NVIDIA founder and CEO Jensen Huang kicked off CES 2025 with a 90-minute keynote that included new products to advance gaming, autonomous vehicles, robotics and agentic AI.
AI is advancing at an ‘incredible pace,’ Huang told an audience of over 6,000 at CES 2025 in Las Vegas.
“It started with perception AI — understanding images, words and sounds. Then generative AI — creating text, images and sound,” Huang said. Now, we’re entering the era of “physical AI, AI that can proceed, reason, plan and act.”
NVIDIA GPUs and platforms are at the heart of this transformation, Huang explained, enabling breakthroughs across industries, including gaming, robotics and autonomous vehicles (AVs).
Key Announcements
Huang’s keynote showcased how NVIDIA’s latest innovations are enabling this new era of AI, with several groundbreaking announcements, including:
The
just-announced NVIDIA Cosmos platform
advances physical AI with new models and video data processing pipelines for robots, autonomous vehicles and vision AI.
New
NVIDIA Blackwell-based GeForce RTX 50 Series GPUs
offer stunning visual realism and unprecedented performance boosts.
AI foundation models introduced at CES for RTX PCs
feature NVIDIA NIM microservices and AI Blueprints for crafting digital humans, podcasts, images and videos.
The
new NVIDIA Project DIGITS
brings the power of NVIDIA Grace Blackwell to developer desktops in a compact package.
NVIDIA is partnering with Toyota
for safe next-gen vehicle development using the NVIDIA DRIVE AGX in-vehicle computer running NVIDIA DriveOS.
Huang started off his talk by reflecting on NVIDIA’s three-decade journey. In 1999, NVIDIA invented the programmable GPU. Since then, modern AI has fundamentally changed how computing works, he said. “Every single layer of the technology stack has been transformed, an incredible transformation, in just 12 years.”
Revolutionizing Graphics With GeForce RTX 50 Series
“GeForce enabled AI to reach the masses, and now AI is coming home to GeForce,” Huang said.
With that, he introduced
the NVIDIA GeForce RTX 5090 GPU
, the most powerful GeForce RTX GPU so far, with 92 billion transistors and delivering 3,352 trillion AI operations per second (TOPS).
“Here it is — our brand-new GeForce RTX 50 series, Blackwell architecture,” Huang said, holding the blacked-out GPU aloft and noting how it’s able to harness advanced AI to enable breakthrough graphics. “The GPU is just a beast.”
“Even the mechanical design is a miracle,” Huang said, noting that the graphics card has two cooling fans.
More variations in the GPU series are coming. The GeForce RTX 5090 and GeForce RTX 5080 desktop GPUs are scheduled to be available Jan. 30. The GeForce RTX 5070 Ti and the GeForce RTX 5070 desktops are slated to be available starting in February. Laptop GPUs are expected in March.
DLSS 4 introduces
Multi Frame Generation, working in unison with the complete suite of DLSS technologies to boost performance by up to 8x.
NVIDIA also unveiled NVIDIA Reflex 2
, which can reduce PC latency by up to 75%.
The latest generation of DLSS can generate three additional frames for every frame we calculate, Huang explained. “As a result, we’re able to render at incredibly high performance, because AI does a lot less computation.”
RTX Neural Shaders
use small neural networks to improve textures, materials and lighting in real-time gameplay. RTX Neural Faces and RTX Hair advance real-time face and hair rendering, using generative AI to animate the most realistic digital characters ever. RTX Mega Geometry increases the number of ray-traced triangles by up to 100x, providing more detail.
Advancing Physical AI With Cosmos
In addition to advancements in graphics, Huang introduced the
NVIDIA Cosmos
world foundation model platform, describing it as a game-changer for robotics and industrial AI.
The next frontier of AI is physical AI, Huang explained. He likened this moment to the transformative impact of large language models on generative AI.
“The ChatGPT moment for general robotics is just around the corner,” he explained.
World foundation models, like large language models, are essential for advancing robots and AVs, but many developers lack the resources or expertise to train these models from scratch, Huang explained.
Cosmos integrates generative models, tokenizers, and a video processing pipeline to power physical AI systems like AVs and robots.
Cosmos equips AI models with advanced simulation capabilities, enabling them to predict and evaluate multiple future scenarios to select the best course of action.
Cosmos models process text, image and video prompts to create detailed virtual environments tailored for robotics and AV simulations.
Leading robotics and automotive companies, including
1X, Agile Robots, Agility, Figure AI, Foretellix, Fourier,
Galbot
,
Hillbot
,
IntBot
,
Neura Robotics
, Skild AI, Virtual Incision, Waabi and XPENG, along with ridesharing giant Uber, are among the first to adopt Cosmos.
Cosmos is open license and available on GitHub.
Empowering Developers With AI Foundation Models
Beyond robotics and autonomous vehicles, NVIDIA is empowering developers and creators with AI foundation models.
Huang introduced AI foundation models for RTX PCs
that supercharge digital humans, content creation, productivity and development.
“These AI models run in every single cloud because NVIDIA GPUs are now available in every single cloud,” Huang said. “It’s available in every single OEM, so you could literally take these models, integrate them into your software packages, create AI agents and deploy them wherever the customers want to run the software.”
Accelerated by GeForce RTX 50 Series GPUs
These models — offered as
NVIDIA NIM
microservices — are accelerated by the new
GeForce RTX 50 Series GPUs
.
The GPUs are designed to run these models efficiently, with support for FP4 computing that boosts AI inference performance by up to 2x while reducing memory usage compared to previous-generation hardware.
Huang explained the potential of new tools for creators: “We’re creating a whole bunch of blueprints that our ecosystem could take advantage of. All of this is completely open source, so you could take it and modify the blueprints.”
Top PC manufacturers and system builders are launching NIM-ready RTX AI PCs with GeForce RTX 50 Series GPUs. “AI PCs are coming to a home near you,” Huang said.
While these tools bring AI capabilities to personal computing, NVIDIA is also advancing AI-driven solutions in the automotive industry, where safety and intelligence are paramount.
Innovations in Autonomous Vehicles
Huang announced the
NVIDIA DRIVE Hyperion AV platform
, built on the new NVIDIA AGX Thor system-on-a-chip (SoC), designed for generative AI models and delivering advanced functional safety and autonomous driving capabilities.
“The autonomous vehicle revolution is here,” Huang said. “Building autonomous vehicles, like all robots, requires three computers: NVIDIA DGX to train AI models, Omniverse to test drive and generate synthetic data, and DRIVE AGX, a supercomputer in the car.”
DRIVE Hyperion, the first end-to-end AV platform, combines advanced SoCs, sensors, and safety systems into a comprehensive suite, already adopted by automotive leaders such as Mercedes-Benz, JLR and Volvo Cars.
Huang highlighted the critical role of synthetic data in advancing autonomous vehicles. Real-world data is limited, so synthetic data is essential for training the autonomous vehicle data factory, he explained.
NVIDIA Omniverse AI models and Cosmos to Build Detailed Driving Scenarios
Using NVIDIA Omniverse AI models and Cosmos, this approach creates highly detailed driving scenarios that significantly expand and improve training datasets for autonomous vehicles.
Using Omniverse and Cosmos, NVIDIA’s AI data factory can scale “hundreds of drives into billions of effective miles,” Huang said, dramatically increasing the datasets needed for safe and advanced autonomous driving.
“We are going to have mountains of training data for autonomous vehicles,” he added.
Toyota, the world’s largest automaker, will build its next-generation vehicles on the NVIDIA DRIVE AGX Orin
, running the safety-certified NVIDIA DriveOS operating system, Huang said.
“Just as computer graphics was revolutionized at such an incredible pace, you’re going to see the pace of AV development increasing tremendously over the next several years,” Huang said. These vehicles will offer functionally safe, advanced driving assistance capabilities.
Agentic AI and Digital Manufacturing
NVIDIA and its partners have launched AI
Blueprints for agentic AI
, including PDF-to-podcast for efficient research and video search and summarization for analyzing large quantities of video and images — enabling developers to build, test and run AI agents anywhere.
AI Blueprints enable developers to create custom agents for automating enterprise workflows. This new offering integrates NVIDIA AI Enterprise software, including NIM microservices and NeMo, with leading platforms like CrewAI, Daily, LangChain, LlamaIndex and Weights & Biases.
Huang also unveiled Llama Nemotron, a new tool designed to enhance the development of generative AI models for enterprise applications.
Developers can use NVIDIA NIM microservices to build AI agents for tasks like customer support, fraud detection and supply chain optimization.
Available as NVIDIA NIM microservices, the models can supercharge AI agents on any accelerated system.
NVIDIA NIM microservices streamline video content management, boosting efficiency and audience engagement in the media industry.
Moving beyond digital applications, NVIDIA’s innovations are paving the way for AI to revolutionize the physical world with robotics.
“All of the enabling technologies that I’ve been talking about are going to make it possible for us in the next several years to see very rapid breakthroughs, surprising breakthroughs, in general robotics.”
NVIDIA Isaac GR00T Blueprint for Synthetic Motion Generation
In manufacturing, the
NVIDIA Isaac GR00T Blueprint
for synthetic motion generation will help developers generate exponentially large synthetic motion data to train their humanoids using imitation learning.
Huang emphasized the importance of training robots efficiently, using NVIDIA Omniverse to generate millions of synthetic motions for humanoid training.
The Mega blueprint powers large-scale simulations of robot fleets, enabling companies like Accenture and KION to revolutionize warehouse automation.
These AI tools set the stage for NVIDIA’s latest innovation: a personal AI supercomputer called Project DIGITS.
NVIDIA Unveils Project DIGITS
Putting NVIDIA Grace Blackwell on every desk and at every AI developer’s fingertips, Huang unveiled
NVIDIA Project DIGITS
.
“I have one more thing that I want to show you,” Huang said. “None of this would be possible if not for this incredible project that we started about a decade ago. Inside the company, it was called Project DIGITS — deep learning GPU intelligence training system.”
Huang highlighted the legacy of NVIDIA’s AI supercomputing journey, telling the story of how in 2016 he delivered the first NVIDIA DGX system to OpenAI. “And obviously, it revolutionized artificial intelligence computing.”
The new Project DIGITS takes this mission further. “Every software engineer, every engineer, every creative artist — everybody who uses computers today as a tool — will need an AI supercomputer,” Huang said.
Huang revealed that Project DIGITS, powered by the GB10 Grace Blackwell Superchip, represents NVIDIA’s smallest yet most powerful AI supercomputer. “This is NVIDIA’s latest AI supercomputer,” Huang said, showcasing the device. “It runs the entire NVIDIA AI stack — all of NVIDIA software runs on this. DGX Cloud runs on this.”
Project DIGITS, NVIDIA’s smallest and most powerful AI supercomputer, will launch in May.
A Year of Breakthroughs
“It’s been an incredible year,” Huang said as he wrapped up the keynote. Huang highlighted NVIDIA’s major achievements: Blackwell systems, physical AI foundation models, and breakthroughs in agentic AI and robotics.
“I want to thank all of you for your partnership,” Huang said.
See
notice
regarding software product information.
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Transportation
NVIDIA 創辦人暨執行長黃仁勳以長達 90 分鐘的主題演講揭開 2025 年 CES 大會的序幕，在這場精彩的演講中提到了包括推動遊戲、自駕車、機器人及代理型 AI 發展的嶄新產品。
他在拉斯維加斯的 Michelob Ultra 體育館對著超過六千名座無虛席的觀眾們說，AI「以驚人的速度進步。」
「我們從理解影像、文字和聲音的感知 AI 開始。接著是創造文字、影像和聲音的生成式 AI。」黃仁勳說。現在，我們正進入「實體 AI」時代，也就是能夠進行、推理、計畫與行動的 AI。
黃仁勳解釋說 NVIDIA 的 GPU 及平台是促進這項轉變的核心，帶動包括遊戲、機器人和自駕車在內各行各業突破性的進展。
黃仁勳在主題演講中展示了 NVIDIA 最新的創新技術如何開啟 AI 的新時代，並且發表了多項突破性的內容，包括：
剛剛發表的 NVIDIA Cosmos 平台
可為機器人、自駕車和視覺 AI 領域帶來全新模型和影片資料處理管道，推動實體 AI 的發展。
全新
NVIDIA Blackwell 架構 GeForce RTX 50 系列 GPU
能夠創作出驚人逼真度的視覺影像效果，又能將運算效能提升到前所未有的程度。
在 CES 大會推出適用於 RTX PC 的 AI 基礎模型
，具有 NVIDIA NIM 微服務與 AI Blueprints，可用於製作數位人類、podcast、圖片與影片。
全新 NVIDIA Project DIGITS
將 NVIDIA Grace Blackwell 的強大功能帶到開發人員的桌面上，而它小巧的身影幾乎可以放進口袋裡。
NVIDIA 攜手豐田（Toyota）汽車
使用運行 NVIDIA DriveOS 的 NVIDIA DRIVE AGX 車載電腦，合作開發安全的新世代車輛。
黃仁動在這場演講一開始，先是回顧 NVIDIA 三十年來的發展歷程。1999 年，NVIDIA 發明了可編程 GPU。黃仁勳說從那時開始，現代 AI 從根本上改變了運算的運作方式。「在短短 12 年間，技術堆疊的每一層都發生了翻天覆地的變化，這是令人難以置信的轉變。」
GeForce RTX 50
系列帶來繪圖技術革命
「GeForce 讓 AI 得以普及到大眾的手中，現在 AI 也回歸到GeForce。」黃仁勳說。
他以此為引向嘉賓們介紹
NVIDIA GeForce RTX 5090 GPU
，這是迄今為止最強大的 GeForce RTX GPU，擁有 920 億個電晶體，每秒可進行 3,352 兆次 AI 運算（TOPS）。
「這就是我們全新的 GeForce RTX 50 系列，Blackwell 架構。」黃仁勳高舉著一塊黑色的 GPU，指出它如何能夠利用先進的 AI 來創造出突破性的繪圖技術。「這顆 GPU 簡直就是一隻野獸。」
「即使是它的機械設計也是奇蹟。」黃仁勳指出顯示卡上有兩個冷卻風扇。
這個 GPU 系列的更多產品即將現身。GeForce RTX 5090 和 GeForce RTX 5080 桌上型 GPU 預定於 1 月 30 日上市。GeForce RTX 5070 Ti 和 GeForce RTX 5070 桌上型 GPU 預計於二月開始上市。筆記型電腦 GPU 預計將於三月上市。
DLSS 4 引入
多畫格生成（Multi Frame Generation）技術，搭配整套 DLSS 技術可以將效能提升八倍。
NVIDIA 還發表了 NVIDIA Reflex 2
，可以將 PC 延遲時間降低 75%。
黃仁勳解釋說最新一代的 DLSS 技術可以為我們計算出的每一個畫格另外產生三個畫格。「由於 AI 要運算的量少了很多，這樣我們就能能夠得到超高的渲染效能。」
RTX Neural Shaders
使用小型神經網路即時改善遊戲裡的紋理、材質與照明。RTX Neural Faces 和 RTX Hair 能夠即時渲染臉部和毛髮，使用生成式 AI 製作史上最有真實感的數位角色動畫。RTX Mega Geometry 可以將光線追蹤三角形的數量增加 100 倍，製作出更精細的畫面。
利用
Cosmos
推動實體
AI
的發展
除了繪圖技術方面的進展之外，黃仁勳還介紹
NVIDIA Cosmos
世界基礎模型平台，指稱其為改變機器人與工業 AI 領域發展遊戲規則的一項技術。
黃仁勳說實體 AI 是 AI 的下一個發展領域。他將這個時刻比喻為大型語言模型對於生成式 AI 所帶來的變革性影響。
他說：「通用機器人的 ChatGPT 時刻就要到來。」
黃仁勳說與大型語言模型一樣，世界基礎模型是推動開發機器人與自駕車的根本，不過並非所有開發人員都有專業知識與資源來訓練自己的模型。
Cosmos 整合了生成模型、標記器和影片處理管道，協助開發自駕車和機器人等實體 AI 系統。
開發 Cosmos 的目的在於將前瞻性與多元宇宙模擬的力量帶入 AI 模型上，讓模型能夠模擬各種可能的未來與選擇最佳行動。
黃仁勳解釋道 Cosmos 模型可以接收文字、圖像或影片提示，並且以影片方式產生虛擬世界狀態。「Cosmos優先處理自駕車和機器人的獨特需求，例如真實世界環境、照明和物體恆存性。」
包括 1X、思靈機器人（Agile Robots）、Agility、Figure AI、Foretellix、Fourier、
Galbot
、
Hillbot
、
IntBot
、
Neura Robotics
、Skild AI、Virtual Incision、Waabi 和小鵬汽車（XPENG）在內的
各大機器人和汽車公司
，以及乘車服務巨擘 Uber，皆為首批採用 Cosmos 的公司。
此外，現代汽車集團（Hyundai Motor Group）也採用 NVIDIA AI 與 Omniverse
，以打造更安全、更聰明的車輛，擁有更強大的製造能力及部署最先進的機器人技術。
可以在 GitHub 上取得採用開放授權形態的 Cosmos。
推出
AI
基礎模型強化開發人員的能力
除了機器人與自駕車，NVIDIA 還推出 AI 基礎模型強化開發人員與創作者的能力。
黃仁勳在演講中介紹了適用於 RTX PC 的 AI 基礎模型
，用於支援開發數位人類、內容創作、提高生產力及輔助各項開發作業。
黃仁勳表示：「現在可以在每一個雲端環境裡使用 NVIDIA GPU，各位便能在每一個雲端環境裡運行這些 AI 模型。每一家 OEM 都可以拿到這些模型，所以各位都能用到，把它們整合到你們的軟體套件裡，建立 AI 代理，然後部署到任何客戶想要執行軟體的地方。」
這些以
NVIDIA NIM
微服務形式提供的模型，由全新的
GeForce RTX 50 系列 GPU
加速。
這些 GPU 有快速執行這些模型的能力，加上支援 FP4 運算，將 AI 推論能力提高兩倍，與前一代硬體相比，能夠用更小的記憶體佔用空間在本機端運行生成式 AI 模型。
黃仁勳解釋創作者可以怎麼利用這些新工具：「我們正在創作一大堆藍圖，讓我們的生態系統可以善加利用。這一切都是完全開源的形態，各位可以自行取用和修改藍圖。」
頂級 PC 製造商和系統建置商將推出搭載 GeForce RTX 50 系列 GPU 的 NIM-ready RTX AI PC。「AI PC 即將進入各位附近的家中。」黃仁勳說。
﻿
在這些工具為 PC 帶來 AI 功能的同時，NVIDIA 也在首重安全與智慧的汽車業推動開發 AI 驅動的解決方案。
自駕車技術創新
黃仁勳發表採用全新 NVIDIA AGX Thor 系統單晶片（SoC）所開發出、專為生成式 AI 模型設計的
NVIDIA DRIVE Hyperion AV 平台
，可提供先進的功能安全與自動駕駛功能。
黃仁勳表示：「自駕車革命已經來臨。就像所有機器人一樣，打造自駕車需要用到三台電腦：用於訓練 AI 模型的 NVIDIA DGX，用於測試駕駛和產生合成資料的 Omniverse，而 DRIVE AGX 則是車內的超級電腦。」
DRIVE Hyperion 是第一個端對端的自駕車平台，整合了適用於下一代汽車的先進 SoC、感測器和安全系統，還有感測器套件與主動安全和 level 2 駕駛堆疊， Mercedes-Benz、捷豹路虎和 Volvo Cars 等引領發展行車安全功能的業者已經採用這個平台。
黃仁勳強調合成資料在推動開發自駕車方面所扮演的重要角色。他解釋說，從現實世界只能得到有限的資料，必須使用合成資料來訓練自駕車輛資料工廠。
在 NVIDIA Omniverse AI 模型和 Cosmos 的驅動下，這種方法可以「產生合成駕駛情境，以成倍方式強化訓練資料。」
黃仁勳表示使用 Omniverse 和 Cosmos，NVIDIA 的 AI 資料工廠可以將「數百次的駕駛擴展為數十億英哩的有效里程」，大幅增加發展安全先進自動駕駛技術所需的資料集。
「我們將為自駕車提供大量訓練資料。」他補充道。
黃仁勳表示
全球最大的汽車製造商豐田汽車將使用 NVIDIA DRIVE AGX Orin 開發下一代汽車
，並且運行通過安全認證的 NVIDIA DriveOS 作業系統。
黃仁勳說：「正如電腦繪圖技術以飛快速度掀起革命，各位在未來幾年內將會看到自駕車的發展速度大幅提升」。這些車輛將提供功能安全又先進的駕駛輔助功能。
代理型
AI
與數位製造
NVIDIA 及其合作夥伴推出
適用於代理式 AI 的 AI Blueprints
，包括用於提高研究效率的 PDF-to-podcast，以及用於分析大量影片與圖像的影片搜尋與摘要 – 這些藍圖都讓開發人員能夠隨時隨地建立、測試和運行 AI 代理。
開發人員可以使用 AI Blueprints 部署客製化代理，自動執行企業裡的工作流程。這一類全新的合作夥伴藍圖整合了 NVIDIA AI Enterprise 軟體，包括 NVIDIA NIM 微服務和 NVIDIA NeMo，以及 CrewAI、Daily、LangChain、LlamaIndex 和 Weights & Biases 等領先供應商的平台。
黃仁勳還宣布推出全新的
Llama Nemotron
。
開發人員可以使用 NVIDIA NIM 微服務建立 AI 代理，以執行客戶支援、詐欺偵測及供應鏈最佳化等工作。
以 NVIDIA NIM 微服務的形式提供這些模型，可以在任何加速系統上增強 AI 代理的效能。
NVIDIA NIM 微服務可以協助媒體業簡化影片內容管理，提升工作效率及觀眾參與度。
除了數位應用，NVIDIA 的創新技術也為 AI 透過機器人來徹底改變實體世界一事打下基礎。
「我一直在講的的這些技術，都會讓我們在未來幾年裡，在通用機器人領域看到非常快速又令人驚訝的突破。」
適用於產生合成動作的
NVIDIA Isaac GR00T Blueprint
將幫助開發人員產生海量合成動作資料，利用模仿學習來訓練製造業所使用的人形機器人。
黃仁勳強調高效率訓練機器人的重要性，利用 NVIDIA 的 Omniverse 平台產生數百萬個合成動作來訓練人形機器人。
Mega 藍圖能夠進行大規模模擬機器人機群，埃森哲（Accenture）及凱傲（KION）等倉儲自動化領導業者已經採用這項藍圖。
這些 AI 工具為 NVIDIA 的最新創新技術奠定基礎：名為 Project DIGITS 的個人 AI 超級電腦。
NVIDIA
推出
Project DIGITS
黃仁勳發表
NVIDIA Project DIGITS
，將 NVIDIA Grace Blackwell 放在每個人的桌上，讓每個 AI 開發人員輕鬆就能獲得 AI 的強大運算能力。
「我還有一個東西要給你們看。如果我們不是大概十年前就展開這麼厲害的專案，這一切都不可能發生。我們在 NVIDIA 裡把它取了 Project DIGITS 這個名字 – 深度學習 GPU 智慧訓練系統。」黃仁勳說。
黃仁勳強調 NVIDIA 在 AI 超級運算之路上的建樹，講述他在 2016 年將第一套 NVIDIA DGX 系統交給 OpenAI 使用的故事。「顯然，它徹底改變了 AI 運算。」
新的 Project DIGITS 又更進一步推動這個使命。「每個軟體工程師、每個工程師、每個創意藝術家 – 每個今天把電腦當成工具來使用的人 – 都會需要一台 AI 超級電腦。」黃仁勳說。
黃仁勳說 Project DIGITS 搭載 GB10 Grace Blackwell 超級晶片，是 NVIDIA 體積最小、功能卻最強大的 AI 超級電腦。「這是 NVIDIA 最新的 AI 超級電腦。」黃仁勳在展示它的時候這麼表示。「它可以運行整個 NVIDIA AI 堆疊 – 所有 NVIDIA 軟體都可以在上面運行。DGX Cloud 便是在這個上面運行。」
外型小巧卻功能強大的 Project DIGITS 預計將於五月上市。
突破的一年
「這是令人難以置信的一年。」黃仁勳在結束這場主題演講時表示。黃仁勳強調 NVIDIA 的主要成就： Blackwell 系統、實體 AI 基礎模型，以及在代理型 AI 和機器人方面的突破。
「我要感謝大家的合作。」黃仁勳說。
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