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Prima Mente is building an epigenetic foundation model for earlier detection of neurodegenerative diseases like Alzheimer’s and Parkinson’s. CEO Ravi Solanki shares how Nebius delivers the elastic, cost-efficient HPC they need to train and scale on NVIDIA-powered clusters. Watch the video below👇 #HealthcareAI #AlzheimersDetection #ParkinsonsDetection

Nebius

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10,725 views • 4 months ago •via X (Twitter)

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MARA

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"The microbiome isn’t just part of your health—it’s the foundation." – Dr. Sabine Hazan With 61 clinical trials underway, Dr. Sabine Hazan and her team are mapping the microbiome’s connection to diseases like diabetes, alopecia areata, pemphigoid, lupus, Alzheimer’s, Parkinson’s, MS, and ALS. What they’ve discovered could change everything. Dysbiosis & Leaky Gut: The Silent Epidemic An imbalanced microbiome (dysbiosis) weakens your first line of defense—your gut barrier. When this fails, pathogens and metabolites leak into the bloodstream, triggering inflammation, nerve damage, and neurodegenerative diseases. Key Findings: - Your stool is your first shield against viruses, fungi, and parasites. - Colonic mucosa → blood vessels → nerves—once breached, toxins travel to the brain. - These "leaky gut" metabolites may drive Alzheimer’s, Parkinson’s, MS, and ALS. The Future of Medicine Starts in the Gut Dr. Hazan’s research, built on 300+ clinical protocols, is decoding how microbiome imbalances fuel chronic disease. The goal? Precision treatments tailored to restore gut health—and stop disease before it starts.

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Camus

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“Our compute nodes don’t run a full copy of the models we train on IOTA. They actually run a small sliver of the model. This means you can train really large frontier sized models using very small building blocks”. CTO crux unpacks how IOTA ・ SN9’s model parallel architecture allows us to train at scale by splitting our models across multiple machines, and then sewing them together. This is core to SN9’s architecture. See the full Eye On A.I. podcast below.

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IOTA ・ SN9

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As AI labs race to train and deploy new frontier models, existing models become more affordable with better tokenomics. ✨ "Everybody's trying to get to the next frontier. And every time they get to the next frontier, the last generation AI tokens, the cost starts to decline about a factor of 10x every year," said NVIDIA CEO Jensen Huang in a recent keynote. Model optimization techniques such as speculative decoding and multi-token prediction, combined with inference serving platforms like NVIDIA Dynamo on NVIDIA Blackwell NVL72 systems, enable AI factories to boost throughput by 10x with one-tenth of the cost per token. Learn more about AI factory tokenomics ➡️

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NVIDIA AI

16,053 views • 5 months ago

🛣️ New NVIDIA DRIVE Labs video on the future of mapless driving! High-definition (HD) maps have been essential for autonomous driving, but their cost and maintenance challenges limit deployment. 🚗 In this episode of #DRIVELabs, we explore how NVIDIA is reducing reliance on HD maps through innovations that eliminate information bottlenecks, improving task accuracy, and accelerate model training and inference times. 🌐 Watch now to see how we’re pushing the boundaries of #maplessdriving with AI! 🚀 #DRIVELabs #MaplessDriving #AutonomousVehicles #AI #NVIDIA #AutonomousDriving

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NVIDIA DRIVE

32,288 views • 1 year ago

Mark my words, Nebius will be the first Trillion dollar Neo-cloud company and here is why (Save this). Roman Chernin, CEO of Nebius just said on 20VC that Nebius raised prices and demand didn't move. When a company can raise prices and still have more demand than supply, that's the opportunity. Chernin also explained why he is deliberately not charging the maximum. As AI shifts from training, a one time cost to inference, which is the ongoing cost of serving every user and every query, compute pricing becomes the cost structure of the entire AI economy. If Nebius prices customers out, those customers cannot grow, and Nebius cannot grow with them. That is the compounding flywheel built directly into the revenue model. The numbers are already confirming it. Q1 2026 revenue came in at $399 million, up 684% year over year. The AI cloud segment grew 840% and represented 98% of total revenue. Adjusted EBITDA flipped positive to $129.5 million. And Nebius signed a long-term agreement with Meta worth up to $27 billion over five years, a hyperscaler outsourcing its own AI compute stack to a neocloud, which tells you that even companies with $50 billion capex budgets cannot build fast enough. Goldman Sachs says the consensus is underestimating 2027 hyperscaler capex by $500 billion. Every dollar hyperscalers cannot provision themselves flows to neoclouds like Nebius. As that gap widens, Nebius captures the overflow with 3 gigawatts of contracted power already secured and a CEO who just told you raising prices did not dent demand. Our subscribers are already up massively on Nebius and come join Milk Road Pro for our full breakdown, how to size Nebius against the broader neocloud opportunity, and our full AI thesis. Link below!

Mark my words, Nebius will be the first Trillion dollar Neo-cloud company and here is why (Save this). Roman Chernin, CEO of Nebius just said on 20VC that Nebius raised prices and demand didn't move. When a company can raise prices and still have more demand than supply, that's the opportunity. Chernin also explained why he is deliberately not charging the maximum. As AI shifts from training, a one time cost to inference, which is the ongoing cost of serving every user and every query, compute pricing becomes the cost structure of the entire AI economy. If Nebius prices customers out, those customers cannot grow, and Nebius cannot grow with them. That is the compounding flywheel built directly into the revenue model. The numbers are already confirming it. Q1 2026 revenue came in at $399 million, up 684% year over year. The AI cloud segment grew 840% and represented 98% of total revenue. Adjusted EBITDA flipped positive to $129.5 million. And Nebius signed a long-term agreement with Meta worth up to $27 billion over five years, a hyperscaler outsourcing its own AI compute stack to a neocloud, which tells you that even companies with $50 billion capex budgets cannot build fast enough. Goldman Sachs says the consensus is underestimating 2027 hyperscaler capex by $500 billion. Every dollar hyperscalers cannot provision themselves flows to neoclouds like Nebius. As that gap widens, Nebius captures the overflow with 3 gigawatts of contracted power already secured and a CEO who just told you raising prices did not dent demand. Our subscribers are already up massively on Nebius and come join Milk Road Pro for our full breakdown, how to size Nebius against the broader neocloud opportunity, and our full AI thesis. Link below!

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15,677 views • 1 month ago

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NVIDIA Robotics

26,155 views • 2 months ago

The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to Lin Qiao, 90% of the world's data is still private and locked inside applications and enterprises. Foundation models are trained on public internet + labeling company data, which is barely 10% of all the data. And this is why your application and foundation models are misaligned by definition. Companies building agents don't treat models as APIs. They opt for a product-model co-design. - Models continuously learn from your private data - Pick up domain-specific intelligence - Run faster - Cost less - Scale to millions of users

The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to Lin Qiao, 90% of the world's data is still private and locked inside applications and enterprises. Foundation models are trained on public internet + labeling company data, which is barely 10% of all the data. And this is why your application and foundation models are misaligned by definition. Companies building agents don't treat models as APIs. They opt for a product-model co-design. - Models continuously learn from your private data - Pick up domain-specific intelligence - Run faster - Cost less - Scale to millions of users

Ivan Burazin

54,964 views • 3 months ago

Krishna Srinivasan, Founder and CEO of Data Bootstrap and former Google DeepMind researcher, discusses the challenges of data scraping and scalability. With experience at prior Apple, Yahoo, and IBM watsonx, Krishna demonstrates the difference between scraping with a single machine versus leveraging OpenLedger's community nodes. The results speak for themselves, parallelized scraping enables significantly higher efficiency and scale. Data Bootstrap is one of many companies building on our Data Intelligence Layer, and we’re excited to support innovations like these. Watch the video below to learn more.

Krishna Srinivasan, Founder and CEO of Data Bootstrap and former Google DeepMind researcher, discusses the challenges of data scraping and scalability. With experience at prior Apple, Yahoo, and IBM watsonx, Krishna demonstrates the difference between scraping with a single machine versus leveraging OpenLedger's community nodes. The results speak for themselves, parallelized scraping enables significantly higher efficiency and scale. Data Bootstrap is one of many companies building on our Data Intelligence Layer, and we’re excited to support innovations like these. Watch the video below to learn more.

OpenLedger

12,079 views • 1 year ago

Ever wondered how AI could understand your company’s private data the way Google understands the web? Elastic is doing just that by being the foundation for context engineering: ▶️ Linking an organisation’s proprietary data to AI, making its data searchable and actionable. ▶️ Enabling multimodal, multilingual AI experiences in India’s Tier II and III cities. ▶️ Driving global business impact for enterprises and governments alike. In this exclusive conversation with Ash Kulkarni, CEO of Elastic, learn how the company is helping enterprises turn data into clarity and real-world outcomes. See the full article and video here: Shradha Sharma

Ever wondered how AI could understand your company’s private data the way Google understands the web? Elastic is doing just that by being the foundation for context engineering: ▶️ Linking an organisation’s proprietary data to AI, making its data searchable and actionable. ▶️ Enabling multimodal, multilingual AI experiences in India’s Tier II and III cities. ▶️ Driving global business impact for enterprises and governments alike. In this exclusive conversation with Ash Kulkarni, CEO of Elastic, learn how the company is helping enterprises turn data into clarity and real-world outcomes. See the full article and video here: Shradha Sharma

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16,476 views • 7 months ago

Nebius will be the first neocloud to hit $1 trillion dollar company and here is exactly why (Save this). As dylan patel says Jensen Huang absolutely hates a world where the hyperscalers have all the power. A world where Microsoft, Amazon, and Google are the only ones building compute is a world where Nvidia is slowly being squeezed by a handful of customers all simultaneously developing custom chips to replace Nvidia GPUs entirely. Google's TPU, Amazon's Trainium and Microsoft's Maia all exist for one reason, to cut Nvidia out of the stack and Jensen knows it so he is playing a long game most investors haven't registered yet. By funding NeoClouds and NeoLabs at scale, Jensen is deliberately engineering a multipolar compute world where no single hyperscaler can dictate terms and where Nvidia hardware remains the default infrastructure layer regardless of which model or platform ultimately wins. Nvidia has deployed roughly $40 billion in AI ecosystem investments across OpenAI, Anthropic, CoreWeave, Nebius, xAI, and dozens of infrastructure companies, all running almost exclusively on Nvidia chips, cementing GPU dependency across the entire AI stack.sedaily Every neocloud that survives and scales becomes a permanent Nvidia GPU customer structurally opposed to the hyperscalers building custom silicon expanding Nvidia's market while simultaneously weakening its biggest competitive threat. Dylan Patel described the neocloud ecosystem as throwing bait into the water and letting the best fish survive, warning that many heavily-backed teams will fail, but the ones that emerge will pull hundreds of millions in ARR right out of the gate. Nebius is that fish because it's the only neocloud operating at hyperscaler scale while remaining fully purpose-engineered for AI workloads from silicon to software. The numbers confirm Nebius has already cleared the survival bar that will eliminate most of the 200+ neoclouds competing right now. Revenue hit $399 million in Q1 2026, up 684% year-over-year, backed by $46 billion in contracted backlog, 3.5 GW of contracted power across seven site and a target of $7–$9 billion in annualized revenue by year-end. When Google approached neoclouds about deploying TPUs, Nebius said no, its Chief Revenue Officer noting that demand is 99% for Nvidia GPUs and that TPU interest comes almost entirely from former Google employees rather than the actual market. That alignment with Nvidia's ecosystem, at this scale, with this backlog, and this level of strategic backing is why Nebius sits in a category of one among the neocloud field. Patel framed the broader play correctly, every neocloud that survives makes Google's TPU and Amazon's Trainium structurally weaker simply by existing and five years from now, the winners will have reshaped the entire compute landscape in Nvidia's favor. Nebius is already hundreds of millions in ARR ahead of the competition while most of the field is still treading water. Milk Road subscribers are already up massively on the Nebius trade, and we are tracking the neocloud buildout as Nvidia works to reshape the entire compute market. Come join Milk Road Pro for our full Nebius breakdown, the valuation framework, the revenue targets we are watching, and the AI infrastructure names we like next for just $1. Link below!

Nebius will be the first neocloud to hit $1 trillion dollar company and here is exactly why (Save this). As dylan patel says Jensen Huang absolutely hates a world where the hyperscalers have all the power. A world where Microsoft, Amazon, and Google are the only ones building compute is a world where Nvidia is slowly being squeezed by a handful of customers all simultaneously developing custom chips to replace Nvidia GPUs entirely. Google's TPU, Amazon's Trainium and Microsoft's Maia all exist for one reason, to cut Nvidia out of the stack and Jensen knows it so he is playing a long game most investors haven't registered yet. By funding NeoClouds and NeoLabs at scale, Jensen is deliberately engineering a multipolar compute world where no single hyperscaler can dictate terms and where Nvidia hardware remains the default infrastructure layer regardless of which model or platform ultimately wins. Nvidia has deployed roughly $40 billion in AI ecosystem investments across OpenAI, Anthropic, CoreWeave, Nebius, xAI, and dozens of infrastructure companies, all running almost exclusively on Nvidia chips, cementing GPU dependency across the entire AI stack.sedaily Every neocloud that survives and scales becomes a permanent Nvidia GPU customer structurally opposed to the hyperscalers building custom silicon expanding Nvidia's market while simultaneously weakening its biggest competitive threat. Dylan Patel described the neocloud ecosystem as throwing bait into the water and letting the best fish survive, warning that many heavily-backed teams will fail, but the ones that emerge will pull hundreds of millions in ARR right out of the gate. Nebius is that fish because it's the only neocloud operating at hyperscaler scale while remaining fully purpose-engineered for AI workloads from silicon to software. The numbers confirm Nebius has already cleared the survival bar that will eliminate most of the 200+ neoclouds competing right now. Revenue hit $399 million in Q1 2026, up 684% year-over-year, backed by $46 billion in contracted backlog, 3.5 GW of contracted power across seven site and a target of $7–$9 billion in annualized revenue by year-end. When Google approached neoclouds about deploying TPUs, Nebius said no, its Chief Revenue Officer noting that demand is 99% for Nvidia GPUs and that TPU interest comes almost entirely from former Google employees rather than the actual market. That alignment with Nvidia's ecosystem, at this scale, with this backlog, and this level of strategic backing is why Nebius sits in a category of one among the neocloud field. Patel framed the broader play correctly, every neocloud that survives makes Google's TPU and Amazon's Trainium structurally weaker simply by existing and five years from now, the winners will have reshaped the entire compute landscape in Nvidia's favor. Nebius is already hundreds of millions in ARR ahead of the competition while most of the field is still treading water. Milk Road subscribers are already up massively on the Nebius trade, and we are tracking the neocloud buildout as Nvidia works to reshape the entire compute market. Come join Milk Road Pro for our full Nebius breakdown, the valuation framework, the revenue targets we are watching, and the AI infrastructure names we like next for just $1. Link below!

Milk Road AI

92,307 views • 16 days ago

The NVIDIA Vera Rubin NVL72 scale-up fabric, built on the sixth-generation NVIDIA NVLink. The NVLink 6 Switch trays connect 72 Rubin GPUs in an all-to-all configuration. The NVLink spine—over 5,000 copper cables make up the vertical NVLink traverse. It securely moves more data than the entire bandwidth of the internet. The single-wide NVIDIA MGX rack design unlocks a cable-free, horizontal NVLink scale-up traverse, running directly on PCB for resiliency at scale. This is how NVIDIA Vera Rubin NVL72 works as one, designed to deliver the lowest token cost and 10x more performance per watt than the previous generation. #NVIDIAVeraRubin

The NVIDIA Vera Rubin NVL72 scale-up fabric, built on the sixth-generation NVIDIA NVLink. The NVLink 6 Switch trays connect 72 Rubin GPUs in an all-to-all configuration. The NVLink spine—over 5,000 copper cables make up the vertical NVLink traverse. It securely moves more data than the entire bandwidth of the internet. The single-wide NVIDIA MGX rack design unlocks a cable-free, horizontal NVLink scale-up traverse, running directly on PCB for resiliency at scale. This is how NVIDIA Vera Rubin NVL72 works as one, designed to deliver the lowest token cost and 10x more performance per watt than the previous generation. #NVIDIAVeraRubin

NVIDIA AI Infrastructure

27,719 views • 2 days ago

Jensen Huang open-sourced NVIDIA's flagship AI model, its weights, its data, AND how they created it. "We open sourced the models," Huang says. "We open sourced the weights." "We open sourced the data." "We open sourced how we created it." Four layers of openness in one model release. "Open source is fundamentally necessary for many industries to join the AI revolution." "NVIDIA has the scale and the motivation to build and continue to build these AI models for as long as we shall live." The chip seller benefits when every model is open. NVIDIA is the chip seller. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

Jensen Huang open-sourced NVIDIA's flagship AI model, its weights, its data, AND how they created it. "We open sourced the models," Huang says. "We open sourced the weights." "We open sourced the data." "We open sourced how we created it." Four layers of openness in one model release. "Open source is fundamentally necessary for many industries to join the AI revolution." "NVIDIA has the scale and the motivation to build and continue to build these AI models for as long as we shall live." The chip seller benefits when every model is open. NVIDIA is the chip seller. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

14,769 views • 1 month ago

Training robot foundation models faces two key hurdles: how to get enough data to train an effective model, and how to make sure that new skills can be acquired quickly. The team at Rhoda AI believes that the answer is training Direct Video Action models from web data. Web data is plentiful, to the point where Rhoda can train their base model on hundreds of years of video data. And then, with the addition of robot data, they can quickly adapt it to new tasks with as little as 20 hours of in-domain data, performing complex, multi-step manipulation tasks with their purpose-built video foundation model. Tongzhou Mu 🤖🦾🦿 Eric Chan and Changan Chen joined us to talk more about their approach. Watch Episode #79 of RoboPapers, with Michael Cho - Rbt/Acc, Chris Paxton, and Jiafei Duan, to learn more!

Training robot foundation models faces two key hurdles: how to get enough data to train an effective model, and how to make sure that new skills can be acquired quickly. The team at Rhoda AI believes that the answer is training Direct Video Action models from web data. Web data is plentiful, to the point where Rhoda can train their base model on hundreds of years of video data. And then, with the addition of robot data, they can quickly adapt it to new tasks with as little as 20 hours of in-domain data, performing complex, multi-step manipulation tasks with their purpose-built video foundation model. Tongzhou Mu 🤖🦾🦿 Eric Chan and Changan Chen joined us to talk more about their approach. Watch Episode #79 of RoboPapers, with Michael Cho - Rbt/Acc, Chris Paxton, and Jiafei Duan, to learn more!

RoboPapers

24,352 views • 2 months ago

Dara (CEO of Uber) on their AI spend: "We blew through our AI budget in a quarter, for the whole year. It is forcing us to adjust. We are going to meter headcount increases because to the extent that my engineers are getting much more efficient, their throughput is increasing. There's a cost to that, and it's a significant cost. AI adoption has been occurring in all parts of the business –– whether it's engineers and how they scope projects, how they build, debugging, platform migrations. I'm pushing the teams to fundamentally use the power of AI to rebuild systems and processes from the bottoms up. I do think it's a combination for us right now of encouraging adoption, but then driving efficiency. We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are open source."

Dara (CEO of Uber) on their AI spend: "We blew through our AI budget in a quarter, for the whole year. It is forcing us to adjust. We are going to meter headcount increases because to the extent that my engineers are getting much more efficient, their throughput is increasing. There's a cost to that, and it's a significant cost. AI adoption has been occurring in all parts of the business –– whether it's engineers and how they scope projects, how they build, debugging, platform migrations. I'm pushing the teams to fundamentally use the power of AI to rebuild systems and processes from the bottoms up. I do think it's a combination for us right now of encouraging adoption, but then driving efficiency. We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are open source."

Patrick OShaughnessy

614,600 views • 1 month ago

BREAKING: Jacob Kimmel on closing $130M in funding for NewLimit and how epigenetic marks work "All the cells in your body have the same DNA code. Since they have the same code base, it presents a question: how do your eyeball, kidney and tongue all do different things?" "The answer is epigenetic marks, which are chemical modifications. They are kind of like control flows in software (genome), and help express different genes from your genome to do different jobs." "Turns out as you age, all of those epigenetic marks get messed up. Your cells stop using the right genes at the right time, and then they degrade in function." "This precipitates a number of diseases and pathologies that arise with age, including things that we don't even traditionally define as disease but should remedy."

BREAKING: Jacob Kimmel on closing $130M in funding for NewLimit and how epigenetic marks work "All the cells in your body have the same DNA code. Since they have the same code base, it presents a question: how do your eyeball, kidney and tongue all do different things?" "The answer is epigenetic marks, which are chemical modifications. They are kind of like control flows in software (genome), and help express different genes from your genome to do different jobs." "Turns out as you age, all of those epigenetic marks get messed up. Your cells stop using the right genes at the right time, and then they degrade in function." "This precipitates a number of diseases and pathologies that arise with age, including things that we don't even traditionally define as disease but should remedy."

TBPN

18,231 views • 1 year ago

MiniMax is building with next-gen AGI, offering foundation AI models and revolutionizing content creation with AI-powered video, music, chat products. With Alibaba's one-stop multimodal data platform, MiniMax can save the complexity of handling multimodal data work with the AI-ready data foundation, and boost streamlined innovation on it. Feifei Li, SVP and President of International Business at Alibaba Cloud Intelligence Group, shares how the right tech stack can elevate AI from potential to powerful. 🚀

MiniMax is building with next-gen AGI, offering foundation AI models and revolutionizing content creation with AI-powered video, music, chat products. With Alibaba's one-stop multimodal data platform, MiniMax can save the complexity of handling multimodal data work with the AI-ready data foundation, and boost streamlined innovation on it. Feifei Li, SVP and President of International Business at Alibaba Cloud Intelligence Group, shares how the right tech stack can elevate AI from potential to powerful. 🚀

Alibaba Group

305,831 views • 7 months ago

Ilario Corna, CTO of the International Olympic Committee (IOC), shares insights on how the partnership with Alibaba is central to the intelligence layer being developed for Milano Cortina 2026. By building on Alibaba’s open-source Qwen model, the IOC gains a powerful and flexible foundation model tailored to the needs of National Olympic Committees (NOCs), Organizing Committees (OCOGs), and IOC teams. Together, we are building on the AI foundations introduced at Paris 2024, integrating them into a unified “Olympic AI” ecosystem. The Olympic Games Milano Cortina 2026

Ilario Corna, CTO of the International Olympic Committee (IOC), shares insights on how the partnership with Alibaba is central to the intelligence layer being developed for Milano Cortina 2026. By building on Alibaba’s open-source Qwen model, the IOC gains a powerful and flexible foundation model tailored to the needs of National Olympic Committees (NOCs), Organizing Committees (OCOGs), and IOC teams. Together, we are building on the AI foundations introduced at Paris 2024, integrating them into a unified “Olympic AI” ecosystem. The Olympic Games Milano Cortina 2026

Alibaba Group

741,654 views • 4 months ago

"Tokenize Everything." 🌎 Nicholas Motz, CIO, and Jakub Bojan, CEO from Soil discuss how tokenization is transforming finance—unlocking liquidity, democratizing access, and bringing real-world assets like BlackRock’s BUIDL and Hamilton Lane’s SCOPE fund to the blockchain. With Securitize as their partner, Soil is paving the way for secure, efficient on-chain investments. 🎥 Watch now to see how they’re shaping the future of RWAs.

"Tokenize Everything." 🌎 Nicholas Motz, CIO, and Jakub Bojan, CEO from Soil discuss how tokenization is transforming finance—unlocking liquidity, democratizing access, and bringing real-world assets like BlackRock’s BUIDL and Hamilton Lane’s SCOPE fund to the blockchain. With Securitize as their partner, Soil is paving the way for secure, efficient on-chain investments. 🎥 Watch now to see how they’re shaping the future of RWAs.

Securitize

28,848 views • 1 year ago