Workflow
NVIDIA
icon
Search documents
AI Agents Unlocked: CACEIS Redefines Client Conversations With VAST Data and NVIDIA
NVIDIA· 2025-06-12 18:34
AI应用与客户服务 - CASE 作为欧洲领先的资产服务公司,利用 AI Agent 捕捉客户交流的真实含义 [1] - 传统 AI 转录遗漏了超过 60% 的客户会议关键信息 [2] - AI Agent 使用 Nemo Retriever 从多模态数据源提取上下文,并利用 Llama Neatron 创建包含完整细节和个人信息修订后的两个版本 [2] - 客户关系 Agent 可以检测情绪、分析异议并触发后续行动,以帮助领导者进行指导 [3] - 产品分析 Agent 使用修订后的数据和人口统计信息来识别 VIP 功能请求并生成 Jira 工单 [3] 技术与合作 - CASE 与 Vast Data 和 Nvidia 合作构建 AI Agent [1] - 借助 NVIDIA Nemo 数据飞轮和 Vast AI 操作系统,Agent 可以不断学习和改进 [4] - VAST 和 NVIDIA 帮助企业为每位员工构建定制 AI Agent [4] 数据处理与安全 - AI Agent 在使用数据的同时,保护访问控制 [3] - AI Agent 可以处理完整细节和个人信息修订后的数据,满足不同角色的需求 [2][3]
Robotic Surgery with Moon Surgical and NVIDIA Physical AI
NVIDIA· 2025-06-11 20:22
I'm Anna Zoa. I'm the CEO at Moon Surgical and I do this job because I'm passionate about bringing new technologies to patients. So, we believe and I think everyone believes that the future is robotic in the sense that there's going to be a continuum of solutions that enhance surgery and turn it into something that is robotic and digital.Partnering closely with NVIDIA is about two things, acceleration and then just sheer feasibility. So the maestro concept which we um uncovered in the lab with professor Gay ...
Meet the Featured Startups at GTC Taipei 2025
NVIDIA· 2025-06-11 17:51
Overview of Nvidia's GDC 2025 - Nvidia is driving breakthroughs across industries with accelerated computing, addressing challenges beyond the capabilities of normal computers [1] - Nvidia's Inception program supports AI startups by providing technical training, VC network access, and product pricing benefits [6] AI Startup Innovations - Nayam Biologics uses genomics, chemistry, and AI to develop therapeutics for cancer, cardiovascular conditions, metabolic disorders, and neurodegenerative diseases [2] - Nayam Biologics' drug discovery platform accelerates traditional timelines by 80% using ambidia rabbits, cuda, bioimmo, and tensorati to screen millions of natural compounds [3] - No X enables designers and manufacturers to generate digital twins of fabrics, accelerating development and streamlining supply chains [4] - Paul innovation developed a collision warning system for Gausong light rail, using camera data and sensors for 3D object tracking [4] - AI robot's Ellis 4 model uses Nvidia Jetson Orin NX to reduce energy requirements and proprietary linear actuators to reduce robot manufacturing costs [5] - ERICO's platform uses jetpack with replicator and tensor RT to automate recycling facilities, decreasing sorting costs and maximizing the value of recovered materials [6] Impact and Future Directions - AI technology is poised to provide critical services in manufacturing, healthcare, and logistics [5] - Nvidia aims to push the frontiers of AI and create solutions that will shape the future of technology and society [7] - ERICO's platform helps countries reach recycling goals set by global sustainability initiatives, contributing to the circular economy [6]
NVIDIA Research Breakthroughs at CVPR 2025
NVIDIA· 2025-06-11 17:41
See what’s new from NVIDIA Research at CVPR 2025 in Nashville! NVIDIA leads the way in physical AI, winning the End-to-End Autonomous Driving Challenge for the second year in a row – and is the only company to win a CVPR challenge for three consecutive years. With more than 60 accepted papers, our research spans automotive, healthcare, robotics and more. In automotive, NVIDIA researchers are advancing physical AI with innovations in perception, planning and data generation. This year, three NVIDIA papers we ...
Accelerating Clinical Research and Commercialization with AI Agents
NVIDIA· 2025-06-11 14:22
[Music] Bringing a life-saving drug to market requires analyzing massive amounts of complex data. The pharmaceutical industry needs a faster, more automated way to extract meaning and act on it. Ivia is using Agentic AI to do exactly that.Training AI agents to navigate more than a million data streams for clinical, medical, and commercial professionals. Its healthcare grade AI platform combines a growing set of AI agents, each designed to streamline how insights turn into action. Built with NVIDIA Neotron m ...
Building the Blackwell NVL72: Millions of Parts, One AI Superchip
NVIDIA· 2025-06-11 14:18
Blackwell B200 Super Chip Manufacturing - Blackwell B200 超级芯片由 12 英寸晶圆上的 2000 亿个晶体管构建而成 [1] - 每个晶圆被划分为单独的 Blackwell 芯片,经过测试和分类,将好的芯片分离出来 [2] - 32 个 Blackwell 芯片和 128 个 HBM 堆栈通过芯片基板工艺连接到定制的硅中介层晶圆上 [2] - 组装完成后,经过烘烤、模塑和固化,形成 Blackwell B200 超级芯片,并在 125° 的烤箱中进行压力测试 [3] - Grace Blackwell PCB 上通过机器人昼夜不停地放置超过 10,000 个组件 [3] Interconnect and Communication - MVLink 开创性高速链路,可连接多个 GPU 并扩展为大型虚拟 GPU [5] - MVLink 交换机托盘由 MVLink 交换机芯片构建,提供每秒 14.4 万亿字节的全互连带宽 [5] - MVLink 主干形成定制的盲插背板,通过 5,000 根铜缆连接所有 72 个 Blackwell 或 144 个 GPU 芯片,形成一个巨大的 GPU,提供每秒 130 万亿字节的全互连带宽 [5] - Connect X7 Super Nix 用于实现横向扩展通信,Bluefield 3 DPU 用于卸载和加速网络、存储和安全任务 [4] System Integration and Scale - 总计 120 万个组件、200 万米铜缆和 130 万亿个晶体管,总重量接近 2 吨 [5] - 定制的液冷铜块用于将芯片保持在最佳温度 [4] - 所有部件集成到 GB200 计算托盘中,最终组装成机架规模的 AI 超级计算机 [4][5] Vision - Blackwell 不仅仅是一项技术奇迹,更是全球协作和创新的力量的证明,推动着塑造我们未来各地的发现和解决方案 [6]
Intelligence is Manufactured With Tokens | GTC Paris at VivaTech 2025 | Official Keynote Intro
NVIDIA· 2025-06-11 14:16
This is how intelligence is made. A new kind of factory, generator of tokens, the building blocks of AI. tokens have opened a new frontier.The first step into an extraordinary world where endless possibilities are born. Tokens transform images into scientific data, charting alien atmospheres and guiding the explorers of tomorrow. They probe the earth's depths to seek out hidden danger.They turn potential into plenty [Music] and help us harvest our bounty. Tokens see disease before it takes hold. Cure with p ...
AI-Native Wireless Network in Action with NVIDIA AI Aerial
NVIDIA· 2025-06-11 14:09
AI Native Wireless Networks Overview - NVIDIA AI Aerial is revolutionizing wireless systems by enabling neural networks to learn from data, adapt in real-time, and scale with complexity [1] - This approach boosts spectral efficiency, lowers costs, and improves connectivity in wireless networks [1] Key Steps & Technologies - Building AI native wireless networks involves three key steps: training, simulation, and deployment, all unified by NVIDIA AI Aerial [2] - NVIDIA uses Shauna and Aerial radio frameworks to train neural network models, replacing traditional 5G channel estimation algorithms [2] - The trained model is deployed on a live 5G network at NVIDIA using Aerial RAN computer [3] - NVIDIA provides the Shona research kit on NVIDIA Jetson, enabling developers to create a working AI model in a live 5G network with minimal code [5] Performance & Results - AI implementation nearly doubles the cell throughput [3] - AI achieves 100% higher throughput on a live 5G network [4] - The AI model continuously improves over time through a feedback loop between the physical and virtual worlds [4] Future Implications - Improved AI models will boost capacity, unlock new applications, increase efficiency, and extend coverage [5] - NVIDIA encourages participation in the 6G developer program to accelerate AI native wireless research [5]
From Prompt to Paris: How AI Agents Launch a Food Truck Dream
NVIDIA· 2025-06-11 13:11
AI agents are digital assistants based on a prompt. They reason through and break down problems into multi-step plans. They use the proper tools, work with other agents, and use context from memory to properly execute the job on NVIDIA accelerated systems.It starts with a simple prompt. Let's ask Perplexity to help start a food truck in Paris. First, the perplexity agent reasons through the prompt and forms a plan.Then calls other agents to help tackle each step using many tools. The market researcher reads ...
NVIDIA DGX Cloud Lepton: Connecting Developers to Global Accelerated Compute
NVIDIA· 2025-06-11 13:11
Developers need easy and reliable access to compute that keeps up with their work wherever they are, whatever they're building. DJX Cloud Leptin provides ondemand access to a global network of GPUs across clouds, regions, and partners like Yoda and Nebus. Multicloud GPU clusters are managed through a single unified interface.Provisioning is fast. Developers can scale up the number of nodes quickly without complex setups and start training right away with pre-integrated tools and training ready infrastructur ...