Fjorden Labs

FOR IMMEDIATE RELEASE Kaiser Research Gathers Global Space Community for ECLIPSE WEEK 2026 in Iceland New York - June 21, 2024 - Kaiser Research is excited to announce ECLIPSE WEEK 2026, a collection of events, international public-private dialogues, and meetings, coinciding with the highly anticipated total solar eclipse in Iceland on August 12, 2026. These activities will celebrate space science and explore new opportunities for peaceful international space collaboration. Captivated by the recent total solar eclipse across the USA, Kaiser Research and several sponsors see the enthusiasm generated as an opportunity to reinforce cooperative bonds in the global space community. Kaiser is initiating an international steering committee that will form a non-profit to shape and manage ECLIPSE WEEK 2026 activities. “For a moment in time, Iceland will be the ‘center of the universe’ as it relates to space. This is a great opportunity to promote optimism for our future through space science and the rapidly growing space economy,” said Bill Patrowicz, CEO of Kaiser Research. Iceland’s involvement in space exploration dates back to the Apollo lunar missions, where Iceland’s unique landscapes provided ideal locations for training astronauts and testing technologies that would later be used on the Moon. Iceland presents many more opportunities to host this important research for extraterrestrial habitats and sustaining life on other planets, physically and logistically. “An eclipse an unforgettable experience and so are Iceland’s landscapes. We are excited to see other efforts taking shape in Iceland for August 12, 2026, and we will do everything we can to support them. We encourage our constituents to experience as much as Iceland will have to offer,” said Bill Patrowicz, CEO of Kaiser Research. For inquiries regarding participation, sponsorship, and partnership opportunities, please contact Bill Patrowicz at eclipseweek2026@kzr.is. About Kaiser Research: Kaiser Research specializes in developing public-private partnerships for scientific initiatives and helping industry transform frontier science into economic opportunities. For media inquiries, please contact: Bill Patrowicz eclipseweek2026@kzr.is Total Eclipse Data on timeanddate.com: https://lnkd.in/gx2F7wMH ###

Thanks to those who reached out after my last update wanting to know more about Fjorden Labs. So, over the next few weeks, I will post very short tidbits about who we are, what we will do, and what we aim to be. Fjorden Labs is a group of advanced AI innovation labs that will serve the world's most sophisticated space, energy, and security organizations and their grand challenges. Our core capabilities are AI supercomputing and AI systems integration. We specialize in the discovery, development, and deployment of AI supercomputing use-cases where emerging chip architectures are the optimal choice. We are deploying two major projects this year. One is in Norway. The other in the US. Many more will follow. There is so much more to talk about, so stay tuned. Feel free to connect with me anytime.

Training LLMs from scratch costs millions. That's why mostly only Big Tech companies or very well-funded startups can do it today. But do you know why? Let me walk you through it. 𝟭/ 𝗗𝗮𝘁𝗮 In the initial phase of pre-training, you need to curate TB of data and then spend a lot of time pre-processing. This process involves collecting, cleaning, and organizing massive amounts of data to ensure the model trains on relevant and high-quality information. This data collection and preparation is a resource-intensive task, requiring significant time and manpower. 𝟮/ 𝗔𝗜 𝗧𝗮𝗹𝗲𝗻𝘁 𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 Developing LLMs requires specialized skills, with top researchers at companies like OpenAI rumored to receive up to $10 million in compensation due to the competitive nature of the field. A team of machine learning, data science, and linguistic experts is essential. They design and refine neural networks, manage training processes, and assess performance. The significant cost of hiring and retaining this skilled workforce is crucial for enhancing the efficiency and accuracy of the model, a vital aspect of AI project success. 𝟯/ 𝗔𝗜 𝗦𝘂𝗽𝗲𝗿𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿 Today's AI models, requiring extensive data for high performance, demand significant computing power and GPUs, leading to a focus on AI supercomputers. IBM's Vela AI supercomputer, located in the Washington D.C. data center, exemplifies this with efficient resource allocation, minimal overhead, and powerful hardware like Nvidia A100 GPUs and fast Ethernet links. Developing models like Granite.13b on such supercomputers is costly; for instance, Granite.13b used 256 GPUs for over 1000 hours, with additional training adding 1152 hours, highlighting the substantial financial investment required in advanced AI development. What does this mean for most businesses? You don't need to engage in the complex process of training LLMs. If you choose to do so, it must be a very strategic move and can be quite worthwhile, but you need to have a solid ROI plan in place. Here's my recommendation: 1. Start with LLMs that are already available in the market. 2. Learn how to effectively prompt them for your specific use case. 3. Enhance them with your own enterprise data, using techniques like RAG or fine-tuning. 4. Choose your AI provider wisely, one that will grant you full ownership of the IP and the AI models you tune. 5. Consider optimizations and smaller models to save costs when moving into production. ____ If you like this content, please repost it ♻️ and follow me, Armand Ruiz, for more similar posts.

We are thrilled to announce that we’ve been chosen by Fortune in their first annual Fortune 50 #AI Innovators list! It’s an honor to be included among the industry’s leading AI companies: https://lnkd.in/esMTkmWT Stay tuned for more incredible solutions from Cerebras that advance AI and beyond!

MarketWatch recently wrote an article about Cerebras, describing our position in the AI landscape and highlighting our largest and fastest-ever computer chip, dedicated to AI. “Because of the way their system is architected, they can handle enormous amounts of data…it is an incredible solution for high-end data sets,” says Jim McGregor, an analyst with Tirias Research. “I would put Cerebras in [the] category of AI factory.” Additionally, Pat Moorhead, founder and chief analyst at Moor Insights and Strategy, says “If they can keep their trajectory going, they could be one of the companies that survives. Ninety out of 100 companies will go out of business. But for the sole fact that they are driving some pretty impressive revenue, they can establish a niche. They have an architectural advantage.” Read the full story here: https://lnkd.in/gVnZhQqd