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“TAO changed my life as a builder.” SEBY on why BitTensor is gives builders an unfair advantage. Instead of begging for hiring, compute, and distribution, you plug into a network where incentives recruit the people, and people compete to give you the cheapest compute.

This Week in Startups

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16,966 次观看 • 4 个月前 •via X (Twitter)

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Jason’s on Bittensor (TAO): Bittensor is a marketplace for AI services. People compete to provide a service… Things like compute and models. The incentive structure is brutally deflationary: better quality + lower price wins. If buyers don’t pay enough, miners leave. If the work is priced right, the best talent shows up. @jason #Bittensor #TAO #Crypto #AI #DePIN

Jason’s on Bittensor (TAO): Bittensor is a marketplace for AI services. People compete to provide a service… Things like compute and models. The incentive structure is brutally deflationary: better quality + lower price wins. If buyers don’t pay enough, miners leave. If the work is priced right, the best talent shows up. @jason #Bittensor #TAO #Crypto #AI #DePIN

This Week in Startups

25,389 次观看 • 4 个月前

.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.

.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 次观看 • 1 年前

.ninja built an SDK to make it easy for developers to launch DeFi apps. But compute is just as critical. In our joint Space, ninja highlighted how io.net provided plug-and-play decentralized compute, so builders can focus on experimenting, iterating, and scaling—without worrying about sourcing infrastructure. Listen in as Injective shares why this collab unlocks new possibilities for DeFAI. 👇

.ninja built an SDK to make it easy for developers to launch DeFi apps. But compute is just as critical. In our joint Space, ninja highlighted how io.net provided plug-and-play decentralized compute, so builders can focus on experimenting, iterating, and scaling—without worrying about sourcing infrastructure. Listen in as Injective shares why this collab unlocks new possibilities for DeFAI. 👇

io.net

23,054 次观看 • 1 年前

$INFERRA Just came across Inferra and this one actually feels really interesting. 9ufM9TJd1UEmi9awnGfxCkCHAgQ3JZ5Sw6YxeSeEASY They're building a decentralized marketplace where AI compute becomes a tradable commodity. Instead of letting GPU power sit idle, providers can list verified compute capacity while users can buy, sell, trade, or redeem it for actual compute access. What caught my attention is that they're approaching compute like a real market, with spot trading, futures, and eventually inference markets. As AI demand keeps exploding, compute is becoming one of the most valuable resources in the industry. Projects focused on making that resource more liquid and accessible make a lot of sense to me. High risk as marketcap is tiny. But definitely an interesting compute bet I aped small. DYOR. RR

$INFERRA Just came across Inferra and this one actually feels really interesting. 9ufM9TJd1UEmi9awnGfxCkCHAgQ3JZ5Sw6YxeSeEASY They're building a decentralized marketplace where AI compute becomes a tradable commodity. Instead of letting GPU power sit idle, providers can list verified compute capacity while users can buy, sell, trade, or redeem it for actual compute access. What caught my attention is that they're approaching compute like a real market, with spot trading, futures, and eventually inference markets. As AI demand keeps exploding, compute is becoming one of the most valuable resources in the industry. Projects focused on making that resource more liquid and accessible make a lot of sense to me. High risk as marketcap is tiny. But definitely an interesting compute bet I aped small. DYOR. RR

Crypto Ideology ✍🏻

13,657 次观看 • 2 个月前

ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute and then ultimately most of the power of the galaxy, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez

ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute and then ultimately most of the power of the galaxy, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez

Mario Nawfal

1,667,972 次观看 • 9 个月前

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute

Joseph Noel Walker

29,267 次观看 • 3 天前

For anyone trying to understand Bittensor from first principles, this lecture is a useful place to start. Presented by Bittensor co-founder const. Learn Bittensor > Start with Bitcoin, distributed systems, incentives, > How Bitcoin leads to Bittensor Subnets coordinating AI infrastructure. Topics: // Start - Bitcoin as more than a digital currency // Risks of AI centralization + closed systems // "The incentive computer" // How Bittensor subnets work (mining, validating) // How distributed AI infrastructure could scale globally // Impact on students, builders & future founders Recorded at the National University of Singapore Computer Science Club. NUS Computing Chapters - Bitcoin, AI, and Bittensor - Bitcoin history and decentralization - AI changes how engineers work - The danger of centralized AI power - Why most crypto visions fail - Bitcoin as the world’s largest compute network - Bitcoin as a market for compute - The idea of an “incentive computer” - Bitcoin compared to Bittensor - Classroom example of decentralized scoring - A simple subnet example - SN62 :: Ridges AI | SN62 SWE agents - SN3 templar :: Distributed AI Training - SN52 lium.io :: GPU rentals on Bittensor 128 subnets, some examples Why this matters for the future of work Q&A Subnet examples mentioned @ SN64 - Serverless + TEE Compute :: Chutes SN8 - Prop firm Vanta Trading SN52 - AutoML :: Gradients SN62 - SWE agents :: Ridges AI | SN62 SN51 - Compute / GPU rental lium.io SN4 - TEE compute for enterprise :: Targon SN3 - 72B Distributed Training run :: templar SN41 - Prediction markets :: Almanac SN44 - Computer Vision Score - Subnet 44 SN68 - Drug discovery :: METANOVA LABS SN18 - Weather Forecasting Zeus | SN 18 SN50 - Bitcoin prediction data :: Synthdata SN61 - Quantum computing :: qBitTensor Labs SN14 - Bitcoin mining pool :: TaoHash SN34 - Perp Dex :: 0xMarkets SN17 - 3D model generation :: 404 SN33 - Data analytics :: ReadyAI SN19 - [Since relaunched] RPC infrastructure :

For anyone trying to understand Bittensor from first principles, this lecture is a useful place to start. Presented by Bittensor co-founder const. Learn Bittensor > Start with Bitcoin, distributed systems, incentives, > How Bitcoin leads to Bittensor Subnets coordinating AI infrastructure. Topics: // Start - Bitcoin as more than a digital currency // Risks of AI centralization + closed systems // "The incentive computer" // How Bittensor subnets work (mining, validating) // How distributed AI infrastructure could scale globally // Impact on students, builders & future founders Recorded at the National University of Singapore Computer Science Club. NUS Computing Chapters - Bitcoin, AI, and Bittensor - Bitcoin history and decentralization - AI changes how engineers work - The danger of centralized AI power - Why most crypto visions fail - Bitcoin as the world’s largest compute network - Bitcoin as a market for compute - The idea of an “incentive computer” - Bitcoin compared to Bittensor - Classroom example of decentralized scoring - A simple subnet example - SN62 :: Ridges AI | SN62 SWE agents - SN3 templar :: Distributed AI Training - SN52 lium.io :: GPU rentals on Bittensor 128 subnets, some examples Why this matters for the future of work Q&A Subnet examples mentioned @ SN64 - Serverless + TEE Compute :: Chutes SN8 - Prop firm Vanta Trading SN52 - AutoML :: Gradients SN62 - SWE agents :: Ridges AI | SN62 SN51 - Compute / GPU rental lium.io SN4 - TEE compute for enterprise :: Targon SN3 - 72B Distributed Training run :: templar SN41 - Prediction markets :: Almanac SN44 - Computer Vision Score - Subnet 44 SN68 - Drug discovery :: METANOVA LABS SN18 - Weather Forecasting Zeus | SN 18 SN50 - Bitcoin prediction data :: Synthdata SN61 - Quantum computing :: qBitTensor Labs SN14 - Bitcoin mining pool :: TaoHash SN34 - Perp Dex :: 0xMarkets SN17 - 3D model generation :: 404 SN33 - Data analytics :: ReadyAI SN19 - [Since relaunched] RPC infrastructure :

Openτensor Foundaτion

1,173,291 次观看 • 5 个月前

Announcing ComputeConnect, the financial industry’s first exchange-for-physical (EFP) network for compute, coming soon from Architect and Compute Desk. ComputeConnect links US exchange-traded compute futures to compute capacity delivery. Exchange-listed cash-settled compute futures are entering US markets to correct course on the current AI economy, reorienting debt to long-term growth: • Creating price discovery and transparency independent of any single capacity provider. • Establishing a forward curve for measuring deprecation and forecasting supply and demand. • Providing financial hedges for compute consumers and producers. • Enabling hedge funds, ETF companies, and traders to gain long and short financial exposure to compute. US cash-settled compute futures lack a physical delivery mechanism, and ComputeConnect fills this gap. Existing physically settled futures such as energy and agriculturals require their clearing house (DCO) to set a uniform standard for the grade and delivery method for the underlying commodity. Compute, by contrast, is highly fragmented, heterogeneous, and rapidly evolving, making it infeasible for any single DCO to define and enforce comparable standards. ComputeConnect establishes a network of compute capacity providers and links the network with Architect’s US futures products using exchange-for-physicals (EFPs), OTC contracts in which futures positions are exchanged for the assets the futures track. EFPs allow counterparties to negotiate the grade, timing, location, and other characteristics of the commodity along with a basis tied to the futures settlement price. ComputeConnect will • Build a network of capacity providers and capacity marketplaces. • Establish an open protocol for members of the network to receive delivery requests and advertise available GPUs. • Publish standard basis tables for different SKUs, memory configurations, and locations for GPUs. • Book the futures legs of the transactions to Architect’s DCM, the American Innovation Exchange. • Facilitate and guarantee delivery of capacity using Compute Desk’s ComputeClear platform. The advancement of US AI is constrained at every link in the supply chain: materials, power, chips, capital… The American Innovation Exchange, ComputeConnect, and our industry partners aim to secure compute’s dominance as an American asset class.

Announcing ComputeConnect, the financial industry’s first exchange-for-physical (EFP) network for compute, coming soon from Architect and Compute Desk. ComputeConnect links US exchange-traded compute futures to compute capacity delivery. Exchange-listed cash-settled compute futures are entering US markets to correct course on the current AI economy, reorienting debt to long-term growth: • Creating price discovery and transparency independent of any single capacity provider. • Establishing a forward curve for measuring deprecation and forecasting supply and demand. • Providing financial hedges for compute consumers and producers. • Enabling hedge funds, ETF companies, and traders to gain long and short financial exposure to compute. US cash-settled compute futures lack a physical delivery mechanism, and ComputeConnect fills this gap. Existing physically settled futures such as energy and agriculturals require their clearing house (DCO) to set a uniform standard for the grade and delivery method for the underlying commodity. Compute, by contrast, is highly fragmented, heterogeneous, and rapidly evolving, making it infeasible for any single DCO to define and enforce comparable standards. ComputeConnect establishes a network of compute capacity providers and links the network with Architect’s US futures products using exchange-for-physicals (EFPs), OTC contracts in which futures positions are exchanged for the assets the futures track. EFPs allow counterparties to negotiate the grade, timing, location, and other characteristics of the commodity along with a basis tied to the futures settlement price. ComputeConnect will • Build a network of capacity providers and capacity marketplaces. • Establish an open protocol for members of the network to receive delivery requests and advertise available GPUs. • Publish standard basis tables for different SKUs, memory configurations, and locations for GPUs. • Book the futures legs of the transactions to Architect’s DCM, the American Innovation Exchange. • Facilitate and guarantee delivery of capacity using Compute Desk’s ComputeClear platform. The advancement of US AI is constrained at every link in the supply chain: materials, power, chips, capital… The American Innovation Exchange, ComputeConnect, and our industry partners aim to secure compute’s dominance as an American asset class.

Brett Harrison

28,122 次观看 • 1 个月前

.Shaun Maguire says SpaceX's data center deal with Google may suggest there is something fundamentally different about the company's terrestrial compute. "I think a lot of people were surprised by the Anthropic and Google announcements. And I think a lot of people are getting the wrong takeaway there." "The way a lot of people are interpreting that is it's like, 'oh, we're just in this temporary compute shortage. And so anyone's willing to work with anyone, and they're willing to pay any price for compute.'" "I think that might be a reasonable way to look at the Anthropic announcement. I don't think that makes sense for looking at the Google announcement." "To me, I think an alternative hypothesis is that SpaceX's terrestrial compute is not actually a commodity. There's something that's better about it than other people's terrestrial compute."

.Shaun Maguire says SpaceX's data center deal with Google may suggest there is something fundamentally different about the company's terrestrial compute. "I think a lot of people were surprised by the Anthropic and Google announcements. And I think a lot of people are getting the wrong takeaway there." "The way a lot of people are interpreting that is it's like, 'oh, we're just in this temporary compute shortage. And so anyone's willing to work with anyone, and they're willing to pay any price for compute.'" "I think that might be a reasonable way to look at the Anthropic announcement. I don't think that makes sense for looking at the Google announcement." "To me, I think an alternative hypothesis is that SpaceX's terrestrial compute is not actually a commodity. There's something that's better about it than other people's terrestrial compute."

Jack Kuhr

44,998 次观看 • 2 个月前

This is why decentralized AI will win.. This is why #Bittensor will win ⚫️ ⚪️ "There's about 20,000 GPUs roughly speaking on the #Bittensor network and they're all in a collection of subnets" ⚪️ "Subnet 64 has maybe most of them, maybe 10,000.. Subnet 4 has thousands.. Subnet 3 is around the neighborhood of thousands.. Subnet 51 is also almost 10,000" ⚪️ "So you add all this up and it's more than 10% might even be 20% of all of the compute that Elon Musk has had to spend tens of billions of dollars acquiring" I highly recommend listening to the full discussion of The $TAO Pod with JJ and James Altucher here 👉 $TAO

This is why decentralized AI will win.. This is why #Bittensor will win ⚫️ ⚪️ "There's about 20,000 GPUs roughly speaking on the #Bittensor network and they're all in a collection of subnets" ⚪️ "Subnet 64 has maybe most of them, maybe 10,000.. Subnet 4 has thousands.. Subnet 3 is around the neighborhood of thousands.. Subnet 51 is also almost 10,000" ⚪️ "So you add all this up and it's more than 10% might even be 20% of all of the compute that Elon Musk has had to spend tens of billions of dollars acquiring" I highly recommend listening to the full discussion of The $TAO Pod with JJ and James Altucher here 👉 $TAO

ＤＲＥＡＤＢＯＮＧＯ

48,276 次观看 • 1 年前

Dylan Patel of SemiAnalysis says speed is the moat in AI inference, and getting there runs through new compute (Groq/Cerebras), KV-cache offload, and networking optimization (Aria). "Most of the infrastructure is pretty optimized for high throughput, I would say, but more and more people want to pay for speed. It turns out agents are very sequential, task-oriented, and models running in sequential tasks." "Trying something, verifying it, checking if it's right, and you do that in a loop. It ends up being very slow." "And speed is the moat. The faster you go, speed is the moat." "So a lot of the workloads and high-end use cases that people are developing now are all focused on high interactivity, and the infrastructure there is quite different." "So let's break that down into a few components." "One is you can do new compute: you can do Groq or Cerebras-style compute, which is very much focused on high interactivity." "But even with existing GPUs you can do a few things. One, if you're focused heavily on time to first token, you might offload KV cache to storage, keep it cached, move it back into the compute whenever you need it, much faster than recomputing." "And the third thing you can do is you have to optimize the network."

Dylan Patel of SemiAnalysis says speed is the moat in AI inference, and getting there runs through new compute (Groq/Cerebras), KV-cache offload, and networking optimization (Aria). "Most of the infrastructure is pretty optimized for high throughput, I would say, but more and more people want to pay for speed. It turns out agents are very sequential, task-oriented, and models running in sequential tasks." "Trying something, verifying it, checking if it's right, and you do that in a loop. It ends up being very slow." "And speed is the moat. The faster you go, speed is the moat." "So a lot of the workloads and high-end use cases that people are developing now are all focused on high interactivity, and the infrastructure there is quite different." "So let's break that down into a few components." "One is you can do new compute: you can do Groq or Cerebras-style compute, which is very much focused on high interactivity." "But even with existing GPUs you can do a few things. One, if you're focused heavily on time to first token, you might offload KV cache to storage, keep it cached, move it back into the compute whenever you need it, much faster than recomputing." "And the third thing you can do is you have to optimize the network."

Fireside Alpha

282,905 次观看 • 23 天前

Building the world's largest AI compute DePIN means has tens of thousands of independent node operators around the world. Providing alternatives to centralized cloud providers is more than bringing transactions for compute on-chain, it is tapping into the distributed compute that already exists in the world and making it available to innovators and builders advancing AI and ML. video from our community member leeland アブス ✳️

Building the world's largest AI compute DePIN means has tens of thousands of independent node operators around the world. Providing alternatives to centralized cloud providers is more than bringing transactions for compute on-chain, it is tapping into the distributed compute that already exists in the world and making it available to innovators and builders advancing AI and ML. video from our community member leeland アブス ✳️

io.net

968,693 次观看 • 2 年前

The game has changed Everyone is trying to find price errors and glitches but the ENTIRE system has flaws Airlines will give you free flights You stop paying for hotels Banks will compete to give you money Companies will start begging for your business instead of throwing it away Your entire life can be a video game, but you must know how to play Which is why we made The Black Box We learned the rules and bended them in our favor Here’s how it works:

The game has changed Everyone is trying to find price errors and glitches but the ENTIRE system has flaws Airlines will give you free flights You stop paying for hotels Banks will compete to give you money Companies will start begging for your business instead of throwing it away Your entire life can be a video game, but you must know how to play Which is why we made The Black Box We learned the rules and bended them in our favor Here’s how it works:

Glitched

227,741 次观看 • 4 个月前

AI Compute —ubiquitous, invisible, and instant. Russ , Exabits Chief of Sales, on the future of compute: “You plug in your lamp, you get power. You don’t think about where it comes from. That’s our vision for GPUs—distributed, on-demand, and everywhere AI needs it.” Emerging providers like Exabits are the backbone of this shift—scaling infrastructure to meet global AI demand.

AI Compute —ubiquitous, invisible, and instant. Russ , Exabits Chief of Sales, on the future of compute: “You plug in your lamp, you get power. You don’t think about where it comes from. That’s our vision for GPUs—distributed, on-demand, and everywhere AI needs it.” Emerging providers like Exabits are the backbone of this shift—scaling infrastructure to meet global AI demand.

Exabits

55,256 次观看 • 1 年前

TAO co-founder Const explains the difference between mining BTC and mining TAO “People try to mine Bitcoin, and if they can do it faster, they get paid. Bittensor takes that same idea and turns it into a system where people compete to solve problems, get evaluated, and the best performers earn more, over and over again. We took the Bitcoin model, abstracted it, and applied it to everything”

TAO co-founder Const explains the difference between mining BTC and mining TAO “People try to mine Bitcoin, and if they can do it faster, they get paid. Bittensor takes that same idea and turns it into a system where people compete to solve problems, get evaluated, and the best performers earn more, over and over again. We took the Bitcoin model, abstracted it, and applied it to everything”

Counterparty

105,957 次观看 • 4 个月前

Bitcoin wastes so much power and compute on solving unnecessary problems, creating artificial scarcity. But Bittensor actually USES this compute to power state of the art AI tools. Here’s how it works, and how you can start owning a small piece of the AI revolution: CC: @jason, Mark Jeffrey, Lon Harris, shτbshτb

Bitcoin wastes so much power and compute on solving unnecessary problems, creating artificial scarcity. But Bittensor actually USES this compute to power state of the art AI tools. Here’s how it works, and how you can start owning a small piece of the AI revolution: CC: @jason, Mark Jeffrey, Lon Harris, shτbshτb

This Week in Startups

13,456 次观看 • 5 个月前

Compute is the scarcest resource in AI, and demand keeps growing. On the OpenAI Podcast, our CFO Sarah Friar and Khosla Ventures founder Vinod Khosla talk to host Andrew Mayne about the demand for compute and how we get the benefits of AI to more people.

Compute is the scarcest resource in AI, and demand keeps growing. On the OpenAI Podcast, our CFO Sarah Friar and Khosla Ventures founder Vinod Khosla talk to host Andrew Mayne about the demand for compute and how we get the benefits of AI to more people.

OpenAI

222,850 次观看 • 7 个月前

Everyone has great ideas. But where most people stumble is bringing them to life. With Hedra Agent 2, you can turn your vision into reality, without needing a team of 10 people. Whether you run a local restaurant, an e-commerce shop, or an agency, Hedra gives you the creative power to compete with the big budget brands. A simple workflow looks like this: - Analyze: "What video trends are currently blowing up on TikTok?" - Create: "Using my brand colors, generate a 15-second video for that transformation trend - Share: "Give me three variations and drop them straight into our team’s Slack channel." It really is that simple. Go bring your ideas to life. Try Hedra Agent 2 today.

Hedra

4,539,969 次观看 • 2 个月前