Temporal Raises $550M at $12.55B Valuation

Nvidia is buying Hugging Face for 12.9 billion dollars. That is not good news for your deployment stack. Ars Technica called Hugging Face 'the GitHub of AI'. That description is exactly the problem. GitHub did not shut down when Microsoft bought it. It just quietly became the best place to work if you were already inside the Microsoft ecosystem. Nvidia will not need to close Hugging Face either. All it needs to do is make model downloads, quantization tools and inference runtimes work a little smoother on CUDA and a little rougher everywhere else. Closed labs are designing their own silicon. Now the open ecosystem is consolidating into one company's hardware story too. Most Indian AI teams pull base models straight from Hugging Face and assume that pipeline stays neutral forever. It will not stay neutral. It will just get slowly less neutral, one optimization at a time. Start testing your inference path on non-Nvidia hardware now, while it still works fine and nobody is forcing the question. What would it cost your team to re-platform your model serving layer if that assumption broke in six months? #SaaS #AIInfrastructure #MultiTenant

NVIDIA is acquiring Hugging Face for $12.9 BILLION!!! But the biggest story isn’t the money At first glance, it looks like another massive AI acquisition. But it made me think about something bigger: the relationship between ownership and open source. GitHub is owned by Microsoft, yet it remains one of the world’s biggest platforms for open-source software. So NVIDIA owning Hugging Face doesn’t automatically mean Hugging Face becomes less open. The more interesting question is: As major technology companies acquire key platforms in the open-source ecosystem, how might ownership influence their direction, governance, and accessibility? More resources could accelerate innovation. More ownership could also mean more influence. Open source isn’t just about who owns the platform. It’s also about how open that platform remains. That’s what makes this acquisition interesting to me. #AI #OpenSource #HuggingFace #NVIDIA #Technology #MachineLearning

Tired of paying a $20/user per-seat tax just to share and deploy AI models with your team? Today, we’re officially launching nexusvllm (https://nexusvllm.com) 🚀 As LLMs evolved, model hubs became bloated and expensive. Engineers shouldn't have to navigate complex CLI setups just to quantize models, or pay massive monthly team fees for basic hub collaboration. We built nexusvllm to solve this: ⚡ 5.1x Inference Throughput: Hardware-aware registry optimized for NVIDIA Hopper, Blackwell, and Ada architectures. 🛠️ 1-Click GGUF & Ollama Quantization: Convert any Hugging Face model directly in your browser with automated Modelfile generation. 💬 Embeddable AI Playground: Drop a live high-speed chatbot widget into any website in 10 seconds. 🛡️ Zero Per-Seat Team Tax: Flat enterprise pricing with unlimited seats. No surprise scaling fees. We’re bootstrapping this in public and would love your brutal feedback: 👉 What’s the biggest bottleneck you face when serving local open-source models today? Check it out live: https://nexusvllm.com #ArtificialIntelligence #MachineLearning #OpenSource #vLLM #NVIDIA #LLM #HuggingFace #TechLaunch #DeepLearning #MLOps

A proud milestone for the team at Stackbrains AI — we’ve officially joined NVIDIA Inception. 🚀 It marks an exciting step forward as we continue building AI-native intelligence Operating System that helps manufacturers connect operations, make smarter decisions, and work more efficiently. Grateful to everyone who has supported our journey. We’re just getting started. #NVIDIAInception #ManufacturingAI #EnterpriseAI #StackbrainsAI

A proud milestone for our team at Stackbrains. We’ve officially joined NVIDIA Inception. 🚀 An exciting step forward as we continue building AI-native intelligence for smarter manufacturing operations. Grateful to everyone supporting our journey. We’re just getting started. #NVIDIAInception #Stackbrains #ManufacturingAI

Big news from Stackbrains! 🚀 We’re proud to announce that Stackbrains has joined NVIDIA Inception. This milestone will give our team access to NVIDIA’s technical resources, developer tools, training and global AI ecosystem as we continue building AI-native intelligence for manufacturing. Our mission remains focused: Connect fragmented operational information, automate coordination and help manufacturers make smarter, faster decisions. We’re grateful to our customers, partners and everyone who has supported our journey. This is an exciting milestone, but we’re only getting started. Discover Stackbrains: www.stackbrains.ai #NVIDIAInception #Stackbrains #ManufacturingAI #AITransformation #SmartManufacturing

It’s been another big week in tech, from Anthropic’s $35B AI-compute deal to New York’s new AI ban in schools, affecting around 600,000 students. Check out this week's TechTarget news roundup, where I cover: 🌟 OpenAI's #Astra model 🌟 #Uber layoffs 🌟 #Anthropic's $35B AI-compute deal with #Lambda 🌟 The New York #AIMoratorium for schools 🌟 Nvidia's #HuggingFace acquisition Plus the latest executive moves and IPO news... Take a look 👇 https://lnkd.in/ejh7eH9F

The most important signal in NVIDIA's Q2 earnings wasn't the revenue beat. It was the composition of where that revenue came from. For most of 2024 and early 2025, NVIDIA's AI revenue was concentrated in a handful of US hyperscalers Microsoft, Google, Amazon, AI at Meta accounting for the bulk of data centre spending. The concern the market has repeatedly raised is whether that concentration represented a fragile, narrow foundation. What Q2 2026 showed is that the foundation has widened substantially. Data centre revenue of $89 billion now draws from HYPERSCALERS, Sovereign AI programmes (governments building national AI infrastructure), Neoclouds, AI-native startups, and enterprise customers deploying at scale. The customer base is no longer a handful of companies. It is an ecosystem. Q3 guidance of $105.8 to $110.1 billion against Wall Street Oasis's expectation of $92.3 billion tells you that NVIDIA's own visibility into demand is substantially higher than the market's best model of it. That gap between guidance and consensus is not a rounding error. It is a signal that the analysts covering the company are still underestimating the pace of infrastructure build-out even now. Two numbers worth holding together: revenue grew 106% year-over-year in Q2. The company is guiding for roughly 70% revenue growth in fiscal 2028. That is a company telling you, with confidence, that deceleration is in the plan but so is continued extraordinary growth for years ahead. The AI infrastructure cycle is not in its final innings. It is in the middle of a broadening phase that looks different from the concentrated hyperscaler-driven surge of 2024. Understanding that distinction is what separates the next wave of opportunity from the last one. #Nvidia #AI #Earnings #TheFXPodcast #TechStocks #Investing #ArtificialIntelligence #DataCenter

NVIDIA just agreed to acquire Hugging Face for $12.93 billion, putting the largest open-model developer platform inside the world's dominant AI infrastructure company. For IT and ServiceNow leaders, this is a supply-chain signal, not just an AI headline. Hugging Face hosts the open-weight models many private-AI and RAG deployments quietly depend on. When the model hub and the hardware layer consolidate under one vendor, roadmap, licensing, and access terms for those models can shift with little warning. The practical move: inventory which open-source models your platform integrations, agents, and internal tools actually pull from Hugging Face, and confirm you have a fallback path (self-hosted weights, alternate registries) if terms or availability change. https://lnkd.in/eXE3EkMG #NVIDIA #AI #ServiceNow #EnterpriseIT