#Nvidia Ai

NVIDIA’s New $249 AI Beast Just Dropped Meet the Jetson Orin Nano Super Developer Kit — a compact AI powerhouse delivering 67 TOPS of performance, a 1.7x boost from the last-gen. ⚡🧠🤖 For just $249, it brings generative AI to the hands of developers, students, and hobbyists alike. 💻🧑‍💻 Under the hood: NVIDIA Ampere GPU with 1,024 CUDA cores + 32 Tensor Cores 🧮 6-core Arm Cortex-A78AE CPU ⚙️ 8GB LPDDR5 RAM with 102GB/s bandwidth 🚀 It’s made for vision transformers, LLMs, robotics, smart vision, and more — all at the edge. 🦾📡 Bonus: Current Jetson Orin Nano users can upgrade via software. In India, it’s on backorder via Robu.in with shipping expected after Feb 28, 2025. 📦🗓️ The future of AI prototyping is here — smaller, faster, smarter. 🤯💡 Source: Nvidia/YT Follow @calminmotivation for more reels 📈 . . . . #enterpreneur #nvidia #jensenhuang #gpu #innovation #viral #ideas #artificialintelligence #ai #cpu #supercomputer #business #success #ideas #explorepage #fyp

Jensen Huang, CEO of Nvidia, argues that AI will not reduce the number of software engineers, but likely increase it. Writing code is just one part of the role. The real value of an engineer lies in diagnosing problems, collaborating with teams, evaluating outcomes, and identifying what to build next. As AI takes over more of the coding itself, the demand for people who can define problems and connect systems may grow even faster. In that sense, automation shifts the work rather than eliminating it. Huang’s view is that innovation does not disappear with better tools. It expands, and with it, the need for engineers who can think, not just code. 👉 Follow @uncover.ai to stay updated with the latest AI news — Media: Lex Fridman

NVIDIA’s CEO, Jensen Huang, outlined the roadmap for the future of AI, taking us from perception AI to generative AI, agentic AI, and finally physical AI. Currently, we are at the generative AI phase, where tools create text, images, and videos from user inputs—technologies valued at over $100 billion in 2023. Agentic AI is next, where AI agents can self-code and create software without human intervention, saving thousands of development hours. This technology will reshape industries, reducing costs and unlocking new possibilities in coding, automation, and problem-solving. The ultimate goal is physical AI, including robotics and autonomous systems like self-driving cars. With AI advancing towards this trillion-dollar opportunity, NVIDIA’s strategy highlights where the biggest innovations—and investments—are headed. Follow @growasentrepreneurs for more! [Jensen Huang, Nvidia, CES, Entrepreneurship, Entrepreneur, Business, Startup] #jensenhuang #nvidia #ces #entrepreneur #entrepreneurship #business #startup #mindset #viral #explore #trending

AI power is getting smaller. And cheaper. NVIDIA just dropped the Jetson Orin Nano Super Developer Kit. Price? Just $249. But the performance is wild: 67 TOPS of AI compute. 1.7× faster than the previous generation. Inside the tiny box: 1,024 CUDA cores on an Ampere GPU. 32 Tensor Cores for AI workloads. 6-core Arm Cortex-A78AE CPU. 8GB LPDDR5 RAM with 102GB/s bandwidth. What can it run? Vision transformers. LLMs. Robotics. Smart cameras. All directly on the edge. No giant data center needed. The biggest shift in AI isn’t just bigger models. It’s powerful AI Getting into everyone’s hands. Developers. Students. Builders. The future of AI prototyping Just got a lot smaller. Follow @noblessence_ for more such reels 🙌🏻🔥 #ai #nvidia #technology #innovation #robotics

@nvidia CEO Jensen Huang on losing your job to AI.

Useful agents will need to interact with the world as it is. NVIDIA CEO Jensen Huang joins Lex Fridman to break down how physical AI agents like humanoid robots will reason, act, and operate in ways that make sense in the real world. Catch the full episode now at the link in bio.

🚨 Nvidia CEO: China’s AI Game Is Strong 🇨🇳 Jensen Huang says he expects to compete with China “for a long time” — and he doesn’t believe they’re far behind the US in AI development. While some assume the US is leading by miles, Huang’s take is clear: China’s catching up fast, and the global AI race is heating up. This isn’t just about chips… it’s about who shapes the future of technology. #AI #Nvidia #JensenHuang #ChinaTech #USvsChina #ArtificialIntelligence #TechTrends #GlobalCompetition

⏳ Reserve your NVIDIA DGX Spark now. 🙌 With your own personal AI supercomputer, you'll be able to prototype, fine-tune, and deploy with ease. ✅ 1 petaFLOP ✅ 128GB of coherent, unified system memory ✅ ConnectX-7 Smart NIC ✅ Up to 4TB Storage ✅ 150mm L x 150mm W x 50.5mm H Get ready to #SparkSomethingBig 💫 See our link-in-bio.

Jensen Huang believes the next generation of software will be built around AI agents that can think, plan, reason, and complete tasks on behalf of users. Instead of people manually handling every step inside apps, these intelligent agents will manage workflows across business platforms, enterprise tools, and daily digital tasks. This shift could reshape industries from customer service to finance, healthcare, and operations, where AI agents may handle repetitive work, assist in decision-making, and speed up complex processes. Follow us (👉@artificialintelligenceee) for everything latest from the AI world. Media: Morgan Stanley

This is what a PC should look like!” – Jensen Huang unveils Nvidia’s AI-driven powerhouse at GTC! With 20 petaflops, 72 CPU cores, HBM memory, and PCIe slots, the future of computing is here. What are your thoughts on this AI revolution? Drop a comment! 👇 FOLLOW @activeprogrammer to learn something new every day! #nvidia #aihardware #technews #futureofcomputing #gtc Media: NVIDIA

Nvidia just launched PersonaPlex 7B, the first open-source AI that can have full two-way conversations.

NVIDIA CEO Jensen Huang recently explained AI as a full stack of layers that all depend on each other, not just models or chatbots at the top. He said AI starts with energy and physical infrastructure. Power, data centers, networks, and cooling come first. Above that are chips like GPUs that handle the heavy computation. Then comes the infrastructure and software layer that lets thousands of chips work together at scale. Only after that do you get AI models, and finally the applications people actually use. Huang also brought up China. He warned that China can build infrastructure far faster than the US, using examples like factories and large projects completed in record time. AI leadership is not only about smarter models but about how quickly countries can build the lower layers. AI is an infrastructure race. If the base layers move faster, everything above them moves faster too. What are your thoughts on this? 🤔💬 🎥: Center for Strategic & International Studies — ➡️ If you want to keep up with all the AI news, useful tips, and important developments, join 80k+ subscribers reading our free newsletter