Steve Fu’s Post

It's finally happened! The Open Source revolution in the AI world is on its way. Meta just dropped Llama 3.1, a 405-billion-parameter open-source AI model and it's a game-changer. “How?”, you may ask.   Well, Meta's evaluation of llama across over 150 Benchmark data sets, and extensive human evaluations shows its competitiveness with leading Foundation models like GPT 4 and Claude 3.5 Sonet across a range of tasks. And this is a huge development for open-source AI, as it echoes a key insight from Mark's announcement where he draws parallels b/w AI's potential trajectory and the rise of Linux while taking a shot at closed ecosystems like Apple's. He describes building services as “constrained” by Apple's platform, highlighting the frustrations of working within a closed system. And using that as an opportunity, Meta is positioning itself as a champion of open innovation. Just as Linux emerged as an open-source alternative to closed Unix systems and eventually became the foundation for cloud computing and mobile operating systems, open-source AI could follow a similar path. This is key to understanding Meta's AI vision. The availability of large-scale open-source models could democratize AI access, empowering researchers, startups, and smaller organizations to participate in AI development. This could lead to a more diverse range of applications and potentially mitigate the concentration of power in the hands of a few tech giants. Now how the developers use this open-source model remains to be seen but do let me know, how do you feel about this development? #ArtificialIntelligence #AI

🌐 Meta has open sourced Llama 3.1 405B finally to give tough fight to GPT-4o 🔑 Key Developments: • 🚀 Meta has open sourced Llama 3.1 405B: First frontier-level open source AI model • 💪 Competitive with advanced closed models • 🔓 Open, modifiable, cost-efficient • 🆕 New improved 70B and 8B models also released 🛠️ Ecosystem Growth: • 🏢 Amazon, Databricks, Nvidia: Fine-tuning services • ⚡ Groq: Low-latency inference • ☁️ Available on major cloud platforms • 🤝 Partnerships with Scale.AI, Dell, Deloitte for enterprise adoption 💡 Benefits for Developers: • 🎯 Customization for specific needs • 🔒 Data protection and control • 💰 ~50% cost reduction vs. closed models like GPT-4 • 🔀 Avoid vendor lock-in 🌍 Why Open Source AI Matters: • 🔬 Accelerates innovation and research • 🤝 Promotes equitable access • 🛡️ Enhances safety through transparency • 🌐 Decentralizes AI power 🔮 Meta's Perspective: • 🏗️ Building best experiences and services • 🔓 Avoiding constraints of closed ecosystems • 📈 Long-term benefits outweigh short-term advantage 🔐 Safety Considerations: • 🧪 Rigorous testing and red-teaming • 👥 Community-wide scrutiny • ⚖️ Balancing innovation and responsible development 🚀 The Future: • 📈 Rapid advancement in open source AI • 🌱 Building robust ecosystem for long-term growth • 🌎 Democratizing AI access globally Join the open source AI revolution! Access Llama 3.1 at llama.meta.com #OpenSourceAI #LlamaAI #AIInnovation #TechFuture

There was a time when tech giants used to innovate rapidly in three different segments like platforms, models and technologies to win the trust of AI consumers/researchers. Like Google Cloud has developed Vertex AI, AutoML etc in platforms, BERT, LamDA, PaLM, Gemini, Gemma in Models, Scikit-Learn, Transformer, Tensorflow 2.0 etc in Technologies. I reckon we are at a shift now, where there is more and more emphasis on collaborations, partnerships etc possibly propelled by the demand for rapidness in innovation, rather than investing entire energy into innovating across the entire spectrum. These collaborations are shaping up between Tech giants like Microsoft, Google, IBM, Meta + Startups who are rapidly innovating + Academia, universities where research is happening at a faster pace too. Tech giants bring infra + data, startups come up with innovative ideas and academia comes with path breaking research. A combination that fosters rapid progress in a decentralised manner. Please share your thoughts in the comments.

Meta just dropped Llama 3.1: The AI Titan That's Breaking All Rules! Here's why it's sending shockwaves through the AI world: 1️⃣ Open-source superhero: Free for all. No strings attached. Innovation unleashed! 2️⃣ Cloud giants, assemble! AWS, Azure, Google Cloud – all onboard. Run it anywhere, everywhere. 3️⃣ Polyglot prodigy: Understand multiple languages. Global reach just got real. 4️⃣ Context king: Understands nuance 5️⃣ Ethical AI champion: Built-in safeguards. Less bias, more trust. 6️⃣ Efficiency ninja: Smoother than a greased lightning bolt. Your hardware will sing! 7️⃣ Parameter powerhouse: Brace yourselves... 405B parameters! 🤯 That's like having the knowledge of a million libraries in one AI brain. But here's the real magic: It's not just about the mind-bending tech. It's about democratizing AI. Imagine a world where: • A startup in a garage competes with Silicon Valley giants • Researchers in Tibet collaborate with labs in Texas • Students in Nigeria access cutting-edge AI for free • Your neighborhood bakery uses enterprise-level AI to perfect croissants Llama 3.1 isn't just leveling the playing field. It's turning the entire tech landscape into one giant playground. Whether you're: • A seasoned developer itching to push boundaries • A curious newbie ready to dip your toes in AI waters • A business owner dreaming of AI-powered innovation • Or just someone who loves watching tech history unfold... This is your moment. The AI revolution is here, and it's open-source, cloud-powered, and more capable than ever. So, what will YOU build with Llama 3.1? #LlamaAI #AIRevolution #OpenSourceAI

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

📢 Elon Musk's Open Source AI Chatbot Grok: A Game Changer for the ML Community! 🌟 🔄 What's New?Elon Musk's XAI has released #Grok ✨ Base model only ✨ MoE architecture (8 experts, 2 active) ✨ 314B params (86B active) ✨ 73% on MMLU, 62.9% GMSK, 63.2% HumanEval ✨ 8K context ✨ RoPe embeddings enabling context extension ✨ Apache 2.0 1️⃣ At first, most won't be able to use it 💻⚠️ Grok needs multiple H100s to run and more to fine-tune, so will remain the preserve of the GPU rich 💰 for now. But, over time the community will find ways to efficiently deploy and fine-tune Grok, cloud providers will then make it accessible opening up use. 2️⃣ Increases pressure on closed #LLM business model 💣 With Grok now, and #Llama 3 soon there will be fewer reasons to pay a premium for #GPT4, #Claude3, #Gemini or #Mistral Large. Eventually, businesses will use frontier models selectively when needed, and choose to privately host next best open models for most workloads. 3️⃣ Reduces reliance on Meta 👑⚔️ Some have bemoaned the reliance on Meta as our sole champion among big tech for #opensource ML. While I disagree given the recent contributions from Tencent, and Google. The release of Grok illustrates there will be continued incentives to release open models and cements a bright future for open ML. 🌈

AI is here to stay, and for all of us participating in building (and monetizing!) the next generation of AI native applications and services, we should all care deeply about supporting a vibrant Open-source AI community. Open-source increases the pace and diversity of innovation, helps shape the technology more dynamically to the market, and perhaps most importantly, brings the cost of these technologies down and makes them economically viable for others to build exciting applications to serve the end customer. I’m sharing this from Saturn Cloud because I like their mission to enable AI with any open-source stack - it's free, it serves the greater good, and it moves the needle in democratizing AI. Check them out if you’re building AI and agree with this philosophy. #AIEngineer #MLOps #NVIDIA

Microsoft Invests $16M in Mistral AI: A Milestone for Web Tech Exciting news for the tech world! Microsoft's $16 million investment in Mistral AI paves the way for groundbreaking advancements in both Web2 and Web3 sectors. This move highlights the growing importance of AI in shaping the future of internet technologies. As a firm deeply involved in Web2 and Web3 development, we see this as a pivotal moment that could spark innovative solutions and collaborative opportunities within the ecosystem. Let's explore how this investment will influence the tech landscape. For more details, check out the full story. https://lnkd.in/d-z6CNPC #Microsoft #MistralAI #WebDevelopment #Innovation

🚀 Meta's Llama 3.1: A Game-Changer in Open Source AI 🦙 Meta just dropped a bombshell in the AI world with Llama 3.1, their "frontier-level" open source model. This isn't just another update - it's a paradigm shift. Why it matters: • Democratizes advanced AI tech • Challenges closed AI systems • Offers better cost-efficiency • Enhances customization & data security Mark Zuckerberg boldly predicts: "Starting next year, we expect future Llama models to become the most advanced in the industry." But here's the kicker: Open source AI isn't just about accessibility. It's about safety through transparency and collective scrutiny. As the AI race heats up, could this open approach be the key to responsible innovation? The tech giants are already lining up. Amazon, NVIDIA, and others are jumping on board to support this open ecosystem. It's not just a trend; it's a movement. As we stand at this AI crossroads, I can't help but wonder: Will Llama 3.1 mark the beginning of the end for closed AI systems? Are we witnessing the Linux moment of artificial intelligence? What's your take? Is open source the future of AI, or are there risks we're overlooking? #OpenSourceAI #AIInnovation #TechTrends #FutureOfAI #DigitalTransformation

Had a blast yesterday morning discussing Open Source for AI models with Yann LeCun, Thomas Wolf and Patrick Pérez at the #Meta AI Startup Program Demo Day! Some key takeaways from our panel and why Open Source is a great opportunity for AI: 💡 The definition of open source for AI Models is still a moving target, with a lot of different components being eligible for open sourcing (the model itself, the data sets, the documentation, the APIs…) but it is a trade-off in terms of allowing flexibility vs guaranteeing the security and fair use of the model, within a legal framework that is still relatively undefined 👀 Open Source is a great way to address the challenges with AI #biases, because opening up the models to more eyeballs and more verification of their choices means better supervision and ultimately fairer results 📹 Developing stronger and higher performing #LLMs currently requires bigger and bigger data sets, and therefore larger and larger investments in terms of compute capacity; however, new technologies are emerging to hone models without additional data, and other types of models (multi-modal or computer vision) will require less data to train 🛠 Why should enterprises implementing AI leverage open source technologies rather than proprietary models? Ultimately it’s about flexibility to adapt and fine-tune the models to each enterprise’s specific use cases, and more control over model costs and model evolution At Scaleway we are strong believers in open source and are releasing our new inference product based exclusively on open source AI models - reach out if you are interested in participating in our beta. Thanks to my fellow panelists and thanks to the Meta team for putting together a great event! Victoire Mine (Goebel) Laurent Solly Cosmina Trifan Doreen Pernel Frédéric Bardolle Fabien Da Silva Pascal Condamine Patrick Pérez Jean-Baptiste Kempf Thomas Wolf