Dr. Wednaud J Ronelus

The launch of an AI supercomputer marks a transformative step in Denmark’s 🇩🇰 technological infrastructure, setting a powerful precedent for countries worldwide. A supercomputing infrastructure similar to #Denmark’s #Gefion from NVIDIA offers Latin America a roadmap to leverage #AI for transformative economic, social, and environmental impacts. Historically, Latin American countries have struggled with barriers to innovation, including limited access to advanced computing power and infrastructure. By embracing a future where AI and supercomputing are accessible, #latam - as a region- 🔮 could level the playing field with more advanced economies, facilitating new growth and innovation opportunities within a global economy increasingly shaped by digital transformation. The multiplier effect of these developments—enhanced innovation capacity, employment growth, and higher GDP contribution—could be profound. Access to advanced computing resources could transform Latin America’s academic landscape, enabling institutions to lead research that addresses local and global challenges To overcome the knowledge gap, educational institutions must prioritize training in AI and advanced computing, creating a workforce equipped to utilize this infrastructure effectively. This infrastructure will not merely power algorithms and data processing—it will power the future. But ⚠️⚠️⚠️ It cannot happen at a country level and cannot happen without a significant private-public collaboration effort. So if we miss this new opportunity it is not because of lack of infrastructure- it will be because a lack of vision, collaboration and leadership… again 😓 #artificialintelligence #latam #leadership

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🌍 The Generative AI Revolution: Transforming Society and Human Interaction (NVIDIA CEO Jensen Huang) A monumental shift in computing that will reshape the way we live, work, and interact. 🤝💻 1. From Retrieval to Generation: A Paradigm Shift ### The #Past: Retrieval-Based Systems 🗄️ - Information was static, pre-recorded, or written down - Recommender systems retrieved relevant data from existing sources - Limited to the knowledge and insights already stored ### The #Future : Generative Computing 🚀 - Starts with a seed of information (prompt) as a catalyst - Generates novel content, ideas, and solutions based on the prompt - Mimics human intelligence, creativity, and adaptability 2. The Societal Impact of Generative Computing Consider the dynamic nature of human conversation. Most of what we communicate is generated in the moment, not retrieved from memory. This is the essence of #intelligence – and it's coming to #computing ! 🧠💬 ### How Generative Computing Will Transform Our World 1. 🌐 Revolutionizing #communication and collaboration 2. 🩺 Accelerating scientific discovery and #healthcare innovation 3. 🎓 Transforming #education and learning experiences 4. 🏭 Optimizing industries and driving economic #growth 5. 🌇 Enhancing urban planning and smart city #development 3. Embracing the Generative Future As we embrace highly generative computing, we're not just accessing #information – we're creating #knowledge, #insights, and #solutions that were previously unimaginable. This shift holds the key to unlocking human potential on an unprecedented scale. 🔓🌟 💡How do you envision generative computing transforming your life, work, and community? Share your thoughts in comments 👇 #ArtificialIntelligence #Innovation

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15 #Graphs That Explain the State of #AI in 2024 https://lnkd.in/ecKsa3EE #fintech #ArtificialIntelligence #MachineLearning #GenerativeAI #GenAI IEEE Spectrum

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https://lnkd.in/eXbCsAnD “He who controls the GPUs, controls the universe.” Access to GPUs, and in particular those made by Nvidia, the leading supplier, is vital for any company that wants to be taken seriously in #ai. Nvidia’s dominance has driven its market value to more than $2trn. 'GPUs do the computational heavy-lifting needed to train & operate large #ai models. Yet, oddly, this is not what they were designed for. The initials stand for “graphics processing unit”, because such chips were originally designed to process video-game graphics. It turned out that, fortunately for Nvidia, they could be repurposed for #ai workloads. 'Might it be better to design specialist ai chips from scratch? That is what many companies, small & large, are now doing in a bid to topple Nvidia. Dedicated ai chips promise to make building and running ai models faster, cheaper or both. Any firm that can mount a credible threat will have no shortage of customers, who dislike its lofty prices and limited supplies. 'GPUs contain several thousand processing engines, or “cores”, which let them run thousands of versions of the same simple task at the same time. Running #ai models similarly involves running lots of copies of the same task in parallel. Figuring out how to rewrite ai code to run on GPUs was one of the factors that triggered the current ai boom. 'Yet GPUs have their limitations, particularly when it comes to the speed with which data can be shuffled on and off them... When training very large #ai models, some GPu cores may be idle as much as half of the time. Andrew Feldman, the boss of Cerebras, a startup based in Sunnyvale, CA, likens it to the gridlock in a grocery store on the day before Thanksgiving. “Everybody’s in a queue, so there are blockages in the parking lot, there are blockages in the aisles, blockages at the checkout. That’s exactly what’s happening with a gpu.” 'Cerebras’s response is to put 900,000 cores, plus lots of memory, onto a single, enormous chip, to reduce the complexity of connecting up multiple chips & piping data between them. 'Groq, a startup from Mountain View, CA, is taking a different approach. Its ai chips, called language processing units (lpus), are optimised to run #llms particularly quickly. 'Yet another approach is that taken by MatX, also based in CA. GPUs contain features & circuitry that provide flexibility for graphics, but are not needed for llms. The firm is working on getting rid of such unnecessary cruft.

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The worlds of #cryptocurrencies and #largelanguagemodels have converged, well at least from a #hardware perspective and #cost. While the #mining hardware still sells for thousands of dollars for the well known #antiminer by BITMAIN, NVIDIA has just announced project #digits at #ces2025. The tiny #computer priced at $3000 will provide #researchers, #ai practitioners will all the juice they need to run AI models with billions of parameters. Details of the impressive hardware can be found in the image below. Although the festive season is over, this is one gift I would not refuse, isn't it NVIDIA? On another note, #nvidia is slowly tapping into the #tesla territory with its #cosmos platform, that uses synthetic #data and #reinforcementlearning to enable what they call #physicalAI and allow #autonomous devices.

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Merging AI and crypto could lead to a new era of blockchain-enabled AI, which prioritizes privacy and unlocks powerful new applications, argues Felix Xu https://lnkd.in/g5avFEEc

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#JensenHuang, the founder and CEO of #NVIDIA, and #MarkZuckerberg, the founder and CEO of #Meta, recently engaged in a public fireside chat at the 51st edition of the SIGGRAPH graphics conference. During this discussion, they explored several key topics: #AI and Simulation: The two leaders delved into the future of AI and simulation. They highlighted how fundamental research plays a pivotal role in enabling breakthroughs in artificial intelligence. Graphics and Virtual Worlds: The conversation centered around the intersection of graphics and technology. They discussed how generative AI and open-source software empower developers and creators, particularly in the context of building virtual worlds. #OpenSourceAI: Mark Zuckerberg announced the launch of “AI Studio,” a new platform that allows users to create, share, and collaborate on AI projects. This platform aims to democratize AI development and foster innovation. #TechnologicalInnovation: The SIGGRAPH conference has a rich history of technological innovation. It introduced groundbreaking demos and research papers, shaping the field of computer graphics. Attendees explored startups at the forefront of computing and graphics, showcasing advancements in diverse fields like robotics, manufacturing, and climate science. In summary, their discussion highlighted the transformative potential of AI, the importance of research, and the role of graphics in shaping our technological future. If you’d like more details, you can find the full chat available for replay on #NVIDIA’s website. #SIGGRAPH The #SIGGRAPH (Special Interest Group on Computer Graphics and Interactive Techniques) conference is an annual event organized by the Association for Computing Machinery (ACM). 👉Here are some key points about SIGGRAPH: ➡️History: #SIGGRAPH has a rich history, starting in 1974. It has become one of the most influential conferences in the field of computer graphics and interactive techniques. ➡️Main Conference: The primary SIGGRAPH conference is held in North America. It serves as a platform for researchers, practitioners, and industry experts to share their latest work, innovations, and insights. ➡️SIGGRAPH Asia: In addition to the main conference, SIGGRAPH Asia is another significant event. It has been held annually since 2008 in various countries across Asia. ➡️Content: SIGGRAPH conferences feature cutting-edge content, including technical papers, art exhibitions, production sessions, panels, courses, and emerging technologies. Attendees can explore the latest advancements in computer graphics, animation, virtual reality, and interactive media. ➡️Community: The SIGGRAPH community fosters collaboration, education, and progress. It’s a place where creative minds come together to shape the future of technology and visual arts. This year, SIGGRAPH 2024 has taken place in Denver, Colorado. #NvidiaTechBlogs #AiBlogs #Meta ##SIGGRAPH

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Nvidia's Blackwell AI Processors Are Sold Out For Next 12 Months Nvidia (NVDA) executives say production of the company's next-generation artificial intelligence processors, called Blackwell, is progressing on schedule and that the product is sold out for the next 12 months. Morgan Stanley analyst Joseph Moore said in a client note Thursday. “Every indication from management is that we are still early in a long-term AI investment cycle," he said. "The clear view continues to be that we are set up for an exceptionally strong 2025." Moore reiterated his overweight, or buy, rating on Nvidia stock with a price target of 150. Further, NVDA stock is his top pick among semiconductor companies. On the stock market today, Nvidia stock advanced 1.6% to close at 134.81. Elsewhere on Wall Street, Evercore ISI analyst Mark Lipacis maintained his outperform rating on Nvidia stock with a price target of 150. At the event, Nvidia said eight partners are currently bringing Blackwell systems to market. The company also said it is on target to reach volume production in the fourth quarter, Lipacis said. In a keynote presentation at the Nvidia AI Summit on Tuesday, Bob Pette, Nvidia's vice president and general manager of enterprise platforms, highlighted how Nvidia accelerated computing is transforming industries like health care, cybersecurity and manufacturing. Credit: investors business daily

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Exciting to see how Generative AI is expanding beyond art and creative industries! SignLLM, a project creating Sign Languages Production Large Language Models, is using automated generative AI sign avatars from Prompt2Sign datasets to assist language-impaired individuals. This innovation is revolutionizing the field of medicine and therapeutics for the hearing impaired, enhancing their everyday experiences. Moreover, this advancement enables seamless translation of sign language into standard and voice video formats. I'm proud that the University of Texas at Dallas, my old college is contributing to this impactful research. #generative #AI Check out the groundbreaking work by SignLLM here: https://signllm.github.io

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A new AI model from OpenAI, called o3, achieved human-level performance on the ARC-AGI benchmark, scoring 85%—significantly surpassing the previous AI best of 55%. #ai #agi #openai

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Wining #AI with Open Source (#GenAI) By open-sourcing a model that rivals proprietary giants, Nvidia isn’t just sharing code—it’s challenging the very structure of the AI industry. The open source model you choose depends on its value proposition and market convergence? So, which one you choose? #comment #innovation #strategy

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Just saw this: https://lnkd.in/gRWMBiPi CUDA is making the jump to becoming standard in the chip industry with this. That's significant, because CUDA is nVidia's secret sauce that gives them such an advantage in the ML space.

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One of the more reasonable articles about the various types of ML/AI and where they might be useful in practical application. Finneran’s Second Law of Compute: The outcome benefit must outweigh the costs. Success = DV > DR Data Value greater than Data Risk. https://lnkd.in/g4Xe6BpX?

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Crypto 101 - Mapping Groups: Adding, Subtracting, Multiplying, Dividing and Exponentiation: https://lnkd.in/e3sSYqpp

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