Day 13: Case Study: The Analog Ecosystem Powering Dynamic Neural Networks Imagine a supply chain that organizes itself, aligned to shared goals in real-time. That’s what we accomplished in the Australian fresh produce industry—a system once weighed down by inefficiencies, waste, and unpredictability. It was fragmented, reactive, and out of sync. The challenge was clear: How do we fix it? The solution wasn’t just to tweak the system, but to reimagine it completely. We stopped thinking of it as a traditional supply chain and envisioned it as a living ecosystem. An analog ecosystem powered by collaboration. We introduced ‘One Touch,’ a simple yet revolutionary system that connected growers, manufacturers, wholesalers, and retailers in real-time. They could see exactly what was happening in the supply chain, at every moment. Inventory, demand, availability—all dynamically adjusting, like neurons responding to live data. The impact? Over a billion dollars saved. Waste slashed. Inventory moved faster. What was once a broken system is now self-organizing, adapting, and thriving. This is the power of thinking differently. When you create an ecosystem that evolves with the world, it transforms how we live, work, and trade. Now, we’ve taken that analog ecosystem and digitally twinned it with a Dynamic Neural Network. And this is just the beginning of what’s possible. #SupplyChain #Sustainability #Innovation #ai #machine #NeuralNetworks #BalancedEcosystemScorecard
Patrick Byrne’s Post
More Relevant Posts
-
Are traditional computational methods losing their edge in the race for AI efficiency? As artificial intelligence reshapes industries from finance to tech, the spotlight is on not just what AI can do—but how efficiently it can do it. In our latest Quanta Byte, we dive deep into the math behind convolutions, a cornerstone of AI architectures. This article explores: - Foundations: The mathematical underpinnings of 2D convolutions, vital for AI image recognition and financial forecasting. - Efficiency: How reimagining convolutions as matrix multiplications, powered by the Fast Fourier Transform, can slash computational complexity. - Applications: From GPUs to quantitative finance, discover how small gains in speed lead to big value in AI training and beyond. If you're ready to geek out on the math driving AI's core operations, this one's for you. Read more: https://bit.ly/3ZikhFO #QuantitativeFinance #ArtificialIntelligence #MathInAI
To view or add a comment, sign in
-
The next quantum leap in AI may not be imminent, and that is a good thing! When LLMs broke into the scene, the quantum leap in GenAI took most of us by surprise. And alongside all the buzz and hype, there were claims that AGI could be in by as early as 2026. But beyond the hyped halls of social media, as experts across the globe sifted through LLMs, conducted real experiments, published papers, started blogging and speaking, a consensus has started to emerge - LLMs do not reason! And GenAI is not a sufficient ingredient for AGI. Of course, there will be interesting domain specific applications that will solve pseudo-reasoning tasks as well, by combining with RAG, through agentic orchestrators etc. But I am definitely leaning towards the school of thought that AGI will need another quantum leap that has not been achieved yet, and it is not imminent! What is more likely, and will create significant business value meanwhile, is that compound systems - consisting of a combination of traditional rule-based software, Classical ML models, GenAI, RAG, Agentic workflows etc will gradually be adopted *widely* and matured *gradually* in useful real world applications beyond generating text, images and video. In the process, we will learn step by step how to use AI in wide real world application, where and why a human in the loop is necessary etc. What do you think? #artificialintelligence #learning
To view or add a comment, sign in
-
🌟 Unlocking Creativity: Exploring Variational Autoencoders (VAEs) 🌟 Are you ready to dive into the cutting-edge world of generative neural networks? Join me on a journey where innovation meets imagination as we explore the captivating realm of Variational Autoencoders (VAEs)! 🎨 **Crafting Creativity**: At the heart of every VAE lies the power to unleash creativity. Imagine a world where machines learn to understand and replicate the essence of art, music, and literature. With VAEs, this dream becomes a tangible reality, as these neural networks master the art of generating new, awe-inspiring samples that mirror the beauty of the original data. 🌌 **Exploring Latent Space**: Step into a dimension where possibilities are limitless. Unlike traditional autoencoders, VAEs offer a continuous and smooth latent space, inviting us to embark on a journey of exploration. From seamlessly morphing faces to composing harmonious melodies, VAEs empower us to traverse this space with boundless creativity, fostering meaningful transitions and transformations along the way. 💡 **Innovative Techniques**: Ever wondered how VAEs achieve such remarkable feats? The answer lies in their innovative techniques. Through the distribution trick and the reparameterization trick, VAEs revolutionize the way we approach generative modeling. By embracing probabilistic concepts and elegant solutions, these networks redefine the boundaries of what's possible in artificial intelligence. 🚀 **Unleash Your Potential**: Whether you're a seasoned AI enthusiast or a curious newcomer, VAEs offer a gateway to unleashing your creative potential. Join the movement of forward-thinkers and visionaries who are harnessing the power of VAEs to push the boundaries of innovation and redefine the future of technology. Ready to embark on this exhilarating journey of discovery? Join me as we unravel the mysteries of VAEs and unlock the boundless possibilities of generative neural networks. Together, let's shape a future where creativity knows no bounds! #VAE #GenerativeAI #Innovation #Creativity #ArtificialIntelligence #FutureTech #LinkedInLearning #AICommunity 🚀🎨🌌
To view or add a comment, sign in
-
What’s the secret sauce behind smarter data-based decisions? Context. Neural networks are cool, but let’s be honest—they are a black box. You put data in, but good luck figuring out how they got to that decision. That’s where knowledge graphs step in, adding one magic ingredient: context. Here’s why that matters: 🤝 Seeing the big picture Knowledge graphs don’t just process data; they reveal how everything connects. Think of it as creating a clear map of a previously uncharted territory. Now, you can see how products, customers, and transactions are linked—making your data infinitely easier to navigate. 😌 Transparency at its best While neural networks give us results, they often leave us scratching our heads. Knowledge graphs? They show you exactly how a conclusion was reached. Clear pathways = smarter, more informed decisions. 🔗 Effortless integration No more wrestling with retraining models or constant adjustments. Knowledge graphs slot right into your existing data ecosystem, seamlessly connecting your sources and keeping everything in sync. Curious for more? Catch Inna Tokarev Sela's interview with SiliconANGLE & theCUBE from last month for more insights. #SemanticAI #AIGovernance #DataGovernance #DataFabric #GenAI
To view or add a comment, sign in
-
𝗙𝗼𝗿𝗴𝗲𝘁 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝘆𝗼𝘂 𝗸𝗻𝗲𝘄 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 - 𝗤𝗜𝗛𝗡𝗡𝘀 𝗮𝗿𝗲 𝗵𝗲𝗿𝗲! The world of AI is moving at warp speed, and there's a new concept generating a lot of buzz: Quantum-Inspired Hypergraph Neural Networks (QIHNNs for short). Buckle up, because these guys have the potential to completely change how we handle complex data. Think of data as Legos, but way cooler. Normal AI uses basic bricks (think nodes and edges), but QIHNNs? They like to connect multiple Legos together in one go (that's a hyperedge). This lets them understand complex relationships between things, making them perfect for untangling messy data in fields like medicine, social media, and even recommending what movie you should watch next (creepy cool, right?). QIHNNs borrow some tricks from quantum computing. It's like they're taking a peek into the future of super-powered computers! Even though true quantum computers are still under development, QIHNNs can use these ideas on regular computers to make them more efficient and powerful. So, how do these QIHNNs actually work? Imagine you're feeding data to the AI. First, it gets transformed into a special kind of Lego structure (the hypergraph) where all the connections are clear. Then, the AI uses some quantum-inspired moves to analyze all this data super quickly, almost like it can explore multiple possibilities at once. Finally, it learns from the data and gets even better at understanding complex stuff. What can we do with QIHNNs? The possibilities are endless! QIHNNs could help us design new medicines, understand how information spreads on social media, and recommend things you'll actually love (not just another pair of shoes you don't need). QIHNNs are a game-changer for AI. They're like the superheroes of data analysis, combining the best of hypergraphs and quantum computing to tackle even the most challenging problems. So, stay curious, stay informed, and get ready to see QIHNNs revolutionize the world around you! #MachineLearning #AI #QuantumComputing #Hypergraphs #Innovation #TechTrends
To view or add a comment, sign in
-
Ever pondered the notion of expanding memory in systems using vectors? 🤔 Imagine the possibilities of treating memory not just as storage but as dynamic vectors, capable of flexible manipulation and optimization. In this thought experiment, consider the implications of vectorized memory expansion across various domains, from machine learning to information retrieval. How might this paradigm shift redefine our understanding of memory utilization and system performance? Explore the intriguing concept of adding memory as vectors and unleash its potential in shaping the future of technology! 💡 #MemoryVectors #TechInnovation #ThoughtExperiment #FutureTech #AI #LLM #Vectors
To view or add a comment, sign in
-
Ever feel like you're drowning in a sea of information? You're not alone. As knowledge rapidly expands, it's becoming increasingly difficult for us to keep up. But what if there was a solution? A New Era of Knowledge. As an AI enthusiast and arm-chair philosopher, I've been fascinated by the rapid expansion of both human and knowledge and its implications for our future. This passion has led me to create a five-part series exploring the implications of the expanding human knowledge. In today's post, we dive into the first aspect of dealing with cognitive overload: the knowledge explosion and how AI and neuromorphic computing can help us keep up. AI to the Rescue: Mastering the Data Deluge. According to R. Buckminster Fuller's "Knowledge Doubling Curve," knowledge doubled every 25 years until the end of World War II. Today, knowledge doubles annually. The sheer volume of data generated is mind-boggling, and our brains simply can't keep up. This is where AI shines. By mimicking the way our brains process information, AI and neuromorphic computing can help us manage cognitive overload and extract valuable insights from vast datasets. Imagine a world where AI-powered systems can analyse medical images in seconds, identifying potential health issues that might otherwise go unnoticed due to human error. But this is just the beginning. As we continue to develop innovative solutions like honey-based memristors and salted DNA storage, we'll be able to store and process even more data, pushing the boundaries of what's possible. Bridging Minds and Machines. As we continue to generate and encounter more information, the role of AI becomes ever more critical. It's not just about managing data; it's about augmenting our understanding and capabilities, pushing the boundaries of what we can achieve. In the coming posts, we'll explore how these advancements are reshaping our understanding of consciousness, breaking down the barriers between mind and body, and paving the way for a new era of human cognition. #AI #innovation #technology
To view or add a comment, sign in
-
From alphabets to algorithms, AI is shaping human progress by transforming vast data into actionable insights, much like the advent of written language did for early societies. This shift highlights AI’s growing role in decoding complex information and accelerating innovation across industries, from health to finance. Explore how AI continues humanity's legacy of advancing knowledge and its broader societal implications in Eton Solutions’ article. Read more here https://lnkd.in/dB3_mmtn
To view or add a comment, sign in
-
Bias is ubiquitous in science and is therefore a concern as we increasingly AI-ify our scientific process. It sneaks into what methods we use, where we look for new materials, how we represent those materials, and even into how we label our experimental outcomes. But perhaps the sneakiest form of bias comes in the form of our a priori biases with respect to what is easy, hard, or impossible to predict with AI. In my talk tomorrow I will provide 4 tangible examples of "materials science intuition" being directly refuted by AI. Specifically I will discuss our own experiences with #AIforMaterials where: What was intuitively easy was actually hard. What we all agreed was hard was actually easy. When the hard task was easy to learn. When the easy task was hard to learn. #BiasInAI #ScienceTalk Come join me at the Materials Research Society #SpringMRS meeting tomorrow (April 24th at 2 pm) in Room 322 Level 3 Summit!!
To view or add a comment, sign in
-
🚀 AI in 60 Seconds: Unpacking Tomorrow's Technology Today! 🕒 Discover how AI is revolutionizing industries in the time it takes to sip your coffee! ☕ #AI #Innovation #TechTrends #Intellika #Machinelearning https://lnkd.in/g-9xAuyX
60 seconds to understand artificial intelligence
https://www.youtube.com/
To view or add a comment, sign in