Campbell North’s Post

NVIDIA AI Introduces Nemotron-4 340B: A Family of Open Models that Developers can Use to Generate Synthetic Data for Training Large Language Models (LLMs) https://lnkd.in/duMwAe74 NVIDIA AI Introduces Nemotron-4 340B: A Family of Open Models Practical Solutions and Value NVIDIA’s Nemotron-4 340B offers practical solutions for generating synthetic data to train large language models (LLMs) across various commercial applications. It provides developers with cost-effective and scalable means to access high-quality training data, crucial for enhancing the performance and accuracy of custom LLMs. Key Features Includes Instruct, Reward, and Base models tailored for data generation and refinement Boasts impressive specifications, such as a 4k context window and training in over 50 programming languages Requires significant computational power, including 16x H100 GPUs in bf16 and approximately 8x H100 in int4 configurations Customization and Optimization The models can be fine-tuned using proprietary data and various datasets to adapt to specific use cases. They are optimized for inference using the NVIDIA TensorRT-LLM library, enhancing efficiency and scalability. Model Security and Evaluation The Instruct model undergoes rigorous safety evaluations, including adversarial testing, to ensure reliability across various risk indicators. Users are advised to evaluate the model outputs thoroughly to ensure the synthetic data generated is safe and accurate. Accessibility and Integration The models are accessible on platforms like Hugging Face and will soon be available as an NVIDIA NIM microservice with a standard API. They are seamlessly integrated with NVIDIA NeMo, an open-source framework supporting end-to-end model training. Conclusion NVIDIA’s Nemotron-4 340B represents a significant advancement in AI, providing developers with powerful tools to create high-quality training data. This innovation is set to drive advancements in AI across various industries, enabling the development of more accurate and effective language models. AI Solutions for Your Company Discover how AI can redefine your way of work, identify automation opportunities, define KPIs, select an AI solution, and implement gradually. For AI KPI management advice and insights into leveraging AI, connect with us at hello@itinai.com or stay tuned on our Telegram and Twitter channels. Practical AI Solution Consider the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. List of Useful Links: AI Lab in Telegram @itinai – free consultation Twitter – @itinaicom #NVIDIA #AI #syntheticdata #languageModels #Nemotron4#artificialintelligence #ai #machinelearning #technology #datascience #python #deeplearning #prog...

🙌 Generative AI Supercomputing for Millions of Businesses & Devs by NVIDIA & Hugging Face! I’m excited to share some amazing news from NVIDIA and Hugging Face, two of the leading companies in the field of generative AI and large language models (LLMs). 🚀They have announced a partnership that will make it easier and faster for developers to build and customize LLMs for various applications, such as chatbots, search and summarization. NVIDIA and Hugging Face will integrate NVIDIA DGX Cloud, a multi-node AI supercomputing platform, with the Hugging Face platform, a collaboration hub for the machine learning community. This will enable developers to access NVIDIA’s powerful AI computing resources with just one click, and train and tune their models with their own data on the Hugging Face platform. 💪 Hugging Face will also offer a new service called Training Cluster as a Service, powered by DGX Cloud, that will simplify the creation of new and custom generative AI models for the enterprise. This service will be available in the coming months. This collaboration will help supercharge industry adoption of generative AI using LLMs that are custom-tailored with business data for industry-specific applications. It will also empower the next generation of machine learning engineers, scientists and end users to learn, collaborate and share their work to build an open and ethical AI future together.🌎 If you are interested in learning more about this partnership and how it can benefit your AI projects, you can watch #NVIDIA CEO Jensen Huang's SIGGRAPH keynote here: https://lnkd.in/gbVdtbYE I think this is a great opportunity for anyone who wants to explore the potential of generative AI and LLMs. What do you think? Let us know in the comments! #ai #llm #generatieveai #aiadvancements #huggingface

At a USD 3.34 trillion valuation, #Nvidia is the highest-valued company bypassing #Microsoft. This remarkable achievement offers two key lessons: 𝗗𝗼𝗺𝗶𝗻𝗮𝗻𝗰𝗲 𝗶𝗻 𝗘𝗺𝗲𝗿𝗴𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: Those who lead in future technologies command significant influence and value today. From the invention of firearms expanding colonial powers to today's advancements in GPUs for data processing, technological leadership has always propelled success. 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻: Advancement within your industry can catapult your success, irrespective of your current position. Nvidia exemplifies this, transforming from a gaming-centric company to a leader in the AI industry through a strategic focus on AI and data centers. It is an example of the power of innovation and adaptation. I often hear startup founders discussing how to capitalize on the current market. 𝗛𝗼𝘄𝗲𝘃𝗲𝗿, 𝗶𝘁’𝘀 𝗰𝗿𝘂𝗰𝗶𝗮𝗹 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗲 𝗮 𝗺𝗮𝗿𝗸𝗲𝘁 𝗯𝘆 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗶𝗻𝗴 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗻𝗼 𝗼𝗻𝗲 𝗵𝗮𝘀 𝘆𝗲𝘁 𝗿𝗲𝗰𝗼𝗴𝗻𝗶𝘇𝗲𝗱. By pioneering new technologies and addressing unseen challenges, you can shape the future and achieve unparalleled success. For instance, OpenAI’s development of GPT models has opened new avenues in conversational AI and natural language processing, transforming how we interact with technology. Similarly, in 2013, a friend approached my first startup to launch a product similar to #ChatGPT. At that time, I was limited by #technology and, as a new entrant to the market, failed to see the potential and skipped that offer. 𝗧𝗼 𝗮𝗹𝗹 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀 𝗼𝘂𝘁 𝘁𝗵𝗲𝗿𝗲: 𝗱𝗼 𝗻𝗼𝘁 𝗰𝗼𝗻𝗳𝗶𝗻𝗲 𝘆𝗼𝘂𝗿 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝗺𝗮𝗿𝗸𝗲𝘁. 𝗧𝗵𝗶𝗻𝗸 𝗯𝗲𝘆𝗼𝗻𝗱 𝗮𝗻𝗱 𝘁𝗵𝗶𝗻𝗸 𝗮𝗵𝗲𝗮𝗱 𝘁𝗼 𝗰𝗼𝗻𝗾𝘂𝗲𝗿 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲.

#wipro and #nvidia just shook hands to bring some serious AI mojo to the healthcare insurance game. It's like Batman teaming up with Iron Man, but for your health records. So, Wipro Limited is throwing a futuristic party with NVIDIA, and they're bringing #generativeai AI as their plus one. What's Generative AI, you ask? It's like the Picasso of artificial intelligence, creating masterpieces out of thin air. And guess what? Healthcare companies are about to be the canvas. Wipro, armed with NVIDIA's AI Enterprise software, is diving headfirst into the healthcare solutions pool. Affordable Care Act, Medicare, and Medicaid are getting a makeover, and it's not just a touch-up; it's a full-blown glow-up. They're on a mission to make your healthcare experience smoother than a fresh jar of peanut butter, increase enrollment, because who doesn't love a good insurance plan? and help sort out claims without the drama. They're not just stopping at Generative AI, they're diving deep into NVIDIA's AI platform, the brains behind generative, speech, and translation AI. It's like they're building the Avengers of the #ai world. Wipro's got this fancy thing called the #enterprise Generative AI (#WeGA) #framework , it's like their secret weapon, and now they're teaming up with NVIDIA to make custom #models for speech, translation, and other language models. It's like crafting a bespoke suit but for AI. And guess what? There's an AI Center of Excellence in the mix. It's like a Hogwarts for #engineers , where they'll learn the magic of NVIDIA’s application frameworks – generative AI, the #metaverse (yeah, it's a thing now), #conversationalai AI, and #dataanalytics analytics. It's like getting an invite to the tech wizardry school. Manuvir Das from NVIDIA is excited too. He's talking about companies wanting the crème de la crème of AI, and Wipro is serving it up on a silver platter. They're basically making sure your AI #experience is top-notch, like the VIP section of a fancy club. And just to sprinkle some real-world magic, Wipro has been working on transforming the #healthcare #contactcentre center experience. Imagine getting accurate, #personalized responses to your health queries based on your medical history, it's like having your own AI-driven health guru. So, there you have it – Wipro and NVIDIA are the dynamic duo shaking up healthcare with a touch of AI wizardry. It's like the future just knocked on our #healthcare system's door, and it's wearing a cape. #ai #cybersecurity #transformationdigital #news

🚀 New AI News from NVIDIA! 🚀 NVIDIA just launched the Nemotron-4 340B, a family of open-source language models that are set to revolutionize how we create synthetic training data and develop powerful AI applications across various industries! 🧠💥 --->But first, what's synthetic data? 🤔 Synthetic data is artificially generated information created by algorithms, rather than collected from real-world events. This type of data is incredibly useful for training AI models, especially when obtaining vast amounts of real-world data is impractical or impossible. Think of it as a digital "imagination" tool that creates data scenarios for AI to learn from, allowing these models to become more robust and capable. 🖥️📊 Here's the scoop: 🔧 The Models: NVIDIA rolled out three stellar models - Base, Instruct, and Reward. These form an impressive ‘pipeline’ designed for generating synthetic data that trains the next generation of LLMs (Large Language Models). 📚 Instruct Model: Trained on a whopping 98% synthetic data, it crafts high-quality training examples to power up new AI systems. 🎯 Reward Model: Acts as the quality gatekeeper, ensuring only the finest data gets through to train AI models. 🏆 Benchmark Dominance: Nemotron-4 models don’t just compete—they lead, outperforming open-source competitors like Llama-3, Mixtral, and Qwen-2 on various benchmarks! ✨ The Mamba-2 Hybrid: NVIDIA also introduced the Mamba-2 Hybrid, a selective state-space model (SSM) that takes accuracy to new heights, surpassing similar transformer-based LLMs. 🐍📊 So, what can these models actually do? 🤖 The Nemotron-4 family is designed to handle a wide array of tasks, including: Generating Synthetic Data: Create realistic data scenarios for training other AI models, particularly useful in environments where real data is scarce or sensitive. It enhances the learning process of AI models by providing diverse and high-quality training data. 🏆🤖Why this is HUGE: NVIDIA isn’t just keeping pace with the AI world—they’re setting the pace. By providing these free, open-source models, they're enabling advancements in #AI development, particularly in the creation of high-quality synthetic data. Image Source: DALL-E

Great point, Andrew Miller Huang’s interview on #Dealbook and his approach as a founder at heart is particularly captivating. His daily balance of success and the continuous EDGE of uncertainty is remarkable. Watching his interview left me with goosebumps, illustrating how a proven CEO can still face each day with a founder’s passion and unease. It’s a powerful reminder of the emotional depth and resilience in leadership. He also refers to the “off the shelf AI”. - noted!! Take a listen. https://lnkd.in/d6JaAazF

NVIDIA acquired OmniML in 2023. OmniML is a startup that shrinks ML Models, including Language Models.  NVIDIA acquired Deci AI in 2024. Deci AI is also a startup that creates a high-performance AI model that can be deployed in production. Why did Nvidia buy OmniML and Deci AI instead of buying a company that is good at autonomous driving or a company that is good at LLM? What is Nvidia dreaming of?  Even when Tesla was creating self-driving software, NVIDIA did not try to create self-driving software that surpassed Tesla. Tesla and self-driving startups simply provided a lot of hardware/software support to provide better self-driving performance.  NVIDIA did not try to create an LLM that surpasses ChatGPT even when OpenAI created ChatGPT3.0. OpenAI simply provided a lot of hardware/software support to make learning faster. When I look at Nvidia, I think it's just like Levi's, which made huge profits by selling jeans to gold miners during the American gold rush. NVIDIA is making efforts to provide hardware and software support to further expand the AI ecosystem so that AI applications can be transferred to more and more people. At this point, what wise career choices should deep learning engineers make? What position is best to maintain in these AI trends and AI ecosystem? I think this is a topic worth thinking about at least once if you are a deep learning engineer or researcher.  Do you want to be like Tesla/OpenAI? Do you want to be like Nvidia? I want to be like Nvidia. The role of porting deep learning models to specific hardware and lightening/accelerating deep learning models allows newly developed deep learning models to be used on less expensive hardware. This is because we believe that this will enable more people to use deep learning models with cheaper price and contribute to further expanding the AI ecosystem.

🚀 Exciting Week in Tech & AI! 🚀 This week has been a whirlwind of incredible announcements in the tech and AI world, pushing the boundaries of what's possible. Here's a quick rundown of the most groundbreaking developments: 🤖New GPT-4 Enhancements: OpenAI has released major updates to GPT-4, enhancing its reasoning capabilities and making it more accessible for developers. This brings us one step closer to more intuitive and powerful AI applications. 🏥Google's AI Breakthroughs Google unveiled its latest AI tools aimed at improving healthcare diagnostics and personalized education. These innovations promise to revolutionize how we approach critical sectors. 🌟AI Ethics and Governance A consortium of tech leaders announced a new framework for AI ethics, emphasizing transparency, fairness, and accountability. This is a significant move towards responsible AI development and deployment. 🚀NVIDIA's New AI Chips NVIDIA launched its next-generation AI chips, promising unprecedented speed and efficiency. These chips are set to power the future of AI, from autonomous vehicles to advanced robotics. ⚙️Microsoft's AI Integration: Microsoft announced deeper AI integration across its Office suite, aiming to boost productivity and streamline workflows. Imagine AI-driven insights and automation right at your fingertips! 🚗Tesla's Autonomous Driving Update: Tesla rolled out its latest software update for autonomous driving, featuring improved safety measures and enhanced real-time decision-making capabilities. This marks a significant milestone in making self-driving cars a reality. 👤Amazon's AI Customer Service: Amazon introduced a new AI-driven customer service platform designed to provide faster, more accurate responses and improve user experience. This AI is set to transform customer service dynamics. 🖥️IBM's Quantum Computing Leap: IBM made headlines with its latest quantum computing advancements, which promise to solve complex problems faster than ever before. Quantum AI could unlock new possibilities in fields like cryptography and material science. 📈Salesforce's AI for CRM: Salesforce launched new AI capabilities within its CRM platform, designed to provide deeper customer insights and predictive analytics. This helps businesses enhance customer relationships and drive sales growth. The future is now, and these advancements are just the beginning. Each of these innovations not only represents a leap forward but also opens up new avenues for how we interact with and benefit from technology. #AI #TechNews #Innovation #GPT4 #GoogleAI #AIEthics #NVIDIA #MicrosoftAI #Tesla #AmazonAI #QuantumComputing #SalesforceAI #FutureTech #AIRevolution

After reading this article, I asked my AI "what should we tell young people today about competing with AI in the future?" The answer is basically perfect: "As AI continues to evolve, it is important to prepare young people for the potential challenges and opportunities that it may present. Here are some key points to convey to young people about competing with AI in the future: Embrace AI as a tool, not a threat: AI is not meant to replace human workers; rather, it is meant to augment human capabilities and productivity. Encourage young people to view AI as a powerful tool that can help them achieve their goals. Develop creativity and critical thinking skills: AI is adept at performing tasks that are repetitive and rule-based, but it struggles with tasks that require creativity and critical thinking. These are the very skills that will be most valuable in the future workforce. Focus on uniquely human skills: AI cannot replicate the full range of human skills, such as empathy, communication, and emotional intelligence. These are the skills that will differentiate humans from AI and lead to success in the future. Continuously learn and adapt: The world is changing rapidly, and AI is a major driver of this change. Encourage young people to develop a growth mindset and be prepared to continuously learn and adapt to new technologies and challenges. Collaborate with AI, not against it: AI is not a competitor; it is a collaborator. Encourage young people to find ways to work with AI to solve problems and create new opportunities. Here are some additional tips for helping young people prepare for the future of work with AI: Expose them to AI early and often: Let young people experiment with AI tools and applications to develop a familiarity and understanding of the technology. Encourage them to pursue STEM education: A foundation in science, technology, engineering, and mathematics (STEM) will provide young people with the skills they need to understand and work with AI. Support their development of soft skills: Encourage young people to develop their soft skills, such as communication, teamwork, and problem-solving, which are essential for success in any field. Help them explore emerging fields: Encourage young people to explore emerging fields that are being driven by AI, such as robotics, data science, and machine learning. By preparing young people to understand, adapt to, and collaborate with AI, we can help them thrive in the future of work." #ai #aiadoption #business #management #trends