Nebius

Over the past two weekends, Nebius supported hackathons organized by Meta and Cerebral Valley in London and Toronto. We provided GPU compute for participants and extended access for the top three winners. In London, 312 hackers participated in the 36-hour event, submitting 59 projects across three key areas: accelerating clean and efficient energy; supporting delivery of public services and healthcare; and breaking down barriers to opportunity. Our own Alexey Tsishevski gave a brief talk and served as a judge in the initial round. The final round was held at Meta's Kings Cross offices, where six finalists presented to a packed audience of participants, government officials and other guests. Karina Zainullina, an ML Engineer from Nebius’ AI R&D team, was our final-round judge. Of the 59 submissions, 19 projects used Nebius resources, including all three winning teams: 🥇 Guardian, saving lives with rapid and accurate A&E triaging. 🥈 Gripmind. In their installation, Llama 3.2 controlled a robotic arm, enabling real-world robotics ops and BCI-based control. 🥉 Pharmallama. A locally-run, privately fine-tuned Llama 3.2 3B quantized model has been trained on a curated pharmacy knowledge dataset to provide medication advice and collaborate with pharmacists securely via iPhone. A week later in Toronto, 230 participants signed up for the second hackathon. The challenges focused on “AI as a public good,” with many submissions addressing accessibility and education. 34 projects out of 40 submitted in total, including the second- and third-place winners, leveraged Nebius resources. Andrei Meganov served as both a speaker and judge. The three winners in Canada were: 🥇 Circuit XR, an educational VR startup that allows you to take a hand-drawn electrical circuit, visualize it in AR using Unity and play with it: unplug a wire, flip a switch, etc. 🥈 EyeSpeak, an original gaze-driven interface for computer control with AI-assisted text entry and text-to-speech to assist paralyzed people. 🥉 Fraudy, a phone call companion that analyzes calls in real-time, alerting users to potential fraud risks. Special thanks to our architects Cyril Kondratenko and Liran Jdanov for providing GPU access and supporting participants throughout the events. And congrats to all the teams! We look forward to partnering with Cerebral Valley again in 2025. Here’s a video created by CV in London to capture the memories.

Efficient drug discovery is all about achieving those “eureka!” moments. For many laboratories in recent years, a reliable AI infrastructure has become the catalyst behind such moments. AI-powered platforms can generate thousands of molecular structures and screen their potential as drug candidates much faster than traditional methods. As we advance more and more in this field, we’ve noticed several cutting-edge organizations pushing the limits of R&D: Atomwise leverages AI to predict compounds’ binding affinity and interaction with disease-related proteins, focusing on structure-based drug design. If they fit together, it’s a hit! By optimizing key physicochemical properties such as stability and molecular interactions, Chemistry42 by Insilico Medicine ensures AI-generated molecules are both effective and viable for further development. Our client Genesis Therapeutics accelerates drug discovery by nailing down the most promising compound candidates for synthesis and testing, running repeated cycles of AI-powered iterations. Patients are at the heart of Exscientia’s methods to streamline drug development. Patient tissue data is key to define optimal profiles for AI-designed drugs, leading to better clinical conditions in cancer patients. #drugdiscovery #AI #biotech #RnD #healthcare

🎯 Excited to share insights from my talk at DSC Europe 2024 on "Structuring Unstructured Data to Boost Computer Vision and GenAI Applications at Scale"! 🔍 We dove deep into unstructured data management and how it powers AI applications. 🚀 Key highlights: • AI and Data Trends - Unstructured Data is a new gold for better AI • Toolset to enrich, transform, and analyze unstructured data - requires scaling and distributed processing • DataChain is an open-source tool to enrich, transform and analyze unstructured data • Use case: Streamlining PDF processing and LLM evaluation • Use case: Enhancing Computer Vision in Fashion • Use case: Managing complex Video Datasets with Frame-Level Annotations for Sport & Fitness applications 🙏 Thanks to everyone who joined and engaged in the discussion! Your questions and insights made the session even more valuable. Many thanks to the DataChain team, Dmitry Petrov, Ivan Shcheklein, David Berenbaum, and Tibor Mach for the opportunity to work together and for use case examples. Good luck with the DataChain tool! Looking for more starts ⭐ on GitHub: https://lnkd.in/dDxYN8xe 🙌 #AI #DataChain #ComputerVision #GenerativeAI #MachineLearning #DataEngineering

In today’s guide on our blog, we’ll build an AI-powered financial planner using the Meta Llama 3.1 70B model via Nebius AI Studio and a full-stack Next.js app: https://lnkd.in/etmCeb8v This solution works seamlessly whether you’re using the Pages Router or the App Router, as much of the customization relies on setting up a custom Next.js server. #demo #opensource #API #guides #appbuilders

Throwback to this fall’s OCP Global Summit, where our hardware R&D team leaders Igor Z. and Oleg Fedorov gave a talk on Nebius’ in-house server and rack design. Hit play to see the full presentation. Our hardware designs are based on several concepts and principles from the Open Compute Project Foundation, so this year, we came full circle by bringing our own developments to the OCP community. Igor and Oleg shared ideas and specs that help us deliver efficient, robust GPU compute, while Anna Amelechkina supported the guys from backstage. This was the first time we revealed what’s inside our server to such a wide audience of hardware experts. Thanks to everyone who attended and provided feedback afterward. #OCP #hardware #servers #RnD

Before any training comes data preparation. We’ve outlined a high-level overview of the kind of pipeline you can build on Nebius to collect and prepare data for ML models. The datasets can then, of course, be used for pre-training and fine-tuning on modern AI-tailored GPUs, all in one cloud. The software stack shown in the image highlights the tools we provide. With these, you can process unstructured data for multi-modal training or manage your structured data in one of our databases. Learn more about our compute environment, storage types and applications: https://lnkd.in/dzBagyXJ. Scroll down to explore resources and articles we’ve created based on our in-house AI R&D expertise. Even if you’re preparing datasets using a different stack, our experience can still prove valuable. #datapreparation #datacollection #databases #storage

Register for the webinar on how Slurm meets K8s: https://lnkd.in/eRxH_HR6 Managing distributed multi-node ML training on Slurm can be challenging. Soperator, our open-source Kubernetes operator for Slurm, offers a streamlined solution for ML and HPC engineers, making it easier to manage and scale workloads. Join out live webinar where we’ll demonstrate how Soperator can manage a multi-node GPU cluster to simplify operations and boost productivity. For who: ML Engineers running distributed training, HPC professionals managing large-scale workloads, DevOps teams supporting ML and HPC environments. In this webinar, you’ll learn how this solution: - Simplifies workload management across multiple GPU nodes. - Utilizes a shared root filesystem to reduce setup and scaling complexity. - Delivers Slurm job scheduling functionality in a modern and convenient form. Meet the speakers: Mikhail Mokrushin, Managed Schedulers Team Leader at Nebius, and Alexander Kim, our Solutions Architect. Where: Zoom. You will receive the link after you register on the Nebius website: https://lnkd.in/eRxH_HR6 #webinars #Kubernetes #Slurm #opensource #orchestration

Register for the webinar with Boris Yangel, Head of AI R&D Team at Nebius! The webinar will take place on Nov 27, next Wednesday, at 17:00 CET: https://lnkd.in/dAvemRc9 Gathered by our sister company Toloka, Boris and three other experts will reveal the strategies, tools and best practices that drive optimal model performance, covering everything from metric tracking and model alignment to handling real-world challenges. Joining Boris will be Aleksei Petrov, Founding Engineer at poolside, Nikita Pavlichenko, Senior ML Engineer at our client JetBrains, and Konstantīns Mihailovs. #LLMs #webinar #largemodels #coding

Nebius opens its first availability zone in the United States🔥 Scheduled to go live in Q1 2025, the Kansas City availability zone will house thousands of state-of-the-art NVIDIA GPUs, primarily H200 Tensor Core GPUs in the initial phase, with the energy-efficient NVIDIA Blackwell platform expected to arrive in 2025. We will become the first colocation tenant in the Kansas City data center owned by our partner Patmos, which provides cloud, high-density compute, software and data center solutions. We selected Patmos for its demonstrated agility and expertise in phased construction, delivering custom data center buildouts faster than the industry standard. The first phase of construction includes extensive infrastructure upgrades: backups, generators and cage space, tailored to support our demanding workload requirements. Patmos recently repurposed the facility, converting the iconic Kansas City Star printing press to a modern AI data center. The colocation can be expanded from an initial 5 MW up to 40 MW, or about 35 thousand GPUs, at full potential capacity. The new availability zone will allow us to meet the demands of US-based AI companies even better. To work more efficiently with them and for the convenience of our growing team, we also recently announced the opening of three offices across the country. This comes just as the first client workloads are being deployed in our Paris colocation data center, the one we unveiled less than two months ago. Along with our own DC in Finland, whose capacity we’re tripling, Nebius will have three availability zones, and this is just the beginning. We will continue building AI infrastructure on both sides of the Atlantic in 2025 and beyond.

Nebius AI Studio has been benchmarked by Artificial Analysis 👍 One of our goals was to make Studio with per-token Inference Service the most affordable solution on the market. We announced new pricing a couple of weeks ago, but you might not have believed us. Now, it’s been validated by Artificial Analysis, a third-party organization that measures inference providers’ specs and shares them with the world. For each model we offer — and we have the most popular ones like Llama, Mistral, Qwen and many others — Nebius AI Studio’s prices are the best, according to AA. In terms of quality and speed, we are on par with the market. There’s always room for improvement — we will keep up the hard work to make our specs even better. The minor mismatch between our own results and AA's measurements is due to latency: physically, we host the models in a data center in the EU, while AA runs tests from the US. We are looking forward to seeing the results of tests conducted in Europe, in line with European clients’ workloads. What’s even more intriguing is how the results will turn out when we start to host the models in our new availability zone in the States in 2025. This is something we’re proud of. Check out the Llama 3.1 Nemotron 70B, Qwen 2.5 72B (the one in the image) or Mistral models — our results for these place us in the most attractive quadrant, outperforming the competition. #benchmarks #GenAI #inference #opensourse #LLMs