Duke Rem 🐢’s Post

Liquid.ai, developer of beyond Transformer AI, raised $250M at $2B Core Principles Dynamic Connectivity: Neurons in LNNs exhibit changing connection patterns, unlike the fixed structures of traditional networks. Time-dependent Computation: LNN computations incorporate time as a key dimension, making them ideal for processing time-series data. Nonlinear Dynamics: LNNs utilize nonlinear functions to represent complex neuron relationships, enhancing their modeling capabilities. How Do Liquid Networks Work? LNNs function primarily through differential equations that govern the behavior of their neurons. These equations continuously adjust the state of the network based on data input.

I AM PLEASED TO ANNOUNCE that we have successfully run the test version of our new foundational AI which is based on artificial swarm intelligence. NEXUS is based on a completely different architecture than that which powers generative AI or LLMs. The neurons (or dants as we call them) are free moving, and using a set of rules, they collect into processing chains designed to solve complex math and optimisation problems. These processing chains are a product of NEXUS triggering emergence in a computational environment. We need to run more tests and collect observational data to discover how powerful the emergence that NEXUS has created is, and how we can develop and control it to do our bidding. I want to manage expectations, but I am very excited about the potential of this new form of AI. We are about to launch a new fund raise in support of bringing NEXUS to the market. Finally, to demonstrate how compute efficient NEXUS is, the initial test was run inside a smart phone. Thank you for your time, David Gammond Founder & CEO www.isda.world #artificialintelligence #machinelearning #isda #nexus #ai #agi #innovation #aibreakthrough #fundraising #venturecapital #equityfunding

🌟 Generative AI Hackathon with IBM Watsonx lablab.ai AI – What an Incredible Journey! 🌟 It's glad to share my experience participating in the Generative AI Hackathon with IBM Watsonx, alongside the amazing Granite Gurus team. Together, we created a groundbreaking project, Granite Gurus Many Eyes, an extension of our work from previous hackathons (Build Your AI Startup, Codestral, and Edge Runners). - Our Project Highlights: Leveraged IBM Granite and OpenGPTs to explore Multidimensional (MD) space using two key principles: Uniqueness – The ability to arrange spatial points in any configuration while maintaining uniqueness. Many Eyes – Understanding entire systems through the symmetries of MD-space. - We built a custom search engine on top of IBM Granite, showcasing how these principles reduce computational costs, improve accuracy, and accelerate processing times. This project has the potential to revolutionize search technology by optimizing resources, delivering faster results, and aligning with sustainability goals. - A massive thank you to iCodeGuru Zafar Shahid, PhD and my team and leader Michael Lively Amna Hassan Shahzil Imran Malaika F. Shabbir Anjum and all the Granite Gurus for their collaboration, innovation, and hard work. It was an honor to work alongside such brilliant minds, pushing the boundaries of AI-driven solutions! 💡 Looking forward to what’s next! #GenerativeAI #IBMWatsonx #AIHackathon #LablabAI #GraniteGurus #ManyEyes #TechInnovation #AI #Teamwork #ThankYou #IBM #Hackathon

🌟 I had an incredible opportunity to attend an insightful session on "Generative AI Development: Overcoming Obstacles and Achieving Excellence" at WSO2. The session provided a deep dive into the development of generative AI applications, highlighting the challenges and strategies involved in integrating advanced AI models with organizational data. The most fascinating part was the behind-the-scenes look at the development of WSO2's cutting-edge Gen-AI features: Asgardeo, Ballerina, and Choreo Copilot. It's amazing to see how these technologies are being shaped and the innovative solutions being implemented to tackle real-world issues. Shoutouts to the speakers who shared their expertise and experiences: 🎤 Mr. Malith Jayasinghe - Vice President, Research & AI 🎤 Mr. Nadheesh Jihan - Technical Lead 🎤 Mr. Chamath Samarawickrama- Associate Technical Lead 🎤 Mr. Anjana Supun - Senior Software Engineer I'm eager to apply these insights and see where the future of generative AI takes us! #GenerativeAI #WSO2 #AIDevelopment #Asgardeo #Ballerina #ChoreoCopilot #javacolombo

I’m thrilled to share that Atomic Agents is approaching 1,000 ⭐️ on GitHub! A massive THANK YOU to the community for your continuous support, contributions, and feedback. Though the community is still relatively young, this wouldn’t be possible without each one of you who believes in the power of building lightweight, modular, and extensible AI applications. To those who are new and are wondering "What is Atomic Agents?" Atomic Agents is a framework designed to simplify the creation of AI applications by eliminating redundant complexity and providing a flexible platform for building powerful, atomic AI components without overhead, complicated abstractions, ... Unlike some frameworks like #LangChain #LangGraph #AutoGen and #CrewAI, #AtomicAgents is extremely lightweight and easy to adapt. I highly recommend to go check out the project and some of the examples and other resources!

If I go silent then it is usually a sign that things are happening. Our team is one of 8 finalists in a “Startup Showdown” taking place at an AI Conference in SF on September 10th, and the ARC-AGI Challenge will be run with one of our mid-assembly systems soon. I had previously estimated the probability of being selected as a finalist for such a conference competition as very low, 5%, denoting the default margin of error. It may be a fluke, a true 5% probability event, or it may be that the AI industry is finally starting to look beyond trash technology like LLMs and the various things built on top of them. I can’t even guess the revised probability yet, pending further evidence. Whether or not the competition gives us a gold star, or whatever one is supposed to “win” at such an event, things are moving in the right direction, and given the right direction then acceleration becomes a “when” rather than an “if”. The score validation process for ARC-AGI is complicated for anything that can’t simply be uploaded to Kaggle like a proprietary and patent-pending cognitive architecture developed over the past 11 years from scratch, but I’d be rather surprised if they proved unwilling to validate a new high score. Our CEO will present the company on stage for the 10th: https://aiconference.com/ I’ll be grading the competence of the VC panel remotely from Japan.

AI Technology Insights Renaissance Philanthropy and XTX Markets Launch $9M AI for Math Fund https://lnkd.in/d2qVCvnP #FinTechInnovation #TechInFinance #AIInFinance #FinancialInclusion #CollaborativeInnovatio 

In the rapidly evolving world of AI, it's easy to focus on the names like Devin with all their tiring social media attention. But true innovation often comes from companies like Magic, who are building their solutions from the ground up. They're pushing the limits with frontier-scale code models, aiming to unlock a whole new level of AI collaboration. Why? - Code = Innovation: They see code generation as the key to groundbreaking products AND the path toward AGI. - Safety first: AGI safety isn't just a concern, it's a solvable problem to them. - Own it to win it: No off-the-shelf models here. They train their own for maximum control and potential. - Beyond transformers: Think bigger context windows for smarter AI. This from-scratch approach allows for greater customization, control, and potential breakthroughs. If you're looking for AI solutions that are tailor-made and truly cutting-edge, keep an eye on companies like Magic. #MagicAI #LLMs #CustomAI #AIinnovation #groundbreakingtech

[News] Pienso has secured $10M in Series A funding Pienso, a startup founded by MIT Media Lab alum Birago Jones and Karthik Dinakar, announced that it secured $10 million in a Series A round led by new investor Latimer Ventures. Pienso offers a no-code platform that enables non-technical users to annotate large volumes of data to train algorithms. https://buff.ly/3VwUwQB ↓ Are you interested in AI? Check out Data Phoenix (https://buff.ly/3Tu1ROf) - the global AI and Data community of 8000+ Engineers, Executives, and Founders. #DataPhoenix #AI #ML #MachineLearning #DataScience #ArtificialIntelligence #News

𝐆𝐫𝐨𝐤-1, the LLM from xAI - Release of the base model weights, and network architecture. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by #𝐱𝐀𝐈. The 𝐰𝐞𝐢𝐠𝐡𝐭𝐬 and the 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 are available under the 𝐀𝐩𝐚𝐜𝐡𝐞 2.0 license. 𝐖𝐢𝐥𝐥 𝐢𝐭 𝐛𝐞 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐛𝐢𝐠 𝐬𝐭𝐞𝐩 𝐭𝐨𝐰𝐚𝐫𝐝𝐬 𝐚𝐧 𝐨𝐩𝐞𝐧 𝐚𝐧𝐝 𝐜𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐞𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦? By open-sourcing one of the world's largest LLMs, xAI is walking the walk in Musk’s perceived moral battle against OpenAI’s closed models. While Grok’s capabilities don’t break any new barriers yet, the move is another big win for collaborative and transparent AI development.