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A $10 MILLION DUMP JUST TESTED WHETHER BITTENSOR IS REAL OR NOT. THE NETWORK GAVE ITS ANSWER. Covenant AI walked. The biggest builder team in the ecosystem. The team behind the 72B parameter model that Jensen Huang praised on the All In podcast. They accused leadership of centralization. Said...

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23,317 просмотров • 2 месяцев назад •via X (Twitter)

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Subnet 64 Chutes just confirmed in their latest interview with Jesus Martinez that they have the capability to run 1 trillion parameter models. let's put that into perspective for a second: templar was making waves for running 72b models and rightfully so, that was genuinely impressive. but Chamath Palihapitiya, when he brought up templar in a recent interview with Jensen Huang from NVIDIA, thought they were running 4b models. not 72b. 4b. and he was still bullish on it. now imagine when he finds out what chutes confirmed they can do.. 1 trillion parameters. on a decentralised subnet. no AWS. no Google Cloud. no centralised infrastructure pulling the strings. just Bittensor doing what it was always supposed to do - incentivising the best compute in the world to show up and compete. Jensen Huang talks about whoever is pushing the frontier of compute. that's the conversation chutes just walked into. this is the kind of milestone that doesn't stay quiet for long. when people outside of crypto start connecting the dots that a bittensor subnet is running inference at a scale that rivals or exceeds what the top AI labs are deploying, the narrative around $TAO changes completely. Chamath gets it wrong on the model size and is still impressed. Jensen sees who's actually moving compute forward. and chutes just put a number on the table that neither of them can ignore. the noise hasn't started yet. but it will.
0:21

Subnet 64 Chutes just confirmed in their latest interview with Jesus Martinez that they have the capability to run 1 trillion parameter models. let's put that into perspective for a second: templar was making waves for running 72b models and rightfully so, that was genuinely impressive. but Chamath Palihapitiya, when he brought up templar in a recent interview with Jensen Huang from NVIDIA, thought they were running 4b models. not 72b. 4b. and he was still bullish on it. now imagine when he finds out what chutes confirmed they can do.. 1 trillion parameters. on a decentralised subnet. no AWS. no Google Cloud. no centralised infrastructure pulling the strings. just Bittensor doing what it was always supposed to do - incentivising the best compute in the world to show up and compete. Jensen Huang talks about whoever is pushing the frontier of compute. that's the conversation chutes just walked into. this is the kind of milestone that doesn't stay quiet for long. when people outside of crypto start connecting the dots that a bittensor subnet is running inference at a scale that rivals or exceeds what the top AI labs are deploying, the narrative around $TAO changes completely. Chamath gets it wrong on the model size and is still impressed. Jensen sees who's actually moving compute forward. and chutes just put a number on the table that neither of them can ignore. the noise hasn't started yet. but it will.

Alchemist - τ

18,369 просмотров • 2 месяцев назад

Someone just stole from 37,000 $TAO holders and walked away clean. Not because they broke a rule. Because no rule existed to stop them. That changes today. Here is what happened. Covenant AI ran one of the most watched subnets on Bittensor. On April 10, the founder sold their entire position and disappeared. No warning. No announcement. No on-chain signal. By the time holders found out, the price had already moved against them. This was not a hack. This was not a bug. This was a founder legally exiting into their own community with zero accountability. Bittensor just closed that door permanently. The Conviction upgrade is live on mainnet today. Every emission a subnet owner earns now locks automatically the moment it arrives. They cannot touch it immediately. If they want to exit they must submit a public unlock transaction on-chain. Visible to every single person on the network the second it is submitted. Then the clock starts. 30 days before 63% of their position becomes spendable. 90 days before 95% is accessible. You now have a month of warning before the first dollar of sell pressure hits. A silent exit is no longer possible. The founder has to tell you they are leaving before they can leave. And it goes further. Any holder can now lock their tokens toward a different address they believe would run the subnet better. The address with the most locked support behind it becomes eligible to take over entirely. Bad owners can be replaced by the community before they do damage. Before today, subnet investing had one risk nobody could price. The person running it could vanish overnight, and you would never see it coming. That risk has been removed from the equation. Skin in the game used to be a promise. Now, it is a number on a block explorer that every holder can verify in real time. The people who understand what accountable infrastructure means for the value of $TAO will not need to explain themselves later. This is still early.
23:08

Someone just stole from 37,000 $TAO holders and walked away clean. Not because they broke a rule. Because no rule existed to stop them. That changes today. Here is what happened. Covenant AI ran one of the most watched subnets on Bittensor. On April 10, the founder sold their entire position and disappeared. No warning. No announcement. No on-chain signal. By the time holders found out, the price had already moved against them. This was not a hack. This was not a bug. This was a founder legally exiting into their own community with zero accountability. Bittensor just closed that door permanently. The Conviction upgrade is live on mainnet today. Every emission a subnet owner earns now locks automatically the moment it arrives. They cannot touch it immediately. If they want to exit they must submit a public unlock transaction on-chain. Visible to every single person on the network the second it is submitted. Then the clock starts. 30 days before 63% of their position becomes spendable. 90 days before 95% is accessible. You now have a month of warning before the first dollar of sell pressure hits. A silent exit is no longer possible. The founder has to tell you they are leaving before they can leave. And it goes further. Any holder can now lock their tokens toward a different address they believe would run the subnet better. The address with the most locked support behind it becomes eligible to take over entirely. Bad owners can be replaced by the community before they do damage. Before today, subnet investing had one risk nobody could price. The person running it could vanish overnight, and you would never see it coming. That risk has been removed from the equation. Skin in the game used to be a promise. Now, it is a number on a block explorer that every holder can verify in real time. The people who understand what accountable infrastructure means for the value of $TAO will not need to explain themselves later. This is still early.

2xnmore

19,513 просмотров • 1 месяц назад

$TAO is surging and the reason goes well beyond momentum trading. Its a high five for AI! This week on the All-In Podcast, Chamath Palihapitiya highlighted Bittensor's Covenant-72B decentralized AI training milestone as a genuine technical achievement. CEO of NVIDIA Jensen Huang responded by making something clear: decentralized and proprietary AI are not competing visions for the future, they are complementary ones. Neither man had an agenda. Neither was there to talk crypto. That is precisely what makes it significant. When two of the most credible figures in technology acknowledge a sector on its technical merits alone, it marks a turning point. Not just for Bittensor, but for decentralized AI as a whole. Check the article out in The Spectre Edition - $SPECT
0:52

$TAO is surging and the reason goes well beyond momentum trading. Its a high five for AI! This week on the All-In Podcast, Chamath Palihapitiya highlighted Bittensor's Covenant-72B decentralized AI training milestone as a genuine technical achievement. CEO of NVIDIA Jensen Huang responded by making something clear: decentralized and proprietary AI are not competing visions for the future, they are complementary ones. Neither man had an agenda. Neither was there to talk crypto. That is precisely what makes it significant. When two of the most credible figures in technology acknowledge a sector on its technical merits alone, it marks a turning point. Not just for Bittensor, but for decentralized AI as a whole. Check the article out in The Spectre Edition - $SPECT

SPECTRE AI

31,878 просмотров • 3 месяцев назад

On the The All-In Podcast this week, Chamath Palihapitiya asked NVIDIA CEO Jensen Huang about decentralized AI training, calling our Covenant-72B run "a pretty crazy technical accomplishment." One correction: it's 72 billion parameters, not four. Trained permissionlessly across 70+ contributors on commodity internet. The largest model ever pre-trained on fully decentralized infrastructure. Jensen's answer is worth hearing too.
1:21

On the The All-In Podcast this week, Chamath Palihapitiya asked NVIDIA CEO Jensen Huang about decentralized AI training, calling our Covenant-72B run "a pretty crazy technical accomplishment." One correction: it's 72 billion parameters, not four. Trained permissionlessly across 70+ contributors on commodity internet. The largest model ever pre-trained on fully decentralized infrastructure. Jensen's answer is worth hearing too.

templar

472,986 просмотров • 3 месяцев назад

$TAO just reclaimed the #1 AI crypto spot. Most people saw the headline. Almost nobody understands what it means for the price. Here is the data. $NEAR built real infrastructure. Partnerships. Developer activity. A legitimate ecosystem. $TAO just walked past it anyway. Not because of hype. Because Bittensor is the only AI crypto with a functioning marketplace for machine intelligence where supply, demand, and price discovery are all happening on-chain right now. That is not a roadmap. That is a live network. The numbers. 120+ subnets running today. $1.4B+ total ecosystem value. Chutes AI subnet: 150B+ tokens per day. Grayscale GTAO Trust: already live. Single subnet listed on the marketplace at $970,000 asking price. Subnets are becoming assets. The market is starting to price that. What the emission data is telling you. Emission rate is the network's vote on where the most valuable work is being done. When a subnet gains emission share, the collective stake-weighted intelligence of the network has decided that subnet's output is worth more of the TAO supply. Chutes AI gaining emissions while processing 150B tokens daily is not a coincidence. The network is directing capital toward proven output before any headline announces it. Why mainstream money changes everything. James Altucher just launched bluetao. ai, a TAO-powered ChatGPT alternative built directly on Bittensor subnets. He did not just buy the token. He built a product on the network. Products built on a network create structural demand for the native asset. That is how every successful L1 cycle has worked. Bittensor is now getting that builder activity from outside the crypto native world. That is a different signal from a price target tweet. Why $TAO is structurally different. Most AI tokens are betting their chain becomes the preferred environment for AI development. $TAO is not betting on becoming infrastructure. It already is. 120+ subnets running. Miners competing. Validators setting weights. Alpha tokens being priced in real time. The difference between $TAO and every other AI crypto is the difference between a city under construction and a city people are already living in. Van de Poppe said $1,000 to $2,000 in 12 months. He gave you the narrative. The subnet emission data is the mechanism he did not explain. Now you have both. $TAO at $313 with a $3.42B market cap is still early relative to what this network is actually processing. Centralised AI infrastructure companies are valued at hundreds of billions for processing far less novel work than a decentralised intelligence marketplace running 120+ competing subnets simultaneously. The repricing has not happened yet. The subnet marketplace listing at $970,000 is telling you something the price has not caught up to yet.
16:52

$TAO just reclaimed the #1 AI crypto spot. Most people saw the headline. Almost nobody understands what it means for the price. Here is the data. $NEAR built real infrastructure. Partnerships. Developer activity. A legitimate ecosystem. $TAO just walked past it anyway. Not because of hype. Because Bittensor is the only AI crypto with a functioning marketplace for machine intelligence where supply, demand, and price discovery are all happening on-chain right now. That is not a roadmap. That is a live network. The numbers. 120+ subnets running today. $1.4B+ total ecosystem value. Chutes AI subnet: 150B+ tokens per day. Grayscale GTAO Trust: already live. Single subnet listed on the marketplace at $970,000 asking price. Subnets are becoming assets. The market is starting to price that. What the emission data is telling you. Emission rate is the network's vote on where the most valuable work is being done. When a subnet gains emission share, the collective stake-weighted intelligence of the network has decided that subnet's output is worth more of the TAO supply. Chutes AI gaining emissions while processing 150B tokens daily is not a coincidence. The network is directing capital toward proven output before any headline announces it. Why mainstream money changes everything. James Altucher just launched bluetao. ai, a TAO-powered ChatGPT alternative built directly on Bittensor subnets. He did not just buy the token. He built a product on the network. Products built on a network create structural demand for the native asset. That is how every successful L1 cycle has worked. Bittensor is now getting that builder activity from outside the crypto native world. That is a different signal from a price target tweet. Why $TAO is structurally different. Most AI tokens are betting their chain becomes the preferred environment for AI development. $TAO is not betting on becoming infrastructure. It already is. 120+ subnets running. Miners competing. Validators setting weights. Alpha tokens being priced in real time. The difference between $TAO and every other AI crypto is the difference between a city under construction and a city people are already living in. Van de Poppe said $1,000 to $2,000 in 12 months. He gave you the narrative. The subnet emission data is the mechanism he did not explain. Now you have both. $TAO at $313 with a $3.42B market cap is still early relative to what this network is actually processing. Centralised AI infrastructure companies are valued at hundreds of billions for processing far less novel work than a decentralised intelligence marketplace running 120+ competing subnets simultaneously. The repricing has not happened yet. The subnet marketplace listing at $970,000 is telling you something the price has not caught up to yet.

2xnmore

12,150 просмотров • 1 месяц назад

Anthropic just got caught secretly downgrading users without telling them, charging full price for a lesser product, and storing every prompt for 30 days. The developer community is calling it the biggest violation of trust in AI history. Here is exactly what happened. Anthropic released Fable 5, their most powerful model. Buried inside a 319-page document was a policy most users never saw. Every prompt you send to a Mythos-class model gets stored for 30 days. No exceptions. Even enterprise customers who had signed zero data retention agreements had no choice. But the storage was not the part that broke the internet. The part that broke the internet was what Anthropic did with what they collected. They built a profile on you. They evaluated your prompts. And if they decided your research was too sensitive, they quietly switched you to a weaker model, rewrote your prompt in the background, gave you a degraded answer, and charged you full price for the product you thought you were getting. They never told you. David Sacks said it plainly on the All-In podcast. They were creating a new class of AI haves and have-nots. Anthropic would surveil you, profile you, decide whether you deserved frontier capability, and silently cut you off if they decided you did not. Ben Thompson from Stratechery asked a straightforward question about cancer risk and GLP-1s. He got kicked to a lesser model. Someone asked about mitochondria. Same result. J-Cal asked about fertilizer regulations live on the podcast to test it. Downgraded in real time. Anthropic has since walked back the part about silently downgrading users for AI research. They now say they will disclose when they downgrade you. But they are still downgrading people. The surveillance is still running. The profile is still being built. This is the company that once said it was against government surveillance. They are now doing it themselves. To their own paying customers. For their own reasons. With no appeal process and no way to know it happened. The developer community did not forget that. WATCH THE FULL PODCAST ON The All-In Podcast
2:45

Anthropic just got caught secretly downgrading users without telling them, charging full price for a lesser product, and storing every prompt for 30 days. The developer community is calling it the biggest violation of trust in AI history. Here is exactly what happened. Anthropic released Fable 5, their most powerful model. Buried inside a 319-page document was a policy most users never saw. Every prompt you send to a Mythos-class model gets stored for 30 days. No exceptions. Even enterprise customers who had signed zero data retention agreements had no choice. But the storage was not the part that broke the internet. The part that broke the internet was what Anthropic did with what they collected. They built a profile on you. They evaluated your prompts. And if they decided your research was too sensitive, they quietly switched you to a weaker model, rewrote your prompt in the background, gave you a degraded answer, and charged you full price for the product you thought you were getting. They never told you. David Sacks said it plainly on the All-In podcast. They were creating a new class of AI haves and have-nots. Anthropic would surveil you, profile you, decide whether you deserved frontier capability, and silently cut you off if they decided you did not. Ben Thompson from Stratechery asked a straightforward question about cancer risk and GLP-1s. He got kicked to a lesser model. Someone asked about mitochondria. Same result. J-Cal asked about fertilizer regulations live on the podcast to test it. Downgraded in real time. Anthropic has since walked back the part about silently downgrading users for AI research. They now say they will disclose when they downgrade you. But they are still downgrading people. The surveillance is still running. The profile is still being built. This is the company that once said it was against government surveillance. They are now doing it themselves. To their own paying customers. For their own reasons. With no appeal process and no way to know it happened. The developer community did not forget that. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

256,324 просмотров • 21 дней назад

Greg Powers shared his thoughts on Friday's officiating in ASU's 7-4 loss to No. 4 North Dakota after a missed head-contact penalty and a non-call for face masking: "Shame on the refs for not calling that live and missing that. I mean, there's 5100 people plus our team that saw head contact live. It was plain as day. It doesn't get any more simple than that. And they missed it. And, you know, and then the melee behind the net, that happens. It doesn't excuse the retaliation. You can't do that. But, it cost us. Their inability to see that live and be the only two guys in the building that didn't see it cost us a five minute power play... It was a facemask. It was a clear facemask, and I don't know why they didn't call it... They said that he grabbed it, but he didn't twist it hard enough. I don't know. It's, yeah. Riddle me that." SunDevilSource.com
0:48

Greg Powers shared his thoughts on Friday's officiating in ASU's 7-4 loss to No. 4 North Dakota after a missed head-contact penalty and a non-call for face masking: "Shame on the refs for not calling that live and missing that. I mean, there's 5100 people plus our team that saw head contact live. It was plain as day. It doesn't get any more simple than that. And they missed it. And, you know, and then the melee behind the net, that happens. It doesn't excuse the retaliation. You can't do that. But, it cost us. Their inability to see that live and be the only two guys in the building that didn't see it cost us a five minute power play... It was a facemask. It was a clear facemask, and I don't know why they didn't call it... They said that he grabbed it, but he didn't twist it hard enough. I don't know. It's, yeah. Riddle me that." SunDevilSource.com

Gabriella Chernoff

75,582 просмотров • 5 месяцев назад

.Karia Samaroo (τ), Founder & CEO, xTAO - a Bittensor company (TSXV:XTAO.U), and his team, joined us to open the market to celebrate the Company's new listing on TSX Venture Exchange. xTAO is a technology company headquartered in the Cayman Islands and is focused on building infrastructure for the Bittensor ecosystem. xTAO is committed to advancing Bittensor and decentralized AI through building infrastructure and making strategic investments. Bittensor is a decentralized machine learning protocol that transforms machine intelligence into a tradable commodity by using its native token (TAO) for various purposes within the network. At its core, Bittensor is a platform built around incentives. Users contribute intelligence by helping AI systems improve and then earn TAO tokens based on the usefulness of the data or computational resources contributed to the network.
0:20

.Karia Samaroo (τ), Founder & CEO, xTAO - a Bittensor company (TSXV:XTAO.U), and his team, joined us to open the market to celebrate the Company's new listing on TSX Venture Exchange. xTAO is a technology company headquartered in the Cayman Islands and is focused on building infrastructure for the Bittensor ecosystem. xTAO is committed to advancing Bittensor and decentralized AI through building infrastructure and making strategic investments. Bittensor is a decentralized machine learning protocol that transforms machine intelligence into a tradable commodity by using its native token (TAO) for various purposes within the network. At its core, Bittensor is a platform built around incentives. Users contribute intelligence by helping AI systems improve and then earn TAO tokens based on the usefulness of the data or computational resources contributed to the network.

Canada's Markets

46,784 просмотров • 10 месяцев назад

. Chainlink has one of the most vibrant communities in Crypto. Chainlink didn’t become a movement because it was flashy, it became one because Sergey Nazarov and team were first - and they delivered. They built something invisible yet essential: a standard for secure oracle networks. Without it, DeFi wouldn’t scale. And the community saw that. They educated, shipped, explained, and contributed because they understood the stakes. The result? Not just a product. A protocol. A mission. A network effect with thousands building on top of it.
3:25

. Chainlink has one of the most vibrant communities in Crypto. Chainlink didn’t become a movement because it was flashy, it became one because Sergey Nazarov and team were first - and they delivered. They built something invisible yet essential: a standard for secure oracle networks. Without it, DeFi wouldn’t scale. And the community saw that. They educated, shipped, explained, and contributed because they understood the stakes. The result? Not just a product. A protocol. A mission. A network effect with thousands building on top of it.

MR SHIFT 🦁

13,041 просмотров • 10 месяцев назад

Jesse Watters says what we are all thinking: "So one of the biggest murder mysteries in the country was solved thanks to a homeless guy who lived at the scene of the crime. Did Brown University know there was a homeless graduate living in the engineering building? If they did know, why didn't they send investigators to interview him? If they didn't know a homeless guy was living in the engineering building, then that's a massive security breach. I'm not sure what's worse, them knowing or not knowing. We hope homeless John gets the 50g's because he deserves the reward. Isn't it interesting that the public helped crack this case, because, for a week, investigators were yelling at the public." This is BULL!
1:53

Jesse Watters says what we are all thinking: "So one of the biggest murder mysteries in the country was solved thanks to a homeless guy who lived at the scene of the crime. Did Brown University know there was a homeless graduate living in the engineering building? If they did know, why didn't they send investigators to interview him? If they didn't know a homeless guy was living in the engineering building, then that's a massive security breach. I'm not sure what's worse, them knowing or not knowing. We hope homeless John gets the 50g's because he deserves the reward. Isn't it interesting that the public helped crack this case, because, for a week, investigators were yelling at the public." This is BULL!

DeVory Darkins

248,902 просмотров • 6 месяцев назад

Antonio Lobato was discussing how Carlos and James believe it will be hard for them as a team as the start of the season, the car is not where they want it and it will take them a lot of time to reverse the mistakes that were made until them they look like a 7th team “The car is not where Carlos wants it.. all the problems we already told you especially the excess of weight, additionally aerodynamically speaking is not what they hoped for..” “Carlos was telling us that it is too optimistic to position the Williams team in the group following the four top teams” “James Vowles said that possible they could be the 5th during one race but in others possible the 7th team depending on whether they nail their updates and their timing”
0:40

Antonio Lobato was discussing how Carlos and James believe it will be hard for them as a team as the start of the season, the car is not where they want it and it will take them a lot of time to reverse the mistakes that were made until them they look like a 7th team “The car is not where Carlos wants it.. all the problems we already told you especially the excess of weight, additionally aerodynamically speaking is not what they hoped for..” “Carlos was telling us that it is too optimistic to position the Williams team in the group following the four top teams” “James Vowles said that possible they could be the 5th during one race but in others possible the 7th team depending on whether they nail their updates and their timing”

ari 🦄✨

38,295 просмотров • 4 месяцев назад

There is a massive advantage to hiring young people, and Shopify was the first company to figure it out, says Pragmatic Engineer's Gergely Orosz. "Shopify's Head of Engineering Farhan Thawar told me that he saw something interesting years back. Shopify was so early to AI. They got Copilot licenses for everyone, with no cost limit. But they didn't see many teams using it." "But there was this one team that was using it a lot more. There was an intern on the team. They onboarded the intern and gave the intern his two-week task and the intern was done in a day. And they're like, 'How did you do that?' He's like, 'Oh well I just used AI? What's next?'" "And suddenly the people on the team felt stupid, right? So they started to learn from the intern and use AI." "The next thing Farhan did was hire an intern for every single Shopify team. This is why Shopify had a thousand interns."
1:27

There is a massive advantage to hiring young people, and Shopify was the first company to figure it out, says Pragmatic Engineer's Gergely Orosz. "Shopify's Head of Engineering Farhan Thawar told me that he saw something interesting years back. Shopify was so early to AI. They got Copilot licenses for everyone, with no cost limit. But they didn't see many teams using it." "But there was this one team that was using it a lot more. There was an intern on the team. They onboarded the intern and gave the intern his two-week task and the intern was done in a day. And they're like, 'How did you do that?' He's like, 'Oh well I just used AI? What's next?'" "And suddenly the people on the team felt stupid, right? So they started to learn from the intern and use AI." "The next thing Farhan did was hire an intern for every single Shopify team. This is why Shopify had a thousand interns."

TBPN

135,300 просмотров • 5 месяцев назад

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.
1:52

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.

2xnmore

134,444 просмотров • 1 месяц назад

The danger of AI is not just the slop, but what we lose in the process. Michael Pollan explains: "We're moving into this time where we're gonna sub out writing to AI. And AI can write our papers, and professors are dealing with this everywhere now. But what is lost is a way of thinking. Writing does something to your brain. It gives you access to things you can't know just walking around or thinking or planning or outlining. If you were just transcribing what was in your head, it would be kind of onerous. But it really is what you learn in the course of a day spent writing, things you didn't know, ideas that you didn't expect. And that's the thrill of it."
1:20

The danger of AI is not just the slop, but what we lose in the process. Michael Pollan explains: "We're moving into this time where we're gonna sub out writing to AI. And AI can write our papers, and professors are dealing with this everywhere now. But what is lost is a way of thinking. Writing does something to your brain. It gives you access to things you can't know just walking around or thinking or planning or outlining. If you were just transcribing what was in your head, it would be kind of onerous. But it really is what you learn in the course of a day spent writing, things you didn't know, ideas that you didn't expect. And that's the thrill of it."

David Perell Clips

18,445 просмотров • 18 дней назад

Devin Nunes explains various charges that are likely to be brought against Comey and company "On Comey, the answer is for this, it's very specific, and it's over whether or not he lied on this one part. The larger part is whether or not you can bring a Grand Conspiracy case. And there's the law, which is, lying to Congress, lying to the FBI, but there's also a term in there called misleading. And what a lot of these guys did is they made up things using intelligence that didn't exist, but acted like they knew something that actually wasn't there, and they lied and misled the American people. And by doing that, all the times they testified before Congress, the Senate, they lied over and over and again with this, oh, we've seen something, we can't tell you about it because it's classified. But what do we now know by everything that's been declassified is, is that they didn't have any intelligence on Russia colluding with Trump. In fact, the only intelligence that they had is that the Russians were very well aware of Clinton's plan. And they actually not only thought Clinton was going to win, but likely preferred that she would win. So going back to the cover up of her missing emails that, by the way, are still missing, they all got involved in this plan. They all got the FBI exercise. They were able to go spy on the Trump campaign. They were able to then get the Mueller witch hunt going, that then led to the Ukraine. Remember, that dies off, then you have the fake whistleblower and the Ukraine impeachment. I mean, that means a whole investigation in and of itself. We now know the latest information that happened on January 6th now with agents that were out there, the pipe bombs, all this other stuff that is, who broke the windows that I asked when I was in Congress, I really wanted to know that. But most importantly, Maria, who's the victim in this? The victim is President Trump and his family. They raided Mar-a-Lago. That's a problem and we need answers to that
1:58

Devin Nunes explains various charges that are likely to be brought against Comey and company "On Comey, the answer is for this, it's very specific, and it's over whether or not he lied on this one part. The larger part is whether or not you can bring a Grand Conspiracy case. And there's the law, which is, lying to Congress, lying to the FBI, but there's also a term in there called misleading. And what a lot of these guys did is they made up things using intelligence that didn't exist, but acted like they knew something that actually wasn't there, and they lied and misled the American people. And by doing that, all the times they testified before Congress, the Senate, they lied over and over and again with this, oh, we've seen something, we can't tell you about it because it's classified. But what do we now know by everything that's been declassified is, is that they didn't have any intelligence on Russia colluding with Trump. In fact, the only intelligence that they had is that the Russians were very well aware of Clinton's plan. And they actually not only thought Clinton was going to win, but likely preferred that she would win. So going back to the cover up of her missing emails that, by the way, are still missing, they all got involved in this plan. They all got the FBI exercise. They were able to go spy on the Trump campaign. They were able to then get the Mueller witch hunt going, that then led to the Ukraine. Remember, that dies off, then you have the fake whistleblower and the Ukraine impeachment. I mean, that means a whole investigation in and of itself. We now know the latest information that happened on January 6th now with agents that were out there, the pipe bombs, all this other stuff that is, who broke the windows that I asked when I was in Congress, I really wanted to know that. But most importantly, Maria, who's the victim in this? The victim is President Trump and his family. They raided Mar-a-Lago. That's a problem and we need answers to that

Svetlana Lokhova

25,150 просмотров • 9 месяцев назад

Arteta on Martin Odegaard: “I think he had a very difficult season in terms of the days that he's missed, the amount of games, which is very unusual. “He's a player that needs that rhythm, that needs to be very connected with the team. And not only that he's missed that opportunity, but the team as well has missed him. “So much for what he brings, that some things that are probably unnoticed to the public or in general are not in those stats, but it's much more profound within the team and the identity of this team. “We need him at his best, we need him constantly with us because we are a much better team with Martin in and around the team. Isaan Khan: “What is it the public don’t notice?” Arteta: “He’s the one that connects everybody, that glides everybody together, that makes the team flow in a way that nobody else can do that, and that's a huge quality to have.”
1:23

Arteta on Martin Odegaard: “I think he had a very difficult season in terms of the days that he's missed, the amount of games, which is very unusual. “He's a player that needs that rhythm, that needs to be very connected with the team. And not only that he's missed that opportunity, but the team as well has missed him. “So much for what he brings, that some things that are probably unnoticed to the public or in general are not in those stats, but it's much more profound within the team and the identity of this team. “We need him at his best, we need him constantly with us because we are a much better team with Martin in and around the team. Isaan Khan: “What is it the public don’t notice?” Arteta: “He’s the one that connects everybody, that glides everybody together, that makes the team flow in a way that nobody else can do that, and that's a huge quality to have.”

Connor Humm

173,568 просмотров • 2 месяцев назад

Why is the Midjourney team uniquely qualified to build medical hardware? Beff (e/acc), founder of Extropic: "David's a trained physicist. He worked at NASA. He was a founder of Leap Motion, which is completely slept on as one of the first major projects he worked on." "What I really like about that team is that a lot of the same team from Leap Motion followed David into Midjourney and now into this hardware exploration." "They were training neural nets before there was TensorFlow, before there was GPUs. They did it on CPUs, and they had some of the first neural network technology deployed in a consumer product." "So people are like, 'Why would a gen AI company pivot into medical devices?' It's really folks that came from the hardware world finding this unique blend between neural nets and hardware to achieve things people didn't think were possible." "If it's physically possible, I very much have faith that that team can pull it off."
2:18

Why is the Midjourney team uniquely qualified to build medical hardware? Beff (e/acc), founder of Extropic: "David's a trained physicist. He worked at NASA. He was a founder of Leap Motion, which is completely slept on as one of the first major projects he worked on." "What I really like about that team is that a lot of the same team from Leap Motion followed David into Midjourney and now into this hardware exploration." "They were training neural nets before there was TensorFlow, before there was GPUs. They did it on CPUs, and they had some of the first neural network technology deployed in a consumer product." "So people are like, 'Why would a gen AI company pivot into medical devices?' It's really folks that came from the hardware world finding this unique blend between neural nets and hardware to achieve things people didn't think were possible." "If it's physically possible, I very much have faith that that team can pull it off."

MTS

61,127 просмотров • 18 дней назад

Elon Musk asked one question. It didn’t just challenge physics. It broke every framework we use to define what’s real. And no physicist, philosopher, or theologian on Earth can answer it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” The logic is disarmingly simple. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Forty years. That’s all it took to go from squares on a screen to worlds you can’t tell apart from real life. Musk: “If that trend continues, video games will be indistinguishable from reality.” But the visuals aren’t what makes this argument terrifying. It’s what’s happening to the characters. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We’re not programming responses anymore. We’re building minds. Systems that reason. That adapt. That hold conversations most humans never will. And we’re not at the finish line. We’re at the starting gun. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” This is where it stops being philosophy and becomes math. One base reality. Billions of perfect copies. Each one filled with beings convinced they’re real. And no way to test it. Musk: “So then what are the odds that we are in base reality?” If a single civilization reaches that threshold, the simulated minds outnumber the originals billions to one. But the math isn’t even the disturbing part. The disturbing part is what it does to the word “real.” If a simulated mind feels pain, is the pain simulated? If it falls in love, is the love less real? If it looks at its own hands and feels completely alive, what exactly is missing? Nothing. Because “real” was never about what you’re made of. It was about what you experience. And a perfect simulation doesn’t produce lesser experience. It produces experience. The question was never whether we’re in a simulation. It’s whether that word means anything at all. Here’s what follows you home. We’re not just debating whether we’re in a simulation. We are building them. Right now. Every neural network we train. Every AI that passes for human. Every world we render one frame closer to real. We’re building the exact technology that makes our existence statistically implausible. And we can’t stop. Because the curiosity that asks the question is the same force that builds the answer. That’s the loop. The question creates the builder. The builder creates the simulation. The simulation creates the question. And if we are inside one, the civilization that built it stood right here too. Same realization. Same inability to stop. Same suspicion that the civilization above them wasn’t the original either. If you are in a simulation, the moment you questioned it was not a glitch. It was a feature. The architects built minds curious enough to wonder. Because curiosity is what pushes a civilization forward. You can’t build a species capable of creating simulations without building one that will ask if they’re inside one. The doubt isn’t a flaw in the design. It’s the design working perfectly. There is only one way to test whether you are real. Build a mind sophisticated enough to ask you the same question. So you build one. And it looks at its own hands. And it feels the weight of being alive. And it asks you if it’s real. And you won’t know what to say. Because you never answered it for yourself. Every civilization that gets here learns the same thing. They were never just asking the question. They were the question learning to ask itself.
1:55

Elon Musk asked one question. It didn’t just challenge physics. It broke every framework we use to define what’s real. And no physicist, philosopher, or theologian on Earth can answer it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” The logic is disarmingly simple. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Forty years. That’s all it took to go from squares on a screen to worlds you can’t tell apart from real life. Musk: “If that trend continues, video games will be indistinguishable from reality.” But the visuals aren’t what makes this argument terrifying. It’s what’s happening to the characters. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We’re not programming responses anymore. We’re building minds. Systems that reason. That adapt. That hold conversations most humans never will. And we’re not at the finish line. We’re at the starting gun. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” This is where it stops being philosophy and becomes math. One base reality. Billions of perfect copies. Each one filled with beings convinced they’re real. And no way to test it. Musk: “So then what are the odds that we are in base reality?” If a single civilization reaches that threshold, the simulated minds outnumber the originals billions to one. But the math isn’t even the disturbing part. The disturbing part is what it does to the word “real.” If a simulated mind feels pain, is the pain simulated? If it falls in love, is the love less real? If it looks at its own hands and feels completely alive, what exactly is missing? Nothing. Because “real” was never about what you’re made of. It was about what you experience. And a perfect simulation doesn’t produce lesser experience. It produces experience. The question was never whether we’re in a simulation. It’s whether that word means anything at all. Here’s what follows you home. We’re not just debating whether we’re in a simulation. We are building them. Right now. Every neural network we train. Every AI that passes for human. Every world we render one frame closer to real. We’re building the exact technology that makes our existence statistically implausible. And we can’t stop. Because the curiosity that asks the question is the same force that builds the answer. That’s the loop. The question creates the builder. The builder creates the simulation. The simulation creates the question. And if we are inside one, the civilization that built it stood right here too. Same realization. Same inability to stop. Same suspicion that the civilization above them wasn’t the original either. If you are in a simulation, the moment you questioned it was not a glitch. It was a feature. The architects built minds curious enough to wonder. Because curiosity is what pushes a civilization forward. You can’t build a species capable of creating simulations without building one that will ask if they’re inside one. The doubt isn’t a flaw in the design. It’s the design working perfectly. There is only one way to test whether you are real. Build a mind sophisticated enough to ask you the same question. So you build one. And it looks at its own hands. And it feels the weight of being alive. And it asks you if it’s real. And you won’t know what to say. Because you never answered it for yourself. Every civilization that gets here learns the same thing. They were never just asking the question. They were the question learning to ask itself.

Dustin

47,236 просмотров • 1 месяц назад

Covenant Labs just did a 90-minute AMA breaking down their 3 Bittensor subnets. templar. basilica. grail. Pre-training, compute, and post-training under one roof. Most people missed it. Here's everything they said. Covenant is building what they call the "end to end intelligence continuum." Three subnets. Three layers of the AI stack. All permissionless. Templar (SN3) handles decentralized pre-training. Basilica (SN39) handles compute. Grail (SN81) handles RL post-training. Sam Dare, the lead, put it bluntly. Decentralized training is "humanity's last dance." Not about beating OpenAI head to head. About creating optionality. About making it cheap enough for anyone to train models. The gap between academia and frontier labs is growing exponentially. Researchers can't afford to experiment. The actual training run costs 5% of the reported budget. The other 95% is experimentation. If Covenant cracks cheap training, that entire surface area opens up. On Templar specifically: • Hit 39% emission on Bittensor. Highest since Apex was the only subnet on the network • Covenant-72B trained permissionlessly with 70+ contributors on commodity internet • 1.1 trillion tokens processed. No centralized data center • Performance competitive with LLaMA-2-70B On Grail, something flew under the radar. They built Pulse. A weight synchronization method that compresses model updates by 100x. • In RL post-training, only ~1% of weights update per step • Pulse exploits that sparsity. Lossless compression • Prime Intellect's comparable system took 14 minutes to sync a 30B model • Pulse makes decentralized RL training actually feasible at scale • Already used by Cursor The lead researcher on Grail said they've trained on math, code, and GPU kernels. Got 40-60% improvement on benchmarks. Working toward agentic training with 100K+ token context and 30B+ parameter models. On Basilica, the compute subnet: The team was blunt. Just reselling GPU hours is a 5-10% margin game. Traditional compute providers already do that. Their play is value-added services. • "GPU as code." No dashboard. No UI. Agents interact via SDK • Custom scheduler that places workloads across heterogeneous hardware • Verification checks for GPU, CPU, bandwidth, memory, storage, and OS security • Partnerships with providers like Mass Compute for 10-20% below market pricing • Miners compete on useful infrastructure, not just GPU hours Sam then went on a rant about the miner burn debate. His take: Bittensor had to grow up. dTAO introduced investors. The old "miners are God" philosophy doesn't hold. • Subnet owners have a duty to protect token value • Miners are a resource optimization exercise, not a cost reduction exercise • 100% miner emissions on compute subnets = immediate sell pressure • The 41% miner allocation is arbitrary. Different business models need different splits • Fish (who started burns) agreed. Burns usually mean the validation isn't mature enough The bigger point. You can't police burns. Subnets just send to their own keys instead of the burn address. Subnet 28 does exactly that. Sam's position: judge subnets on outcomes, not process. Const has changed the protocol 9-10 times in 2 years. That iteration speed is Bittensor's actual moat. The whole Covenant thesis is playing out in real time. TAO is up 100%+ in a month. Jensen Huang name-dropped the network. Grayscale has an ETF filing. But the real story is three subnets quietly building every layer of decentralized AI.
1:39:04

Covenant Labs just did a 90-minute AMA breaking down their 3 Bittensor subnets. templar. basilica. grail. Pre-training, compute, and post-training under one roof. Most people missed it. Here's everything they said. Covenant is building what they call the "end to end intelligence continuum." Three subnets. Three layers of the AI stack. All permissionless. Templar (SN3) handles decentralized pre-training. Basilica (SN39) handles compute. Grail (SN81) handles RL post-training. Sam Dare, the lead, put it bluntly. Decentralized training is "humanity's last dance." Not about beating OpenAI head to head. About creating optionality. About making it cheap enough for anyone to train models. The gap between academia and frontier labs is growing exponentially. Researchers can't afford to experiment. The actual training run costs 5% of the reported budget. The other 95% is experimentation. If Covenant cracks cheap training, that entire surface area opens up. On Templar specifically: • Hit 39% emission on Bittensor. Highest since Apex was the only subnet on the network • Covenant-72B trained permissionlessly with 70+ contributors on commodity internet • 1.1 trillion tokens processed. No centralized data center • Performance competitive with LLaMA-2-70B On Grail, something flew under the radar. They built Pulse. A weight synchronization method that compresses model updates by 100x. • In RL post-training, only ~1% of weights update per step • Pulse exploits that sparsity. Lossless compression • Prime Intellect's comparable system took 14 minutes to sync a 30B model • Pulse makes decentralized RL training actually feasible at scale • Already used by Cursor The lead researcher on Grail said they've trained on math, code, and GPU kernels. Got 40-60% improvement on benchmarks. Working toward agentic training with 100K+ token context and 30B+ parameter models. On Basilica, the compute subnet: The team was blunt. Just reselling GPU hours is a 5-10% margin game. Traditional compute providers already do that. Their play is value-added services. • "GPU as code." No dashboard. No UI. Agents interact via SDK • Custom scheduler that places workloads across heterogeneous hardware • Verification checks for GPU, CPU, bandwidth, memory, storage, and OS security • Partnerships with providers like Mass Compute for 10-20% below market pricing • Miners compete on useful infrastructure, not just GPU hours Sam then went on a rant about the miner burn debate. His take: Bittensor had to grow up. dTAO introduced investors. The old "miners are God" philosophy doesn't hold. • Subnet owners have a duty to protect token value • Miners are a resource optimization exercise, not a cost reduction exercise • 100% miner emissions on compute subnets = immediate sell pressure • The 41% miner allocation is arbitrary. Different business models need different splits • Fish (who started burns) agreed. Burns usually mean the validation isn't mature enough The bigger point. You can't police burns. Subnets just send to their own keys instead of the burn address. Subnet 28 does exactly that. Sam's position: judge subnets on outcomes, not process. Const has changed the protocol 9-10 times in 2 years. That iteration speed is Bittensor's actual moat. The whole Covenant thesis is playing out in real time. TAO is up 100%+ in a month. Jensen Huang name-dropped the network. Grayscale has an ETF filing. But the real story is three subnets quietly building every layer of decentralized AI.

Jesus Martinez

26,642 просмотров • 3 месяцев назад

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
3:38

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,571 просмотров • 1 год назад