Researchers from the University of Pennsylvania have developed a silicon chip that utilizes light waves to accelerate the processing speed and thus reduce energy consumption. The team achieved this by controlling the height of the silicon wafer at a specific region which allowed to control the propagation of light through the chip. The team also ensured the light traveled in a straight line after any scattering thus transferring the information at light speed. The design could also help to reduce the reliance on computational storage capacity (memory) since calculations are done in real-time. The team believes the silicon-photonic (SiPh) chip will find its application in GPU and AI over the coming years #semiconductor #chip #chipdesign #AI #aritificialintelligence Link: https://lnkd.in/g9ghjDtf https://lnkd.in/gKEWtKVH https://lnkd.in/gs8gCR9i Research Paper: https://lnkd.in/g43dNf2h
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Revolutionary SiPh Chip Unveils, Now the Juicy Part... The Big Leap... University of Pennsylvania engineers unveiled a silicon-photonic (SiPh) chip, revolutionizing AI training with light instead of electricity. This marks a major shift in computing power and efficiency. Innovative Design... Combining nanoscale manipulation and silicon technology, the chip excels in vector-matrix multiplication, crucial for neural networks. Its architecture promises to drastically speed up processing. The Breakdown: Published in Nature Photonics, the chip's design facilitates unprecedented processing speeds by manipulating light. This innovation could redefine GPU performance and energy consumption. The Winners... The chip's potential extends to enhancing GPUs and offering better privacy features, positioning it as a pivotal advancement in AI computing. Its implications for the tech industry are profound and far-reaching.
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A possible alternative to the Nvidia H100 GPU’s where demand is well in excess of supply. Perhaps this new innovation in Artificial Intelligence can close the demand gap for processing power.
Princeton Engineering - Built for AI, this chip moves beyond transistors for huge computational gains
https://engineering.princeton.edu
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Neuromorphic Computing Market Size, Share & Trends Analysis Report By Deployment (Edge Computing, Cloud Computing), By Offering (Hardware, Software), By Industry Vertical (Automotive, IT & Telecom, Aerospace & Defense, Industrial, Healthcare, Others), By Application (Image Recognition, Signal Recognition, Data Mining, Others), COVID-19 Impact Analysis, Regional Outlook, Growth Potential, Price Trends, Competitive Market Share & Forecast, 2022 - 2028. The neuromorphic computing market is poised for significant growth as advancements in AI, machine learning, and robotics continue to demand more efficient and powerful computing solutions. As research progresses and the understanding of brain functions deepens, neuromorphic systems are expected to become increasingly capable and versatile, leading to broader adoption across various industries. The growing emphasis on energy-efficient computing, particularly in the context of AI and IoT, will further drive interest and investment in neuromorphic computing technologies. With ongoing research and development, the potential applications of neuromorphic computing are vast, ranging from healthcare and autonomous systems to smart cities and advanced robotics. Overall, the future of neuromorphic computing holds great promise for revolutionizing the way we approach computing, data processing, and intelligent systems. IMIR Market Research Pvt. Ltd. 𝐆𝐞𝐭 𝐭𝐡𝐞 𝐬𝐚𝐦𝐩𝐥𝐞 𝐜𝐨𝐩𝐲 𝐨𝐟 𝐭𝐡𝐢𝐬 𝐩𝐫𝐞𝐦𝐢𝐮𝐦 𝐫𝐞𝐩𝐨𝐫𝐭: https://lnkd.in/d6XMuji4 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐢𝐧 𝐭𝐡𝐞 𝐦𝐚𝐫𝐤𝐞𝐭: Applied Brain Research Applied Materials Brain Corp BrainChip RainGrid, Inc. Brain-Machine Interface Systems Lab Brainwave Technologies CEA-Leti CognitiveScale Cortical.io Deep Vision Consulting Element Materials Technology Entropix Ltd General Vision, Inc. Graphcore GreenWaves Technologies HACARUS Hewlett Packard Enterprise HRL Laboratories, LLC IBM ICRON Intel Corporation KNOWME Koniku Lattice Semiconductor MemComputing, Inc. Merck KGaA, Darmstadt, Germany Mythic Neurala NeuroBlade Neuromorphic LLC Neuronic.ai NNAISENSE Numenta #computing #tech #technology #computer #software #b #programming #computerscience #computers #iphone #business #developer #socialmedia #cloud #maintenance #wordpress #cms #instagood #javascriptdeveloper #developerdiaries #agency #marketingdigital #it #codegency #gaming #programmer #engineering #engineer #webdevelopment #stem
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📱💡Did you know your smartphone actually starts… as sand? The journey of making a computer chip is a fascinating, high-tech process, transforming grains of sand into powerful microchips. At the University of Twente, researchers are not only developing new chips but are also finding ways to make chip production faster, smarter, and more sustainable.🌱 For example, PhD student Reinier Cool is working on “brain-inspired computing,” a new chip technology modeled after the human brain. These chips could be up to ten thousand times more energy-efficient for AI tasks, creating a more sustainable way to use artificial intelligence. Curious about how chips are made? Read the full article and discover how Twente is shaping the future of technology! https://lnkd.in/dSMwCGsV #utwente#chipinnovation #tech
From sand to smartphone - Stories
utwente.nl
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📱💡Did you know your smartphone actually starts… as sand? The journey of making a computer chip is a fascinating, high-tech process, transforming grains of sand into powerful microchips. At the University of Twente, researchers are not only developing new chips but are also finding ways to make chip production faster, smarter, and more sustainable.🌱 For example, PhD student Reinier Cool is working on “brain-inspired computing,” a new chip technology modeled after the human brain. These chips could be up to ten thousand times more energy-efficient for AI tasks, creating a more sustainable way to use artificial intelligence. Curious about how chips are made? Read the full article and discover how Twente is shaping the future of technology! https://lnkd.in/empVh9dv #utwente#chipinnovation #tech
From sand to smartphone - Stories
utwente.nl
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Taiwan Researchers Develop World's Smallest Single-Photon Quantum Computer Researchers at Taiwan's National Tsing Hua University have successfully developed the world's smallest quantum computer, capable of performing complex algorithms using a single photon. Led by Professor Chuu Chih-sung, the team demonstrated their box-sized device's ability to complete prime factorization according to Shor's algorithm approach. This breakthrough technology encodes information in 32 time-bins or dimensions within the wave packet of a single high-dimensional photon, offering lower energy costs and minimal interference during long-distance transmission. Unlike other quantum computer types that require cooler temperatures, this photonic device can maintain stable quantum states at room temperature. National Tsing Hua University President Kao Wei-yuan hailed the achievement as a major milestone in quantum technology, while Professor Mou Chung-yu predicted widespread applications in fields such as drug development, logistics optimization, data security, and artificial intelligence. https://lnkd.in/em-xCVJW
Taiwan Researchers Develop World's Smallest Single-Photon Quantum Computer
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Manipulating Quantum Particles at a Distance: A Theoretical Framework It is theoretically possible to manipulate and control quantum particles at a distance using forces vector processes.** This concept is rooted in the principles of quantum mechanics, specifically quantum entanglement and quantum teleportation. Quantum Entanglement: The Foundation * **Entangled Pairs:** When two particles are entangled, their properties become correlated, regardless of the distance between them. * **Instantaneous Influence:** Changes to one particle instantly affect the other, even if they are light-years apart. Forces Vector Processes * **Quantum Gates:** These are operations that can be performed on entangled particles to manipulate their quantum states. * **Quantum Teleportation:** A technique that allows the transfer of a quantum state from one particle to another, even over large distances. Potential Applications * **Quantum Computing:** Entangled particles can form the basis of quantum computers, which have the potential to solve certain problems exponentially faster than classical computers. * **Quantum Communication:** Quantum teleportation can be used to create secure communication channels that are immune to eavesdropping. * **Quantum Sensing:** Entangled particles can be used to create highly sensitive sensors for applications such as gravitational wave detection and biological imaging. **While the theoretical framework for manipulating quantum particles at a distance exists, there are significant technical challenges to overcome.** These include maintaining the coherence of entangled states, developing efficient quantum gates, and dealing with decoherence caused by interactions with the environment. **However, ongoing research and technological advancements are making progress towards realizing these theoretical possibilities.** As our understanding of quantum mechanics deepens and experimental techniques improve, we may one day be able to manipulate and control quantum particles at a distance to create novel materials, devices, and technologies.
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Neuromorphic Computing Market Report 2023 By Key Players, Regions, Competitive landscape and Forecast Till 2028 Neuromorphic Computing Market Size, Share & Trends Analysis Report By Deployment (Edge Computing, Cloud Computing), By Offering (Hardware, Software), By Industry Vertical (Automotive, IT & Telecom, Aerospace & Defense, Industrial, Healthcare, Others), By Application (Image Recognition, Signal Recognition, Data Mining, Others), COVID-19 Impact Analysis, Regional Outlook, Growth Potential, Price Trends, Competitive Market Share & Forecast, 2022 - 2028 🌐IMIR Market Research Pvt. Ltd. Global Neuromorphic Computing Market size was valued at USD 30.74 Million in 2021 and is projected to reach USD 8843.36 Million by 2028, growing at a CAGR of 83.2% from 2021 to 2028 according to a new report by Intellectual Market Insights Research. 📚 𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲 𝘀𝗮𝗺𝗽𝗹𝗲 𝗥𝗲𝗽𝗼𝗿𝘁:👇https://lnkd.in/d6XMuji4 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐢𝐧 𝐭𝐡𝐞 𝐦𝐚𝐫𝐤𝐞𝐭👇 Applied Brain Research Applied Materials Brain Corp BrainChip RainGrid, Inc. Brain-Machine Interface Systems Lab Brainwave Technologies CEA-Leti CognitiveScale Cortical.io Deep Vision Consulting Entropix, LLC General Vision Services. Graphcore. GreenWaves Technologies HACARUS Hewlett-Packard Development Company, L.P. HRL Laboratories, LLC IBM ICRON | Planning and Optimization Solutions Intel Corporation KNOWME Koniku. Lattice Semiconductor MemComputing, Inc. Merck KGaA, Darmstadt, Germany Mythic Neurala NeuroBlade Neuromorphic LLC Neuronic.ai NNAISENSE Numenta #computing #technology #tech #computer #b #computerscience #business #gaming #software #engineering #cloud #bhfyp #internet #networking #android #communication #computers #electronics #programming #automation #technological #pc #manufacturing #technews #industry #robotics #instatechnology #vintagecomputer #technical #data
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Scientists in China have built a new type of tensor processing unit (TPU) — a special type of computer chip — using carbon nanotubes instead of a traditional silicon semiconductor. They say the new chip could open the door to more energy-efficient artificial intelligence (AI). TPUs, however, this new chip is the first to use carbon nanotubes — tiny, cylindrical structures made of carbon atoms arranged in a hexagonal pattern — in place of traditional semiconductor materials like silicon. This structure allows electrons (charged particles) to flow through them with minimal resistance, making carbon nanotubes excellent conductors of electricity. The scientists published their research on July 22 in the journal Nature Electronics. Credit: Owen Hughes via Live Science #technology #ai #aichip #scientist #carbon #china https://lnkd.in/ecqEkVba
Specialist 'carbon nanotube' AI chip built by Chinese scientists is 1st of its kind and highly energy-efficient
livescience.com
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A team of Penn Engineers has made a groundbreaking leap with the development of a new chip that harnesses light waves for computing, setting the stage for a revolution in AI processing speeds and energy efficiency. This innovative silicon-photonic (SiPh) chip merges Engheta's cutting-edge research in nanoscale material manipulation with light—the fastest communication medium—with the widely-used silicon technology, aiming to overcome the limitations of traditional, electricity-based chips. Their work, published in Nature Photonics, showcases a chip designed for high-speed, low-energy vector-matrix multiplication, crucial for neural networks and AI applications. Leveraging light instead of electricity, this chip not only promises unparalleled processing speeds but also introduces significant energy savings and enhanced privacy, with the potential to perform complex computations without storing sensitive data. As the demand for advanced AI capabilities grows, this chip could be a game-changer, especially for applications requiring rapid data processing and stringent security measures. A future with faster, more efficient, and secure computing is on the horizon, thanks to the visionary efforts of Engheta, Aflatouni, and their teams. https://lnkd.in/eHsMBhyT #AI #Innovation #Engineering #SiliconPhotonics #SustainableTech #FutureOfComputing
New Chip Opens Door to AI Computing at Light Speed - Penn Engineering Blog
https://blog.seas.upenn.edu
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