Quantum computing is the advancement of treditional computing. Can AI predict a new advancement in computing to make Quantum computing as treditional computing? #ArtificialIntelligence #GenAI #QuantumComputing #creativeThinking #AIResearch

Quantum Computing: The Elephant in the Room Quantum computing never ceases to amaze us. Every week we read about impressive hardware breakthroughs: more qubits, lower error rates, and better correction techniques. But are we seeing the whole picture? There's an elephant in the room that hardly anyone talks about: the applications. Or, to be more precise, their notable absence. It's been more than 30 years since Shor's revolutionary algorithm and more than 40 since the idea of using these systems to simulate other quantum systems was proposed. And the truth is, to this day, these remain their most concrete promises. It's not due to a lack of effort, but because many recent discoveries offer only marginal advantages on problems that remain enormously complex, or on tasks without any practical application other than to show that they can be solved. Think about something as simple as sorting a list of numbers. We don't even have a good way to represent those numbers or to design a quantum algorithm for this task. The software is lagging far behind the hardware. Does this mean quantum computers are just a curiosity? Not at all. The potential is undeniable. But for them not to become just an academic toy, we need an urgent shift in focus: more investment and talent dedicated to developing real applications. It's time for the software to catch up with the hardware. #️⃣ #QuantumComputing #Technology #Innovation #AI #SoftwareDevelopment #TechChallenges #Hardware

🤔 Ever wondered how AI and quantum computing could team up? LLMs are now designing quantum circuits that actually work better on real hardware... Mind-blowing research just came out of the University of Tokyo. As a software engineer, I'm genuinely excited about what this means for the future of computing. Here's what makes this special: 🔹 LLMs can now design quantum circuits autonomously 🔹 These AI-designed circuits are optimized for real-world hardware limitations 🔹 12-qubit model successfully tested on IBM quantum hardware 🔹 Performance beats traditional circuit designs The practical impact? They tested it on financial modeling - specifically Japanese bond interest rates. The results were impressive. Two things that really caught my attention: 1. The AI-designed circuits were shallower than standard approaches 2. They actually worked better on real quantum hardware (not just in theory!) This could be huge for making quantum computing practical. The fact that AI can help design better quantum circuits feels like science fiction becoming reality. What do you think about this convergence of AI and quantum computing? Are you as excited as I am about the potential applications? #QuantumComputing #AI #TechInnovation 𝗦𝗼𝘂𝗿𝗰𝗲꞉ https://lnkd.in/eV8YMawd

> Sharing Resource < Interesting paper this morning: "Behind the scenes of the Quantum Extreme Learning Machines" by A. De Lorenzis, M. P. Casado, N. Lo Gullo, T. Lux, F. Plastina, A. Riera Abstract: In recent years, Quantum Machine Learning (QML) has grown rapidly, emerging as a promising approach to make quantum computing implementation competitive. In this work, we investigate Quantum Extreme Learning Machines (QELM), a quantum variant of Extreme Learning Machines where training is restricted to the output layer. The proposed architecture combines dimensionality reduction (via PCA or Autoencoders), quantum state encoding, evolution under an XX Hamiltonian, and measurement, providing features for a single-layer classifier. By analyzing the performance of QELMs as a function of the evolution time, we identify a relatively sharp transition from a low-accuracy to a high-accuracy regime, after which the accuracy saturates. Remarkably, the saturation value matches that achieved with random unitaries, which induce maximally complex dynamics and optimally scramble information across the system. Across all cases studied, the critical transition time is sufficient for information to reach nearest neighbors, enabling feature extraction for learning, and is independent of the system size (i.e., the number of qubits). This independence implies that QELMs can be efficiently simulated classically for a broad class of tasks. Link: https://lnkd.in/eyv53YJY #quantummachinelearning #quantumcomputing #research #paper #quantumextrememachinelearning

🚀 Day-6 of the Quantum Computing Challenge | Qohort-3 of Quantum Learning QuCode 📌 Today’s Focus: - Bra–Ket Notation - Operators - Basis States In quantum mechanics and quantum computing, these are essential tools: 🔹 Bra–Ket Notation: a concise mathematical language describing quantum states and their relationships. 🔹 Operators: represent measurable quantities and transformations in quantum systems. 🔹 Basis States: the “building blocks” of quantum states, essential for representing qubits. Together, they form the foundation for expressing, analyzing, and manipulating quantum systems, crucial knowledge before delving into quantum algorithms. Excited to continue expanding on these core concepts as we progress on this journey! ⚡ hashtag #QuantumComputing hashtag #QuantumLearning hashtag #BraKetNotation hashtag #BasisStates hashtag #Operators hashtag #Qohort3 hashtag #STEM hashtag #QuCode hashtag #QuantumIndia hashtag #NationalQuantumMission hashtag #DeepTech hashtag #FutureOfComputing hashtag #QuantumStartups hashtag #ResearchAndInnovation hashtag #LearnQuantum hashtag #QuantumAlgorithms hashtag #QuantumCommunity hashtag #NextGenTech hashtag #DigitalIndia hashtag #TechForGood

Quantum Extreme Learning Machines Achieve High Accuracy Via Evolution and Dimensionality Reduction This research demonstrates that a quantum machine learning approach, utilising short periods of quantum evolution, achieves comparable accuracy to more complex quantum algorithms while remaining efficiently simulatable on conventional computers #quantum #quantumcomputing #technology https://lnkd.in/dwv_p5nW

🔮 Quantum Supercomputing: The Next Leap in Human Ingenuity Imagine a computer that doesn’t just calculate faster — it rethinks what calculation even means. That’s the promise of Quantum Supercomputing. Unlike classical supercomputers, which rely on bits (0s and 1s), quantum systems use qubits — capable of existing in multiple states simultaneously. Combine this with the massive scale of high-performance computing (HPC), and you get machines that could: ⚛️ Simulate molecules for drug discovery in hours (instead of decades). 🌍 Model climate systems with accuracy beyond current limits. 🔐 Break and rebuild cryptography at unimaginable speed. 📊 Optimize logistics, finance, and AI models at scales previously thought impossible. Germany, the U.S., and the U.K. are already investing billions to build these systems — not just as computers, but as national infrastructures for the future. But here’s the experience: Working with a quantum supercomputer isn’t just coding. It’s like standing at the edge of the unknown, writing instructions in probabilities and interference, and letting physics itself compute. 💡 For professionals, this means new skills: Quantum programming languages (Qiskit, Cirq) Hybrid quantum-classical algorithms Understanding decoherence, error correction, and scaling challenges We’re not just using technology anymore — we’re shaping the next era of discovery. --- ✨ Question for you: If you had access to a quantum supercomputer tomorrow, what problem would you solve first? #QuantumComputing #Supercomputing #Innovation #FutureOfWork #AI

Completed an introductory course on quantum computing, fascinating. When you complement this with Agentic AI, it releases a wealth of business and social benefits: Business Value at the Intersection When genetic AI meets quantum computing, the result is a “next-gen optimization engine” with transformative potential across industries: 1. “Accelerated Problem Solving” Quantum computers can evaluate multiple genetic algorithm solutions simultaneously, dramatically speeding up convergence toward optimal outcomes. This means faster decision-making in areas like: - Portfolio optimization in finance - Route planning in logistics - Resource allocation in manufacturing 2. “Smarter Simulations” Genetic AI thrives on iterative simulations. Quantum computing can supercharge this by handling “massive data sets and complex variables” in real time—ideal for: - Drug molecule modeling in biotech - Climate modeling in energy - Predictive maintenance in aerospace 3. “Strategic Advantage” Companies that integrate quantum-enhanced genetic AI can unlock “competitive advantages” by: - Reducing time-to-market for products - Enhancing operational efficiency - Solving problems previously deemed intractable 4. “Scalable Innovation” Quantum-native AI models allow businesses to scale innovation without being bottlenecked by classical computing limits. This opens doors to: - Autonomous system design - Hyper-personalized customer experiences - Real-time supply chain optimization Real-World Implications According to [Forbes](https://lnkd.in/e5Pqh-EU), companies that lead in developing quantum-native AI architectures will gain a “strategic edge”. The synergy enables faster automation, deeper insights, and more agile innovation cycles. "Introduction to Quantum Computing" by Jonathan Reichental! Check it out: https://lnkd.in/e5ifC6MJ #quantumcomputing.

⚛️ Quantum Computing: A Glimpse Into the Future What if solving today’s hardest problems, drug discovery, climate modelling, financial risk, or even cracking unbreakable codes, wasn’t about faster computers, but about rethinking how computers work? That’s the promise of quantum computing. At IBM and other labs, these machines sit inside systems cooled to colder than outer space, because they run on the fragile laws of quantum mechanics, where particles can exist in multiple states at once. 🖥️ Classical computer → stores information in bits (0 or 1), solving problems step by step. ⚛️ Quantum computer → stores information in qubits (0 and 1 at the same time), exploring countless possibilities simultaneously, like checking millions of doors at once instead of one by one. This doesn’t mean your phone will be replaced by a quantum computer. Instead, they’ll tackle problems classical computers could never realistically solve: ✅ Simulating molecules to design new medicines ✅ Optimising global supply chains ✅ Supercharging AI beyond what we imagine today In short, quantum computers aren’t faster than laptops. They’re a new paradigm new language of computation that could reshape science, technology, and the global economy. 👉 The coldest machine in the universe might just be the hottest spark for humanity’s future. ❓ Question: If quantum computers were in every lab tomorrow, what problem would you want solved first? 🔹 Follow AIPOOOL to Stay Ahead in the Race of Tech & AI 🚀 📩 Subscribe to our newsletter on LinkedIn 🔗 https://lnkd.in/gnUKzght #QuantumComputing #Future #Tech #IBM #Research #NextGenComputing #STEMeducation #PhysicsInAction #Technology #Chipularity #Science #ComputingFuture #AI #AIPOOOL

Researchers Accelerate Power Flow Studies Using Variational Circuits and Machine Learning Techniques Researchers demonstrate that variational quantum circuits, trained with power grid data, can accurately and efficiently predict power flow solutions, offering a potential advantage over conventional methods despite requiring fewer computational resources #quantum #quantumcomputing #technology https://lnkd.in/ezW2NJ8B