Black Forest Labs

Dear friends, I’m so excited to introduce Living Encyclopedia: Large Nature Model (LNM)—an AI-powered platform of DATALAND that reimagines the traditional concept of an encyclopedia by transforming vast nature-based datasets into immersive, multi-sensory experiences. Powered by cutting-edge AI and new epic Image Diffusion AI research collaboration Black Forest Labs LNM connects us to the beauty and complexity of the natural world in ways that feel dynamic and alive. Instead of presenting static information, LNM offers an evolving space for exploration, where knowledge is experienced through generative text, visuals, and sound. This marks a groundbreaking step forward in how we engage with data—an experience that invites curiosity, reflection, and wonder. The Living Encyclopedia offers three modes of interaction. In Research Mode, you can dive into detailed ecosystems, explore real-time weather simulations, and engage with environmental data. In Create Mode, you can generate scientifically accurate images of flora, fauna, and fungi based on text prompts. Dream Mode offers a meditative journey through evolving landscapes, visuals, and nature sounds—creating a space for calm and connection. As we prepare for the grand opening of DATALAND in 2025 at The Grand LA, we invite you to help shape this evolving project by joining our beta community. Be among the first to experience LNM and contribute to its future in Web3 space and beyond. Learn more and apply for beta access at LNM.dataland.art

Announcing fast, frugal and flexible FLUX on Fireworks in partnership with Black Forest Labs! Commercially usable FLUX.1 [dev] and FLUX.1 [schnell] models are now available on Fireworks https://lnkd.in/dFP7daXs 💨 Speed and 💰 Cost-Efficiency: FLUX runs on Fireworks with FP8 precision, offering 2x faster inference at half the cost of other platforms ($0.0014 for FLUX.1 [schnell] and $0.014 for FLUX.1 [dev]) ⚙️ Multiple Deployment Options: Use FLUX serverless to start instantly and pay per image. Deploy to private on-demand GPUs for consistent speeds in production ✏️ Customization: Leverage FLUX with custom ControlNet and LoRA adapter support to fine-tune your AI applications. Get started with FLUX.1 models for serverless image generation on Fireworks. Commercial usage is enabled through our partnership with Black Forest Labs. https://lnkd.in/d8zd9JH7 https://lnkd.in/d-rbe7ED Scale as you need: Deploy auto-scaling GPUs to handle production traffic. FLUX.1 [dev] and [schnell] both fit on an A100 or H100 GPU. https://lnkd.in/d3iAsDyc https://lnkd.in/dxD48p8P Use LoRA, ControlNet, or create custom server apps to fit FLUX into your broader AI systems. Ready to build your next AI innovation? Start customizing FLUX today: https://lnkd.in/dFP7daXs

One Model Will Not Rule Them All 🤖 This was the conversation during the GenAI Breakfast, during the ARRtist Berlin SaaS Week, hosted by Amazon Web Services (AWS) at the Merantix AI Campus! Yesterday we had a panel discussion featuring Andreas Blattmann (Co-Founder, Black Forest Labs), Jasper Masemann (Partner at Cherry Ventures), 🐙 Marc Mengler (CEO & Co-founder Octomind) and Gergo Kalcsics (Amazon Web Services (AWS). Here are our 5 key insights from the discussion: 📟 Specialized Models Over One Model to Rule Them All: While large foundation models are powerful, the trend in business applications is towards specialized models and model workflows tailored for specific tasks and industries. This customization is essential for delivering real value to users. 🤝 Open Source Drives Innovation and Safety: Open sourcing models, while carefully protecting core IP, is crucial for accelerating innovation and improving model safety. It allows for community feedback, fosters independent research, and leads to the development of valuable tooling and customization options. 🔥 Real-World Performance Over Benchmarks: Academic benchmarks are often flawed and don't accurately reflect real-world performance. Prioritizing human evaluation and building robust, evolving benchmarks that mirror user behavior are essential for developing truly useful models. 🏆 Data Quality Trumps Model Size for Customization: When customizing models, investing in high-quality data and annotation is more impactful than simply opting for larger models. Prioritizing data quality leads to better performance and efficiency. ⚙️The Importance of Product and Tooling: Building a successful AI product requires more than just a powerful model. Strong product design, intuitive tooling, and a deep understanding of user needs and workflows are essential for driving adoption and delivering value. Big thanks to the speakers, organizers, and attendees for making it such a great breakfast session! 🎫 If you would like to attend the Campus events, keep an eye on our website https://lnkd.in/eySq-s_P #GenerativeAI #OpenSource #AIModels #ImageGeneration #TextToImage #AIProductDevelopment #AICustomization #AIStartups #AISafety #HumanInTheLoop #AIBenchmarks #DataQuality #DiffusionModels #VentureCapital #merantixaicampus #aicampus #genai