#NvidiaAI

[govindhtech]

NVIDIA AI Blueprints For Build Visual AI Data In Any Sector

NVIDIA AI Blueprints

Businesses and government agencies worldwide are creating AI agents to improve the skills of workers who depend on visual data from an increasing number of devices, such as cameras, Internet of Things sensors, and automobiles.

Developers in almost any industry will be able to create visual AI agents that analyze image and video information with the help of a new NVIDIA AI Blueprints for video search and summarization. These agents are able to provide summaries, respond to customer inquiries, and activate alerts for particular situations.

The blueprint is a configurable workflow that integrates NVIDIA computer vision and generative AI technologies and is a component of NVIDIA Metropolis, a suite of developer tools for creating vision AI applications.

The NVIDIA AI Blueprints for visual search and summarization is being brought to businesses and cities around the world by global systems integrators and technology solutions providers like Accenture, Dell Technologies, and Lenovo. This is launching the next wave of AI applications that can be used to increase productivity and safety in factories, warehouses, shops, airports, traffic intersections, and more.

The NVIDIA AI Blueprint, which was unveiled prior to the Smart City Expo World Congress, provides visual computing developers with a comprehensive set of optimized tools for creating and implementing generative AI-powered agents that are capable of consuming and comprehending enormous amounts of data archives or live video feeds.

Deploying virtual assistants across sectors and smart city applications is made easier by the fact that users can modify these visual AI agents using natural language prompts rather than strict software code.

NVIDIA AI Blueprint Harnesses Vision Language Models

Vision language models (VLMs), a subclass of generative AI models, enable visual AI agents to perceive the physical world and carry out reasoning tasks by fusing language comprehension and computer vision.

NVIDIA NIM microservices for VLMs like NVIDIA VILA, LLMs like Meta’s Llama 3.1 405B, and AI models for GPU-accelerated question answering and context-aware retrieval-augmented generation may all be used to configure the NVIDIA AI Blueprint for video search and summarization. The NVIDIA NeMo platform makes it simple for developers to modify other VLMs, LLMs, and graph databases to suit their particular use cases and settings.

By using the NVIDIA AI Blueprints, developers may be able to avoid spending months researching and refining generative AI models for use in smart city applications. It can significantly speed up the process of searching through video archives to find important moments when installed on NVIDIA GPUs at the edge, on-site, or in the cloud.

An AI agent developed using this methodology could notify employees in a warehouse setting if safety procedures are broken. An AI bot could detect traffic accidents at busy crossroads and provide reports to support emergency response activities. Additionally, to promote preventative maintenance in the realm of public infrastructure, maintenance personnel could request AI agents to analyze overhead imagery and spot deteriorating roads, train tracks, or bridges.

In addition to smart places, visual AI agents could be used to automatically create video summaries for visually impaired individuals, classify large visual datasets for training other AI models, and summarize videos for those with visual impairments.

The workflow for video search and summarization is part of a set of NVIDIA AI blueprints that facilitate the creation of digital avatars driven by AI, the development of virtual assistants for individualized customer support, and the extraction of enterprise insights from PDF data.

With NVIDIA AI Enterprise, an end-to-end software platform that speeds up data science pipelines and simplifies the development and deployment of generative AI, developers can test and download NVIDIA AI Blueprints for free. These blueprints can then be implemented in production across accelerated data centers and clouds.

AI Agents to Deliver Insights From Warehouses to World Capitals

With the assistance of NVIDIA’s partner ecosystem, enterprise and public sector clients can also utilize the entire library of NVIDIA AI Blueprints.

With its Accenture AI Refinery, which is based on NVIDIA AI Foundry and allows clients to create custom AI models trained on enterprise data, the multinational professional services firm Accenture has integrated NVIDIA AI Blueprints.

For smart city and intelligent transportation applications, global systems integrators in Southeast Asia, such as ITMAX in Malaysia and FPT in Vietnam, are developing AI agents based on the NVIDIA AI Blueprint for video search and summarization.

Using computing, networking, and software from international server manufacturers, developers can also create and implement NVIDIA AI Blueprints on NVIDIA AI systems.

In order to improve current edge AI applications and develop new edge AI-enabled capabilities, Dell will combine VLM and agent techniques with its NativeEdge platform. VLM capabilities in specialized AI workflows for data center, edge, and on-premises multimodal corporate use cases will be supported by the NVIDIA AI Blueprint for video search and summarization and the Dell Reference Designs for the Dell AI Factory with NVIDIA.

Lenovo Hybrid AI solutions powered by NVIDIA also utilize NVIDIA AI blueprints.

The new NVIDIA AI Blueprint will be used by businesses such as K2K, a smart city application supplier in the NVIDIA Metropolis ecosystem, to create AI agents that can evaluate real-time traffic camera data. City officials will be able to inquire about street activities and get suggestions on how to make things better with to this. Additionally, the company is utilizing NIM microservices and NVIDIA AI blueprints to deploy visual AI agents in collaboration with city traffic management in Palermo, Italy.

NVIDIA booth at the Smart Cities Expo World Congress, which is being held in Barcelona until November 7, to learn more about the NVIDIA AI Blueprints for video search and summarization.

Read more on Govindhtech.com

[maryjohnfinds]

Intel made a HUGE Mistake… and Nvidia ran Away with ai | Ai Vault

Join us as we explore why two of the biggest tech giants, Intel and Samsung, are struggling to keep up in the AI revolution. Once leaders in the semiconductor industry, both companies have found themselves falling behind in the race for AI supremacy, with competitors like Nvidia and TSMC taking the lead. From missed opportunities to manufacturing delays, we’ll dive deep into the factors that have led to their struggles and what this means for the future of AI hardware.

[baskingamer]

NVIDIA’s G-Assist: Your AI Companion for Peak PC Performance - Baskingamer

Are you tired of spending endless hours tweaking...

readmore

https://baskingamer.com/nvidias-g-assist-your-ai-companion-for-peak-pc-performance/

@NVIDIAGeForce @NVIDIAAI

[ailatestupdate]

Isaac GR00T N1 – NVIDIA's

[nextaitool]

Nvidia’s New AI Steps Into the Spotlight

Nvidia’s new AI model bringing smarter tech and real advantages for everyday businesses.

Nvidia just shook up the AI world with a surprise release. Meet Llama-3.1-Nemotron-70B-Instruct. It’s an AI model that's got everyone buzzing. Why? Because it beats big names like OpenAI's GPT-4.

Nvidia's Unexpected Hit

Nvidia launched this model on Hugging Face on Tuesday. Thing is, they skipped the big fanfare. Yet, it still caught everyone's eye. Why? Simple. It blew existing benchmarks out of the water. Here's the scoop: - Arena Hard benchmark: Scored 85.0 - AlpacaEval 2 LC: Hit 57.6 - GPT-4-Turbo MT-Bench: Achieved 8.98

What's the takeaway? Nvidia's new model is now the leader in language tricks and AI smarts.

Nvidia: From Chips to Code

Nvidia's played a big role in making GPUs—the backbone of AI tech. Now, they’re diving deep into AI software. Before, they were all about the hardware. Now, with Llama-3.1-Nemotron-70B-Instruct, they’ve proven they're serious about AI software too. They took Meta’s Llama 3.1 and made it even better using cool methods like RLHF, which helps the model think more like us humans.

Why It Matters for Businesses

Nvidia wants their AI to align with what users want. This means happier customers. For businesses, that’s a huge plus. It means fewer mistakes and better customer service.

Thinking about trying AI? Check out Nvidia’s model because: - It’s free to test on their build.nvidia.com. - It works with OpenAI APIs.

That means any business can tap into advanced AI tools without breaking the bank.

In short, Nvidia’s new model is worth a look if you’re exploring AI. Just keep its strengths and limits in mind, and you’ll be ahead in the AI game.

For more news like this: thenextaitool.com/news

[agreementpaper]

Contract Management Software for Legal Departments - Agreementpaper

Say goodbye to missed clauses and compliance risks! Agreementpaper offers advanced AI-powered tools for precise document analysis and automated risk assessment. Protect your budget and simplify contract management—let’s get started! Book a demo now.

[luxlaff]

🚀 Nvidia: Leading the AI Revolution 🚀

In the rapidly evolving landscape of technology, Nvidia stands as a titan, driving the future of artificial intelligence (AI) with pioneering chip innovations and computational systems. Their breakthroughs, from the Blackwell and Hopper chips to their unmatched collaborations with tech giants like AWS and Google, are not just technological feats; they are milestones marking the path to a future where AI reshapes our world.

🚀 From Concept to Reality: Nvidia's AI Innovations

Nvidia's journey from enhancing chip performance through crystal fusion to developing AI-driven digital twins and chatbots showcases their commitment to pushing the boundaries of what AI can achieve. The collaboration with industry leaders has led to the integration of AI technologies that are transforming business practices and daily life.

💡 AI for a Better Tomorrow

The practical applications of Nvidia's AI technologies, such as optimizing manufacturing processes and advancing machine learning through projects like General Robotics 003, are testaments to the transformative power of AI. These innovations offer a glimpse into a future where AI not only enhances efficiency but also pioneers new realms of creativity and exploration.

🌍 A Call to Action

As we stand on the brink of this new era, the importance of community and collaboration in AI development has never been clearer. Nvidia's journey underscores the potential of AI to revolutionize industries and improve lives, inviting us all to engage, contribute, and shape the future of technology.

Explore how Nvidia is leading the charge into the AI-driven future and join the conversation on how we can collectively navigate the promises and challenges of this technological revolution. Check out the full story here: Revolutionizing the Future: Nvidia's AI Breakthroughs and Collaborative Innovation.

[insurgentepress]

Tech Mahindra transformará las operaciones de red autónomas con un nuevo modelo de telecomunicaciones basado en @NVIDIAAI e infraestructura de nube de @awscloud.

[govindhtech]

NVIDIA AI Workflows Detect False Credit Card Transactions

A Novel AI Workflow from NVIDIA Identifies False Credit Card Transactions.

The process, which is powered by the NVIDIA AI platform on AWS, may reduce risk and save money for financial services companies.

By 2026, global credit card transaction fraud is predicted to cause $43 billion in damages.

Using rapid data processing and sophisticated algorithms, a new fraud detection NVIDIA AI workflows on Amazon Web Services (AWS) will assist fight this growing pandemic by enhancing AI’s capacity to identify and stop credit card transaction fraud.

In contrast to conventional techniques, the process, which was introduced this week at the Money20/20 fintech conference, helps financial institutions spot minute trends and irregularities in transaction data by analyzing user behavior. This increases accuracy and lowers false positives.

Users may use the NVIDIA AI Enterprise software platform and NVIDIA GPU instances to expedite the transition of their fraud detection operations from conventional computation to accelerated compute.

Companies that use complete machine learning tools and methods may see an estimated 40% increase in the accuracy of fraud detection, which will help them find and stop criminals more quickly and lessen damage.

As a result, top financial institutions like Capital One and American Express have started using AI to develop exclusive solutions that improve client safety and reduce fraud.

With the help of NVIDIA AI, the new NVIDIA workflow speeds up data processing, model training, and inference while showcasing how these elements can be combined into a single, user-friendly software package.

The procedure, which is now geared for credit card transaction fraud, might be modified for use cases including money laundering, account takeover, and new account fraud.

Enhanced Processing for Fraud Identification

It is more crucial than ever for businesses in all sectors, including financial services, to use computational capacity that is economical and energy-efficient as AI models grow in complexity, size, and variety.

Conventional data science pipelines don’t have the compute acceleration needed to process the enormous amounts of data needed to combat fraud in the face of the industry’s continually increasing losses. Payment organizations may be able to save money and time on data processing by using NVIDIA RAPIDS Accelerator for Apache Spark.

Financial institutions are using NVIDIA’s AI and accelerated computing solutions to effectively handle massive datasets and provide real-time AI performance with intricate AI models.

The industry standard for detecting fraud has long been the use of gradient-boosted decision trees, a kind of machine learning technique that uses libraries like XGBoost.

Utilizing the NVIDIA RAPIDS suite of AI libraries, the new NVIDIA AI workflows for fraud detection improves XGBoost by adding graph neural network (GNN) embeddings as extra features to assist lower false positives.

In order to generate and train a model that can be coordinated with the NVIDIA Triton Inference Server and the NVIDIA Morpheus Runtime Core library for real-time inferencing, the GNN embeddings are fed into XGBoost.

All incoming data is safely inspected and categorized by the NVIDIA Morpheus framework, which also flags potentially suspicious behavior and tags it with patterns. The NVIDIA Triton Inference Server optimizes throughput, latency, and utilization while making it easier to infer all kinds of AI model deployments in production.

NVIDIA AI Enterprise provides Morpheus, RAPIDS, and Triton Inference Server.

Leading Financial Services Companies Use AI

AI is assisting in the fight against the growing trend of online or mobile fraud losses, which are being reported by several major financial institutions in North America.

American Express started using artificial intelligence (AI) to combat fraud in 2010. The company uses fraud detection algorithms to track all client transactions worldwide in real time, producing fraud determinations in a matter of milliseconds. American Express improved model accuracy by using a variety of sophisticated algorithms, one of which used the NVIDIA AI platform, therefore strengthening the organization’s capacity to combat fraud.

Large language models and generative AI are used by the European digital bank Bunq to assist in the detection of fraud and money laundering. With NVIDIA accelerated processing, its AI-powered transaction-monitoring system was able to train models at over 100 times quicker rates.

In March, BNY said that it was the first big bank to implement an NVIDIA DGX SuperPOD with DGX H100 systems. This would aid in the development of solutions that enable use cases such as fraud detection.

In order to improve their financial services apps and help protect their clients’ funds, identities, and digital accounts, systems integrators, software suppliers, and cloud service providers may now include the new NVIDIA AI workflows for fraud detection. NVIDIA Technical Blog post on enhancing fraud detection with GNNs and investigate the NVIDIA AI workflows for fraud detection.

Read more on Govindhtech.com

[manmishra]

🚀💻 BREAKING: Nvidia’s AI Ultra Chip is coming! 🤯🔥 With Reuben Architecture, this next-gen chip will make AI computing ⚙️💡 faster, smarter & more powerful! 🤖⚡ 💊🏥 Healthcare: Faster diagnosis & drug discovery 💉🧠 🚗🚦 Self-driving cars: Real-time decision making 🏎️🔋 💰📊 Finance: Accurate predictions 💹📈 🎮🕹️ Gaming: Ultra-realistic graphics 🎨👾 But can Nvidia stay ahead of AMD, Intel, Google & Microsoft? 🤔💡 👉 Read more! 📖🔍 #NvidiaAI #FutureOfAI #TechNews #AIUltraChip 🚀💻

[teragames]

NVIDIA lanza modelos de agentes NIM para que las empresas desarrollen su propia IA

Lus socios globales de @nvidiaai lanzan modelos de agentes NIM para que las empresas desarrollen su propia Inteligencia Artificial.

NVIDIA anuncia NVIDIA NIM Agent Blueprints, un catálogo de flujos de trabajo de IA preentrenados y personalizables que equipa a millones de desarrolladores empresariales con un conjunto completo de software para crear e implantar aplicaciones de IA generativa para casos de uso canónicos como avatares de atención al cliente, generación aumentada mediante recuperación y cribado virtual para el…

[cryptonomytech]

GPU AS A SERVICE: PROYECTOS QUE CREECERAN FUERTEMENTE

#GPU AS A SERVICE: PROYECTOS QUE CREECERAN FUERTEMENTE dentro de las narrativas de #DePIN #ai #IA #ArtificialIntelligence #Cloud  https://youtu.be/i64TOWP6k7M?si=kfROwOCJsuxvBb3F via @rendernetwork @nvidia @NVIDIAGeForce @NVIDIAGeForceES @NVIDIAGeForceFR @NVIDIAAI @InferixGPU @AethirCloud @aethirCSD 

[ailatestupdate]

Isaac GR00T N1 – NVIDIA's groundbreaking humanoid robot foundation model is here! Designed to accelerate AI-driven robotics, it revolutionizes simulation, automation, and real-world adaptability. With cutting-edge machine learning and next-gen simulation frameworks, Isaac GR00T N1 is shaping the future of intelligent robots.

[whats-ai]

I just published Create 3D Models from Images! AI and Game Development, Design… Read more (link in story): https://ift.tt/3glseny posted on Instagram - https://instagr.am/p/CNzxIARgPqh/