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𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 𝗶𝗻 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 -- 𝗠𝘆𝘁𝗵 𝗼𝗿 𝗥𝗲𝗮𝗹𝗶𝘁𝘆? #QuantumComputing holds the potential to shake up the manufacturing sector, bringing in exceptional computational capabilities to drive new levels of operational efficiency and innovation within the framework of #Industry40. 𝗧𝗵𝗲 𝗕𝗮𝘀𝗶𝗰𝘀 Unlike classical computers that use bits (0s and 1s), quantum computers use #qubits, which can be both 0 and 1 at the same time. This unique ability, known as superposition, along with entanglement, enables quantum computers to process massive amounts of data incredibly fast, opening new frontiers in operational excellence and informed decision-making. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗔𝗜 Quantum computing's power to handle large datasets quickly is set to push #manufacturing data #analytics and #AI to new heights. Quantum algorithms, like quantum neural networks and support vector machines, can make #ML models more accurate, something particularly exciting for areas with limited data, such as detecting defects in new processes. The result? More reliable products and faster innovation cycles. 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗮𝗻𝗱 𝗟𝗼𝗴𝗶𝘀𝘁𝗶𝗰𝘀 Quantum computing excels at solving complex optimization problems, like the traveling salesman dilemma; it finds the shortest route for deliveries, considering all variables—traffic, weather, etc. This translates into lower costs and faster delivery times. In manufacturing, it means better resource allocation, ensuring machinery, materials, and labor are used in the most effective way. 𝗠𝗮𝘁𝗲𝗿𝗶𝗮𝗹𝘀 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 Quantum computers can simulate molecular and material behavior at an atomic level, allowing manufacturers to develop new materials with desired properties more efficiently (imagine stronger, lighter, and more durable products). Quantum computing also improves the accuracy of #DigitalTwins, helping in fine-tuning designs and processes, leading to higher-quality products. 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 Quantum algorithms can optimize the movements of robots and #AGVs, making them more efficient and reducing energy consumption. Improved control algorithms mean robots can work more precisely and adaptively, leading to smoother operations and fewer hiccups on the production line. 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 Quantum computing can reduce waste and improve resource use by optimizing manufacturing processes at a granular level. One exciting impact is on energy consumption; imagine a power grid that produces energy exactly when needed. This is not only more efficient but also greener. Although we will witness quantum computing's impact in the long term, it's evident that it's not a myth but a tangible reality. Source: https://shorturl.at/OoeAX ***** ▪ Follow me and Ring the 🔔 to stay current on #IndustrialAutomation, #IndustrialSoftware, #SmartManufacturing, and #Industry40 Trends and Growth Opportunities!

Imagine a Quantum leap in #Healthcare that radically reduce the 10 years we currently must wait before a drug reaches the market. The amazing part of #QuantumComputing is that it can do things that no current computer can do such as Revolutionising medicine, communication, encryption, and AI. Think of AI as the Application on your phone and a Quantum Computer being the phone itself. #QuantumComputers harness the peculiar and counterintuitive properties of the quantum world, promising a step change in computing power that could #Transform our world. By manipulating all possible states of quantum particles, quantum computers can more efficiently and speedily perform many tasks that are extremely hard, indeed impossible, to perform with existing methods. This approach holds significant promise in crunching complex sums and modelling intricate processes. Wherever there is #ComplexMaths that cannot be solved on classical computing, we should seriously consider what quantum computers could do or contribute to solve these problems. Modelling and simulating drug interactions is a Healthcare example from real life quantum computing. To make this tangible, consider medicine and drug discovery. Today the best way to identify new compounds and understand their effects is to synthesise them and run practical experiments. Imagine if we could #Simulate these molecules, their behaviour and their effects on the human body, something currently too complex to do with classical computers. Another major challenge for the drug industry is #Acceleration of the whole process. This means not only the drug discovery process step, which can be done at the very beginning of the process, but also optimising each process step thereby digitisation the entire process. #Digitisation in this context means that there will be several complex mathematical operations to perform. It might be searching exceptionally large  databases, some optimisation, forecasts, etc. All these computations are complex, and certain problems are NP-Hard - that means they cannot be solved on #ClassicComputers which is why quantum computers are required to solve these major problems for the pharma industry. There are 15 companies in Healthcare Quantum Computing, including ProteinQure, Kuano, Menten, Algorithmiq and Polaris Quantum Biotech. We may also be able to better fight #GlobalWarming if quantum simulations can tackle materials-science problems, such as finding compounds for more-efficient batteries, better solar cells, and new kinds of power lines that transmit energy more efficiently.   To improve your Business or Industry - #Value Creation and Realization capabilities, follow me and contact us: https://lnkd.in/dDf6v5GZ. Also learn more by following our Business Pages #TMTdigtal at: https://lnkd.in/ersCKxQy and #TMTCrossCare at: https://lnkd.in/gVKaW4cj.   #QuantumHealthRevolution #ValueRealization #Leadership #Strategy #Transformation #DigitalBusiness #Partnership

Want to see the future of computing? Learn how AI is revolutionizing quantum computing! → It's solving our biggest obstacles and helps us get there faster. Here's how AI is making a difference: 1. Making Quantum Algorithms Better ↳ AI helps find new ways to solve technical problems faster. ↳ It tweaks algorithm settings to achieve better results. AI-driven insights lead to more efficient quantum solutions. 2. Reducing Errors and Noise ↳ Quantum computers are hypersensitive to errors. ↳ AI finds and fixes these errors. It also predicts noise sources to keep qubits stable. 3. Creating Quantum Materials and Hardware ↳ Building new quantum devices is tough. ↳ AI helps find the best materials quickly. This speeds up research and discovery. 4. Improving Quantum System Control ↳ Precise control of qubits is crucial. ↳ AI optimizes control sequences for accuracy. It also uses learning to improve strategies over time. 5. Blending Quantum and Classical Systems ↳ AI helps mix quantum and classical computing. ↳ It optimizes workflows for complex problems. Seamless integration enhances computational capabilities. These advancements push quantum computing forward. Remember, AI isn't just changing quantum computing, It's revolutionizing the future of technology. Stay curious and keep learning. Want to explore more? 🔮Follow XPANSE now! #XPANSE

Exciting news in the world of quantum computing! The first step towards creating quantum computers that can work at room temperature has been achieved. This breakthrough could lead to the development of desk or even phone-size quantum computers in just 10 years. The potential applications of this technology on AI, ML, and overall computing are stupendous. Stay tuned for more updates on this groundbreaking development! https://lnkd.in/ewvi9JqJ #QuantumComputing #AI #ML #Computing

AI has been under fire for various reasons—copyright issues, ethical concerns about job displacement, and more recently, its soaring energy consumption. Training large AI models is CO2 intensive (check out our previous post for more on that). The computational power required for AI means massive data centres consuming vast amounts of electricity. Enter #QuantumComputing—a groundbreaking technology that promises to revolutionise complex computations and significantly reduce energy usage. Why Quantum Computing? Quantum computers operate on a completely different level than classical computers. Using the principles of quantum mechanics, they process information in a fundamentally new way. Unlike classical bits, which are either a 0 or a 1, quantum bits (or qubits) can exist in multiple states simultaneously. This allows quantum computers to handle a vast array of possibilities all at once. Here’s why this is crucial for addressing AI's energy demands: 👩💻 Exponential Speed-Up: Quantum computers can solve complex problems much faster than classical ones. This could drastically cut down the time and energy needed for AI model training and execution. 👩💻 Efficiency: The ability of qubits to exist in multiple states allows for more efficient computations, potentially reducing the energy required for processing large datasets. 👩💻 Optimization: Many AI tasks involve optimisation problems, which quantum computers excel at solving more efficiently. This can lead to more energy-efficient AI solutions and boost our #EnergyEfficiency goals. When Will Quantum Computing Be Ready? Quantum computing is still in its early stages, but progress is accelerating. Today, quantum computers are mostly experimental. Companies like IBM, Google, and Microsoft are developing prototypes and achieving milestones like quantum supremacy. Quantum supremacy is the point at which a quantum computer can perform a task that is infeasible for classical computers to accomplish in a reasonable timeframe. The Road Ahead Integrating quantum computing with AI represents a promising frontier for #TechInnovation and #GreenTech. As we work towards making quantum computing a reality, we must continue to innovate responsibly and strive for a sustainable future. Quantum computing holds the potential to transform our approach to AI, significantly reducing its environmental impact and paving the way for a greener, more energy-efficient future. 🌱⚛️ Join the Conversation! What are your thoughts on the potential of quantum computing in addressing AI's energy demands? How soon do you think we will see practical applications? Share your insights!

🚀 AI and Quantum Computing: Transforming Unavailable Tech Solutions🌟 As we venture into the future of technology, the convergence of AI and quantum computing is set to revolutionize industries. Quantum computing, with its ability to process vast amounts of data simultaneously, complements AI's capacity for learning and adaptation, creating unparalleled opportunities for innovation. 🔍 The Synergy of AI and Quantum Computing Quantum computers leverage quantum bits (qubits) to perform complex calculations at unprecedented speeds. This ability to handle and analyze massive datasets enables AI models to achieve more accurate predictions and insights. For instance, in drug discovery, quantum computing can simulate molecular structures rapidly, allowing AI algorithms to identify potential treatments with remarkable efficiency. 🌐 Applications in Unavailable Tech Solutions 1. Enhanced Data Security: Quantum encryption offers a level of security that classical methods can't match. When combined with AI, this technology can predict and counteract potential security threats in real-time, safeguarding sensitive data. 2. Optimized Logistics: Quantum algorithms can solve intricate optimization problems in logistics, such as route planning and resource allocation. AI can then use this data to enhance operational efficiency, reducing costs and improving service delivery. 3. Personalized Healthcare: AI-driven quantum computing can analyze patient data at a granular level, leading to highly personalized treatment plans. This could revolutionize patient care by predicting health issues before they arise and tailoring interventions to individual needs. 4. Advanced Climate Modeling: Quantum computing can model complex climate systems more accurately, while AI can analyze these models to develop actionable strategies for combating climate change. Together, they can drive innovative solutions for a more sustainable future. 🔮 The Path Forward Integrating AI with quantum computing is still in its nascent stages, but the potential is immense. As these technologies evolve, we can expect to see groundbreaking advancements that address previously unattainable tech solutions. Embracing this synergy will not only drive innovation but also reshape our approach to solving some of the world's most pressing challenges. Let's stay ahead of the curve and explore the limitless possibilities that AI and quantum computing bring to the table! 🌐💡 #AI #QuantumComputing #TechInnovation #FutureTech #DataSecurity #Healthcare #ClimateChange #Logistics

Imagine a Quantum leap in #Healthcare that radically reduce the 10 years we currently must wait before a drug reaches the market. The amazing part of #QuantumComputing is that it can do things that no current computer can do such as Revolutionising medicine, communication, encryption, and AI. Think of AI as the Application on your phone and a Quantum Computer being the phone itself. #QuantumComputers harness the peculiar and counterintuitive properties of the quantum world, promising a step change in computing power that could #Transform our world. By manipulating all possible states of quantum particles, quantum computers can more efficiently and speedily perform many tasks that are extremely hard, indeed impossible, to perform with existing methods. This approach holds significant promise in crunching complex sums and modelling intricate processes. Wherever there is #ComplexMaths that cannot be solved on classical computing, we should seriously consider what quantum computers could do or contribute to solve these problems. Modelling and simulating drug interactions is a Healthcare example from real life quantum computing. To make this tangible, consider medicine and drug discovery. Today the best way to identify new compounds and understand their effects is to synthesise them and run practical experiments. Imagine if we could #Simulate these molecules, their behaviour and their effects on the human body, something currently too complex to do with classical computers. Another major challenge for the drug industry is #Acceleration of the whole process. This means not only the drug discovery process step, which can be done at the very beginning of the process, but also optimising each process step thereby digitisation the entire process. #Digitisation in this context means that there will be several complex mathematical operations to perform. It might be searching exceptionally large  databases, some optimisation, forecasts, etc. All these computations are complex, and certain problems are NP-Hard - that means they cannot be solved on #ClassicComputers which is why quantum computers are required to solve these major problems for the pharma industry. There are 15 companies in Healthcare Quantum Computing, including ProteinQure, Kuano, Menten, Algorithmiq and Polaris Quantum Biotech. We may also be able to better fight #GlobalWarming if quantum simulations can tackle materials-science problems, such as finding compounds for more-efficient batteries, better solar cells, and new kinds of power lines that transmit energy more efficiently.   To improve your Business or Industry - #Value Creation and Realization capabilities, follow me and contact us: https://lnkd.in/dDf6v5GZ. Also learn more by following our Business Pages #TMTdigtal at: https://lnkd.in/ersCKxQy and #TMTCrossCare at: https://lnkd.in/gVKaW4cj.   #QuantumHealthRevolution #ValueRealization #Leadership #Strategy #Transformation #DigitalBusiness #Partnership

Technology move with such a way that building a new factor is very important in certain categories our new recent project innovate all these categories for next 5 years to come Just to give you an example Here Are 6 Actual Uses for Near-Term Quantum Computers quantum computer is a special purpose accelerator,” says Matthias Troyer, corporate vice president of Microsoft Quantum and member of the Xprize competition’s advisory board. “It can have a huge impact for special problems where quantum mechanics can help you solve them Drug Metabolism In a 2022 paper published in PNAS, a collaboration between pharmaceutical company Boehringer Ingelheim, Columbia University, Google Quantum AI, and quantum simulation company QSimulate examined an enzyme called cytochrome P450. This particular enzyme is responsible for metabolizing roughly 70 percent of the drugs that enter the human body.The oxidation process by which the enzyme metabolizes drugs is inherently quantum, in a way that is difficult to simulate classically (classical methods work well when there are not a lot of quantum correlations at different scales) they found that a quantum computer of a few million qubits would be able to simulate the process faster and more precisely than state-of-the-art classical techniques. “We find that the higher accuracy offered by a quantum computer is needed to correctly resolve the chemistry in this system, so not only will a quantum computer be better, it will be necessary,” the researchers (including Babbush) wrote in a blog post CO2 Sequestration one strategy to lower the amount of carbon dioxide in the atmosphere is sequestration—using a catalyst to react with the carbon dioxide and form a compound that can be stored for a long time. Sequestration strategies exist, but are not cost or energy efficient enough to make a significant dent in the emissions.severalrecentstudies have suggested that quantum computers of the near future should be able to model carbon dioxide reactions with various catalysts more accurately than classical computers. If true, this would allow scientists to more effectively estimate the efficiency of various sequestration agricultural most farmland today is fertilized with ammonia produced under high temperature and pressure in large plants via the Haber-Bosch process. In 2017, a team at Microsoft Research and ETH Zurich considered an alternative ammonia production method—nitrogen fixation by way of the enzyme nitrogenase—that would work at ambient temperature and pressure Alternate Battery Cathodes Many lithium-ion batteries use cobalt in their cathodes. Cobalt mining has some practical drawbacks, including environmental concerns Unlike quantum computers, quantum sensors are already having an impact in the real world. These sensors can measure magnetic fields more precisely than any other technology There are also advantageous quantum algorithms still in search of definitive use cases i sunny faridi find these fascinating factors great

Quantum Computing's Symbiotic Relationship with Generative AI A Game-Changer for Industry Leaders In the 1970s, the promise of artificial intelligence was hindered by the lack of computational power. Fast forward to today, and advancements in AI, fueled by powerful GPUs, have transformed our interaction with technology, enabling bespoke content creation and more. Yet, the next leap in AI innovation is poised to come from quantum computing. Quantum computing's unique approach using qubits—subatomic particles that can exist in multiple states simultaneously—offers an exponential increase in processing power. This leap is set to revolutionize AI by allowing it to tackle even more complex tasks, from natural process simulation to advanced data analysis. Industry leaders must pay close attention to these developments. IBM's recent quantum processors, including the Heron and Condor chips, exemplify how quantum technology is breaking new ground. These chips, with their high qubit counts and advanced error correction capabilities, are paving the way for what IBM calls "quantum utility." Meanwhile, companies like Quantinuum are exploring alternative quantum technologies, such as trapped-ion systems, which offer their own unique advantages. These advancements underscore a critical point for CXOs: the quantum race is not about finding a single winner but understanding the diverse approaches and their potential applications. For CEOs and other C-suite executives, the synergy between generative AI and quantum computing represents an unprecedented opportunity. Quantum computing's ability to enhance AI's data processing capabilities will unlock new efficiencies and innovations across industries, from pharmaceuticals to finance. As global competition in quantum technology heats up, particularly between the U.S. and China, staying informed and investing in quantum research and talent will be crucial. The next wave of digital transformation will be driven by the integration of AI and quantum computing, a partnership that promises to solve some of the world's most complex challenges. #QuantumComputing #GenerativeAI #DigitalTransformation #FutureOfTech #CXOInsights #TechInnovation https://lnkd.in/gn3sGmuZ

Breakthrough set to push AI and quantum technologies even further. READ MORE: https://buff.ly/4eosvlh READ PAPER: https://buff.ly/4ewieno Processing power generally only makes the news when Apple launches its latest iPhone, but researchers from TMOS, the ARC Centre of Excellence for Transformative Meta-Optical Systems have made a breakthrough in the fundamental science that drives processors with the development of on-chip light sources for photonic integrated circuits. This breakthrough could lead to near-lightspeed communication on your phone, quantum computing power in your hand, as well as highly sophisticated artificial intelligence as your 24/7 know-it-all companion. In research published in ACS Nano, TMOS researchers describe an on-chip light source that will significantly increase the integration density of photonic chips and lead to vastly higher processing powers. This will enable emerging technologies such as highly sophisticated AI and quantum computing to operate on smaller devices, such as mobile phones. The researchers have grown microring lasers using a bottom-up approach. These microring lasers are only five micrometers in diameter with quantum wells inside each ring. Previous attempts at microring lasers for communication purposes used top-down or transfer methods of fabrication, where the microring laser was etched out of a substance, similar to how statues are carved out of marble. These methods created rough surfaces on the quantum wells that made them highly inefficient, and limited the device performance, especially for laser dimensions. Lead author Wei Wen Wong says, “Recent decades have seen an exponential growth in data capacities of photonic chips, however on-chip light sources that enable high integration density of these photonic integrated circuits have remained elusive, primarily due to fabrication challenges. Our method successfully grows quantum wells with excellent crystal quality and morphology that conforms to the microring cavity. Importantly, it does not require any post-growth cavity etching. The results were underpinned by a rigorous analysis by researchers at The University of Manchester led by Dr. Stephen Church and Dr. Patrick Parkinson, who used an AI algorithm to measure the light output from the thousands of microrings and construct a dataset that shows the consistency of the growth process across the entire chip. Wong says, “The contribution from the team at Manchester University allows us to demonstrate the high quality of the full sample set, rather than just a few individual examples, which gives an added layer of confidence in the scalability of our fabrication process.” TMOS Chief Investigator Hoe Tan says, “The next steps for this research will be to fabricate these lasers that can be electrically powered and also on silicon wafers as many photonic chips are made on this platform. For more information about this research, contact [email protected]