Mayssem Ben Ammar’s Post

Curious about how enterprises view AI adoption? In this carousel, check out Authority Hacker's AI Statistics 🔥 Find the full report at https://lnkd.in/eiAhxZBX What exciting AI projects are you working on? We’d love to hear in the comments! Reserve access to our NVIDIA H100 SXM Supercloud, the most advanced AI cluster of its kind, at https://lnkd.in/eRWjFhzB #AIStatistics #AI #AISurvey #AIAdoption #MachineLearning #NVIDIA #GPU #Cloud #AISupercloud

Interesting analysis from Fundrise about potential value of AI Revolution, based on historical precedents of previous disruptive technology waves (PC, Internet, Mobile and Cloud). https://lnkd.in/gAHRv9eK Per Benjamin Miller, his analysis revealed a consistent "Rule of 3" pattern of ~3X-3.5X increase in value creation from one technology wave to another, which leads to $20 trillion estimated value creation from current AI wave. The analysis emphasizes that "Nvidia or GPUs are producing more compute faster than Moore's law" to highlight that their estimates might be conservative. In my opinion, one of the main bottlenecks in AI scaling is GARGANTUAN POWER NEEDS (and not only physical compute units) required to operate enormous expected scale of AI applications. It takes around 10 years to fully grasp the impact of major technology wave - exciting milestone to watch for! #GenerativeAI #largelanguagemodels #artificialintelligence #airevolution

NVIDIA Launches Llama-3.1-Nemotron-70B-Instruct, Outperforming GPT-4o And Claude 3.5 Sonnet. AI at Meta Llama 3.1 framework, developed with transformer technology to create coherent language, forms the base for Nemotron-70B, surprisingly enough performing better than its bigger models in benchmark tests. It achieved outstanding results in Arena Hard, with a score of 85.0, AlpacaEval 2 LC, scoring 57.6, and GPT-4-Turbo MT-Bench, at 8.98. Some other models competed against it while winning several important metrics. These benchmarks thus stress the model to produce responses as sharp as those of humans by providing viable performance in general queries and coding applications. We’ve just published a step-by-step guide on deploying Llama-3.1-Nemotron-70B-Instruct on a Virtual Machine in the Cloud! ✔Read more here: https://lnkd.in/g6QSWWyw #NVIDIA #Aimodels #AI #Nemotron #Cloud #GPUs #Virtualmachine

Don’t forget to join us tomorrow on Sept 26 for the virtual AI, ML and Computer Vision Meetup! Register for the Zoom:https://lnkd.in/gGAWAuhp Talks will include: * GPUs at Scale: Trials of a GPUaaS Provider - Mischa van Kesteren at NexGen Cloud * Scaling Industrial AI - Daniel G. at Voxel51 #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #nvidia #gpu #blackwell

🗞️ Big News! 🗞️ Google's latest AI breakthrough, Project Astra, is set to redefine the future of AI! 🚀 Unveiled at their annual developer conference, Project Astra is a multimodal #AI assistant capable of real-time responses across video, audio, and text. This advancement highlights the incredible potential of AI to transform our daily interactions and professional workflows. At NexGen Cloud, we're excited by these advancements. Our GPU cloud services provide the robust, scalable infrastructure needed to support such cutting-edge AI technologies. As AI continues to evolve, NexGen Cloud is here to power the innovations of tomorrow. Have you tried Project Astra yet? What are your thoughts, or do you plan on using it soon? Let's discuss! 🗣️ Read the full article for more insights: https://lnkd.in/grX4KuQY #TechInnovation #NexGenCloud #GenerativeAI #GPUPower #Innovation #CloudComputing #NVIDIA #GPU #Cloud #AIInfrastructure #GPUisWhatWeDo

Join our webinar with industry experts from Supermicro and NVIDIA as we explore: - What is an AI factory?  - What is the opportunity for telecom companies with AI factories?  - What are examples of telecom companies that are becoming AI cloud providers? - How do Supermicro and NVIDIA support sovereign AI factory providers?

Join our webinar with industry experts from Supermicro and NVIDIA as we explore: - What is an AI factory? - What is the opportunity for telecom companies with AI factories? - What are examples of telecom companies that are becoming AI cloud providers? - How do Supermicro and NVIDIA support sovereign AI factory providers?

AI requires ultra-fast storage designed for IO-intensive workloads. This is precisely what simplyblock delivers. Charlie Boyle, NVIDIA's Vice President and General Manager of DGX Systems, recently highlighted key data challenges for customers embarking on AI projects. Discussing storage demands, Boyle emphasized that training larger models from scratch requires very fast storage, stating, "A lot of the way AI training works is they all hit the same file at the same time because everything's done in parallel." He also stressed the IO-intensive nature of checkpointing. At simplyblock, we've built our system with these requirements in mind, delivering low-latency storage at massive scale in the cloud. It's encouraging to see NVIDIA executives openly acknowledging the critical role of storage in AI. The reality is though that we still don't know how exactly this market will evolve in terms of enterprise needs. While there are different approaches to building AI applications, we believe that operations at scale will be tremendously different. #AI #AIStorage #Cloud

Exciting new blog by Chandan K. on "Optimizing LLM Deployment with LLaMA 3.2 and Denvr Cloud." In this post, we’ll explore how Llama 3.2—a refined and optimized version of its predecessors— bridges this gap, allowing powerful AI chatbots to operate on both high-end and constrained hardware setups. We’ll also show why using Denvr Cloud’s NVIDIA A100 GPUs offers an efficient solution for training and scaling these models, reducing costs while maximizing performance. #ai #chatbots #denvrcloud #denvrdataworks #llm #nvidia #gpu https://lnkd.in/daUbrRjk Post

Something pretty cool is happening in the AI world - NVIDIA's new NIM (NVIDIA Inference Microservices). So here's the deal: NIM is basically NVIDIA saying, "We got you" to all the businesses trying to jump on the AI train but feeling overwhelmed. It's like a Swiss Army knife for deploying AI – works on cloud, on-premise, even on your local machine. And get this – it's optimized for NVIDIA's GPU tech, so it's lightning fast. The best part? You don't need to be an AI wizard to use it. They've made it super easy with APIs, and it plays nice with popular open-source models like Llama-3 and Mistral. I'm genuinely stoked about this because it means more of us can start experimenting with AI without needing a PhD or a massive IT department. Plus, they're saying it can make your infrastructure up to 3 times more efficient. That's not just tech talk – that's real money saved! #NVIDIA #AI #VentureCapital