#IntelAI

[govindhtech]

Intel AI for Alibaba Cloud Qwen2 Large Language Model Ops

Intel  AI Solutions Optimized for Alibaba  Cloud Qwen2 Large Language Model Operations.

Intel AI solutions

Working with innovators and leaders in the industry,  Intel is always improving the performance of its  AI solutions for use in state-of-the-art models. We are thrilled to inform today that Intel AI solutions have been optimized from the datacenter to the client and edge for the global launch of Alibaba Cloud’s Qwen2.

Alibaba Cloud released its Qwen2 large language models today. Their launch day support offers developers and clients robust AI solutions that are tailored for the newest AI models and software available on the market.

Software Enhancement

A full array of software optimization is necessary to maximize the performance of LLMs, such as Alibaba  Cloud Qwen2. These optimizations span from sophisticated quantization methods that strike a balance between accuracy and speed to high-performance fused kernels. To improve inference efficiency, tensor parallelism, Paged Attention methods, and key-value (KV) caching are also used. S

Software frameworks and tools like PyTorch &  Intel Extension for PyTorch, OpenVINO Toolkit, DeepSpeed, Hugging Face libraries, and vLLM for maximum LLM inference performance are used to accelerate Intel processors.

In order to create an environment that stimulates innovation, Alibaba  Cloud and  Intel work together on  AI software for datacenter, client, and edge platforms. A few instances of this collaboration are ModelScope, Alibaba Cloud PAI, OpenVINO, and other projects. Alibaba  Cloud’s AI models may therefore be optimised for use in a variety of computing settings.

Intel Gaudi AI Accelerator Benchmarking

The high-performance acceleration of generative AI and LLMs is the purpose of the Intel Gaudi AI accelerators. The new LLMs models can be implemented with ease using the most recent version of Optimum for  Intel Gaudi. We have used Intel Gaudi 2 to test the throughput for inference and parameter fine-tuning of the Qwen2 7B and 72B models. This is a full list of the performance metrics.

Evaluation of Intel Xeon Processor Benchmarks

The global backbone of general computing, Intel Xeon processors provide simple access to strong processing capabilities. Due to their widespread availability and presence in data centres of all sizes,  Intel Xeon processors are a great option for businesses wishing to swiftly implement  AI solutions without requiring specialized equipment. The Intel Advanced Matrix Extensions (Intel AMX) feature, which addresses a variety of  AI workloads and speeds up AI inference, are integrated into every core of the  Intel Xeon processor.

AI Desktops

Developers can now deploy LLMs locally thanks to AI PCs that use the newest Intel Core  CPUs and Intel Arc graphics to bring AI power to the client and edge. To tackle difficult AI activities at the edge, AI PCs are outfitted with specialized AI hardware, such as Neural Processing Units and available built-in Arc GPUs, or  Intel Arc A-Series Graphics with Intel X Matrix Extensions acceleration. Fast reaction times, improved privacy, and personalized  AI experiences are all made possible by this local processing capacity, and these features are essential for interactive applications.

Start Now

These are the resources that will help you begin using  Intel  AI products.

Get Started on Intel Xeon with a Quick Start on Gaudi2 PyTorch

OpenVINO Get Started example for Qwen2 (for AI  PCs, Arc GPUs, and Intel Xeon) PyTorch Get Started on Intel GPUs.

Intelligent Solutions Overview

Intel leads the rapidly evolving field of artificial intelligence (AI), providing cutting-edge solutions for a variety of computational needs. From edge to cloud,  Intel AI solutions use a variety of hardware and software to accelerate  AI workloads. These modifications are crucial for AI model scalability and performance in large-scale applications.

Qwen2 on Alibaba Cloud: An Overview

One of the most sophisticated large language models (LLMs) available today is Alibaba  Cloud Qwen2. Built for high-performance computing settings, Qwen2 uses Alibaba  Cloud’s vast infrastructure to provide previously unheard-of natural language processing (NLP) capabilities. Because of its architecture, which is designed to handle large volumes of data, it is an effective tool for businesses looking to take use of  artificial intelligence.

The Alibaba Cloud Qwen2 and Intel AI Synergy

By combining Alibaba Cloud Qwen2 with  Intel AI technologies, a synergistic environment is created that increases the efficacy and efficiency of  AI installations. Through this agreement, Alibaba’s strong cloud infrastructure and Intel’s experience in AI hardware acceleration will be combined to improve the scalability and performance of huge language models.

Hardware Efficiency

Alibaba  Cloud Qwen2’s performance is greatly enhanced by  Intel’s AI hardware, which includes Xeon Scalable CPUs and Intel AI accelerators. Large-scale AI workloads can be supported by these processors since they are designed to handle computationally demanding jobs with ease and provide the necessary power. Qwen2 can attain more throughput and reduced latency by utilising Intel’s cutting-edge hardware, which is crucial for real-time  artificial intelligence applications.

Software Enhancement

The oneAPI software framework from  Intel provides a uniform programming model that makes creating and implementing  AI applications easier. Developers are able to maximise Qwen2’s performance on many Intel architectures with oneAPI, which guarantees improved efficiency and easy integration. A set of tools and libraries offered by the framework facilitate the fine-tuning of  AI models, resulting in increased accuracy and quicker inference times.

Enhancement of Performance and Scalability

Dispersed Computing

Scaling AI workloads across distributed computing infrastructures is a key benefit of integrating Alibaba  Cloud Qwen2 with Intel AI solutions. For example, Qwen2’s large data requirements are supported by a high-performance, scalable storage system offered by  Intel’s Distributed Asynchronous Object Storage (DAOS). This improves the language model’s overall performance by guaranteeing that it can handle and analyse big datasets effectively.

High-Efficiency Connections

Silicon Photonics technology and Ethernet adapters from  Intel are key components of high-speed, low-latency networking solutions. By enabling quick data flow between compute nodes, these technologies reduce bottlenecks and guarantee Qwen2 runs smoothly. Because of this, businesses can use  AI systems that need to analyze data instantly and reliably knowing that they will function as intended.

Sustainability and Energy Efficiency

Control of Power

Intel must priorities energy efficiency in its search for sustainable  AI solutions. Advanced power management technologies included in  Intel AI systems save energy usage without sacrificing functionality. Large language models like Qwen2, which need a lot of processing power, will especially benefit from this. Intel assists businesses in lowering their operational expenses and carbon footprint by optimizing power utilization.

Eco-Friendly Data Centres

 Intel AI technologies in its green data centres demonstrate Alibaba  Cloud’s commitment to sustainability. Data centres employ renewable energy and cutting-edge cooling systems to lessen their environmental effect. Alibaba’s green infrastructure and Intel’s energy-efficient technology fuel and sustain  AI applications.

Safety and Adherence

Data Security

Intel AI solutions offer strong security measures that safeguard sensitive data in a time when data security is crucial.  Intel Software Guard Extensions (SGX) protect sensitive data during processing with hardware-based encryption. For enterprises employing Qwen2 for sensitive data applications, this is crucial.

Respect for Regulations

GDPR and CCPA compliance are just two of the strict data protection laws that Intel AI products are made to abide by. Because of this compliance, businesses can use Alibaba  Cloud Qwen2 to deploy  AI applications with confidence, knowing that their data handling procedures adhere to international standards. Businesses in regulated industries like healthcare and banking need this.

Future prospects and innovations

Constant Enhancement

The collaboration between Alibaba Cloud and  Intel is positioned for continual innovation, as efforts are being made to improve Qwen2’s functionality and performance. Because of  Intel’s dedication to R&D, its  AI solutions are always at the forefront of technical breakthroughs, giving businesses cutting-edge capabilities to be competitive in the AI market.

New Technologies

Intel is exploring quantum and neuromorphic AI. New technologies with unprecedented processing power and efficiency could alter AI. The combination of these technologies with Alibaba  Cloud Qwen2 may open up new avenues for  AI applications, leading to innovations across a range of industries.

In summary

A notable advancement in AI technology is the optimization of  Intel AI solutions for Alibaba Cloud Qwen2 large language models. Together, Alibaba’s strong cloud infrastructure and Intel’s cutting-edge technology and software provide unmatched performance, scalability, and sustainability. Businesses may use these optimized solutions to boost productivity, stimulate creativity, and confidently accomplish their  AI objectives.

Read more on govindhtech.com

[cameliaferdon]

Intel Introduces New AI Solutions with Xeon 6 and Gaudi 3

Intel has launched its latest AI solutions featuring the Xeon 6 processors and Gaudi 3 AI accelerators. These advancements promise improved performance and efficiency for AI tasks. With the new Xeon 6, you get better AI and HPC workloads, while Gaudi 3 offers enhanced throughput and cost-effectiveness. Perfect for powering the next generation of AI applications! 🚀

#IntelAI #Innovation #TechNews

Read More Here

[atarion]

Steam Leak, Doom Fallout, AI Delays, Linux, Kubernetes, Home Lab & More  #steam #steamdeck #leak #doomthedarkages #doom #kubernetes #homelab #metaai #Cohere_Ai #llms #microsoft #epicgames #fatalfuryspecial_flops #waymo #granola #xoople #nvidia #intelai #linux #linuxkernel #redhatlinux #raspberrypi #sbc #nginx #minisforum

[groovy-computers]

🚀 Thrilling shake-ups at Intel as new CEO Lip-Bu Tan tackles the AI sector head-on! Brace for transformative changes! 🧠 Lip-Bu Tan, Intel's newly appointed CEO, is taking strategic steps to revitalize the AI Arm of Team Blue. With the creation of a "chief AI" officer position, Tan aims to stabilize sub-par performance in the evolving semiconductor landscape. This bold restructuring empowers key divisions to report directly to him, intensifying Intel’s focus on AI advancements. In an internal memo, Tan expressed his commitment to closely collaborate with engineering and product teams to enhance AI solutions. The decision is fueled by necessity, as Intel's Gaudi AI accelerators lagged behind industry leaders like NVIDIA and AMD. He believes adapting quickly and making hard yet significant decisions can overturn the current dynamics. The lesson? In tech, pivoting with bold leadership moves can make all the difference. How will Intel's new strategy redefine the market landscape? 🧐 What do you think about Intel's aggressive strategy under Tan's leadership? Comment below! 🔍 #IntelInnovation #AITechnology #TechLeadership #LipBuTan #SemiconductorRevolution #IntelAI #TeamBlue #TechNews

[mysocial8onetech]

Science is about discovering new things and solving complex problems. But what if there was an AI model that could help scientists do that faster and better? That’s the vision behind Intel’s Aurora genAI, a trillion-parameter generative AI model for science that will be trained on the Aurora supercomputer. Aurora genAI will be able to produce text, code, data, and images based on scientific text and data from biology, chemistry, physics, medicine, and more. In this article, I will show you how Aurora genAI works, what it can do for science, and how you can access and use it.

Continue Reading

[ericnyquist]

Find the problem! More artwork for @intel in #nyc and #dc With @tbwachiatla @jigishabouverat @buckhaus @m.wood_rob @dlux08 #intel #ericnyquist #illustration #artificialintelligence #intelai #gears #subwayads #bouveratcollective

[analyticsindiam]

Intel Readies For An AI Revolution With A Comprehensive AI Solutions Stack

Global technology player Intel has been a catalyst for some of the most significant technology transformations in the last 50 years, preparing its partners, customers and enterprise users for a digital era. In the area of artificial intelligence (AI) and deep learning (DL), Intel is at the forefront of providing end-to-end solutions that are creating immense business value. But there’s one more area where the technology giant is playing a central role. Intel is going to the heart of the developer community by providing a wealth of software and developer tools that can simplify building and deployment of DL-driven solutions and take care of all computing requirements so that data scientists, machine learning engineers and practitioners can focus on delivering solutions that grant real business value. The company’s software offerings provide a range of options to meet the varying needs of data scientists, developers and researchers at various levels of AI expertise. So, why are AI software development tools more important now than ever? As architectural diversity increases and the compute environment becomes more sophisticated, the developer community needs access to a comprehensive suite of tools that can enable them to build applications better, faster and more easily and reliably without worrying about the underlying architecture. What Intel is primarily doing is empowering coders, data scientists and researchers to become more productive by taking away the code complexity. Intel Makes AI More Accessible For The Developer Community In more ways than one, software has become the last mile between the developers and the underlying hardware infrastructure, enabling them to utilise the optimization capabilities of processors. Analytics India Magazine spoke to Akanksha Bilani, Country Lead – India, Singapore, ANZ at Intel Software to understand why, in today’s world, transformation of software is key to driving effective business, usage models and market opportunity. “Gone are the days where adding more racks to existing platforms helped drive productivity. Moore’s law and AI advocates that the way to take advantage of hardware is by driving innovation on software that runs on top of it. Studies show that modernization, parallelisation and optimization of software on the hardware helps in doubling the performance of our hardware,” she emphasizes. Going forward, the convergence of architecture innovation and optimized software for platforms will be the only way to harness the potential of future paradigms of AI, High Performance Computing (HPC) and the Internet of Everything (IoE). Intel’s Naveen Rao, Corporate Vice President and General Manager, Artificial Intelligence Products Group at Intel Corporation, summed up the above statement at the recently concluded AI Hardware1 summit.  It’s not just a ‘fast chip’ - but a portfolio of products with a software roadmap that can enable the developer community to leverage the capabilities of the new AI hardware. “AI models are growing by 2x every 3 months. So it will take a village of technologies to meet the demands: 2x by software, 2x by architecture, 2x by silicon process and 4x by interconnect,” he stated.  Simplifying AI Workflows With Intel® Software Development Tools As the global technology major leads the way forward in data-driven transformation, we are seeing Intel® Software2 solutions open up a new set of possibilities across multiple sectors. In retail,  the Intel® Distribution of OpenVINO™ Toolkit is helping business leaders3 take advantage of near real-time insights to help make better decisions faster. Wipro4 has built groundbreaking edge AI solutions on server class Intel® Xeon® Scalable Processors and the Intel® Distribution of OpenVINO™ Toolkit. Today, data scientists who are building cutting-edge AI algorithms rely very heavily on Intel® Distribution for Python to get higher performance gains. While stock Python products bring a great deal performance to the table, the Intel performance libraries that come already plugged in with Intel® Distribution for Python help programmes gain more significant speed-ups as compared to the open source scikit-learn. Now, those working in distributed environments leverage BigDL, a DL library for Apache Spark. This distributed DL library helps data scientists accelerate DL inference on CPUs in their Spark environment. “BigDL is an add-on to the machine learning pipeline and delivers an incredible amount of performance gains,” Bilani elaborates.  Then there’s also Intel® Data Analytics Acceleration Library (Intel® DAAL), widely used by data scientists for its range of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms. For every stage in the development pipeline, there are tools providing APIs and it can be used with other popular data platforms such as Hadoop, Matlab, Spark and R. There is also another audience that Intel caters to — the tuning experts who really understand their programs and want to get the maximum performance out of their architecture. For these users, the company offers its Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN) — an open source, performance-enhancing library which has been abstracted to a great extent to allow developers to utilise DL frameworks featuring optimized performance on Intel hardware. This platform can accelerate DL frameworks on Intel architecture and developers can also learn more about this tool through tutorials.  The developer community is also excited about yet another ambitious undertaking from Intel, which will soon be out in beta and that truly takes away the complexity brought on by heterogeneous architectures. OneAPI, one of the most ground-breaking multi-year software projects from Intel, offers a single programming methodology across heterogeneous architectures. The end benefit to application developers is that they need no longer maintain separate code bases, multiple programming languages, and different tools and workflows which means that they can now get maximum performance out of their hardware. As Prakash Mallya, Vice President and Managing Director, Sales and Marketing Group, Intel India, explains, “The magic of OneAPI is that it takes away the complexity of the programme and developers can take advantage of the heterogeneity of architectures which implies they can use the architecture that best fits their usage model or use case. It is an ambitious multi-year project and we are committed to working through it every single day to ensure we simplify and not compromise our performance.” According to Bilani, the bottomline of leveraging OneAPI is that it provides an abstracted, unified programming language that actually delivers a one view/OneAPI across all the various architectures. OneAPI will be out in beta in October. How Intel Is Reimagining Computing As architectures get more diverse, Intel is doubling down on a broader roadmap for domain-specific architectures coupled with simplified software tools (libraries and frameworks) that enable abstraction and faster prototyping across its comprehensive AI solutions stack. The company is also scaling adoption of its hardware assets — CPUs, FPGAs, VPUs and the soon to be released Intel Nervana™ Neural Network Processor product line. As Mallya puts it, “Hardware is foundational to our company. We have been building architectures for the last 50 years and we are committed to doing that in the future but if there is one thing I would like to reinforce, it is that in an AI-driven world, as data-centric workloads become more diverse, there’s no single architecture that can fit in.”  That’s why Intel focuses on multiple architectures — whether it is scalar (CPU), vector (GPU), matrix (AI) or spatial (FPGA). The Intel team is working towards offering more synchrony between all the hardware layers and software. For example, Intel Xeon Scalable processors have undergone generational improvements and are now seeing a drift towards instructions which are very specific to AI.  Vector Neural Network Instruction (VNNI), built into the 2nd Generation Intel Xeon Scalable processors, delivers enhanced AI performance. Advanced Vector Extensions (AVX), on the other hand, are instructions that have already been a part of Intel Xeon technology for the last five years. While AVX allows engineers to get the performance they need on a Xeon processor, VNNI enables data scientists and machine learning engineers to maximize AI performance. Here’s where Intel is upping the game in terms of heterogeneity — from generic CPUs (2nd Gen Intel Xeon Scalable processors) running specific instructions for AI to actually having a complete product built for both training and inference. Earlier in August at the Hot Chips 2019, Intel announced the Intel Nervana Neural Network processors4, designed from the ground up to run full AI workloads that cannot run on GPUs which are more general purpose. The Bottomline: a) Deploy AI anywhere with unprecedented hardware choice  b) Software capabilities that sit on top of hardware  c) Enriching community support to get up to speed with the latest tools  Winning the AI Race For Intel, the winning factor has been staying closely aligned with its strategy of ‘no one size fits all’ approach and ensuring its evolving portfolio of solutions and products stays AI-relevant. The technology behemoth has been at the forefront of the AI revolution, helping enterprises and startups operationalize AI by reimagining computing and offering full-stack AI solutions, spanning software and hardware that add additional value to end customers. Intel has also heavily built up a complete ecosystem of partnerships and has made significant inroads into specific industry verticals and applications like telecom, healthcare and retail, helping the company drive long-term growth. As Mallya sums up, the way forward is through meaningful collaborations and making the vision of AI for India a reality using powerful best-in-class tools.  Sources 1AI Hardware Summit: https://twitter.com/karlfreund 2Intel Software Solutions: https://software.intel.com/en-us 3Accelerate Vision Anywhere With OpenVINO™ Toolkit: https://www.intel.in/content/www/in/en/internet-of-things/openvino-toolkit.html 4At Hot Chips, Intel Pushes ��AI Everywhere’: https://newsroom.intel.com/news/hot-chips-2019/#gs.8w7pme Read the full article

[dreamer-gus]

Can you see that future starts now? #IntelAI #IntelNoMack (at Auditorio Ruy Barbosa)

[alex-leonhart]

Python, comanda! #IntelAi #IntelSoftware #IntelNaFatecSantos (em Fatec Baixada Santista - Rubens Lara)

[skyecam]

Behind the scenes of our Intel Artificial Intelligence project. Working with Intel has been an epic adventure. Stayed Tuned! * * * * * #intel #intelai #kenya #setlife #bts #drone #aerialdp #uas #djiglobal #cameradept #film #aerialcinematography #set #drones #dronephotography #production #dronestagram #filmcrew #filmmaking #poachers #dronelife #director #droneworld #skyecam http://www.skyecam.com (at Kenya) https://www.instagram.com/skyecam_/p/BwFhzQiB5Wo/?utm_source=ig_tumblr_share&igshid=1efwh5pdslc18

[fondazioneterradotranto]

Nuovo post su https://is.gd/J4TARM

L’arte del costruire nel Salento. Il cemento e il conglomerato cementizio

Continuiamo la serie dei saggi scritti dall’ingegnere Mario Colomba, che ha lasciato questo mondo oggi 6 agosto 2021. I suoi scritti, pietre miliari per la conoscenza dell’edilizia nel Salento, continueranno ad essere pubblicati su questo spazio, per tenere vivo il suo ricordo e il suo sapere

  di Mario Colomba

  L’uso del cemento come materiale da costruzione nelle sue varie applicazioni, dal cemento armato ai vari tipi di malta, rappresenta l’inizio di un cambiamento epocale nella pratica costruttiva,  non solo dal punto di vista tecnologico ma anche e soprattutto per l’introduzione di una diversa mentalità. Si affermano nuove e diverse abilità personali che non riguardano più la corrispondenza con il manufatto, la capacità creativa o la ricerca della perfezione dei particolari. Prevale l’interesse della produzione e dell’economia di scala in cui l’individuo non rappresenta più il riferimento principale. E’ l’affermazione di un nuovo ambiente di lavoro in cui tutto è già programmato, in cui non si tollerano più margini di tempo impiegato per inventare o soltanto per riflettere.

Ogni addetto si deve limitare a svolgere,  nel minor tempo possibile e  comunque non superiore a certi standards codificati,  le operazioni che gli vengono affidate senza aggiungere nulla di suo.

Col passare del tempo, man mano che prendono piede le nuove pratiche costruttive, si perdono le conoscenze delle nozioni tradizionali trasmesse oralmente. Di conseguenza,  viene meno il rispetto personale per i depositari della conoscenza delle tecniche e tecnologie ormai desuete. Si verifica così una profonda modificazione dell’ambiente di lavoro. La divulgazione di elaborati progettuali (disegni e schede tecniche) esige un  minimo di conoscenze che di fatto determina una discriminazione, emarginando chi, per difetto di istruzione o difficoltà di apprendimento, non è più in grado di aggiornarsi e di adeguarsi alle esigenze della produzione e della produttività.

In un sistema produttivo come  quello delle costruzioni si verifica un cambiamento radicale che si manifesta prepotentemente, stimolato da una imponente domanda. Localmente però l’abbandono  dei vecchi sistemi costruttivi presenta una certa viscosità. Vi è riluttanza, per esempio nella realizzazione di edifici a struttura intelaiata. ad abbandonare l’impiego della pietra di tufo per l’esecuzione di tramezzature o murature di tompagno o nell’adoperare materiali alternativi  alle chianche di Cursi per le pavimentazioni solari. Si vanno conservando tuttora, anche per salvaguardare numerosi posti di lavoro,  tecniche,  materiali e tecnologie che mal si adattano alla coesistenza con strutture intelaiate elastiche.

Il progressivo contemporaneo sviluppo della meccanizzazione, provoca la nascita di specializzazioni del tutto nuove e fortemente settorializzate,   in deciso contrasto con le eclettiche capacità degli addetti tradizionali di qualifica più elevata (cucchiare) che erano in grado non solo di realizzare murature  ma anche di mettere in opera pavimentazioni o intonacare pareti.

Già negli anni ’30 si registrano da noi le prime applicazioni del cemento come nuovo materiale da costruzione. Però, è solo nel dopoguerra che si diffonde progressivamente l’uso del cemento portland , prodotto negli stabilimenti di Monopoli o Modugno dalla Italcementi.

L’uso più diffuso si riscontra, inizialmente,  per la confezione della malta cementizia e della malta bastarda, che si utilizzano sia per la posa in opera che per la fabbricazione di pavimentazioni nelle diverse tipologie (pavimenti in cemento e graniglia levigati a mano, mattonelle in pastina di cemento per pavimenti decorati, marmette in cemento e scaglie di marmo, ecc.) con limitati impieghi nel conglomerato cementizio per strutture in c.a. semplici (architravi, cordoli, ecc.) fino all’impiego più esteso  nella realizzazione delle coperture piane (“alla margherita”).

(continua)

Per le parti precedenti vedi qui:

Libri| L’arte del costruire a Nardò e dintorni – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

L’arte del costruire nel Salento. Gli arnesi del mestiere – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

Maestri e maestranze nel cantiere edile a Nardò e nel Salento. La produzione edilizia – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

L’arte del costruire nel Salento. Strutture murarie di copertura: archi e volte – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

Cantiere edile (fondazioneterradotranto.it)

Arte del costruire e riutilizzo presso il popolo salentino – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

Reclutamento di manodopera e approvvigionamento di materiale edilizio nelle costruzioni del Salento – Fondazione Terra D’Otranto (fondazioneterradotranto.it)

L’arte del costruire nel Salento. I materiali da costruzione

L’arte del costruire nel Salento. I materiali da costruzione

[mayrarsouza-blog1]

Workshop #intelAI #intelnauniritter (em UniRitter)

[ahli-marie]

Musical sounds and chants keep coming to me…I spell them as I feel too…I’m happy to share them..

Mi Adonai es in selcar ue endescreas mu loi es Mi Adonai…ti cue les insetese une mu rae intelai Sun-e Specara….🎼 A Lia tre de Sun-e Mi Adonai…Rissai Rissai Mi Adonai…ALieghe….🎼

❤️ALi-One-SoAL❤️

❤️ALLi s On-e❤️

✨✨Bea-m✨✨Aethereal ✨✨Light✨✨

[libr-tumbl-alternative]

"From fields and streams to offices, factories, hospitals and transportation systems, organizations are using internet of things (IoT) sensors to collect massive amounts of data in order to improve operations and increase sustainability. ". Reblog with caption 🙃

[groovy-computers]

🚀 Elevate your AI prowess with Intel's Gaudi 3 now on IBM Cloud! 🌐 Discover scalability & savings like never before within IBM's ecosystem. IBM Cloud makes the first-of-its-kind move to integrate Intel's Gaudi 3 AI accelerator, offering a cost-effective alternative to NVIDIA's options. Available in Frankfurt & Washington, D.C., with Dallas expansion set for Q2 2025. This launch, unveiled at Intel Vision 2025, promises enterprises a transformative AI experience. Gaudi 3 presents: - Standalone server control within IBM Cloud VPC 🌐 - Red Hat OpenShift AI for containerized environments arriving Q2 2025 🚀 - Seamless integration with watsonx.ai 🤝 Priced to challenge NVIDIA, Gaudi 3 combines power efficiency with secure, scalable AI solutions. Intel's strengthened position delivers innovations for generative AI workloads. Are you ready to transform your AI infrastructure? 🔧 #IntelAI #Gaudi3 #IBMCloud #TechInnovation #AIFuture #NVIDIAalternatives #EnterpriseTechnology #GenerativeAI #ScalableAI #CloudComputing #Watsonx #CostEffectiveness

[rahul-tiwary]

Intel on Monday said it will work with Reliance Jio to develop 5G networking technology. Intel's venture capital unit last year invested $250 million (roughly Rs. 1,857.42 crores) in Reliance's Jio Platforms unit, saying the two companies would find areas of technology partnership. On Monday, Intel said it will work on "co-innovations" with Reliance Jio for its 5G radio-access network (RAN), among other things. . . . Like ❤️ Save 🔐 Share ⬆️ and Comment 💌 . . . Do let me know what do you think in the comments below . Follow ➡️@techpix96 Follow ➡️@techpix96 Follow ➡️@techpix96 . . . #intel #jio #5g #5gphone #5gIndia #5gtechnology #5gtowers #5gsmartphone #reliancejio #jiosim #jiodigitallife #jio5g #5gnetworks #jiostudios #intelgaming #intelcore #intelcorei7 #intelcorei5 #intelcorei9 #inteloptane #intelprocessor #intelpentium #intelpartner #intelai #5gready #5gtechnology #5gtowers #5gishere #digitalindia #4G #techpix #technews (at New Delhi, India) https://www.instagram.com/p/CQgLHE2jL-v/?utm_medium=tumblr