Nvidia | Business Upturn

Netweb Technologies reports ₹21,835.6 million revenue for FY26

Arunika Jain — Sat, 02 May 2026 15:00:43 +0000

Netweb Technologies India Limited has announced its audited financial results for the fiscal year ending 31 March 2026, revealing a robust revenue from operations amounting to ₹21,835.6 million. The company, recognised as a leading provider of high-end computing solutions (HCS) in India, continues to strengthen its position in the market through strategic collaborations and indigenous technology development.

The financial metrics for the year highlight an operating EBITDA margin of 13.0% and a profit after tax (PAT) margin of 9.3%. Netweb Technologies also reported a return on capital employed (ROCE) of 37.5% and a return on equity (ROE) of 32.9%, reflecting strong financial performance and efficient capital utilisation.

Netweb Technologies has been at the forefront of the high-performance computing sector, offering a comprehensive suite of products and solutions. The company partners with technology giants such as Nvidia, AMD, Intel, and Samsung to deliver cutting-edge computing solutions. It is also one of the select original equipment manufacturers (OEMs) globally for designing and manufacturing the latest generation AI GPU systems in partnership with NVIDIA.

The company’s growth is further supported by favourable government policies such as the ‘Make in India’ and ‘Make AI in India’ initiatives, which have spurred demand for domestic manufacturing and AI infrastructure. Additionally, the global surge in sovereign AI infrastructure demand and increased supercomputing adoption across various sectors have provided significant business tailwinds.

Netweb Technologies has a strong footprint in India, with over 600 supercomputing systems installed and more than 7,000 accelerator/GPU-based AI systems deployed. The company has also achieved significant milestones, including the deployment of India’s fastest supercomputing system at VSSC, Trivandrum, and the commissioning of India’s flagship end-to-end, high-end SMT facility in Faridabad.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

Wipro launches AI-DC solution to accelerate enterprise-scale AI adoption

Arunika Jain — Fri, 20 Mar 2026 10:15:03 +0000

Wipro Limited has unveiled its Wipro AI-Data Center (DC) solution, designed to enhance enterprise-scale AI adoption and modernise data centre environments. The solution integrates NVIDIA‘s AI Enterprise within Wipro Intelligence™, offering a unified suite of AI-enabled solutions to transform customer experience operations.

The collaboration between Wipro and NVIDIA aims to move organisations beyond isolated AI pilots to enterprise-wide AI deployment. Satish Yadavalli, Global Business Head – Cloud, Infrastructure and Security Services at Wipro, highlighted the solution’s potential to support organisations in modernising data centres and preparing for AI-native workloads. The AI-DC solution, powered by NVIDIA, offers scalable, secure, and infrastructure-ready AI solutions.

John Fanelli, Vice President of Enterprise Software at NVIDIA, emphasised the challenges enterprises face in integrating AI into core data centre operations. He noted that the Wipro AI-DC solution provides the necessary operational model, governance, and secure scaling capabilities for businesses to industrialise intelligence across their organisations.

The AI-DC solution will also power an AI-driven contact centre agent assist solution, featuring NVIDIA NeMo™ and GPU-accelerated inference. This ensures low-latency, high-performance AI across distributed enterprise environments, delivering real-time transcription, contextual summarisation, and sentiment-aware engagement insights.

Wipro Partner Labs, part of the Wipro Innovation Network, supports the ecosystem developed on NVIDIA, extending AI enablement and scaling across enterprises. This collaborative model facilitates rapid co-creation and deployment of AI use cases, enabling innovations to move seamlessly from concept to production.

Available globally across industries such as telecommunications, banking, retail, and healthcare, the Wipro AI-DC solution reinforces Wipro’s leadership in AI-led infrastructure and data centre transformation services.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

LTM named NVIDIA Partner Network ‘Rising Star Consulting Partner of the Year’ at NVIDIA GTC 2026

Business Desk — Wed, 18 Mar 2026 02:25:13 +0000

LTM, a prominent global technology services and consulting company, has been honoured as the NVIDIA Partner Network (NPN) ‘Rising Star Consulting Partner of the Year’ at the NVIDIA GTC 2026. This accolade underscores LTM‘s robust collaboration with NVIDIA and its pivotal role in aiding enterprises to transition from AI experimentation to scalable, enterprise-ready adoption.

The NVIDIA Partner Network is a global ecosystem comprising technology and consulting partners who work closely with NVIDIA to deliver cutting-edge AI solutions. As an NPN partner, LTM collaborates deeply with NVIDIA, assisting clients in moving from AI pilot projects to enterprise-scale deployments. This involves integrating NVIDIA’s advanced AI technologies with LTM’s industry and domain expertise to drive tangible outcomes.

The Rising Star Consulting Partner of the Year award highlights LTM’s progress in delivering AI solutions that are production-grade, secure, and designed for enterprise scale. This recognition is a testament to the strength of LTM’s partnership with NVIDIA and their shared commitment to providing AI solutions that offer meaningful and measurable value to clients.

Venu Lambu, Chief Executive Officer and Managing Director of LTM, expressed the significance of being part of the NVIDIA Partner Network, stating, “Being part of the NVIDIA Partner Network is extremely meaningful because it places us at the centre of NVIDIA’s innovation ecosystem. Direct collaboration with NVIDIA’s innovators, product leaders, and experts enables us to rapidly build, refine, and scale enterprise-ready AI solutions, significantly accelerating the journey from concept to customer impact.”

As AI becomes integral to enterprise strategy, solutions built on NVIDIA’s trusted technology are opening new avenues for clients to innovate confidently, ensuring performance, security, and scalability. Through its collaboration with NVIDIA, LTM continues to support enterprises across various industries in adopting AI responsibly and at scale.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

Fractal introduces LLM Studio for enterprise-grade GenAI customisation with NVIDIA technology

Business Desk — Tue, 17 Mar 2026 07:26:35 +0000

Fractal has launched LLM Studio, a new platform designed to help enterprises build and manage domain-specific language models using NVIDIA AI infrastructure. The platform will be demonstrated at NVIDIA GTC 2026 in California.

LLM Studio is aimed at organisations seeking more control over their language models, offering tools for design, evaluation, and operation. It features AutoLLM for creating specialised models and LLMOps for managing their life cycle. The platform helps reduce costs and improve performance by using open-source models and NVIDIA’s technology.

“Enterprises are past the experimentation phase with generative AI. They need solutions that are governed, cost predictable, and reliable in production,” said Pranay Agrawal, CEO of Fractal.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

This article is written by Business Desk and reviewed by Aditya Bhagchandani before publication.

Persistent Systems launches AI-powered drug discovery solution with NVIDIA

Business Desk — Tue, 17 Mar 2026 07:02:24 +0000

Persistent Systems has announced a collaboration with NVIDIA to enhance AI-powered solutions for the Healthcare and Life Sciences industry. This partnership aims to accelerate computational drug discovery and improve research outcomes through the use of Generative AI and advanced analytics.

The initiative will leverage NVIDIA’s AI Enterprise platform to support specialised Life Sciences R&D applications, including preclinical research. Persistent’s new Generative Molecules and Virtual Screening solution, powered by NVIDIA’s BioNeMo platform, will facilitate high-fidelity molecular simulations and virtual screenings. This approach aims to streamline drug discovery workflows and improve the efficiency of early-stage research.

Persistent plans to utilise NVIDIA Nemotron open models to enhance its solution further. The company will also employ NVIDIA accelerated computing resources to develop scalable, production-grade AI applications. This infrastructure will support real-time scientific decision-making in regulated research environments.

Ganesh Nathella, Executive Vice President at Persistent, highlighted the importance of speeding up therapy discovery processes, while John Fanelli, Vice President at NVIDIA, emphasised the shift towards AI-driven research in the industry.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

L&T Technology Services launches NVIDIA-powered AI lung digital twin platform

Business Desk — Mon, 16 Mar 2026 10:39:48 +0000

L&T Technology Services has unveiled an AI-powered digital twin platform for advanced respiratory diagnostics, leveraging NVIDIA technology for enhanced precision.

The platform integrates with CT imaging workflows, using deep learning to create a 3D digital twin of the lungs. This allows clinicians to explore patient-specific lung anatomy in a digital environment, improving bronchoscopy and biopsy planning. Powered by NVIDIA’s AI infrastructure, the platform offers interactive 3D visualisation and optimised AI inference performance. It aims to transform static CT scans into dynamic lung models, enhancing surgical planning and procedural safety. The initiative reflects a shift towards predictive, simulation-driven intervention planning in respiratory care.

Disclaimer: This article is based on a regulatory filing submitted to the National Stock Exchange of India (NSE).

NVIDIA to collaborate with E2E Networks, L&T and Yotta to build advanced AI factories in India

Aman Shukla — Wed, 18 Feb 2026 05:19:00 +0000

NVIDIA has announced a collaboration with E2E Networks, Larsen & Toubro and Yotta to develop advanced AI factories in India, strengthening the country’s artificial intelligence infrastructure and cloud computing capabilities.

Under the arrangement, E2E Networks is building an NVIDIA Blackwell GPU cluster on its TIR cloud platform. The infrastructure will be hosted at the L&T Vyoma Data Center in Chennai, providing high-performance computing capacity tailored for large-scale AI training and inference workloads. The TIR cloud compute platform will feature NVIDIA HGX B200 systems, designed to handle complex AI models and enterprise-grade applications.

The deployment of Blackwell GPUs combined with HGX B200 systems is expected to enhance compute efficiency and enable faster processing for AI-driven services across public-sector institutions, financial systems and enterprise operations. The collaboration is positioned to support India’s growing demand for advanced data processing and AI model development within domestic cloud environments.

As part of the initiative, NVIDIA will introduce its Nemotron AI models to support multilingual services across government and enterprise use cases. The focus on multiple Indian languages aims to improve accessibility and scalability for digital services while enabling localized AI-driven automation.

In addition, NVIDIA is partnering with leading Indian venture capital firms, including Peak XV Partners, Elevation Capital, Accel, Z47 and Nexus Venture Partners, to identify and support promising AI startups that can leverage the new AI factory infrastructure.

Cantor Fitzgerald raises Nvidia price target to $300, the highest on Wall Street

Markets Desk — Thu, 09 Oct 2025 11:23:43 +0000

Cantor Fitzgerald has raised its price target for NVIDIA Corporation (NASDAQ: NVDA) to $300 from $240, maintaining an “Overweight” rating on the stock. The firm cited accelerating growth across the artificial intelligence (AI) ecosystem and strong confidence from NVIDIA’s leadership following a recent series of investor meetings in New York City.

In the report titled “On the Road with Jensen – Still Born to Run on Today’s AI Runaway American Dream,” Cantor analysts highlighted their discussions with NVIDIA’s executive team, including CEO Jensen Huang, CFO Colette Kress, and IR head Toshiya Hari. The meetings underscored management’s bullish outlook on the future of AI infrastructure and sustained demand from major technology partners.

“At a high level, a lot has changed from a year ago, with things moving at exponential speed,” wrote Cantor analyst C.J. Muse. “Jensen was quite bullish and with great reason, in our view. We are still in the early innings of a multi-trillion-dollar AI infrastructure build-out.”

Cantor’s report emphasized that the ongoing wave of AI investment—driven by hyperscalers, enterprise adoption, and emerging “Neo-Clouds”—continues to fuel NVIDIA’s growth trajectory. The firm believes that demand visibility extends well into the next several years, dispelling concerns of a near-term slowdown or market bubble.

As of October 9, 2025, NVIDIA shares trade at $189.11, with a 52-week range between $86.62 and $191.05. The company currently holds a market capitalization of approximately $4.6 trillion.

Cantor concluded that NVIDIA remains “born to run” in today’s AI-driven landscape, positioning it as a cornerstone of the next phase of digital transformation.

NVIDIA stock plunges 8% as on China’s tariff fears

Aditya Bhagchandani — Fri, 04 Apr 2025 18:43:28 +0000

NVIDIA Corp. (NASDAQ: NVDA) shares dropped sharply in Friday’s session, falling 7.9% to $93.76, down $8.05 from the previous close of $101.80. The drop erased billions in market capitalization, dragging the stock to one of its worst single-day performances in recent months.

The selloff comes amid a broader pullback in tech stocks as global markets reel from escalating tariff tensions and signs of economic slowdown. NVIDIA, a major beneficiary of the artificial intelligence boom, is now facing renewed scrutiny over its valuation amid rising macro uncertainty.

Key stock metrics as of April 4 (2:43 PM ET):

Current Price: $93.76
Previous Close: $101.80
Day’s Range: $92.11 – $100.13
Market Cap: $2.29 trillion
P/E Ratio: 31.95
Dividend Yield: 0.04%
52-Week Range: $75.61 – $153.13
Avg Volume: 295.62 million

Why is NVIDIA stock falling?

1. AI rally fatigue
After months of bullish momentum, the AI-driven tech surge appears to be losing steam. Investors are beginning to question whether chip demand will keep pace with lofty expectations. Analysts warn that continued outperformance in earnings is essential to justify NVIDIA’s high valuation multiples.

2. Broader tech market sell-off
Markets are grappling with the aftermath of U.S. President Donald Trump’s sweeping tariffs. The resulting fears of recession and tighter monetary policy have triggered a sell-off across high-growth sectors, including semiconductors.

3. Profit-taking
NVIDIA surged over 50% in the first quarter of 2025 alone. With mounting uncertainty and upcoming earnings season risks, traders are choosing to lock in profits.

NVIDIA’s next earnings call will be closely watched by investors looking for reassurance about the AI chip cycle’s longevity in an increasingly volatile market.

Mukesh Ambani & Sunil Mittal Partner with Big Tech Giants Like Google, Nvidia for AI & 5G Growth

Prakriti Mitra — Tue, 04 Mar 2025 10:43:13 +0000

Ambani & Mittal Join Forces with Big Tech for AI and 5G Expansion

India’s telecom giants Mukesh Ambani’s Reliance Jio and Sunil Mittal’s Bharti Airtel are forging strategic partnerships with global tech leaders like Google, Nvidia, and Microsoft to accelerate AI adoption, 5G expansion, and digital transformation in the country. This collaboration aims to leverage cutting-edge technologies to boost India’s telecom, cloud computing, and AI-driven industries.

Key Highlights of the Partnership

AI Integration: Companies plan to incorporate advanced AI solutions into telecom operations, enhancing automation and network efficiency.
5G & Cloud Computing: Reliance and Airtel are working with Google Cloud and Nvidia to develop scalable 5G applications and cloud-based solutions.
Digital Infrastructure: investments will focus on expanding data centres, AI-powered services, and telecom infrastructure across India.
Strategic Tech Support: Google, Nvidia, and other tech giants will provide AI models, cloud computing resources, and semiconductor advancements for next-gen innovations.

Impact on India’s Tech Ecosystem

The collaboration marks a major step in India’s ambition to become a global AI and digital powerhouse. With 5G rollouts in full swing, the focus is now shifting towards AI-driven telecom networks, smart cities, and enterprise solutions. Experts believe this partnership will:

Enhance digital connectivity, driving economic growth.
Boost AI-driven businesses, fostering new-age tech startups.
Create job opportunities in the telecom, AI, and cloud computing sectors.

Mukesh Ambani and Sunil Mittal’s partnership with big tech firms signifies India’s commitment to technological leadership. With AI and 5G as key growth drivers, the country is set to witness a transformational shift in its digital and telecom landscape.

Google cloud unveils sixth-generation trillium TPUs: A game-changer in AI performance and efficiency

Matrika Shukla — Sat, 28 Dec 2024 10:21:39 +0000

Google Cloud has officially rolled out its sixth-generation Tensor Processing Unit (TPU), branded as Trillium, marking a significant milestone in the evolution of artificial intelligence (AI) accelerators. The Trillium TPUs, designed to address the rising demands of large-scale AI workloads, bring major advancements in performance, energy efficiency, and scalability.

Initially announced in May, Trillium is now generally available (GA) and forms a key component of Google Cloud’s AI Hypercomputer, a next-generation supercomputer architecture. This system integrates high-performance hardware, open-source software, popular machine learning frameworks, and adaptable consumption models, offering a more cohesive AI ecosystem.

The introduction of Trillium TPUs comes with notable improvements to the AI Hypercomputer’s software layer, including optimized compilers like the XLA and popular frameworks such as JAX, PyTorch, and TensorFlow. These enhancements are designed to improve price-performance ratios in both AI training and inference tasks. Additionally, Trillium TPUs leverage features like host-offloading and high-bandwidth memory (HBM) for enhanced energy efficiency.

In terms of performance, Trillium delivers over four times the training performance and up to three times the inference throughput compared to its predecessor. The new generation boasts a 67% improvement in energy efficiency, making it not only faster but also more environmentally friendly, in line with the growing push for sustainable technology. Its peak compute performance per chip is 4.7 times higher than that of the previous generation, positioning it as an ideal solution for complex computational tasks.

Trillium TPUs have already proven their capabilities in training Google’s Gemini 2.0 AI model. An active discussion on Hacker News highlighted the long-standing use of Google’s TPUs in training deep learning models for ads, with capacity now potentially surpassing that of combined CPUs and GPUs.

While Nvidia currently dominates the AI data center chip market, holding 70% to 95% of the market share, Google’s TPUs continue to play a significant role in the AI ecosystem. Google does not sell these chips directly but instead offers access to them through its cloud platform, emphasizing the value of efficient AI technology over hardware alone.

With the GA release of Trillium TPUs, Google Cloud is setting a new benchmark for AI acceleration, promising faster, more efficient, and scalable solutions for the future of AI.

Reliance and Nvidia partner to build AI infrastructure in India

Aditya Bhagchandani — Thu, 24 Oct 2024 07:04:43 +0000

Nvidia is embarking on a series of partnerships with Indian firms to deploy its AI chips and technology, deepening its push into a key growth market. The U.S. chip designer’s CEO, Jensen Huang, announced that the company has partnered with Reliance, India’s most valuable company, to build infrastructure for AI applications in the country.

At Nvidia’s ongoing AI Summit event in Mumbai, Huang revealed that the company is also collaborating with Tech Mahindra to develop Indus 2.0, an AI model in Hindi, using Nvidia’s chips and software. Additionally, infrastructure providers Tata Communications and Yotta Data Services plan to purchase and use tens of thousands of Nvidia H100 chips by the end of the year.

Huang emphasized India’s potential in AI, stating, “India used to be a country that exported software. In the future, India will be a country that exports AI.”

Indian tech giants like Infosys and Wipro have been working with Nvidia to enhance their AI capabilities. Wipro has trained 225,000 employees on Nvidia’s AI platforms, while Tata Consultancy Services has trained 50,000 staff as AI associates. Nvidia’s developer program has attracted over 500,000 developers from India.

Furthermore, Indian e-commerce firm Flipkart and software provider Zoho plan to use Nvidia’s technology to build large language models in Hindi, further contributing to the AI ecosystem in India.

The partnership with Reliance Industries, which builds on existing collaborations to create large language models for Indian languages, includes plans for AI cloud infrastructure and training programs for employees. A few Indian startups, such as CoRover.ai, are already leveraging Nvidia’s technology—CoRover’s chatbot for Indian Railways handles 150,000 daily queries in multiple languages.

Nvidia is competing with rivals AMD and Intel for India’s expanding AI chip market, having already trained more than 100,000 Indian AI developers. This extensive engagement highlights Nvidia’s commitment to becoming a key player in India’s AI revolution.

NetApp partners with NVIDIA to transform enterprise AI with advanced RAG and agentic AI solutions

News Desk — Mon, 30 Sep 2024 07:30:04 +0000

NetApp’s end-to-end enterprise AI vision and intelligent ONTAP data infrastructure — combined with powerful NVIDIA NeMo Retriever and NIM microservices — transform how customers discover, search and curate data across hybrid multi-cloud to fuel AI applications

Bengaluru, India – September 30, 2024 – NetApp®️ (NASDAQ: NTAP), the intelligent data infrastructure company, today unveiled an advanced generative AI data vision and end-to-end integrated solutions that combine NVIDIA AI software and accelerated computing with NetApp intelligent data infrastructure for enterprise retrieval augmented generation (RAG) to power the future of agentic AI applications.

This will bring new capabilities to the NetApp ONTAP unified storage operating system that can leverage a new NetApp global metadata namespace to unify data stores for the tens of thousands of enterprises that trust NetApp for their data infrastructure. It opens up exabytes of enterprise data stored across clouds and on-premises infrastructure to drive RAG capabilities that can put enterprises’ entire data estate to work, accelerating next-generation agentic AI applications.

The solution brings together proven NetApp AIPod architecture with NetApp ONTAP and the NetApp BlueXP unified control plane, with NVIDIA NeMo Retriever and NIM microservices, which are part of the NVIDIA AI Enterprise software platform.

“To power AI applications and drive transformative progress for their business, enterprises must unlock the potential of their data,” said Harv Bhela, Chief Product Officer at NetApp. “Combining the NetApp data management engine and NVIDIA AI software empowers AI applications to securely access and leverage vast amounts of data, paving the way for intelligent, agentic AI that tackles complex business challenges and fuels innovation.”

“Data is fundamental to the evolution of generative AI,” said Manuvir Das, vice president, Enterprise Computing at NVIDIA. “By combining NVIDIA AI software and accelerated computing with NetApp intelligent data infrastructure, enterprises can turn their data into knowledge, and AI agents can turn that knowledge into action.”

With the new NetApp AI capabilities built into NetApp AIPod – certified for NVIDIA DGX BasePOD infrastructure and NVIDIA OVX solutions— and managed through BlueXP, NetApp customers will be able to easily discover, search, and curate data on-prem and in the public cloud based on a set of criteria, honouring existing policy-based governance criteria.

Once the data collection has been established through NetApp BlueXP, it can be dynamically connected to NVIDIA NeMo Retriever, where the dataset will be processed and vectorised to be accessible for enterprise GenAI deployments with appropriate access controls and privacy guardrails. This creates the foundation for a generative AI flywheel to power next-generation agentic AI applications that can autonomously and securely tap into data to complete a broad range of tasks to support customer service, business operations, financial services and more.

The end-to-end integration unlocks enterprise data for AI and takes a responsible approach by preserving the security and policy guardrails throughout the AI data and model lifecycle. This integration was first referenced as a proof-of-concept shown by Huang in his NVIDIA GTC 2024 keynote address. This secure and compliant GenAI integration will be available for customers to experience at NetApp INSIGHT today and is targeted to be released as a technology preview to customers later this calendar year.

NetApp has also begun the NVIDIA certification process of NetApp ONTAP storage on the AFF A90 platform with NVIDIA DGX SuperPOD, which will enable organisations to leverage industry-leading data management capabilities for their largest AI projects. This certification will complement and build upon NetApp ONTAP’s existing certification with NVIDIA DGX BasePOD. NetApp ONTAP addresses data management challenges for large language models, eliminating the need to compromise data management for AI training workloads.

Wipro expands AI capabilities through partnership with Dell and NVIDIA

Markets Desk — Tue, 27 Aug 2024 12:11:46 +0000

Wipro today has announced an expansion of its strategic collaboration with Dell Technologies, integrating Dell’s AI Factory with NVIDIA into Wipro’s Enterprise AI-Ready Platform. This partnership aims to enhance cost control and risk mitigation while accelerating AI adoption across cloud, data center, and edge environments.

The collaboration will leverage Dell AI Factory’s capabilities, including Dell Validated Designs for Generative AI, offering GenAI processing power without the need for extensive upfront investment. Supported by NVIDIA’s AI Enterprise software, H100 Tensor Core GPUs, and Spectrum-X Ethernet networking platform, Wipro’s AI-Ready Platform promises to deliver cutting-edge technology to enterprises.

Wipro has also introduced the Wipro AI Control Center as part of this initiative. The Control Center is an advanced orchestration layer that seamlessly integrates AI across IT and business functions, enhancing AI capabilities within the Dell infrastructure. This addition ensures smooth AI lifecycle management, from pilot to production, while maintaining sustainable governance, observability, and automation.

Jo Debecker, Managing Partner & Global Head of Wipro FullStride Cloud, emphasized the importance of this collaboration in enabling businesses to harness AI effectively. “Our goal is to make AI consumption as efficient, agile, reliable, and sustainable as possible—ultimately helping advance the adoption of enterprise-level AI,” Debecker stated.

Denise Millard, Chief Partner Officer at Dell Technologies, highlighted Dell’s role in the partnership, noting, “As the market demand for AI-enabled solutions continues to climb, Dell is innovating at every level of the AI technology stack to deliver future-proof data centers.”

The Dell AI Factory, integrated with NVIDIA technologies, is available for clients to experience at Wipro’s FullStride Cloud Studio in Bengaluru. The collaboration underscores Wipro’s commitment to advancing AI technology and providing enterprises with the tools needed to navigate the evolving digital landscape.

Here’s how to score an internship at Nvidia

Bhavya Rai — Sat, 10 Aug 2024 16:47:52 +0000

Nvidia is a top player in the fields of AI and semiconductors, making it a popular choice for job seekers. Known for its innovative work and attractive pay, getting an internship at Nvidia is tough but worth it. Linh Nguyen, who manages university recruitment at Nvidia, has shared some helpful advice for students who want to stand out and land an internship.

Nguyen emphasizes that it’s not just about having technical skills. Understanding Nvidia’s mission and showing a real enthusiasm for their technology are also crucial.

She notes, “I’m always impressed by students who truly get our company’s mission and its impact, or who have actually used Nvidia’s technology themselves,” as mentioned on the company blog.

Here are three key tips from Nguyen to boost your chances of securing an internship at Nvidia:

Get to Know Nvidia’s Work and Technology: Make sure you’re well-acquainted with Nvidia’s wide range of products, services, and projects. Check out their website and read what employees have to say about their work to get a clear picture of Nvidia’s influence and tech innovations.
Show Your Passion for Nvidia’s Tech: Successful applicants can clearly express why they’re excited about working at Nvidia and how their interests align with the company’s goals. Think about what specifically attracts you to Nvidia’s technology and use that in your application.
Quality Over Quantity: Instead of applying to many different roles, Nguyen suggests focusing on two or three positions that genuinely interest you and where you can really make a difference.

To find open internship positions, check out Nvidia’s University Recruiting Careers page. The recruitment process usually starts in the fall.

HPE and Nvidia team up on private cloud for Gen AI workloads

Bhavya Rai — Wed, 19 Jun 2024 13:29:14 +0000

Hewlett Packard Enterprise (HPE) has made several significant announcements aimed at addressing the increasing demands of artificial intelligence (AI), highlighted by the launch of a new private cloud solution.

Key Announcements from HPE

Collaboration with Nvidia

In a strategic partnership with Nvidia, HPE aims to accelerate the adoption of generative AI across highly regulated industries by providing a more private and controlled environment for AI deployment.

New Private Cloud AI Solution

Unveiled at the HPE Discover conference, the “Nvidia AI Computing by HPE” portfolio includes solutions and joint go-to-market integrations designed to speed up AI implementation for enterprises. Central to this portfolio is the launch of what HPE touts as the “first-of-its-kind turnkey, private-cloud AI solution.”

Features of the Private Cloud AI Solution

Deep Integration: This solution promises the deepest integration with Nvidia AI computing, networking, and software to date, along with access to HPE’s AI storage, compute resources, and the HPE GreenLake cloud platform.
Enterprise-Grade Control: It offers enterprise-level control over privacy and security, supporting various AI workloads including inference, fine-tuning, and retrieval-augmented generation (RAG) that leverage proprietary data.
Advanced Hardware Support: HPE also announced support for Nvidia’s latest GPUs, CPUs, and Superchips, including the HPE Cray XD670 server, which supports eight Nvidia H200 NVL Tensor Core GPUs tailored for large language model (LLM) builders.

Industry Impact and Availability

Addressing AI Complexity: HPE President and CEO Antonio Neri emphasized that this new solution aims to mitigate the risks and barriers posed by fragmented AI technologies, which have hindered large-scale enterprise adoption.
Enhanced AI Infrastructure: Nvidia CEO Jensen Huang highlighted that this collaboration represents an unprecedented level of integration between Nvidia and HPE technologies, combining Nvidia’s entire AI computing stack with HPE’s private cloud technology to offer cutting-edge computing infrastructure and services for enterprise clients and AI professionals.

Timeline for Release

Private Cloud AI Solution: Expected to become generally available in the fall, though no specific timeframe has been provided.
HPE Cray XD670 Server: Anticipated to go live over the summer.

HPE’s latest announcements, in partnership with Nvidia, mark a significant step towards enhancing AI deployment in regulated industries. The new private cloud AI solution promises to deliver a secure, integrated, and high-performance platform tailored to meet the complex demands of enterprise AI applications.

Stay tuned for more updates as HPE’s advanced AI solutions roll out later this year, potentially transforming how enterprises leverage AI technologies for innovation and growth.

Nvidia soars past Microsoft to become World’s Most Valuable Company

Sadhika — Wed, 19 Jun 2024 08:21:20 +0000

Nvidia has achieved a historic milestone, transcending tech giant Microsoft to become the world’s most valuable company. Nvidia’s stock surged 3.5% to $135.58, pushing its market capitalization to a staggering $3.34 trillion. This ascent marks a significant moment in financial history, as Nvidia, known for its cutting-edge AI chips, overtakes Microsoft’s $3.32 trillion and Apple’s $3.29 trillion in market value.

The AI Revolution Fuels Nvidia’s Growth

Nvidia’s meteoric rise is emblematic of the fervent optimism surrounding artificial intelligence (AI). The company’s high-performance processors are the cornerstone of the AI revolution, powering technologies from autonomous vehicles to sophisticated data analysis tools. Demand for these AI processors has outpaced supply, driving Nvidia’s stock to nearly triple in value this year, a feat unmatched by other tech heavyweights. In comparison, Microsoft’s shares have risen by 19%, while Apple’s have seen an 11% increase.

Nvidia’s Superior AI Chips Attract Tech Giants

The rapid appreciation in Nvidia’s market cap is fueled by its superior AI chips, which are considered unparalleled in the industry. This has led to a scramble among tech giants like Microsoft, Meta Platforms, and Alphabet to integrate Nvidia’s processors into their AI infrastructures. The resultant surge in demand has seen Nvidia’s revenue and profitability soar, consistently surpassing Wall Street’s high expectations.

Stock Split Democratizes Ownership and Boosts Value

Adding to its appeal, Nvidia recently executed a 10-for-1 stock split, significantly lowering the price per share and making it more accessible to individual investors. This move has not only democratized its ownership but also further bolstered its market value. As of late, Nvidia has become the most traded company on Wall Street, with daily trading volumes averaging $50 billion, dwarfing the $10 billion turnovers of Apple, Microsoft, and Tesla.

Nvidia’s Future as the World’s Most Valuable Company

Nvidia’s climb to the top is a milestone, highlighting the pivotal role of AI in shaping the future of technology and the stock market. As Nvidia continues to lead in AI development, its strategic decisions and technological advancements will be closely watched by investors and industry players alike.

The Nvidia RTX 5070 might come with an unexpected downgrade

Bhavya Rai — Tue, 11 Jun 2024 15:12:34 +0000

Rumors are circulating about Nvidia’s upcoming RTX 50-series GPUs, expected to begin rolling out later this year. Known leaker kopite7kimi shared specs for the full range of desktop cards on X (formerly Twitter), suggesting that the next generation might see a reduction in core count compared to the current generation.

Nvidia RTX 5070 Leaked Specs Overview

Core Counts and Memory Interface

The rumored core counts and memory interface details for the suspected range of GPUs are as follows:

GB202: 12*8, 512-bit GDDR7
GB203: 7*6, 256-bit GDDR7
GB205: 5*5, 192-bit GDDR7
GB206: 3*6, 128-bit GDDR7
GB207: 2*5, 128-bit GDDR6

Notable Changes

RTX 5070: Expected to feature the GB205 GPU with 50 Streaming Multiprocessors (SMs). For comparison, the AD104 GPU in the current RTX 4070 series has 60 SMs.
RTX 5060: Anticipated to use the GB207 GPU with 20 SMs, down from 24 SMs in the AD107 GPU used in the RTX 4060.

Understanding the Implications

GPU vs. Graphics Card Specs

It’s important to note that these are GPU specs, not final graphics card specs. Nvidia often trims down its GPUs for different models. For example, the AD104 GPU has 60 SMs, but the RTX 4070 only uses 46 SMs, with the RTX 4070 Ti using the full GPU core. A similar strategy could be applied in the next generation.

Memory Types

The rumored specs suggest that only the GB207 GPU will use GDDR6 memory, while the rest of the range will adopt the newer GDDR7 standard. This could position the RTX 5060 at a disadvantage compared to the rest of the series, given its reduced core count and older memory technology.

Market Context and Speculation

Performance and Architecture

Despite the rumored core count reductions, the new Blackwell architecture could bring significant performance improvements. Nvidia has yet to confirm any details about the RTX 50-series GPUs, but the architecture’s advancements may compensate for the lower core counts.

Release Timeline

There is still some uncertainty about the exact release date of the RTX 50-series. While some rumors suggest a launch later this year, others point to early 2025. Nvidia typically announces new desktop graphics cards during its fall Graphics Technology Conference (GTC) event, so the appearance of a fall GTC event on Nvidia’s calendar could indicate an imminent announcement.

The rumored specs for Nvidia’s RTX 50-series GPUs suggest potential downgrades in core counts for some models, but the impact on overall performance remains to be seen. With the introduction of the Blackwell architecture and the adoption of GDDR7 memory (except for the RTX 5060), Nvidia might still deliver substantial performance enhancements. As we approach the second half of the year, more concrete information is likely to emerge, especially around Nvidia’s GTC event.

Nvidia’s Spectrum-X Ethernet networking platform promises adaptive routing and congestion control

Bhavya Rai — Sat, 08 Jun 2024 12:56:41 +0000

Nvidia has unleashed a wave of excitement with the widespread embrace of its Spectrum-X Ethernet networking platform, coupled with an accelerated product launch schedule.

Diving into the technical realm, Nvidia touts Spectrum-X as the world’s inaugural Ethernet fabric tailored explicitly for artificial intelligence. With a staggering 1.6 times enhancement in generative AI network performance compared to conventional Ethernet fabrics, Spectrum-X encompasses the Spectrum SN5600 Ethernet switch and the BlueField-3 SuperNIC. This dynamic duo furnishes the indispensable performance and features requisite for generative AI clouds to thrive.

Speaking at the Computex keynote in Taiwan, Nvidia’s visionary founder and CEO, Jensen Huang, revealed the company’s ambitious blueprint of rolling out fresh Spectrum-X offerings on an annual basis. These cutting-edge products promise ramped-up bandwidth, expanded port arrays, and fortified software functionalities and programmability, all primed to spearhead AI Ethernet networking performance.

The timing of Spectrum-X’s arrival couldn’t be more intriguing. Sporting adaptive routing and congestion control mechanisms, Spectrum-X ensures maximum bandwidth utilization and noise isolation, thereby guaranteeing predictable outcomes across a multitude of simultaneous AI workloads, irrespective of scale.

The roster of Nvidia partners swiftly jumping on the Spectrum-X bandwagon is impressive, featuring heavyweights like ASRock Rack, Asus, and Gigabyte, who join stalwarts such as Dell, Hewlett Packard Enterprise, and Lenovo in seamlessly integrating the platform into their offerings.

In a bold declaration, Gilad Shainer, Nvidia’s senior vice president of networking, emphasizes the pivotal role of networking innovation in driving business competitiveness, especially in the face of groundbreaking technologies like generative AI. According to Shainer, Nvidia Spectrum-X is the linchpin for businesses aiming to fully harness the transformative potential of their AI infrastructures, thereby reshaping entire industries.

Yet, amidst this buzz, Nvidia’s announcement intersects with a fascinating narrative. As behemoths like Microsoft, Google, and Meta strive to lessen their reliance on Nvidia’s technology, the unveiling of UALink, an open industry standard alternative to Nvidia’s NVLink, underscores the shifting landscape of AI hardware innovation.

In the dynamic world of AI, Nvidia’s Spectrum-X stands as a beacon of progress, heralding a new era of Ethernet networking tailored explicitly for the demands of artificial intelligence.

How to Invest directly in NVIDIA stock from India

News Desk — Thu, 23 May 2024 02:30:34 +0000

As an Indian investor, you may be interested in tapping into the growth potential of NVIDIA (NASDAQ: NVDA), a company that has been making waves in the tech industry. With its impressive financial results and surging stock price, NVIDIA has become the 3rd largest public company globally, with a market capitalization that has surpassed the combined value of Tesla and Amazon, and even the entire German stock market.

If you’re looking to gain direct exposure to NVIDIA stock, here are some options available to Indian investors:

Open an International Trading Account To invest in NVIDIA stock directly, you’ll need to open an international trading account through platforms such as Groww, Angel One, or others. This process involves submitting your bank account details and completing the necessary Know Your Customer (KYC) documentation.
Choose a Brokerage Platform Once your international trading account is set up, you can access NVIDIA stock through global brokerage platforms like Charles Schwab, Ameritrade, or Interactive Brokers. These platforms will allow you to buy and sell NVIDIA shares.
Consider Mutual Funds If you prefer a more diversified approach, you can invest in Indian mutual fund schemes that offer exposure to NVIDIA stock. Some options include Motilal Oswal Nasdaq ETF, Kotak Nasdaq 100 Fund of Funds, and Mirae Asset NYSE FANG ETF. As of January 2024, Indian mutual funds had a total exposure of nearly Rs 1699 crore in NVIDIA, with an additional Rs 980 crore through ETFs.

NVIDIA’s recent financial performance has been impressive, with the company reporting revenue of $22.1 billion for the first quarter of fiscal 2025, representing a 22% increase from the previous quarter and a 265% year-over-year growth. This strong performance has contributed to the stock’s upward trajectory, leading to a market cap that is only 17% away from overtaking Apple.

Reasons to Invest in NVIDIA:

Exposure to the AI Revolution: NVIDIA’s GPUs are essential for powering artificial intelligence (AI) applications, which are experiencing rapid growth. As companies invest in building data centers to support AI, NVIDIA’s business has flourished.
Dominance in the GPU Market: NVIDIA holds a strong position in the GPU market, which is projected to reach $773 billion by 2032. As the demand for GPUs continues to rise, NVIDIA is well-positioned to benefit.
Innovative Products: NVIDIA is continuously innovating, with plans to launch the H200 GPU in Q2 2024, which is expected to double the computing capacity compared to the current H100 model. This will drive upgrades and further solidify NVIDIA’s leadership in the GPU market.
Long-term Growth Potential: Despite the significant growth in NVIDIA’s stock price, it still trades at a reasonable forward price-to-earnings (P/E) ratio compared to other tech giants like Microsoft, suggesting that there is still room for steady, market-beating growth in the long run.

Risks and Considerations:

Volatility: NVIDIA’s stock can be volatile and may experience short-term losses.
Dependence on Gaming Market: While NVIDIA’s AI and data center businesses are growing rapidly, the company still relies heavily on the gaming market. A slowdown in gaming-related spending could impact NVIDIA’s performance.
High Expectations: With NVIDIA’s stock price already soaring, there are high expectations for the company’s future performance. Failure to meet these expectations could lead to a correction in the stock price.

Before making any investment decisions, it’s crucial to carefully consider your financial goals, risk tolerance, and conduct thorough research. Investing in NVIDIA stock can be an attractive option for Indian investors looking to gain exposure to the AI and GPU markets, but it’s essential to weigh the potential risks and rewards.

Nvidia’s Blackwell platform set to revolutionize AI with trillion-parameter Models

Tushar Aggarwal — Tue, 19 Mar 2024 10:37:12 +0000

Nvidia’s Blackwell platform is poised to revolutionize AI initiatives for companies, with major players like AWS, Microsoft, Google, Meta, Dell Technologies, and OpenAI gearing up to accelerate their AI endeavors.

Nvidia has been at the forefront of innovation, particularly with its invention of the graphics processing unit (GPU) in 1999, which revolutionized computer graphics and sparked the growth of the PC gaming market. Fast forward to today, Nvidia’s solutions are driving the era of modern AI, with groundbreaking chips like the H100 powering the training of large language models, including OpenAI’s GPT4.

Nvidia experienced significant breakthroughs in AI and generative AI (Gen AI), leading CEO and Founder Jensen Huang to predict that it would become the world’s first trillion-dollar semiconductor stock.

At Nvidia’s annual GTC conference, the company unveiled its latest generation Blackwell platform, designed to enable organizations worldwide to build and run real-time generative AI on trillion-parameter large language models at a fraction of the cost and energy consumption compared to its predecessor. The Blackwell GPU architecture boasts six transformative technologies for accelerated computing, promising breakthroughs in various domains, including data processing, engineering simulation, drug design, and Gen AI.

The conference also saw the introduction of Nvidia’s latest HGX B200 and HGX B100 chips, set to propel data centers into a new era of accelerated computing and Gen AI. These chips offer up to 15 times more inference performance than the previous generation and are tailored for demanding generative AI, data analytics, and high-performance computing (HPC) workloads.

Named in honor of mathematician David Harold Blackwell, the first Black scholar inducted into the National Academy of Sciences, Nvidia’s Blackwell architecture succeeds the Hopper architecture. Major technology companies like AWS, Dell Technologies, Google, Meta, Microsoft, OpenAI, Oracle, Tesla, and xAI are expected to adopt Blackwell.

Google Cloud and Nvidia announced an expanded partnership at GTC to empower the machine learning (ML) community with technology that accelerates the development of Gen AI applications. Similarly, AWS will offer Nvidia GB200 Grace Blackwell Superchip and B100 Tensor Core GPUs to extend their collaboration, providing customers with advanced infrastructure, software, and services to unlock new Gen AI capabilities.

Nvidia’s collaboration with AWS dates back over 13 years, and today, AWS offers the widest range of GPU solutions in the cloud. The partnership aims to make AWS the best platform for running Nvidia GPUs in the cloud, with joint efforts like Project Ceiba combining Nvidia’s next-generation Grace Blackwell Superchips with AWS Nitro System’s advanced virtualization and networking capabilities for AI research and development. Through ongoing innovation, Nvidia and AWS continue to push the boundaries of what’s possible in AI computing.

Nvidia’s unrivaled ascension in the artificial intelligence landscape

Girish Linganna — Sun, 03 Mar 2024 12:30:02 +0000

According to the Economist, no company has gained as significantly from the artificial intelligence (AI) explosion as Nvidia. The chipmaker’s stock value has experienced a remarkable increase of nearly 450% since January 2023. Nvidia’s market capitalisation is nearing $2 trillion, positioning it as the third-largest company in the United States, trailing only behind Microsoft and Apple.

For the latest quarter, Nvidia reported revenues of $22 billion, a significant increase from $6 billion in the corresponding quarter of the previous year.

The majority of analysts anticipate that Nvidia, holding over 95% of the specialist AI chip market, is poised for rapid expansion in the coming years. What sets its chips apart?

Originally developed for video gaming, Nvidia’s AI chips, commonly referred to as graphics processor units (GPUs) or “accelerators,” have found a broader application.

Nvidia’s chips operate using a method known as parallel processing. This technique involves splitting up a complex calculation into smaller pieces, and then simultaneously processing these pieces across numerous “cores” — which can be thought of as the chip’s mini-brains. This approach allows the chip to handle multiple tasks at the same time, significantly speeding up the processing of data and making the chips highly efficient for tasks requiring intense computation, such as AI and gaming.

This approach enables a GPU to perform calculations much quicker than if it were to process tasks one after the other. Such a method is perfectly suited for gaming, where creating realistic graphics necessitates the simultaneous rendering of numerous pixels on the screen. Nvidia’s top-tier chips currently make up 80% of the gaming GPU market.

Fortunately for Nvidia, its chips have discovered a broader array of applications beyond their original purpose, including cryptocurrency mining, autonomous vehicles, and most notably, the training of AI models.AI is powered by machine-learning algorithms that utilize a subset of deep learning known as artificial neural networks. Within these networks, computers can identify rules and patterns by analyzing extensive datasets.

Algorithms are step-by-step instructions or rules designed to perform specific tasks or solve problems, used in computing to process data and make decisions.

Deep learning is a type of machine learning where computers learn from examples in a way similar to human learning. It uses artificial neural networks, which are designed to imitate the human brain, to help computers understand data, recognize patterns, and make decisions.

Educating a network requires vast amounts of computations. However, since these tasks can be divided into smaller segments, utilizing parallel processing significantly accelerates the process. A high-end GPU possesses over a thousand cores, enabling it to execute thousands of calculations concurrently.

Upon recognizing the high efficiency of its accelerators in training AI models, Nvidia shifted its focus towards tailoring them for this specific market. The company’s chips have evolved to match the growing complexity of AI models, achieving a 1,000-fold enhancement in computational speed over the decade leading up to 2023.

Nvidia’s skyrocketing value isn’t solely due to the enhanced speed of its chips. Its advantage also spans two additional domains, including networking. As AI models become increasingly complex, the data centers operating them require thousands of GPUs linked together to amplify computational capacity, whereas most computers typically utilize just a few.

Nvidia links its GPUs using a high-speed network built on technology from Mellanox, a networking technology provider it purchased in 2019 for $7 billion. This integration enables Nvidia to enhance the performance of its chip network in a manner unmatched by its rivals.

Another key advantage for Nvidia is CUDA, a software platform that enables users to precisely adjust the performance of its processors. Nvidia has been developing this software since the mid-2000s and has actively promoted its use among developers for creating and experimenting with AI applications. As a result, CUDA has become the recognized industry standard.

Nvidia’s substantial profit margins, coupled with the swift expansion of the AI accelerator market—expected to hit $400 billion annually by 2027—have drawn the attention of competitors. Companies like Amazon and Alphabet are developing their own AI chips for use in their data centers.

Other major chip manufacturers and startups are eyeing a portion of Nvidia’s market share. In December 2023, Advanced Micro Devices (AMD), a rival chipmaker, launched a chip that, by certain metrics, is approximately twice as potent as Nvidia’s most sophisticated chip.

However, surpassing Nvidia in hardware alone might not suffice. Nvidia leads the AI chip industry due to its superior chips, networking equipment, and software. For any rival aiming to overtake this semiconductor giant, excelling in all three domains is necessary. Achieving this is a formidable challenge.

(The author Girish Linganna of this article is a Defence, Aerospace & Political Analyst based in Bengaluru. He is also Director of ADD Engineering Components, India, Pvt. Ltd, a subsidiary of ADD Engineering GmbH, Germany. You can reach out to him at: girishlinganna@gmail.com)

Nvidia unveils new AI-Enhanced GPUs for professional use

Tushar Aggarwal — Tue, 27 Feb 2024 10:02:47 +0000

Nvidia, a leading technology company known for its graphics processing units (GPUs), has announced its latest offerings in the AI-enhanced GPU market — the RTX 500 and RTX 1000. These GPUs are designed to meet the increasing demand for AI technology integration in professional settings, offering enhanced performance and capabilities for a wide range of applications.

The new GPUs are built upon Nvidia’s Ada Lovelace architecture, which is known for its high performance and efficiency. While Nvidia’s previous GPU series, such as the RTX 2000 through 5000, have been popular among gamers, the RTX 500 and RTX 1000 are specifically targeted towards professionals who require advanced AI capabilities for their work.

One of the key features of the RTX 500 and RTX 1000 GPUs is their focus on high-quality video conferencing. With more professionals working remotely, the demand for high-quality video calls has increased significantly. These new GPUs offer enhanced video processing capabilities, ensuring that video calls are clear, crisp, and free from lag or distortion.

Another important feature of the RTX 500 and RTX 1000 GPUs is their AI-driven image upscaling capabilities. This feature allows professionals to upscale images and videos to higher resolutions, making them suitable for large displays or high-resolution printing. This is particularly useful for professionals working in fields such as graphic design, photography, and video editing.

In addition to video conferencing and image upscaling, the RTX 500 and RTX 1000 GPUs offer a range of other features designed to streamline workflows and improve productivity. These include advanced rendering capabilities, real-time AI processing, and support for advanced graphics technologies such as ray tracing and DLSS.

Internally, the RTX 500 and RTX 1000 GPUs feature significant upgrades over their predecessors. They include third-generation ray tracing cores, fourth-generation Tensor Cores, Ada generation CUDA cores, DLSS 3, and an AV1 encoder. These upgrades result in improved performance and efficiency, making the new GPUs ideal for professional use.

Nvidia has announced that the RTX 500 and RTX 1000 GPUs will be available in collaboration with major laptop manufacturers such as Dell, Lenovo, and HP. Laptops equipped with these GPUs are expected to hit the market sometime this spring, offering professionals a powerful and efficient tool for their work.

Honor’s AI Era Revolution: Open collaboration and Tech giant Partnerships

Tushar Aggarwal — Sun, 25 Feb 2024 14:30:28 +0000

In a announcement at the 2024 Global Conference in Barcelona, Spain, Honor unveiled its ambitious vision for the AI era with a focus on openness and collaboration. Under the theme “Embracing the Future with Open Collaboration,” Honor outlined its strategy to revolutionize AI technology and create an open ecosystem that delivers unparalleled experiences for consumers.

Central to this strategy is Honor’s all-scene approach to AI, which aims to accelerate the realization of AI-enabled interconnection and interoperability across all aspects of daily life. At the core of this approach is a commitment to human-centered interaction, ensuring that AI technology enhances and enriches the lives of users.

Key to Honor’s strategy is its partnership with tech giants including Microsoft, Google, Intel, NVIDIA, and Qualcomm. This collaboration has resulted in significant advancements, including a 25% reduction in power consumption, a 500% increase in network speed, and the achievement of 8-way business concurrency. Users can now seamlessly share networks, screens, keyboards and mice, cameras, windows, files, calls, and notifications across devices and platforms.

One of the most exciting developments is the introduction of Honor MagicOS 8.0, which brings an innovative function driven by platform-level AI. This enables intelligent prediction of user interaction intent across applications, delivering a personalized, humanized, and privacy-protected experience unlike any other.

With this bold strategy and groundbreaking partnerships, Honor is poised to lead the charge into a new era of AI-driven innovation. By empowering users with seamless connectivity and personalized experiences, Honor is setting new standards for the future of technology.

Microsoft’s strategic Shift: Developing own networking hardware to boost AI Speeds

Tushar Aggarwal — Wed, 21 Feb 2024 17:10:51 +0000

Microsoft’s recent endeavor to develop its own networking hardware could signal a significant shift in the landscape of artificial intelligence (AI) infrastructure. The company is reportedly working on its own network cards to enhance the performance of its Maia AI server chip, a move that could reduce its reliance on Nvidia and potentially supercharge AI speeds.

The project, reportedly led by Pradeep Sindhu, Corporate Vice President of Silicon at Microsoft and CEO of Fungible (a server chip startup acquired by Microsoft in 2023), aims to optimize the performance of Microsoft’s Maia AI server chip. This chip is crucial for supporting large language models (LLMs) and AI computing, areas where Microsoft has been heavily investing, including its backing of OpenAI, the organization behind the popular ChatGPT AI chatbot.

By developing its own network cards similar to Nvidia’s ConnectX-7 card, Microsoft could achieve several key objectives. Firstly, it could reduce the time required for training AI models on Microsoft servers, improving cost efficiency and potentially enhancing the performance of AI applications. Secondly, it could decrease its reliance on Nvidia, which currently provides many crucial components for AI infrastructure.

This move comes at a time when Microsoft and Nvidia are both major players in the AI space. Microsoft’s Maia chip and its investments in OpenAI demonstrate its commitment to advancing AI technology. Meanwhile, Nvidia’s GPUs are widely used for AI training and have contributed significantly to the company’s market value.

While Microsoft’s development of its own networking hardware may not immediately impact Nvidia’s position, it could have long-term implications. By diversifying its hardware offerings and reducing reliance on external suppliers, Microsoft could strengthen its position in the AI market and potentially disrupt Nvidia’s dominance.

Microsoft’s move underscores the growing importance of AI infrastructure in the tech industry. As AI applications become more prevalent, companies are seeking ways to optimize their AI infrastructure to improve performance and reduce costs. Developing custom networking hardware could be a strategic move for Microsoft to stay ahead in the rapidly evolving AI landscape.

In conclusion, Microsoft’s decision to develop its own networking hardware for AI applications is a bold strategic move that could have far-reaching implications. By reducing its reliance on Nvidia and optimizing its AI infrastructure, Microsoft aims to supercharge AI speeds and solidify its position as a leader in the AI space.

Nvidia’s Jensen Huang: AI sparks a new Industrial Revolution worldwide

Tushar Aggarwal — Tue, 13 Feb 2024 05:02:46 +0000

In the ever-evolving landscape of technology, few advancements have captured the world’s imagination and potential like artificial intelligence (AI). Jensen Huang, the visionary founder of Nvidia, is at the forefront of this AI revolution, envisioning a future where AI transforms industries and societies on a global scale. With Nvidia’s graphics processing units (GPUs) powering the AI revolution, Huang’s insights offer a compelling glimpse into the transformative power of AI technology.

Describing AI as the harbinger of a new industrial revolution, Huang emphasizes the global ‘awakening’ to AI’s potential across countries and industries. In Huang’s view, Nvidia has played a pivotal role in democratizing AI computation infrastructure, making it accessible to researchers, companies, and governments worldwide. However, Huang emphasizes that the responsibility now lies with individual countries to seize the initiative, activate their industries, and build the necessary infrastructure to harness AI’s transformative potential fully.

Central to Huang’s vision is the notion of codifying language and cultural data into large language models, laying the foundation for AI-driven innovation and creativity. By investing in AI infrastructure and empowering researchers in diverse domains, countries can unlock unprecedented opportunities for AI-driven breakthroughs in areas such as language processing, biology, physical sciences, climate research, robotics, and manufacturing.

Huang underscores the importance of recognizing AI’s multifaceted nature, highlighting the myriad domains where AI revolutions are underway simultaneously. From language processing to the study of proteins and chemicals, from climate research to the Internet of Things (IoT) and robotics, AI is revolutionizing diverse fields with its transformative capabilities. By building robust AI infrastructure, countries can activate researchers across these domains, driving innovation and progress in their respective industries.

The democratization of AI infrastructure, according to Huang, is not only feasible but also essential for countries looking to compete in the digital age. Drawing parallels with the internet and agriculture, Huang emphasizes that AI infrastructure is a fundamental enabler of digital transformation, akin to the essential role played by the internet in today’s digital economy. Without AI infrastructure, countries risk falling behind in the race for technological advancement and innovation.

Moreover, Huang challenges the perception of AI as a mystifying and complex technology, asserting that AI is fundamentally about computation and data analysis. By leveraging off-the-shelf hardware and existing expertise, countries can accelerate their AI initiatives and capitalize on the transformative potential of AI technology. Huang’s pragmatic approach underscores the accessibility of AI infrastructure and the importance of concerted efforts to activate AI research and development globally.

As countries embark on their AI journeys, Huang’s roadmap provides a clear path forward, emphasizing the need for strategic investment in AI infrastructure and the cultivation of a vibrant AI ecosystem. By codifying language, investing in research, and fostering collaboration across industries, countries can unlock the full potential of AI and usher in a new era of innovation and progress.

Jensen Huang’s vision of AI as the catalyst for a new industrial revolution underscores the transformative potential of this groundbreaking technology. With Nvidia’s GPUs driving AI innovation, Huang advocates for a global ‘awakening’ to AI’s possibilities and urges countries to seize the opportunity to build AI infrastructure and unlock unprecedented opportunities for progress and prosperity. As the world embraces AI-driven transformation, Huang’s insights offer valuable guidance for countries seeking to harness the power of AI to drive innovation, economic growth, and societal advancement on a global scale.

Indian AI Industry to boom with Reliance & NVIDIA collaboration

Sidharth Badlani — Fri, 08 Sep 2023 12:58:54 +0000

Reliance Industries Limited, which is run by billionaire Mukesh Ambani, said on September 8 that it would collaborate with American chipmaker NVIDIA to enhance artificial intelligence in India.

India’s goals for artificial intelligence and semiconductor chips are being advanced by the alliance. In addition, the collaboration will support the creation of an indigenous foundation large language model that is designed for generative Al applications and trained on the variety of national languages.

In accordance with the agreement, NVIDIA will offer Jio end-to-end AI supercomputer technology, including CPU, GPU, networking, and AI operating systems and frameworks for creating the most sophisticated AI models. Jio will be in charge of consumer interaction and access as well as managing and maintaining the AI cloud infrastructure.

According to specifics, data centres that can extend to 2,000 MW would host the AI infrastructure.

Jensen Huang, CEO and founder of NVIDIA, said, “We are happy to cooperate with Reliance to construct cutting-edge Al supercomputers in India.

India has talent, scale, and data. Reliance can create its own huge language models that power generative Al apps built in India, for the people of India, using the most cutting-edge computing resources, he continued.

According to the report, the most recent development in the business world supports Reliance’s goal of acting as a sizable, comprehensive digital, cloud, and networking platform for both consumers and business clients.

Nvidia hits $1 Trillion market cap

Aditya Bhagchandani — Tue, 30 May 2023 13:41:24 +0000

Nvidia, the renowned chipmaker, briefly reached a market capitalization of $1 trillion as trading commenced on Tuesday. This milestone placed Nvidia in the exclusive club of predominantly technology companies that have achieved such a feat. To maintain this distinction throughout the day, Nvidia’s shares needed to remain above $404.86.

The surge in Nvidia’s stock price can be attributed to its impressive quarterly earnings report, which surpassed consensus estimates on both the top and bottom lines. This remarkable performance not only boosted Nvidia but also had a positive impact on other chipmakers, with the exception of Intel. Additionally, Nvidia’s optimistic forecasts contributed to the stock’s rise, as the projected sales for the fiscal second quarter of 2024 alone were 50% higher than the consensus estimates of $7.15 billion, amounting to $11 billion.

The chip industry, as well as the technology sector as a whole, has experienced a prosperous year, partly driven by the growing excitement around artificial intelligence (AI) and the potential slowdown in Federal Reserve rate hikes. Nvidia’s success resonated with other tech giants such as Alphabet, Meta, and Microsoft, which also saw their stocks surge in last week’s trading.

Nvidia’s graphics processing units (GPUs) play a critical role in generative AI platforms like OpenAI’s ChatGPT and Google’s Bard. While GPUs were historically associated with intensive gaming, the rise of cryptocurrency mining and AI applications has revolutionized their perception. As a result, GPU manufacturers and suppliers like Nvidia, AMD, and TSMC have witnessed substantial increases in their share prices in recent months.

As AI boom drives stellar forecasts, Nvidia is on the verge of becoming the first trillion-dollar chip company

Avinash Ram — Fri, 26 May 2023 03:53:45 +0000

Highlights :

The share price of Nvidia reached a record high in premarket trading.
The positive profits spurred a surge in the semiconductor industry, and Alphabet
Microsoft, and AMD all saw gains of between 2 and 8 percent.

The rise of generative artificial intelligence (AI) is everything, everywhere, at once, according to Nvidia.

The stock of the chip designer increased by 25% on Thursday as a brilliant projection revealed that Wall Street has not yet priced in the AI potential of the business, which has already doubled in value by 2023.

Nvidia was expected to increase its market valuation by around $189 billion (about Rs. 15,63,914 crore) to $945 billion (nearly Rs. 78,19,572 crore), causing its shares to reach an all-time high in premarket trade.

Stock markets from Japan to Europe rose as a result of the positive earnings, which also prompted a surge in the semiconductor industry and AI-focused companies. Companies including Alphabet, Microsoft, and AMD had gains of between 2 and 8 percent in the US.

In a hurry, analysts increased their price targets for Nvidia stock, with 21 analysts changing their opinion that the business holds the key to the future of AI since it supplies the processors that enable ChatGPT and several other services of a similar nature.

“In the more than 15 years we have been in this business, we have never seen a guide like the one Nvidia just put up with the second-quarter outlook that was by all accounts cosmological, and which annihilated expectations,” said Stacy Rasgon of Bernstein.

On Wednesday, Nvidia, the fifth-most valuable US firm, forecast quarterly revenue that was more than 50% higher than Wall Street expectations. The company also stated that it will have more AI chips available in the second half of the year to satisfy increased demand.

A $1 trillion (approximately Rs. 82,74,230 crore) of present equipment in data centres would need to be replaced with AI chips when generative AI is integrated into every good and service, according to CEO Jensen Huang.

The results are encouraging for Big Tech firms, who have moved their attention to AI in the belief that the technology could boost demand at a time when their key revenue generators, cloud computing and digital advertising, are under pressure from a sluggish economy.

“This Nvidia forecast transforms the entire narrative surrounding artificial intelligence and demand projections in the industry. Nvidia is the important barometer, and there may be a historical turning point in the AI Revolution, according to Dan Ives of Wedbush.

Check out details of the launch of Nvidia GeForce RTX 4060 Ti and GeForce RTX 4060

Kashvi Basu — Thu, 18 May 2023 20:05:07 +0000

Nvidia GeForce RTX 4060 and GeForce RTX 4060 Ti which were launched by the company on Thursday as the company’s premier graphics cards built on the current-gen Ada Lovelace architecture. The more powerful GeForce RTX 4060 Ti is available in 8GB and 16GB memory configurations, while the RTX 4060 model is available with 8GB of memory. Both models support Nvidia’s deep learning super sampling for over 300 games as well as upcoming titles such as The Lord of the Rings: Gollum and Diablo IV.

The company has announced at the new GeForce RTX 4060 Ti graphics card is 1.7 times faster than the GeForce RTX 3060 Ti model. It is equipped with 8GB or 16GB of GDDR6 video memory, along with 32MB of L2 cache. Meanwhile, the GeForce RTX 4060 model has 24MB of L2 cache and is available in a single 8GB memory configuration. Actually, these chips are intended for gamers, video editors, 3D artists, and other content creators such as broadcasters, who will see 40 percent better encoding efficiency, with the eighth NVENC video encoder from Nvidia. Similarly, 3D artists will see 45 percent faster performance over last year’s RTX 3060 GPU series, according to Nvidia. It says that the new GPUs based on the company’s Ada Lovelace architecture are equipped with third-generation ray tracing (RT) cores and fourth-generation Tensor cores — the latter are aimed at speeding up artificial intelligence tasks, including Nvidia’s own framerate-multiplying DLSS 3 technology. It has further improved itself by adding shade execution reordering, opacity micromap, and displaced micro-mesh engines to improve ray tracing performance over the previous generation.

The initial pricing for the Nvidia GeForce RTX 4060 Ti starts at Rs. 41,000 for the model with 8GB of video memory, and will go on sale on May 24. The RTX 4060 Ti 16GB variant is priced at Rs. 51,000 and will go on sale in July, along with the RTX 4060 GPU with 8GB of memory, which is priced at Rs. 31,000. For comparison, pricing for the Nvidia GeForce RTX 4070 Ti starts at Rs. 80,000 while the RTX 4070 starts at Rs. 62,000.

Nvidia reports net profit of $3 billion in Q4

Vineet Jain — Thu, 17 Feb 2022 13:30:21 +0000

Nvidia Corp. reported record quarterly earnings throughout its business and forecasted a further increase in the current quarter as it moves on from its unsuccessful buyout offer for semiconductor-design specialist Arm Ltd.

The graphics-chip producer reported $7.64 billion in revenue in the most recent quarter, a 53 percent increase over the same period last year. It reported $3 billion in net profitability, more than double the previous year’s figure, and above Wall Street projections in both revenue and gross sales.

Semiconductor manufacturers are seeing strong demand as more products and services become chip-dependent. The insatiable need for food has resulted in a global chip scarcity, which some executives anticipate will last until 2024, and has had a mixed impact on the industry. It has hurt chip sales since customers such as automotive and computer manufacturers have had to postpone selling their products while they await missing components, but it has also driven up prices for some semiconductors.

Nvidia, located in Santa Clara, Calif., said its expected revenue for the current quarter to be about $8.1 billion, which is higher than the $8.1 billion predicted by analysts polled by FactSet. Nvidia monetary head Colette Kress stated on a conference call with analysts that knowledge-centre and videogame revenues are expected to be the primary drivers of the hike.

Nvidia’s stock ended at $265.11 on Wednesday, down less than 1% after the company reported its quarterly results. During the pandemic, the company saw a strong period of revenue growth as videogame consumption increased and more consumers and businesses began using digital services that depend on data centres.

Nvidia’s key gaming business increased revenue by 37% year on year, while data-centres revenue increased by 71%. Automobile sales, on the other hand, fell 14% year on year, with supply-chain restrictions continuing to weigh on auto manufacturing and automakers phasing out certain older equipment that employs Nvidia processors.

Ms. Kress stated that Nvidia anticipates automotive earnings to rebound in the current quarter and pick up pace in the second half of the fiscal year.

Earlier this week, the chipmaker announced a collaboration with carmaker Jaguar Land Rover to develop software-heavy cars. Nvidia Chief Executive Officer Jensen Huang stated on the choice that new automobiles with self-driving programs and other services employing synthetic intelligence from the cooperation should begin appearing in 2025.

Nvidia has also witnessed fluctuations in demand from crypto miners, who have typically utilized its video cards to generate digital currency. Last year, the company released a microprocessor aimed at meeting market demand. Income from its bitcoin chip was $24 million in the third quarter, up from nearly nothing the previous year but far less than the $105 million made by the machine in the previous quarter.

Nvidia decided to abandon its acquisition of Arm last week in the face of regulatory scrutiny.

Nvidia agreed to buy Arm from SoftBank Group Corp. for $40 billion in September 2020, in what would have been the biggest acquisition in the semiconductor industry’s history. The Federal Trade Commission moved to halt the deal in December. Officers at the U.S. Department of Justice had also launched an investigation into whether the proposed transaction was anticompetitive.

Nvidia acquires 90% stake in Arm Ltd

Aditi Swarup — Mon, 14 Sep 2020 08:56:32 +0000

American multinational technology company, Nvidia has acquired a 90% stake in the semiconductor and software design company Arm.
Analysts and reports suggest that this will come with a lot of resistance from Arm’s customers. Arms customers include Intel Corp, Qualcomm Inc, Samsung Electronics Co, and Apple iPhones.
This is primarily because this deal will bring Arm under the jurisdiction of the United Staes and might hamper Arm’s open policy of licensing its designs to customers.
Reportedly the sale took place for $40 billion.

Nvidia’s $40 billion agreement to acquire Arm Ltd from SoftBank is likely to meet strong opposition from its chip industry rivals, according to analysts https://t.co/ubLrnDdDHa pic.twitter.com/7JuxNeAuEc

— Reuters Business (@ReutersBiz) September 14, 2020

Nvidia to buy $40 Billion Chipmaker Arm from SoftBank in $12 Million cash

Apurva Khairnar — Mon, 14 Sep 2020 06:12:05 +0000

Softbank group said that it has agreed to sell chip designer Arm to Nvidia in a $40 billion deal, this deal is set to reshape the semiconductor landscape. Nvidia will pay SoftBank $21.5billion in shares and $12 million in cash, including $2 billon on signing.

The deal puts a vital supplier to Apple and others across the industry under the control of a single player. Nvidia is the leading maker of GPU’s which Arm also designs, but other than its Tegra line of mobile chipsets used in devices like the Nintendo switch.

Nvidia CEO said he will retain Arm’s neutral licensing model and expand it y licensing out Nvidia intellectual property for the first time. Nvidia will license its flagship graphical processor unit through Arm’s network of silicon partners.

Softbank could also be paid an additional $5 billion in cash or shares depending on the chip designer’s business performance, with Arm employees to be paid $1.5 billion in Nvidia shares

The deal is subject to regulatory approvals including in Britain, United States and China and is expected to close in March 2022.

SoftBank to sell UK’s Arm Holdings to Nvidia for over $40bn: Reports

News Desk — Sun, 13 Sep 2020 08:12:47 +0000

SoftBank will reportedly sell the UK’s Arm Holdings to US chip company Nvidia for over $40bn, a few years after its founder Masayoshi Son bought the chip designer.

Sources revealed a cash-and-stock takeover of Arm Holdings by Nvidia may be announced as soon as possible, and that SoftBank will become the largest shareholder in the US chip company.

Nvidia, known for its graphics chips, also developed for other markets including AI, self-driving cars, and data centres.

For the American multinational technology company, this deal will further consolidate the company’s position at the centre of the semiconductor industry.