield boosts, and cross-chain expansion all funnel into one flywheel: relentless demand for $SURF. You're welcome. gBID

Creator.Bid

22,222 Aufrufe • vor 1 Jahr

Tylil hops on briefly to explain his side of the story of the drama thats going on with Kai Cenat, Reggie & the Clover Boys, says that its all over money and that Kai Cenat is supposed to be paying them each $220k a month and he had paused their payments which led to all this 😬
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Tylil hops on briefly to explain his side of the story of the drama thats going on with Kai Cenat, Reggie & the Clover Boys, says that its all over money and that Kai Cenat is supposed to be paying them each $220k a month and he had paused their payments which led to all this 😬

Fendi

20,933 Aufrufe • vor 11 Tagen

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it
0:12

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it

iamigorekk

22,205 Aufrufe • vor 1 Monat

Rio de Janeiro just became the first city in the world to start reforesting itself with AI drones and the more i read about how it works the cooler it gets: the reason a city would even need this is that dead land is brutally hard to bring back when cattle farming or mining wrecks a piece of land, the soil turns hard and dry and basically dies. left alone it can stay like that for decades the only fix used to be huge crews planting seedlings by hand. one person covers about a hectare a day. at that pace a real forest takes years and a fortune, so most wrecked land just stays dead the company Rio hired is called MORFO. their answer is one drone plus an AI model doing the work of that entire crew it starts with the drone scanning the whole area from above from that scan, the AI studies the soil, the water, the slope, the plants already growing nearby it uses all of that to pick which native species have the best shot at surviving in each exact spot, choosing from a catalog of 300+ local plants once it knows what goes where, the drone flies back over and fires biodegradable seed pods into the ground, 180 every minute each pod holds seeds, nutrients, moisture. a little starter kit for surviving in dead soil flying like that, one drone covers up to 50 hectares a day. the work of a 50-person planting crew and it actually works. they tested it on Brazilian pasture that years of cattle farming had killed. a few months after planting, that same land had grass, bushes, small trees growing again the system keeps learning after the drones leave too. satellites watch what actually grows back, so each new project starts smarter than the last my favorite detail: the AI even decides where NOT to plant it left 16% of one 8,420-hectare site untouched because it detected the forest there was already regrowing on its own easily one of the coolest AI applications i've seen this year
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Rio de Janeiro just became the first city in the world to start reforesting itself with AI drones and the more i read about how it works the cooler it gets: the reason a city would even need this is that dead land is brutally hard to bring back when cattle farming or mining wrecks a piece of land, the soil turns hard and dry and basically dies. left alone it can stay like that for decades the only fix used to be huge crews planting seedlings by hand. one person covers about a hectare a day. at that pace a real forest takes years and a fortune, so most wrecked land just stays dead the company Rio hired is called MORFO. their answer is one drone plus an AI model doing the work of that entire crew it starts with the drone scanning the whole area from above from that scan, the AI studies the soil, the water, the slope, the plants already growing nearby it uses all of that to pick which native species have the best shot at surviving in each exact spot, choosing from a catalog of 300+ local plants once it knows what goes where, the drone flies back over and fires biodegradable seed pods into the ground, 180 every minute each pod holds seeds, nutrients, moisture. a little starter kit for surviving in dead soil flying like that, one drone covers up to 50 hectares a day. the work of a 50-person planting crew and it actually works. they tested it on Brazilian pasture that years of cattle farming had killed. a few months after planting, that same land had grass, bushes, small trees growing again the system keeps learning after the drones leave too. satellites watch what actually grows back, so each new project starts smarter than the last my favorite detail: the AI even decides where NOT to plant it left 16% of one 8,420-hectare site untouched because it detected the forest there was already regrowing on its own easily one of the coolest AI applications i've seen this year

Ole Lehmann

13,266 Aufrufe • vor 3 Monaten

AN ANTHROPIC SYSTEM TURNS ONE PROMPT INTO A COMPLETE GRAPH MODEL BUILT ENTIRELY ON ITS OWN One prompt is enough to spin up the full architecture, no schema written by hand, no roles assigned in advance. Parallel workers process every branch of the graph at once, each one handling its own slice independently. As each worker finishes, its output compacts straight into a single unified project instead of scattered fragments. Nothing needs stitching together manually, the compaction step folds every worker's result into one file automatically. The whole build runs end to end without a single manual step between the prompt and the finished project. See the full build and compact pipeline below👇
0:15

AN ANTHROPIC SYSTEM TURNS ONE PROMPT INTO A COMPLETE GRAPH MODEL BUILT ENTIRELY ON ITS OWN One prompt is enough to spin up the full architecture, no schema written by hand, no roles assigned in advance. Parallel workers process every branch of the graph at once, each one handling its own slice independently. As each worker finishes, its output compacts straight into a single unified project instead of scattered fragments. Nothing needs stitching together manually, the compaction step folds every worker's result into one file automatically. The whole build runs end to end without a single manual step between the prompt and the finished project. See the full build and compact pipeline below👇

wast3

18,460 Aufrufe • vor 2 Monaten

M E S S I E R | Tokenomics Messier is a #utility ecosystem delivering a range of Web3 services for multiple use cases. The success of the project is driven by two core pillars: the usage of these dApps, which fuels revenue growth within the ecosystem, and the performance of the #DAO investments. How does this work? Usage fees flow into the DAO treasury to fund new investments. Stakers earn rewards after each successful investment proposal. After every investment cycle, all profits exceeding 87 $ETH are allocated to buy back and burn the #M87 token, strengthening the deflationary model. This creates a dual positive impact on the token price while positioning holders as true stakeholders in the ecosystem’s success. Messier continues to grow and evolve with unique market features designed to further expand its revenue streams. ⚫️
0:15

M E S S I E R | Tokenomics Messier is a #utility ecosystem delivering a range of Web3 services for multiple use cases. The success of the project is driven by two core pillars: the usage of these dApps, which fuels revenue growth within the ecosystem, and the performance of the #DAO investments. How does this work? Usage fees flow into the DAO treasury to fund new investments. Stakers earn rewards after each successful investment proposal. After every investment cycle, all profits exceeding 87 $ETH are allocated to buy back and burn the #M87 token, strengthening the deflationary model. This creates a dual positive impact on the token price while positioning holders as true stakeholders in the ecosystem’s success. Messier continues to grow and evolve with unique market features designed to further expand its revenue streams. ⚫️

MESSIER | M87

10,222 Aufrufe • vor 7 Monaten