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Medium
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“How NVIDIA Dominated the AI Revolution and Became a Key Industry Leader”
- NVIDIA, founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, initially aimed to revolutionize computer graphics.
- Their breakthrough came in 1999 with the invention of the GPU, starting with the GeForce 256, which transformed visual computing.
- NVIDIA's GPUs, designed for parallel processing, proved crucial beyond gaming, especially for AI tasks due to their computational power.
- The introduction of CUDA in 2006 allowed GPUs to be used for general-purpose computing, paving the way for AI applications by accelerating complex operations.
- NVIDIA capitalized on the deep learning boom with innovations like Tensor Cores and high-bandwidth memory, setting new standards in AI hardware.
- The company's focus on building a comprehensive AI ecosystem with CUDA, cuDNN, and strategic investments positioned them as a leader in AI technology.
- NVIDIA's involvement in generative AI with products like ChatGPT powered by thousands of GPUs has driven unprecedented demand and revenue growth.
- Despite competition and challenges from rivals, NVIDIA's dominance in AI is supported by its entrenched CUDA ecosystem and innovative approach.
- NVIDIA's future lies in advancing AI applications across industries like healthcare, autonomous vehicles, and climate modeling, solidifying its legacy.
- By recognizing the broader potential of GPUs, investing in AI, and embracing change, NVIDIA has not just adapted but spearheaded the AI revolution.
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Insider
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Jensen Huang's quantum mea culpa didn't convince Nvidia GTC panelists that he felt bad for trashing the tech
- Nvidia's GTC featured Quantum Day, with Jensen Huang highlighting the field.
- Huang termed the event as an apology for his earlier dismissive comments on quantum tech.
- Some panelists remained unconvinced of his contrition, as the market impact was already felt.
- The GTC panels included discussions among executives from various quantum computing companies and researchers.
- Huang's previous comments had caused quantum stocks to plummet over 60%.
- Some panelists appreciated the global exposure for quantum tech, while others questioned Huang's sincerity.
- Huang's attitude towards the timeline and utility of quantum computing was a point of concern among panelists.
- Various quantum companies announced advancements at GTC, with a focus on technical approaches.
- Panelists discussed potential renaming to 'quantum processing' for better consumer understanding.
- Despite Huang's efforts to apologize, quantum stocks are yet to fully recover from the impact of his comments.
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Insider
7d
320
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The historical figures who inspired Nvidia's product names, from Grace Hopper to David Blackwell
- Nvidia's AI chips are named after notable mathematicians and scientists.
- Some of the historical figures include Grace Hopper, a computer scientist and mathematician.
- David Blackwell, a mathematician and statistician, also inspired Nvidia's chip names.
- Other figures include Ada Lovelace, known as the mother of programming, and Vera Rubin, an astronomer who provided evidence of dark matter.
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Fourweekmba
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Image Credit: Fourweekmba
The AI Value Chain
- The AI industry is structured in layers, starting from hardware to cloud infrastructure, AI models, vertical AI applications, and consumer apps/hardware.
- Key players in AI hardware include NVIDIA, Google, AMD, Intel, and startups like Cerebras, Graphcore, and Hailo.
- Leading cloud AI providers are AWS, Microsoft Azure, Google Cloud, IBM Cloud, and Oracle Cloud.
- Key players in AI models include OpenAI, DeepMind, Microsoft, Hugging Face, and Run:ai.
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Siliconangle
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Image Credit: Siliconangle
Nvidia GTC takeaway: AI will follow the data
- At Nvidia's GTC keynote, CEO Jensen Huang discussed AI in the context of cloud, data centers, and robotics, emphasizing the importance of data locality.
- The rise of a new computing era driven by extreme parallel processing and accelerated computing is transforming the trillion-dollar data center business.
- Data center spending grew significantly in 2024, with AI workloads seeing a substantial increase while traditional workloads declined.
- During market transitions like the shift to AI workloads, companies must adapt quickly to align with new conditions and technologies to succeed.
- David Floyer's methodology analyzes technology adoption based on value, volume, and velocity, offering insights into market transitions.
- Upcoming analysis will focus on the AI inference at the edge of networks and the robotic opportunity, aiming to quantify the potential market.
- Quantifying the massive AI market will aid in forecasting the transition to accelerated workloads and drive better understanding of emerging technologies.
- Disclosure: Statements made regarding companies are views held by SiliconANGLE Media and should not be considered as investment advice.
- SiliconANGLE co-founder, John Furrier, emphasizes the importance of community support to provide free, relevant content in the industry.
- Community support is vital for platforms like TheCUBE to continue delivering valuable content and insights from industry experts.
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Insider
1w
96
Image Credit: Insider
Nvidia CEO Jensen Huang joked about something that could cost his biggest customers billions of dollars
- Nvidia's new Blackwell GPUs make older Hopper models less useful, affecting cloud giants.
- Rapid tech advancements may force cloud giants to adjust asset depreciation, denting earnings.
- Amazon leads in adjusting server lifespan, Meta and Google could see profit hits.
- Nvidia CEO Jensen Huang jokingly mentioned that Blackwell GPUs would make Hoppers undesirable, causing potential problems for big customers.
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Insider
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230
Image Credit: Insider
5 big takeaways from Nvidia's GTC conference
- Nvidia's GTC conference has evolved to cover advancements in AI, robotics, and quantum computing, becoming a significant event for the tech industry.
- The event highlighted Nvidia's shift to an AI infrastructure company selling 'AI factories' and emphasized the importance of revenue generation for all in the AI ecosystem.
- With Nvidia at the forefront of AI innovation, the company sets benchmarks for technological possibilities and performance in the industry.
- The pace of AI model innovation has accelerated, with new paradigms emerging every six months, driving urgency and focus in the ecosystem.
- While robots were featured at the conference, there is still progress to be made before widespread adoption, with Nvidia working on open-source models to accelerate development.
- Quantum computing took center stage at the conference, with Nvidia hosting its first Quantum Day and highlighting the technology's potential in various sectors.
- Contributions from companies like Microsoft, Amazon Web Services, Google, D-Wave, IonQ, and Rigetti showcased progress in quantum computing at the event.
- Nvidia's commitment to future Quantum Days at GTC indicates a growing focus on quantum computing advancements in the tech sector.
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The Robot Report
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Recap: Check out the robots at Promat and GTC 2025
- In Episode 188 of The Robot Report Podcast, co-hosts Steve Crowe, Mike Oitzman, and Eugene Demaitre recap robotics encountered at ProMat 2025 and NVIDIA GTC 2025.
- Steve and Gene attended ProMat in Chicago, while Mike attended GTC in San Jose, CA.
- The podcast provides a timeline of the show, with Steve and Gene recapping ProMat and Mike recapping GTC.
- The episode also highlights robot demos, such as Agility Robotics Digit humanoid and 1X NEO humanoid at GTC 2025, as well as Disney Engineering BDX robots.
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Pymnts
1w
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Image Credit: Pymnts
This Week in AI: Apple’s Siri Struggles, AI Agent-to-Agent Payment Systems
- Apple struggles with AI upgrades for Siri and demotes its top executive in charge of Siri upgrades.
- Nvidia CEO Jensen Huang predicts that the next stage of AI will require 100-fold more computing power.
- Hollywood voices concern over AI and intellectual property issues, urging the US government to protect copyright laws in AI model training.
- Goldman Sachs is focusing on scaling AI capabilities across its business, with plans to adopt and utilize AI at a larger scale by 2025.
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Siliconangle
1w
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Image Credit: Siliconangle
Quest for qubits: Quantum computing leaders make their case at Nvidia GTC
- Quantum computing is gaining attention as a potential revolutionary technological change, similar to the rise of artificial intelligence.
- At Nvidia GTC conference, discussions around quantum computing highlighted the challenges and possibilities in the field.
- Nvidia CEO's remarks about the timeline for useful quantum computers led to a debate among quantum industry leaders.
- Companies like D-Wave, Quantum Inc., Quantinuum Inc., and IonQ Inc. are exploring different approaches to harness quantum power.
- Efforts include using qubits for computational processing and developing quantum computers on a chip for accelerated computing.
- Error correction is a significant challenge in quantum computing, with research focusing on using AI algorithms for accuracy.
- The future of quantum computing holds promises for scientific research, drug discoveries, and applications requiring massive computing power.
- The industry's focus is on increasing qubit capacity, with investments in quantum computing startups on the rise.
- Quantum's impact on various industries and the need for continuous technological advancements were emphasized at the conference.
- Overall, there is optimism about quantum computing's future despite the complexities and challenges involved in its development.
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The Robot Report
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Sanctuary AI uses NVIDIA Isaac Lab to accelerate robot training
- Sanctuary AI uses NVIDIA Isaac Lab to accelerate robot training.
- Sanctuary AI uses NVIDIA Isaac Lab to simulate dexterity-focused training environments and train its hydraulic hands.
- Isaac Lab uses PhysX for physics simulation and RTX rendering to bridge the gap between simulation and perception-based robot training.
- Sanctuary AI can use simulation to train thousands of hands at once, drastically accelerating the learning process.
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Pcgamesn
1w
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Nvidia RTX 5090 laptop demo doubles RTX 4090 frame rates, but there’s a catch
- Laptop gamers could benefit from Nvidia GeForce RTX 5090 gaming GPUs.
- A benchmark demo showcases a significant performance boost for the laptop RTX 5090 over the RTX 4090.
- Nvidia DLSS 4 upscaling improvements and multi-frame generation contribute to the performance difference.
- The comparison highlights the potential of Nvidia's software improvements for gaming laptops.
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Sdtimes
1w
114
Image Credit: Sdtimes
Mar 21, 2025: AI updates from the past week — Anthropic web search, Gemini Canvas, new OpenAI audio models, and more
- Anthropic's Claude can now search the web to generate up-to-date and relevant responses, citing web sources for fact-checking.
- Google launches Canvas to facilitate collaboration with Gemini, offering an interactive space to create and refine code.
- OpenAI introduces new speech-to-text and text-to-speech models for enhanced voice agent capabilities, including improved transcription quality.
- Nvidia announces AI advancements at GTC, such as AI-Q Blueprint and Llama Nemotron open reasoning AI models.
- IBM Research reveals the Agent Communication Protocol (ACP) for standardized agent communication, enhancing interoperability and development simplicity.
- Oracle introduces AI Agent Studio for creating, extending, and managing AI agents within the Oracle Fusion Cloud Applications Suite.
- WSO2 updates AI-powered IDP Choreo with customizable CI pipelines, AI-driven cost insights, and other new features.
- Stravito enhances its generative AI assistant with Focus Mode for deep analysis, Snapshots for instant report summaries, and support for over 100 languages.
- These AI updates represent advancements in various aspects of AI technology, catering to developers and enterprises seeking innovative AI solutions.
- The developments aim to streamline processes, enhance collaboration, improve user experience, and enable more efficient use of AI in different applications.
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Siliconangle
1w
273
Image Credit: Siliconangle
Nvidia partners with Equinix to deliver ready-made AI factories
- Nvidia partners with Equinix to deliver ready-made AI factories.
- Equinix will manage Nvidia's Instant AI Factory, a service for building AI-ready data centers in a short time frame.
- The partnership will provide preconfigured facilities in over 45 markets worldwide to effectively scale up and manage infrastructure solutions.
- Nvidia's latest generation of DGX SuperPOD, the DGX GB300, incorporates Grace Blackwell Architecture, aiming to democratize companies' AI deployment.
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Digitaltrends
1w
332
Image Credit: Digitaltrends
The RTX 50-series is the worst GPU launch in recent memory
- The RTX 50-series GPU launch by Nvidia is considered the worst in recent memory.
- The grandiose claims made at CES 2025 for RTX 50 series were not met with actual performance.
- The RTX 50 series failed to deliver the promised performance, with only marginal improvements over the previous generation.
- The GPUs in the RTX 50 series faced issues like stock shortages and inflated prices, making them inaccessible to many gamers.
- Reports of melting power cables and connectors in the RTX 50 series GPUs have raised safety concerns.
- Some Nvidia GPUs in the RTX 50 series have hardware defects, leading to performance issues for affected users.
- The delay in launching more affordable RTX 50-series cards and limited stock availability have frustrated consumers.
- Nvidia's decision to stop production of the 40-series GPUs before the 50 series launch caused shortages and price hikes.
- AMD's RX 9000 GPUs provided a more stable and reasonably priced alternative to Nvidia's troubled RTX 50 series.
- Gamers are advised to wait for stock levels to improve before investing in either Nvidia's RTX 50 series or AMD's RX 9000 GPUs.
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