#NextGenComputer

[govindhtech]

Intel Geti Platform: Next-Gen Computer Vision AI Software

What is Intel Geti Software?

Intel’s latest software can create computer vision models with less data and in a quarter of the time. Teams can now create unique AI models at scale with to this software, which streamlines time-consuming data labeling, model training, and optimization processes throughout the AI model creation process.

Create Robust AI Models for Computer Vision

Small data sets, active learning, an easy-to-use user interface, and integrated collaboration make training AI models straightforward.

Automate and Digitize Projects More Quickly

Teams can rapidly create vision models for a variety of processes, such as identifying faulty parts in a production line, cutting downtime on the factory floor, automating inventory management, or other digitization and automation projects, by streamlining labor-intensive data upload, labeling, training, model optimization, and retraining tasks. The Intel Geti software simplifies the process and significantly reduces the time-to-value of developing AI models.

Core Capabilities Behind the Next-Generation Computer Vision AI Software

Interactive Model Training

Use as little as 20–30 photos to begin annotating data, and then use active learning to train the model as it learns.

Multiple Computer Vision Tasks

Build models for AI tasks such as anomaly detection, object identification, categorization, and semantic segmentation.

Task Chaining

By chaining two or more tasks together, you may train your model into a multistep, intelligent application without writing extra code.

Smart Annotations

Use professional drawing tools like a pencil, polygon tool, and OpenCV GrabCut to quickly annotate data and segment pictures.

Production-Ready Models

Produce deep learning models as optimized models for the OpenVINO toolkit to operate on Intel architecture CPUs, GPUs, and VPUs, or in TensorFlow or PyTorch formats, if available.

Hyperparameter Optimization

The model’s learning process depends on the hyperparameters being adjusted. The work of a data scientist is made simpler by Intel Geti software’s integrated optimization.

Rotated Bounding Boxes

The accuracy and ease of training are extended to datasets with non-axis-aligned pictures with to support for rotated bounding boxes.

Model Evaluation

Assessment of the Model thorough statistics to evaluate the success of your model.

Flexible Deployment Options to Get You Started

Simply set up your environment and infrastructure and prepare to install Intel Geti software, regardless of whether you want to use your system infrastructure inside your network or benefit from the cloud virtual machine without managing infrastructure.

On Premise

Virtual Machine

Enabling Collaboration that Adds Value

In a single instance, cross-functional AI teams work together to examine outcomes instantly. Team members with little to no familiarity with AI may assist in training computer vision models with to the graphical user interface. Drag-and-drop model training is made easy by enabling features like object identification helpers, drawing features, and annotation assistants.

Intel Geti Platform Use Cases

Convolutional neural network models are retrained using the Intel Geti platform for important computer vision applications, such as:

Semantic and instance segmentation, including counting

Single-label, multi-label, and hierarchical classification

Anomaly classification, detection, and segmentation

Axis-aligned and rotational object detection

Task chaining is also supported, allowing you to create intelligent, multi-step applications.

Manufacturing: Create AI for industrial controls, worker safety systems, autonomous assembly, and defect detection.

Smart Agriculture: Create models for self-governing devices that can assess crop health, detect weeds and pests, apply spot fertilizer and treatment, and harvest crops.

Smart Cities: Create AI-powered traffic-management systems to automatically route traffic, create emergency-recognition and response systems, and utilize video data to enhance safety in real time.

Retail: Create AI for accurate, touchless checkout, better safety and loss prevention, and self-governing inventory management systems.

Video Safety: Create task-specific models for the identification of safety gear, PPE, social distancing, and video analytics.

Medical Care: Create models to help with diagnosis and procedures, assess lab data and count cultures, identify abnormalities in medical pictures, and expedite medical research.

REST APIs and a software development kit (SDK) may be used to incorporate all of these models into your pipeline, or you can use the OpenVINO toolkit to distribute them.

FAQs

What types of data can Intel Geti handle?

Text, photos, videos, and structured data are just a few of the data kinds that Intel Geti can manage. It excels in processing unstructured data, such as audio and visual inputs for deep learning applications.

Read more on govindhtech.com

[fatihulusoy]

CL1: The Biological Computer That Plays Pong with Actual Brain Cells

Greetings folks! Strap in, because this one's not science fiction — it’s science right now. What you’re about to read involves a computer that thinks using actual, living brain cells. Cortical Labs has built a system that doesn’t just simulate intelligence — it is intelligence. Meet CL1: a hybrid of silicon, stem cells, and sheer bioengineering brilliance.

TL;DR:

Cortical Labs built a biological computer using living neurons from stem cells. These neurons live on a chip, respond to stimuli, and learn to play Pong through feedback. No lines of code needed — just raw, biological learning. It’s a new chapter in computing where machines grow brains instead of running on silicon alone.

🧠 So, What Is CL1?

Imagine this: you take living neurons — derived from either human or mouse induced pluripotent stem cells (iPSCs) — and grow them on top of a microchip covered in electrodes. These electrodes can talk to the neurons using electrical pulses.

Now give that system a goal — say, playing Pong — and watch what happens. With no pre-programming, these little neuron networks start to learn, just by reacting to inputs and adjusting over time.

This isn't a simulation. These are real cells doing real-time problem solving. Welcome to the era of wetware.

⚙️ CL1's Technical Side:

Neurons: Human/mouse neurons derived from iPSCs

Interface: Multi-Electrode Array (MEA)

OS: biOS (as base biological operating system)

Feedback Loop: Electrical stimulation + live response tracking

Learning Mechanism: Hebbian plasticity ("neurons that fire together wire together")

🧬 How the Heck Does This Actually Work?

Let’s break it down — both biologically and technically:

👾 The Digital-to-Bio Feedback Loop:

CL1 is a closed-loop system:

The digital system tells the neurons what's happening (e.g., “pong ball moving left”)

Neurons fire back electrical responses

The system interprets those firings

Correct response? They get rewarded. Wrong one? They get a gentle digital slap

Over time, the neuron network self-organizes, learning the task through synaptic plasticity

🧪 The Biology Bit:

The neurons are grown from induced pluripotent stem cells (iPSCs) — adult cells reprogrammed into a stem-cell-like state

These are then developed into cortical neurons

The network grows on a multi-electrode array that can both stimulate and read from the cells

🖥 The Tech Stack:

biOS (Biological Operating System): Simulates digital environments (like Pong) and interprets neural activity in real time

Signal Processing Engine: Converts biological signals into digital responses

Environmental Control: Keeps the neuron dish alive with precise nutrient feeds, CO₂ levels, and temperature management

💡 Why This Is a Huge Freaking Deal

This isn't about playing Pong. It’s about building a new class of machines that learn like we do. That adapt. That grow. This rewires the concept of computing from algorithm-based logic to biological self-organization.

Potential future uses:

Ultra-low-power, self-learning bio-AI chips

Medical models for brain diseases, drug testing, or trauma simulation

Robotic systems that use real neurons for adaptive control

In short: this is the birth of organic computing.

🔮 Can We Upload Knowledge Yet? Like Matrix Style?

Not quite. Right now, CL1 learns via real-time feedback — it’s still trial-and-error. But researchers are exploring:

Pre-conditioning neural responses

Chemical memory injection

Patterned stimulation to train in behaviors

In the future? We might literally write instincts into neural systems like flashing a bootloader. One day, your drone might come preloaded with lizard-brain reflexes — not software, but neurons.

🧱 What Comes Next?

We’re at the beginning of something radical:

Neural prosthetics with muscle memory

Bio-computers that can evolve new solutions on their own

Robots that aren’t just “smart” — they’re alive-ish

CL1 is laying the foundation for a new kind of intelligence — not modeled after the brain, but actually made of one.

🔗 Sources:

Cortical Labs Official

Nature Article

The Verge Feature

ABC Science News

MIT Tech Review

Neuron Journal Study

[radhavallabhcomputers]

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[ortmoragency]

Explore Google's Quantum AI breakthrough with Willow, a revolutionary step towards scalable quantum computing, unlocking new possibilities for science and technology

[amrtechinsights]

Unlock the future of computing with #Google's groundbreaking Quantum AI Lab! 🚀 From revolutionizing industries to shaping the next era of technology, quantum computing is here to stay. 🌐🔍 #QuantumComputing #AI #TechInnovation #FutureOfTech #GoogleAI #DisruptTheNorm #NextGenComputing #TechRevolution

[knowledge-wale]

NVIDIA's Grace Hopper Superchip is revolutionizing AI workloads in data centers, designed specifically to handle massive AI and machine learning tasks. It combines a 144-core ARM CPU with a powerful GPU, delivering up to 10x faster performance for AI training and inference compared to traditional systems. The chip is optimized for H100 Tensor Core GPUs, pushing the boundaries of data processing speeds and reducing latency, making it ideal for next-gen AI applications like self-driving cars, language models, and real-time analytics. This breakthrough is expected to accelerate the AI industry's evolution and drive more efficient data center architectures. https://t.ly/2jokn

[astuteanalyticablog]

The Future of Quantum Computing: Predictions and Trends to Watch Out

Organizations that embrace the power of quantum computing could aid humanity in resolving some of the world’s most pressing issues and making advances in vital sectors ranging from drug research to worldwide agriculture and beyond. But how people are near a world in which computing is commonplace, and how can data centers prepare for it? Many of the applications of computing are currently experimental or conceptual. In this blog, let’s discuss the trends and predictions of quantum computing.

The government continues to invest in quantum computing, cybercrime is on the rise, and more industries, including banking, chemicals and finance, and defense, are embracing the technology. As a result, these elements fuel market growth. In addition, according to a research report by Astute Analytica, the Global Quantum Computing Market is likely to grow at a compound annual growth rate (CAGR) of 30% over the projection period from 2023 to 2031.

Here are a few practical trends and predictions of quantum computing that people might see in the future:

Cybersecurity:

Quantum computing has the potential to have an immediate impact on encryption and privacy. Given the continually changing nature of the cybersecurity surroundings, computers could aid in the encryption of data while in use, offering at-rest protection and both in-transit protections.

Manufacturing:

Quantum computers are capable of performing more precise and authentic prototyping and testing. This could assist lower the price of prototyping in the manufacturing arena, resulting in better ideas that don’t require as much testing. 

Development of novel quantum algorithms and optimization techniques:

As quantum computers’ capabilities improve, this leads to the creation of new algorithms and strategies to make use of quantum computing’s unique features. These include error correction, machine learning, and optimization techniques.

Optimization of traffic and routes:

Optimal route design is essential for efficient supply chain operations and transportation. The most difficult task is capturing all of the real-time data that affects this planning, from shifting weather conditions to traffic movement. That’s where quantum computers can work. They could evaluate all of that data in real-time and alter routes for a full fleet of cars at the same time, putting each on the best way forward.

Financial simulation:

Financial institutions might employ quantum computing’s modeling skills to effectively model the behavior of securities and assets at scale. This could assist decrease risk, optimizing large-scale portfolios, and enabling financial organizations better understand the global financial economy’s trends and movements.

Chemical and pharmaceutical research:

Quantum computers can construct superior models for how atoms interact with one another, resulting in a higher and more accurate understanding of molecular structure. This could have a direct impact on medical and chemical research, as well as the way novel goods and medicines are generated. The foresight of quantum computers could potentially provide insight into how substances and medications will develop, evolve, and interact with other components throughout time.

The utilization of artificial intelligence and quantum machine learning:

Researchers are investigating the utilization of quantum computing for creating new artificial intelligence algorithms and machine learning that can make use of the unique features of quantum systems.

SOURCE: The Future of Quantum Computing: Predictions and Trends to Watch Out 

[groovy-computers]

Could Huawei’s latest quad-chiplet AI processor finally challenge Nvidia’s dominance? Rumors suggest Huawei's Ascend 910D, potentially rivaling Nvidia’s H100, may use packaging tech that rivals TSMC… and it’s all rooted in a recent patent leak. This innovative approach could help Huawei bypass US sanctions and accelerate China’s AI chip development. What does this mean for AI training and inference performance? Huawei's focus on advanced chip packaging hints at a future where Chinese chips match or even surpass Western counterparts, bridging gaps in process lithography. Are you excited to see more competition in the AI GPU market? Let us know your thoughts and stay tuned for updates! Explore custom computer builds tailored to your tech ambitions at GroovyComputers.ca. #AI #GPUs #Huawei #TechInnovation #ArtificialIntelligence #ChipDesign #TechNews #NextGenComputing #CustomPC #Gaming #PerformanceBoost

[govindhtech]

Next-Gen Computing: Exploring the Dell PowerEdge XR8000

Dell PowerEdge XR8000 is your Edge Hero. They can assist you in realizing this ideal with the Dell PowerEdge XR8000, which is built for simplicity, efficiency, and flexibility.

The Dell PowerEdge XR8000 is a game-changer, allowing for the seamless integration of artificial intelligence (AI), User Plane Function (UPF) and Multi-access Edge Computing (MEC) to enable a multitude of functionality at the edge. For applications like autonomous vehicles, smart cities, and industrial automation, the XR8000’s MEC reduces latency and improves user experience by bringing processing capacity closer to the data source.

Because of its AI capabilities, enterprises may implement machine learning models, inferencing, and intelligent analytics right at the edge, resulting in operational efficiency and real-time decision-making. It can facilitate data traffic control for UPF workloads in 5G networks, enhancing network dependability and performance.

Combining these capabilities makes the Dell PowerEdge XR8000 a vital tool for businesses looking to remain ahead of the rapidly changing digital landscape. It provides a reliable solution that can be tailored to even the most demanding edge computing environments and is future-proof.

Multi-Access Edge Computing (MEC)

By using MEC and bringing processing capability closer to data creation, communications service providers (CSPs) can boost IoT applications and real-time analytics for enterprises. This deliberate move takes advantage of 5G’s low latency and high bandwidth and establishes new revenue streams by offering cutting-edge solutions that drive digital transformation in multiple industries.

STL expects the MEC addressable market will expand 48% to $445 billion by 2030. MEC benefits business, public utilities, gaming and entertainment, and healthcare with its many applications.

Collaboration amongst several ecosystem participants is necessary for the implementation of MEC, including CSPs, infrastructure providers, and third-party application providers. The efficiency of the MEC hardware at the edge and the third-party MEC apps that are essential for particular industrial verticals determine the success of a MEC solution. The fact that Dell Technologies is an authority in the business sector is a plus.

Dell PowerEdge XR8000 provides a computational infrastructure for the MEC platform that may be utilized to host the MEC applications thanks to its distinctive sled-based architecture. Better ROI for consumers is made possible by its support for L4 GPUs, best-in-class Network Interface Cards, and 12-year warranty after purchase. Gaming, video surveillance, and content delivery networks are a few of the main uses.

The Dell PowerEdge XR8000 fulfils every criteria a provider might have in terms of hardware to meet MEC regulations. Because of its small depth and ruggedized design (NEBS level 3 Certification), this platform may be installed in an edge environment with confidence. Dense computation, ease of deployment, and a safe cyber platform for client data at the edge are all features of the XR8000.

Artificial intelligence (AI)

 AI’s growing needs in the telecom industry highlight the need for edge computing solutions strengthened by more powerful GPUs, more cores, and more thermal design power (TDP). With a projected size of $20.39 billion in 2023 and a projected growth rate of 27.5% from 2024 to 2032, the worldwide edge AI market is expected to reach $186.44 billion by 2032.

The buzz surrounding the newest AI capabilities for telecom companies significantly enhanced operations and open doors for new services needs to be balanced with the need to use a server platform built for AI in telecom networks.

Edge computing and artificial intelligence are two new technologies that are combined to create  AI at the edge. AI provides business intelligence to the processed data for business insights, and edge computing assists in processing data at the edge.

Because there is no need to send the data back to the core, AI at the edge offers amazing benefits like reduced latency, more security, and cheaper operating costs in addition to greater bandwidth efficiency. Less data transmission volume to the cloud and real-time data processing while preserving data security and integrity are further advantages.

The latest Intel Xeon CPUs are supported by the Dell poweredge XR8000, which is a ruggedised AI-capable server for the edge thanks to its support for NVIDIA L4 GPUs. It is a processing powerhouse for  AI and GenAI that can support up to six L4 GPUs in a 2U form size, which greatly enhances computer vision, inference performance, and data analytics.

The ability of the Dell PowerEdge XR8000 for AI to handle several AI workloads on a single chassis is what sets it apart from the competition and allows CSPs to diversify their deployment to diverse AI telecom workloads while also improving return on investment. Because of its flexible, compute-dense sled architecture, CSPs will be able to quickly enable new AI capabilities and confidently and easily deploy solutions.

As an AI server, the Dell PowerEdge XR8000 can be used to target the automotive, manufacturing, healthcare, energy, and telecom industries.

User Plane Function (UPF) 5G brings numerous new use services and performs faster, more reliably, and with lower latency than 4G deployments. The breakdown of 5G core into control and use planes (CUPS) enables CSPs to deploy UPF at different places and platforms, even though RAN plays a crucial role in helping 5G achieve goals.

By taking advantage of this, Distributed User Plane Function (D-UPF) allows CSPs to locate UPF close to the edge where data is created. This will lower backhaul networking costs for CSPs and allow them diversify income streams and charge more for differentiated services.

For optimal performance, the UPF should be hosted on a commercially available off-the-shelf (COTS) platform, which can take use of cloudification and virtualization. A hardware platform that has been ruggedized for the edge is necessary for the deployment of edge UPF. The Dell PowerEdge XR8000 platform is a NEBS level 3 certified system that is highly suitable for D-UPF due to its temperature tolerance range of -20 to 65 degrees Celsius.

The hot pluggable sled-based architecture of the PowerEdge XR8000 provides redundancy in both power and computing. CSPs choose it as their preferred platform for D-UPF.

Championing technology, the Dell PowerEdge XR8000 is the most optimized edge server platform available. By putting processing capacity closer to the data source, lowering latency, and enhancing real-time processing, it strengthens MEC. Because of its strong architecture, which can withstand powerful  AI and GenAI capabilities, it enables intelligent data analysis and edge decision-making, sparking innovation in a variety of industries.

The Dell PowerEdge XR8000 guarantees smooth data routing and network traffic management for UPF, which is crucial for 5G installations. Discover the Dell PowerEdge XR8000 hero and open up new revenue opportunities at the edge.

Read more on govindhtech.com

[techpulsecanada]

Nvidia is betting big on the future of AI with plans to build 100 AI factories worldwide, aiming to dominate in data center innovation. 📊 These facilities will focus solely on training and running AI models, utilizing Nvidia's cutting-edge GPUs and CPUs. As Nvidia's data center revenue soared to nearly 90% in late 2024, Jensen Huang's vision of a 50-year AI infrastructure rollout is shaping industries and shaping the future. For custom, high-performance AI-ready systems, trust GroovyComputers.ca for expert builds that cater to next-gen needs. Don't just watch the AI revolution—be a part of it with a powerful, custom computer. What features do you think are essential in the AI factories of tomorrow? Share your thoughts below! Explore top-tier gaming and AI desktops at GroovyComputers.ca today. #AI #DataCenters #GamingPC #CustomBuilds #Nvidia #AIInfrastructure #FutureTech #HighPerformance #TechRevolution #NextGenComputing #AIChoices

[gis56]

GPU-as-a-Service = Cloud Power Level: OVER 9000! ⚙️☁️ From $5.6B → $28.4B by 2034 #GPUaaS #NextGenComputing

GPU as a Service (GPUaaS) is revolutionizing computing by providing scalable, high-performance GPU resources through the cloud. This model enables businesses, developers, and researchers to access powerful graphics processing units without investing in expensive hardware. From AI model training and deep learning to 3D rendering, gaming, and video processing, GPUaaS delivers unmatched speed and efficiency. 

To Request Sample Report : https://www.globalinsightservices.com/request-sample/?id=GIS24347 &utm_source=SnehaPatil&utm_medium=Article

Its flexibility allows users to scale resources based on workload demands, making it ideal for startups, enterprises, and institutions pursuing innovation. With seamless integration, global access, and pay-as-you-go pricing, GPUaaS fuels faster development cycles and reduces time to market. As demand for compute-intensive tasks grows across industries like healthcare, automotive, fintech, and entertainment, GPUaaS is set to be the cornerstone of next-gen digital infrastructure.

#gpuservice #gpuaas #cloudgpu #highperformancecomputing #aiacceleration #deeplearninggpu #renderingincloud #3dgraphicscloud #cloudgaming #machinelearningpower #datacentergpu #remotegpuresources #gputraining #computeintensive #cloudinfrastructure #gpuoncloud #payasyougpu #techacceleration #innovationaservice #aidevelopmenttools #gpurendering #videoprocessingcloud #scalablegpu #gpubasedai #virtualgpu #edgecomputinggpu #startupsincloud #gpuforml #scientificcomputing #medicalimaginggpu #enterpriseai #nextgentech #gpuinfrastructure #cloudinnovation #gpucloudservices #smartcomputing

Research Scope:

· Estimates and forecast the overall market size for the total market, across type, application, and region

· Detailed information and key takeaways on qualitative and quantitative trends, dynamics, business framework, competitive landscape, and company profiling

· Identify factors influencing market growth and challenges, opportunities, drivers, and restraints

· Identify factors that could limit company participation in identified international markets to help properly calibrate market share expectations and growth rates

· Trace and evaluate key development strategies like acquisitions, product launches, mergers, collaborations, business expansions, agreements, partnerships, and R&D activities

About Us:

Global Insight Services (GIS) is a leading multi-industry market research firm headquartered in Delaware, US. We are committed to providing our clients with highest quality data, analysis, and tools to meet all their market research needs. With GIS, you can be assured of the quality of the deliverables, robust & transparent research methodology, and superior service.

Contact Us:

Global Insight Services LLC  16192, Coastal Highway, Lewes DE 19958  E-mail: info@globalinsightservices.com  Phone: +1–833–761–1700  Website: https://www.globalinsightservices.com/

[mkcecollege]

Nanotechnology in engineering is revolutionizing industries by enabling nanoscale innovations that enhance efficiency and sustainability. From advanced medical treatments to energy solutions and next-gen electronics, its impact is profound. At M.Kumarasamy College of Engineering (MKCE), we equip students with the skills to drive these advancements. Join us in exploring the future of nanotechnology and shaping a smarter world!

To know more : https://mkce.ac.in/blog/nanotechnology-in-engineering-and-revolutionary-advances-with-big-impact-at-the-smallest-scale/

Nanotechnology

NanoEngineering

AdvancedMaterials

SmartMaterials

NanoTechRevolution

MedicalNanotechnology

FutureOfEngineering

EnergyInnovation

NanoMedicine

SustainableTech

NanoSensors

QuantumDots

GrapheneTechnology

NextGenComputing

NanoManufacturing

WaterPurificationTech

BiomedicalEngineering

ElectronicsInnovation

NanotechApplications

MKCEInnovation

Nanotechnology in Engineering

Innovations at the Nanoscale

Applications of Nanotechnology in Medicine

Innovations at the Nanoscale

Nanotechnology in Engineering

Nanotechnology for Clean Energy Solutions

Water Purification with Nanotechnology

Nanoscale Transistors in Electronics

Smart Materials and Self-Healing Polymers

Nano-Robots for Precision Medicine

Quantum Dots in Ultra-High-Definition Displays

MKCE’s Commitment to Nanotechnology Research

[neuroscientistsawards]

Meet Willow: The Future of Quantum Computing #neuroscience #sciencefathe...

Meet Willow, our state-of-the-art quantum chip designed to push the boundaries of computational power. With cutting-edge technology, unmatched precision, and energy efficiency, Willow paves the way for breakthroughs in AI, cryptography, material science, and more. Experience the future of quantum computing today. #QuantumComputing #Innovation #TechRevolution #FutureIsNow #QuantumChip #WillowTech #NextGenComputing #AI #Cryptography #TechInnovation #Breakthrough __________________________________________________________________________________________________________________

 MoreInfo: 

 Websiten link: https://neuroscientists.net/ 

Contact: supportteam@neuroscientists.net 

 Nomination link: https://neuroscientists.net/award-nomination/?ecategory=Awards&rcategory=Awardee ________________________________________________________________________________________________________________ 

 Socialmedia: 

Youtube: https://www.youtube.com/channel/UCZ9RPAjr0vKVJ91LUi4o4ig

Twitter: https://x.com/ScientistsNeuro

 Pininterest: https://in.pinterest.com/neuroscientistsawards/ 

Linked in: https://www.linkedin.com/feed/ 

Instagram link: https://www.instagram.com/laramaria3040/

 blogger:https://www.blogger.com/blog/posts/4217723762166

[amo-physicsawards10]

Quantum-centric supercomputing for materials science represents a transformative approach to computational research, aiming to leverage the power of quantum computing to solve complex problems in material design and discovery. Contact For Enquiries: physics@scifat.com Get Connected Here ---------------------- ---------------------- Instagram: www.instagram.com/amophysicsawards/ Facebook: www.facebook.com/profile.php?id=100092029748922 twitter: twitter.com/home pinterest: in.pinterest.com/physicsresearch2000/ blogger: www.blogger.com/u/5/blog/posts/4758468583908890312?pli=1 #QuantumComputing #Supercomputing #MaterialsScience #QuantumMaterials #QuantumTechnology #ComputationalScience #QuantumSimulations #QuantumAlgorithms #HighPerformanceComputing #QuantumFuture #MaterialDesign #QuantumPhysics #QuantumResearch #QuantumCentric #ScientificComputing #QuantumModeling #QuantumChallenges #NextGenComputing #QuantumInnovation #MaterialsResearch #QuantumEngineering #QuantumAdvancements #SupercomputerTech #QuantumMechanics #QuantumPotential #EmergingTechnologies #QuantumSimulations #QuantumTheory #QuantumRevolution #MaterialsInnovation

[groovy-computers]

Nvidia is betting big on the future of AI with plans to build 100 AI factories worldwide, aiming to dominate in data center innovation. 📊 These facilities will focus solely on training and running AI models, utilizing Nvidia's cutting-edge GPUs and CPUs. As Nvidia's data center revenue soared to nearly 90% in late 2024, Jensen Huang's vision of a 50-year AI infrastructure rollout is shaping industries and shaping the future. For custom, high-performance AI-ready systems, trust GroovyComputers.ca for expert builds that cater to next-gen needs. Don't just watch the AI revolution—be a part of it with a powerful, custom computer. What features do you think are essential in the AI factories of tomorrow? Share your thoughts below! Explore top-tier gaming and AI desktops at GroovyComputers.ca today. #AI #DataCenters #GamingPC #CustomBuilds #Nvidia #AIInfrastructure #FutureTech #HighPerformance #TechRevolution #NextGenComputing #AIChoices