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Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with... show more

CoreWeave

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28,320 views • 3 months ago •via X (Twitter)

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The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.

The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.

CoreWeave

487,192 views • 1 month ago

Something NVIDIA & Google do better than anyone else is software-hardware-system co-design, and not just optimizing hardware for current model architectures, but predicting future ones. Back in early 2022, when NVIDIA started the design process for NVL72, MoE (Mixture of Experts) models were not yet the standard, and dense models were still dominant for frontier models. However, NVIDIA's strong software-hardware co-design culture enabled them to make a calculated bet that MoEs were the future, and they built NVL72 specifically for best MoE performance per TCO (Total Cost of Ownership). Furthermore, back in 2022, disaggregated prefill and wide expert parallelism (wideEP) MoE inference optimizations hadn't been invented yet, but it turns out that these MoE inference optimizations work best on large-scale systems like NVL72. While most other AI chip companies' in-house AI labs focus on training small 5B models that mainly use data parallelism, NVIDIA and Google's in-house AI labs continuously push the boundaries of model architecture and training recipes, such as NVFP4 training. Just like Super Idol & IShowSpeed, there must be a strong partnership between software engineers and hardware engineers to deliver the best systems that maximize performance per TCO.

Something NVIDIA & Google do better than anyone else is software-hardware-system co-design, and not just optimizing hardware for current model architectures, but predicting future ones. Back in early 2022, when NVIDIA started the design process for NVL72, MoE (Mixture of Experts) models were not yet the standard, and dense models were still dominant for frontier models. However, NVIDIA's strong software-hardware co-design culture enabled them to make a calculated bet that MoEs were the future, and they built NVL72 specifically for best MoE performance per TCO (Total Cost of Ownership). Furthermore, back in 2022, disaggregated prefill and wide expert parallelism (wideEP) MoE inference optimizations hadn't been invented yet, but it turns out that these MoE inference optimizations work best on large-scale systems like NVL72. While most other AI chip companies' in-house AI labs focus on training small 5B models that mainly use data parallelism, NVIDIA and Google's in-house AI labs continuously push the boundaries of model architecture and training recipes, such as NVFP4 training. Just like Super Idol & IShowSpeed, there must be a strong partnership between software engineers and hardware engineers to deliver the best systems that maximize performance per TCO.

SemiAnalysis

51,021 views • 9 months ago

SMRT x NVIDIA🤝 We are excited to announce we have been enrolled into the NVIDIA Developer program! Included in this prestigious program is access to advanced tools and SDKs, training resources, early access programs and unlimited use of NVIDIA On-Demand Services. Additionally, the SmartMoney team will be attending the NVIDIA GTC AI Conference, networking with the top brains in AI development who will be in attendance, including Jensen Huang CEO of NVIDIA and Brad Lightcap COO of OpenAI . As a nascent AI Blockchain project, this partnership will be crucial as we scale and build out our platform and services, given NVIDIA's wealth of resources in the AI industry. Make sure to follow our twitter for more updates as we continue to partner with and learn from the strongest projects and firms in our field.

SMRT x NVIDIA🤝 We are excited to announce we have been enrolled into the NVIDIA Developer program! Included in this prestigious program is access to advanced tools and SDKs, training resources, early access programs and unlimited use of NVIDIA On-Demand Services. Additionally, the SmartMoney team will be attending the NVIDIA GTC AI Conference, networking with the top brains in AI development who will be in attendance, including Jensen Huang CEO of NVIDIA and Brad Lightcap COO of OpenAI . As a nascent AI Blockchain project, this partnership will be crucial as we scale and build out our platform and services, given NVIDIA's wealth of resources in the AI industry. Make sure to follow our twitter for more updates as we continue to partner with and learn from the strongest projects and firms in our field.

SmartMoney

21,233 views • 2 years ago

Open weights just caught up to the frontier. GLM-5.2 from Z.ai tops the open-model rankings on Artificial Analysis and Arena.ai's Agent Arena. It's now live on CoreWeave Serverless Inference at $1.39 in and $4.40 out per 1M tokens. Ship more for less.

Open weights just caught up to the frontier. GLM-5.2 from Z.ai tops the open-model rankings on Artificial Analysis and Arena.ai's Agent Arena. It's now live on CoreWeave Serverless Inference at $1.39 in and $4.40 out per 1M tokens. Ship more for less.

CoreWeave

16,637 views • 2 months ago

As a supporter of the open weights ecosystem, we're proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.

As a supporter of the open weights ecosystem, we're proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.

Applied Compute

25,234 views • 26 days ago

“HUMAIN and Luma AI announce HUMAIN Create - the future of creative intelligence” The future of storytelling is being re-written by AI. Introducing HUMAIN Create. Announced at LIONS | The Home of Creativity by Sir Martin Sorrell, this bold new global partnership unites Luma’s frontier creative intelligence models with HUMAIN’s next-generation AI infrastructure to scale generative AI for entertainment, gaming, and advertising to an unprecedented scale. Explore the future of gaming and interactive entertainment now: Missed “The Future of Storytelling: Generative AI, Creative Power, and the New Marketing Imagination” at Cannes Lions? Watch it here: Luma AI #HUMAINCreate #HUMAINAI #LumaAI #Ray2 #TheEndOfLimits #CannesLions2025

“HUMAIN and Luma AI announce HUMAIN Create - the future of creative intelligence” The future of storytelling is being re-written by AI. Introducing HUMAIN Create. Announced at LIONS | The Home of Creativity by Sir Martin Sorrell, this bold new global partnership unites Luma’s frontier creative intelligence models with HUMAIN’s next-generation AI infrastructure to scale generative AI for entertainment, gaming, and advertising to an unprecedented scale. Explore the future of gaming and interactive entertainment now: Missed “The Future of Storytelling: Generative AI, Creative Power, and the New Marketing Imagination” at Cannes Lions? Watch it here: Luma AI #HUMAINCreate #HUMAINAI #LumaAI #Ray2 #TheEndOfLimits #CannesLions2025

HUMAIN

26,802 views • 1 year ago

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

Chris

60,278 views • 5 months ago

🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: NVIDIA just announced the Isaac GR00T Reference Humanoid Robot. The first fully open humanoid robot reference design built on Jetson Thor, and it's going straight to the world's top research institutions. This is Jensen Huang's bet on open physical AI infrastructure. The hardware stack is serious: → Unitree H2 Plus chassis, 6 feet tall, 150 pounds, 31 degrees of freedom → Sharpa Wave tactile five-finger hands, 22 degrees of freedom, bringing total to 75 across the full body → NVIDIA Jetson AGX Thor onboard compute, 2,070 FP4 teraflops of AI performance, 128GB unified memory → Multi-view sensing, stereo head camera, wrist cameras, IMU Alongside this announcement, Unitree also introduced the H2 Plus as a standalone product, a frontier humanoid combining Unitree's own body, Sharpa's five-finger hands and NVIDIA Robotics Jetson Thor compute into one fully integrated research platform. The full Isaac GR00T software stack ships with it, teleoperation for data capture, open foundation models, Isaac Sim for training, Isaac Lab for evaluation, and accelerated ROS middleware for deployment. The complete loop from data to real-world robot in one unified platform. ETH Zürich, Stanford Robotics Center, UC San Diego and Ai2 are already on board as launch research partners. NVIDIA Robotics did to AI what it's now doing to robotics, build the platform, open the ecosystem, let the world build on top of it. Whoever owns the infrastructure layer wins. NVIDIA knows this better than anyone. 👀 Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

16,062 views • 3 months ago

Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.

Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.

Satya Nadella

849,769 views • 7 months ago

Today we’re introducing Google AI Threat Defense - a comprehensive AI-powered cybersecurity solution designed to help continuously monitor for and stop AI-powered threats before they can impact your business. Here’s how it works: 1. AI Threat Defense uses our cybersecurity platform Wiz to scan and prioritize what applications and systems have the highest security risk. 2. Gemini and other frontier AI models can then autonomously perform continual deep scanning of your applications - starting with those at the highest risk - to identify security vulnerabilities. 3. The capabilities of CodeMender - a new software repair agent - are then used to verify and accelerate the patching of vulnerabilities. 4. And our Wiz autonomous agents continuously test your systems to find unknown vulnerabilities before adversaries do so that you can remediate them before you are attacked. While other model providers focus on using AI to find and flag vulnerabilities, Google AI Threat Defense actively prioritizes your most critical real-world risks and accelerates their remediation using a variety of models since no single model finds a superset of the vulnerabilities found by all other models.

Today we’re introducing Google AI Threat Defense - a comprehensive AI-powered cybersecurity solution designed to help continuously monitor for and stop AI-powered threats before they can impact your business. Here’s how it works: 1. AI Threat Defense uses our cybersecurity platform Wiz to scan and prioritize what applications and systems have the highest security risk. 2. Gemini and other frontier AI models can then autonomously perform continual deep scanning of your applications - starting with those at the highest risk - to identify security vulnerabilities. 3. The capabilities of CodeMender - a new software repair agent - are then used to verify and accelerate the patching of vulnerabilities. 4. And our Wiz autonomous agents continuously test your systems to find unknown vulnerabilities before adversaries do so that you can remediate them before you are attacked. While other model providers focus on using AI to find and flag vulnerabilities, Google AI Threat Defense actively prioritizes your most critical real-world risks and accelerates their remediation using a variety of models since no single model finds a superset of the vulnerabilities found by all other models.

Thomas Kurian

198,248 views • 3 months ago

The future fight won’t be won by size or scale alone. It’ll be won by those who can innovate, adapt, and move at speed. That idea was at the heart of Booz Allen CEO Horacio Rozanski’s recent conversation with Erik Torenberg of Andreesen Horowitz and Gary Steele Steele, CEO of Shield AI on The a16z Podcast. In a time of accelerating geopolitical risk, Horacio shared why speed—in technology, partnerships, and deployment—is the decisive factor for national security. Together with Shield AI and its Hivemind autonomy stack, Booz Allen is helping bring advanced, mission-ready AI to the edge faster. Listen to the full episode:

The future fight won’t be won by size or scale alone. It’ll be won by those who can innovate, adapt, and move at speed. That idea was at the heart of Booz Allen CEO Horacio Rozanski’s recent conversation with Erik Torenberg of Andreesen Horowitz and Gary Steele Steele, CEO of Shield AI on The a16z Podcast. In a time of accelerating geopolitical risk, Horacio shared why speed—in technology, partnerships, and deployment—is the decisive factor for national security. Together with Shield AI and its Hivemind autonomy stack, Booz Allen is helping bring advanced, mission-ready AI to the edge faster. Listen to the full episode:

Booz Allen Hamilton

59,729 views • 10 months ago

Registration for #FullyConnected26 is open: 🗓️ September 29 – Oct 1 📍San Francisco 3 days and 3 tracks to accelerate the superintelligence loop. 2,000+ AI Leaders in the room. This is where you need to be.

Registration for #FullyConnected26 is open: 🗓️ September 29 – Oct 1 📍San Francisco 3 days and 3 tracks to accelerate the superintelligence loop. 2,000+ AI Leaders in the room. This is where you need to be.

CoreWeave

15,135 views • 3 months ago

Can industrial AI do more than just observe? Nicolas Cerisier, Vice President of 3DEXPERIENCE Platform R&D at Dassault Systèmes explains how the shift from SaaS to "Agent-as-a-Service" is introducing "Industry World Models" that understand the scientific laws of physics and engineering to power autonomous virtual companions.

Can industrial AI do more than just observe? Nicolas Cerisier, Vice President of 3DEXPERIENCE Platform R&D at Dassault Systèmes explains how the shift from SaaS to "Agent-as-a-Service" is introducing "Industry World Models" that understand the scientific laws of physics and engineering to power autonomous virtual companions.

NVIDIA

25,743 views • 4 months ago

We’re delighted to announce that Pineapple has officially joined the NVIDIA Developer Program! 🍍🤝 What Benefits Does This Provide To Pineapple? ✅🍍 Enables Innovations with GPU-Optimized Software: The heart of NVIDIA’s developer resources is access to hundreds of software and performance analysis tools across diverse industries and use cases, from AI and HPC to autonomous vehicles, robotics, simulation, and more. These SDKs and tools can be obtained in multiple ways, including containers, pre-trained models, and Helm charts from the NGC catalog applications from Linux repositories, and source code from NVIDIA's GitHub repositories. ✅🍍Accelerates Higher Education and Research: NVIDIA offers an array of benefits to developers, educators, and researchers in academia, including NVIDIA DLI Teaching Kits , DLI Programs for Educators, Higher Education and Research Grants , Educational Pricing, and Graduate Fellowships. ✅🍍Supports Cutting-Edge Startups with NVIDIA Inception: NVIDIA Inception - the leading accelerator of AI, data science, and HPC startups - supports startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through NVIDIA’s Deep Learning Institute, preferred pricing on hardware through our global network of distributors, invitations to exclusive networking events, and more. ✅🍍Pineapple will utilise NVIDIA’s cutting-edge tools and technology to accelerate development in decentralized trading. This will help us bring even more powerful features to the our ecosystem! $PAPPLE

We’re delighted to announce that Pineapple has officially joined the NVIDIA Developer Program! 🍍🤝 What Benefits Does This Provide To Pineapple? ✅🍍 Enables Innovations with GPU-Optimized Software: The heart of NVIDIA’s developer resources is access to hundreds of software and performance analysis tools across diverse industries and use cases, from AI and HPC to autonomous vehicles, robotics, simulation, and more. These SDKs and tools can be obtained in multiple ways, including containers, pre-trained models, and Helm charts from the NGC catalog applications from Linux repositories, and source code from NVIDIA's GitHub repositories. ✅🍍Accelerates Higher Education and Research: NVIDIA offers an array of benefits to developers, educators, and researchers in academia, including NVIDIA DLI Teaching Kits , DLI Programs for Educators, Higher Education and Research Grants , Educational Pricing, and Graduate Fellowships. ✅🍍Supports Cutting-Edge Startups with NVIDIA Inception: NVIDIA Inception - the leading accelerator of AI, data science, and HPC startups - supports startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through NVIDIA’s Deep Learning Institute, preferred pricing on hardware through our global network of distributors, invitations to exclusive networking events, and more. ✅🍍Pineapple will utilise NVIDIA’s cutting-edge tools and technology to accelerate development in decentralized trading. This will help us bring even more powerful features to the our ecosystem! $PAPPLE

Pineapple $PAPPLE

16,871 views • 1 year ago

🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:

🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:

Sahara AI 🔆

2,700,909 views • 1 year ago

Most AI Projects In Crypto Are Liars. Sentient is different. It is the only project in Web3 pursuing true Artificial General Intelligence. A few facts that set it apart: 1. First-of-its-kind: Sentient is not just building AI tools, but an open, crypto-native path to AGI. 2. Community-owned intelligence: Instead of Big Tech locking up breakthroughs, progress is built openly and shared on-chain. 3. Value capture: Every step forward in intelligence accrues to the ecosystem itself, not to a closed corporation. 4. Product before hype: While dozens of AI projects launch at $300M–$2B FDV with little to show, Sentient is shipping real technology first. 5. Designed to evolve: Its architecture is built to learn, adapt, and scale like a human mind. 6. The singularity play in crypto: Many see Sentient as the Tesla-equivalent for AGI—but crypto-native. In time, people will understand that this isn’t just another AI project. It’s the beginning of decentralized intelligence.

Most AI Projects In Crypto Are Liars. Sentient is different. It is the only project in Web3 pursuing true Artificial General Intelligence. A few facts that set it apart: 1. First-of-its-kind: Sentient is not just building AI tools, but an open, crypto-native path to AGI. 2. Community-owned intelligence: Instead of Big Tech locking up breakthroughs, progress is built openly and shared on-chain. 3. Value capture: Every step forward in intelligence accrues to the ecosystem itself, not to a closed corporation. 4. Product before hype: While dozens of AI projects launch at $300M–$2B FDV with little to show, Sentient is shipping real technology first. 5. Designed to evolve: Its architecture is built to learn, adapt, and scale like a human mind. 6. The singularity play in crypto: Many see Sentient as the Tesla-equivalent for AGI—but crypto-native. In time, people will understand that this isn’t just another AI project. It’s the beginning of decentralized intelligence.

BillionAireSon 🛡️

16,141 views • 11 months ago

$LTX 2.5 JUST WENT FASTER THAN REAL TIME LTX (LTX.io) is already one of the world's most widely used open video models. We just made its latest release, LTX 2.5, fast enough for rapid iteration and affordable enough for production at scale. It’s live on TensorScaleAI now, generating a 5-sec 1080p video in just 3.12s at $0.04 per second. That's faster than real time, at a fraction of the cost! For creative teams, that means less waiting time, more ideas explored, and lower production costs. For robotics and physical AI teams, that means more data generated at scale, more scenarios tested, and shorter development and deployment cycles. Request early access today and we’ll get you onboarded! (link:$

LTX 2.5 JUST WENT FASTER THAN REAL TIME LTX (LTX.io) is already one of the world's most widely used open video models. We just made its latest release, LTX 2.5, fast enough for rapid iteration and affordable enough for production at scale. It’s live on TensorScaleAI now, generating a 5-sec 1080p video in just 3.12s at $0.04 per second. That's faster than real time, at a fraction of the cost! For creative teams, that means less waiting time, more ideas explored, and lower production costs. For robotics and physical AI teams, that means more data generated at scale, more scenarios tested, and shorter development and deployment cycles. Request early access today and we’ll get you onboarded! (link:

Yao Zhang

15,789 views • 12 days ago

AI token usage is up 10x in 7 months, compounding 40%/MONTH! There is NO BUBBLE when demand is STILL accelerating And this is just OpenRouter, it doesn't count the labs direct token usage and APIs But here's what's interesting about these numbers, the demand is coming from everywhere at once US models (OpenAI, Anthropic, Google) keep growing, while Chinese open weight models (DeepSeek, Tencent, Xiaomi, Minimax) grew even faster and now drive over 60% of usage on OpenRouter Closed source and open source both compounding at the same time. This is literally the best case scenario for AI Infra investors It means both frontier model tokens and cheaper tokens have product market fit. This means the application layer is finding ways to use both and generate ROI with both types Demand for tokens IS demand for compute. This is why SpaceX is looking to build 10GW of compute by next year, because the demand is clearly here Now combine this demand set up, with NVIDIA yesterday announcing financing platforms with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to mobilize over $500 billion of third party capital for AI infrastructure And Jensen has said publicly he expects $3 to $4 TRILLION of AI infrastructure spend by 2030 The build out will have to continue for a lot longer than the market is expecting, that is very clear to me. Don't let this consolidation period in AI infra stocks shake you out, they will have their moment again and take their next leg higher p.s. if you want to see how im investing in this, you can track my real-time portfolio and the research of all 5 Milk Road PRO analysts with live trade notifications, and it's just $1 to try it out (insane price just to check it out). Learn more here: Good luck out there!

AI token usage is up 10x in 7 months, compounding 40%/MONTH! There is NO BUBBLE when demand is STILL accelerating And this is just OpenRouter, it doesn't count the labs direct token usage and APIs But here's what's interesting about these numbers, the demand is coming from everywhere at once US models (OpenAI, Anthropic, Google) keep growing, while Chinese open weight models (DeepSeek, Tencent, Xiaomi, Minimax) grew even faster and now drive over 60% of usage on OpenRouter Closed source and open source both compounding at the same time. This is literally the best case scenario for AI Infra investors It means both frontier model tokens and cheaper tokens have product market fit. This means the application layer is finding ways to use both and generate ROI with both types Demand for tokens IS demand for compute. This is why SpaceX is looking to build 10GW of compute by next year, because the demand is clearly here Now combine this demand set up, with NVIDIA yesterday announcing financing platforms with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to mobilize over $500 billion of third party capital for AI infrastructure And Jensen has said publicly he expects $3 to $4 TRILLION of AI infrastructure spend by 2030 The build out will have to continue for a lot longer than the market is expecting, that is very clear to me. Don't let this consolidation period in AI infra stocks shake you out, they will have their moment again and take their next leg higher p.s. if you want to see how im investing in this, you can track my real-time portfolio and the research of all 5 Milk Road PRO analysts with live trade notifications, and it's just $1 to try it out (insane price just to check it out). Learn more here: Good luck out there!

Kyle Reidhead | Milk Road

28,320 views • 20 days ago

Sparky is ready... are you? 🔥 It's time for Day 1 of #GoogleIO! We're sharing lots of updates on how you can prototype, build, and run modern, full-stack apps in the AI era with Firebase. Here's where to catch the latest from Firebase: 1️⃣ Developer keynote at 1:30pm PT 2️⃣ What's New in Firebase livestream at 4:30pm PT

Sparky is ready... are you? 🔥 It's time for Day 1 of #GoogleIO! We're sharing lots of updates on how you can prototype, build, and run modern, full-stack apps in the AI era with Firebase. Here's where to catch the latest from Firebase: 1️⃣ Developer keynote at 1:30pm PT 2️⃣ What's New in Firebase livestream at 4:30pm PT

Firebase

19,792 views • 1 year ago