Mark Zuckerberg stated that Meta will require 10 times more computing power to train their next-generation AI model, Llama 4, compared to Llama 3. This indicates Meta's dedication to scaling their AI capabilities, potentially bringing even more advanced AI models to the market. This bold declaration raises questions: How will Meta address the energy and infrastructure requirements for this massive computing power increase? Also, Will Llama 4 surpass current industry leaders like GPT-4? And finally... Could this lead to more affordable and accessible AI solutions for businesses and consumers? Fun fact: Meta's Llama 2, the predecessor to Llama 3, was downloaded over 150,000 times in just three days after its release, demonstrating the immense interest and demand for their AI models. #Meta #AI #Llama4 #ComputingPower Source: https://lnkd.in/dVXi-a-G
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Here is a unique prelude to a LinkedIn post in 4 sentences and 5 hashtags: As Meta continues to push the boundaries of AI innovation, Mark Zuckerberg reveals that training Llama 4 will require a significant increase in computing power, a staggering 10 times more than what was needed for Llama 3. This underscores the company's commitment to staying ahead of the curve in AI development. With each new iteration, the demand for computing resources grows exponentially, highlighting the importance of strategic planning and investment in infrastructure. Meta's dedication to building capacity for future AI advancements sets a precedent for the industry. #AI #ComputingPower #LlamaModel #Meta #InnovationInvestment https://lnkd.in/eFrBSHDV
Zuckerberg says Meta will need 10x more computing power to train Llama 4 than Llama 3 | TechCrunch
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No time to check the news this week? Let's dive into the latest Tech highlights you shouldn't miss this week, one new at a time 💥 1️⃣ Meta Unleashes Llama 3 Meta has unveiled Llama 3, claiming it's one of the best open models out there. This new generative AI model aims to enhance how we interact with machine learning across various applications. https://lnkd.in/dZdjKy7x 2️⃣ Hugging Face's New AI Benchmark: Hugging Face introduces a new benchmark for evaluating generative AI in health-related tasks. This could revolutionize how AI supports decision-making in healthcare, offering more accurate and reliable tools. 🏥 https://lnkd.in/dD3qawnt 3️⃣ LinkedIn Premium Upgrade LinkedIn's latest update boosts visibility for Premium company pages, offering deeper insights into who's checking out your business. This could be a game-changer for B2B engagement on the platform. 📈 https://lnkd.in/dUsG5A45 4️⃣ Intel's Open AI Commitment Intel is stepping up with other tech giants to commit to building open generative AI tools for enterprise use. This collaborative effort underscores the industry's move towards more transparent and accessible AI solutions. https://lnkd.in/dG769Nkm 5️⃣ Google Cloud Next Google is going all-in on generative AI at its Google Cloud Next event to shape the future of cloud. They're integrating AI deeply into their cloud offerings, signaling a major shift in how businesses will use cloud computing. ☁️ https://lnkd.in/dpBfAxAw Exciting AI news just dropped! From Meta's Llama3 to the Google's all-in on AI, the future is zooming towards us! Stay tuned as we continue exploring these tech marvels. Keep innovating, keep learning! 🚀 Did you like this TechRoundUp? Then you better subscribe MLPills and enjoy free Machine Learning and Data Science content straight to your email every Saturday! 😉 https://t.co/ZHtPRHgyUT
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Breaking News! 🚨 #Meta and #Microsoft have teamed up to launch #Llama 3.1, an AI model boasting an incredible 405 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 𝗽𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿𝘀! 🤖 𝗪𝗵𝘆 𝗟𝗹𝗮𝗺𝗮 3.1 𝗶𝘀 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴? 👉 𝗧𝗼𝗽 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Imagine an AI model that outperforms giants like GPT-4o and Claude 3.5 Sonnet. Llama 3.1 is the new champion in the AI arena, delivering unmatched performance! 👉 🥇 𝗢𝗽𝗲𝗻 𝘁𝗼 𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲: Unlike many AI models, Llama 3.1 is open-source. This means developers from all over the world can access, use, and improve it. It's a game-changer for innovation! 👉 🛠️ 𝗨𝗻𝗶𝗾𝘂𝗲 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵: Meta is taking a different path by focusing on long-term innovation rather than immediate profits. This approach is set to drive more creativity and progress in the AI field. 🌟 𝗪𝗵𝗮𝘁’𝘀 𝗡𝗲𝘅𝘁? 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗕𝗼𝗼𝗺: With Llama 3.1 being open-source, we can expect a surge in creative AI applications and projects. This model will act as a catalyst for countless new ideas and innovations. 🚀 𝗣𝗼𝘄𝗲𝗿 𝗧𝗲𝗮𝗺: The collaboration between Meta and Microsoft is bringing together the strengths of both companies. This partnership is bound to have a huge impact on the AI world! https://lnkd.in/g57rhhy4 #AI #Llama3.1 #OpenSource #ArtificialIntelligence
Meta releases Llama 3.1 models, sticks with open strategy | DailyAI
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Meta's Llama 3.1 405B Shows Great Open-Source AI Performance. I just read that Meta has unleashed its most potent AI language model yet - Llama 3.1 405B. This colossal 405 billion parameter model is set to redefine the open-source AI landscape. Here's why it matters. 📍 Rivals proprietary models: Benchmarks show it competing with GPT-4 and Claude 3.5 Sonnet across various tasks. 📍 Massive scale: Trained on 15+ trillion tokens using 16,000 NVIDIA H100 GPUs. 📍 Enhanced capabilities: 128K token context window, multilingual support for eight languages, and advanced reasoning skills. 📍 Open accessibility: It is available on Hugging Face and through cloud partners like #AWS, #Azure, Google Cloud and IBM watsonx today. 📍 Ecosystem boost: Potential to accelerate innovation in AI research and commercial applications. While debates around its truly "open-source" nature continue Llama 3.1 405B undoubtedly marks a significant milestone in democratizing cutting-edge AI technology. What are your thoughts on this release? How might it impact the AI industry moving forward? #AI #OpenSource #Llama3 #Meta
Meta releases its biggest 'open' AI model yet | TechCrunch
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The first half of 2024 has been a period of rapid advancements and significant developments in the field of #AI. Here’s a summary of the key trends and insights shaping the AI landscape, from soaring training costs to groundbreaking new technologies and models. Escalating Costs of AI Training Training AI platforms is becoming increasingly expensive, with costs doubling every nine months, as highlighted by research from Epoch AI. This exponential rise in expenses means that training new models could soon exceed $1 billion when accounting for electricity, hardware, and employee compensation. Whether this trend will continue into the next decade remains uncertain. Some analysts predict that data shortages and rising AI chip prices could plateau both costs and performance gains; overall, this cost explosion will make it harder for smaller startups to compete with industry giants. Huge AI Infrastructure Investments at Major Players Microsoft, in collaboration with OpenAI, is developing a supercomputer with an estimated cost of over $100 billion, comprising millions of chips. This project underscores the massive scale and financial commitment required to advance AI infrastructure, with costs significantly surpassing those of modern-day data centers. Similarly, Meta is ramping up its infrastructure investments, planning to spend billions of dollars more on servers and data centers. Meta’s CEO, Mark Zuckerberg, has pointed out that energy constraints are a limiting factor in their data center buildout. Despite these challenges, Meta forecasts 2024 capital expenditures in the range of $35 billion to $40 billion, making it the largest CapEx investment in the company’s history. The Rise of AI Video Technology June 2024 marks a significant milestone for AI video technology, with tools like Sora, Kling, Dream Machine, and Runway’s Gen 3 AI video model gaining traction. These tools are transforming content creation, enabling more sophisticated and efficient video production processes. Open AI: OpenAI’s Latest Model GPT-4o & Preparing for GPT-5 [read more on the blog post] Alphabet’s AI Innovations & Issues with Google’s AI overview [read more on the blog post] AI PCs and New Chip Technologies [read more on the blog post] Global AI Safety Initiatives & Regulation [read more on the blog post] #artificialintelligence #ai #technology #innovation #alphabet #meta #google #openai #ibm #newsletter #microsoft #future #news
Major Milestones and Trends in AI Development in the First Half of 2024 - For Digital Movers: Digitale Transformation, Softwareentwicklung, IT Offshore
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🚀Meta Unleashes Llama 3.1: A New Era in Open-Source AI Meta, the tech giant formerly known as Facebook, has just dropped a bombshell in the AI world. Meet Llama 3.1, the largest-ever open-source AI model, boasting a whopping 405 billion parameters. But what’s the fuss all about? Let’s dive in!🤓 🔍Llama 3.1 isn’t just flexing its parameter muscles; it’s also flexing its performance. Meta claims that Llama 3.1 outperforms both OpenAI’s GPT-4 and GPT-4o, as well as Anthropic’s Claude 3.5 Sonnet, across various benchmark tests. Not too shabby, right? 📊 🌐 Meta is on a mission to democratize AI. They’re making the Llama-based Meta AI assistant available in more countries and languages. Plus, they’ve added a nifty feature: image generation based on someone’s likeness. Say cheese! 📸 💰Now, you might wonder why Meta is giving away this AI powerhouse. Llama 3.1 was trained using over 16,000 of Nvidia’s ultraexpensive H100 GPUs (yes, you read that right). The cost? Likely hundreds of millions of dollars. But Meta believes in open-source magic. Just like Linux revolutionized operating systems, Llama 3.1 could be the catalyst for a shift toward open-source AI.🌟 🤝 Meta isn’t going it alone. They’re teaming up with heavyweights like Microsoft, Amazon, Google, Nvidia, and Databricks to help developers deploy their own Llama 3.1 versions. And guess what? It’s roughly half the cost of OpenAI’s GPT-4o to run in production. Cha-ching! 💸 🔍Meta’s keeping the data it used to train Llama 3.1 under wraps. Trade secrets, you know? But here’s a tidbit: synthetic data (generated by models, not humans) played a key role in fine-tuning this behemoth. Llama 3.1 is like the wise teacher guiding smaller models toward greatness. 🧠 🔮Will we hit a data shortage wall? Meta’s VP of generative AI thinks there’s still room to run. But predicting the future? Tricky business. 🤔 So, buckle up! Llama 3.1 is here, and it’s rewriting the AI playbook. 🎉 #AI #opensource #llama31 #MetalMagic Disclaimer: No llamas were harmed in the making of this model. 🦙😉
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"Meta is currently operating many data centers with GPU training clusters across the world. Our data centers are the backbone of our operations, meticulously designed to support the scaling demands of compute and storage. A year ago, however, as the industry reached a critical inflection point due to the rise of artificial intelligence (AI), we recognized that to lead in the generative AI space we’d need to transform our fleet." At Systems @Scale on June 12, Saranyan Vigraham and Benjamin Leonhardi shared their perspective on maintaining large scale AI capacity at Meta. To understand more about their work, visit their post at https://lnkd.in/gxY7C-zc on the Engineering at Meta blog. To see their full talk, and visit all of the past @Scale content, visit https://lnkd.in/gq6wKtE3. #SystemsAtScale
Maintaining large-scale AI capacity at Meta
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Very Interesting Benjamin Hamburger, thanks ! I strongly believe in the transformative power of open source to drive radical innovation and change. However, throughout history, business cases built purely on open-source models have rarely become the dominant forces in the market. Instead, proprietary solutions often capture the largest market share, as evidenced by figures like Bill Gates, whose wealth stems from closed-source models rather than open source. Having considered open-sourcing some of my past projects (or some of my clients), I believe this is due to two main factors: 1) Complexity and Accessibility: Open-source solutions are inherently less accessible and often more complex or abstract for most end users. Most customers prioritize simplicity and usability over customizability, and many lack the technical expertise to navigate open-source ecosystems effectively. 2) Business Strategy and Sales Power: Companies that dominate the market tend to rely on well-funded sales teams, polished end products, and massive marketing budgets. These factors contribute to widespread adoption among consumers who value ease of use and established brand reputation. From this perspective, Meta ’s move to embrace open source in AI is strategic, likely serving as a "defensive" or alternative innovation strategy. Meta doesn’t hold at all the same foothold in the B2B AI software market as competitors like Microsoft, OpenAI (with Microsoft's support), and Google. Open source might provide Meta with a great pathway to strongly participate and federate a community in the AI landscape fueling its own businesses but without directly challenging these established players head-on. Looking forward to continue the conversation with you dear friends. #PlanetImpactConversations #GenAI #OpenSource
We are starting to see a pattern in AI: almost every release of a high performing AI model is often quickly followed by a free, open source version. But who is mainly responsible for that? Mark Zuckerberg. Here is an overview of the recent examples of Zuck delivering: ▪ April 2024: Google releases Notebook LLM worldwide ▪May 2024: OpenAI releases GPT-4o ▪July 2024: Meta releases Llama 3.2 ▪October 2024: Meta releases Notebook Llama ➡ What does it mean exactly for the market of generative AI? In contrast to its competitors, Meta is trying to be the “linux of AI”, as the foundational layer of AI. This strategy has two advantages: ▪It enables Meta to create a reference infrastructure system, with an open ecosystem of third-party apps built on top of it, in contrast with constrained, closed ecosystems like Google or Apple ▪Every release of a new open source model that tops the performances of the latest OpenAI model undermines the premium pricing of these companies The fact that OpenAI spends billions building models and expects to make a direct profit of it, makes open source releases a threat long term for them. Of course, you could argue that for now, OpenAI is maintaining a very high market share and doesn't seem really affected. That is because the AI market - implementation side - is currently immature: most companies do not have the capabilities or desire to build their own internal AI system using open source models, preferring plug-and-play, ready to use solutions. But once the market matures, two things could happen: ▪ Implementing open source AI models will be more accessible: cheaper, easier, and flexible ▪ As high-performing open source models become a standard, large models may become a commodity What do you think ? Picture by Maxime Labonne on X #GenerativeAI #Llama #Meta #Strategy #AI #Opensource
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Has Llama-3 just killed proprietary AI models? - Meta's Llama-3 release marks a turning point: open source models closed the gap to proprietary AI vendors. The benchmarks show that Llama-3 70B comes close to GPT-4 in many tasks. - Meta can likely outspend OpenAI on compute and talent. OpenAI has $2b in revenue and is most likely very unprofitable. Meta makes over $100b gross profit. - The big winners are developers, who benefit from removed vendor lock-in, self-hostable fine-tuned models with GPT-level performance, and faster, cheaper hardware. Read more in our latest blog post 👇
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🚀 Breaking News: Meta Launches Llama 3.1 - The Future of Open-Source AI🚀 🌍 Meta unveils Llama 3.1 405B, a groundbreaking open-source AI model rivaling GPT-4 and Claude 3.5 Sonnet. With unmatched performance, 128K token context length, and multilingual support. It's ideal for synthetic data generation, model distillation, and more. Supported by AWS, NVIDIA, and Google Cloud, Llama 3.1 democratizes AI, making advanced capabilities accessible to all. 🔹 Key Highlights 🔹 • Unmatched Performance: Llama 3.1 405B, the first frontier-level open-source AI model, rivals the best closed-source models in knowledge, steerability, and multilingual translation. • Extended Context: With a context length of 128K tokens, Llama 3.1 supports more complex and nuanced interactions. • Multilingual Support: Available in eight languages, expanding global accessibility. • Cutting-Edge Applications: Perfect for synthetic data generation, model distillation, and advanced tool use. • Robust Ecosystem: Supported by over 25 partners, including AWS, NVIDIA, and Google Cloud, ensuring seamless integration and deployment. 🌟 Unlock the Full Potential of Generative AI with DataCouch Consultancy & Training! 🌟 Are you excited about Llama 3.1 and eager to leverage its power in your projects? DataCouch offers comprehensive consultancy and professional training in Generative AI, designed to equip you with the skills needed to master the latest advancements in AI. Enroll Now - https://zurl.co/YHU5 Join our community of learners and innovators. Partner with DataCouch for consultancy and professional training in Generative AI and stay ahead in the rapidly evolving world of AI. #MetaAI #Llama31 #OpenSourceAI #GenerativeAI #ArtificialIntelligence #MachineLearning #AIInnovation #DataScience #TechNews #AITraining #DataCouch #AIConsultancy #FutureOfAI #TechTrends #AIRevolution #MultilingualAI #AdvancedAI #AICommunity #CloudComputing #NVIDIA #AWS #GoogleCloud
Meta Launches Llama 3.1
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