Recursive neural network

BrainChip and Frontgrade Gaisler to Augment Space-Grade Microprocessors with AI Capabilities

Retrieved on: 
Sunday, May 5, 2024
Semiconductor, Technology, Aerospace, Manufacturing, Artificial Intelligence, Hardware, Leg, Recursive neural network, Data, OTCQX, AI, SOC, ASX, Agency, Artificial intelligence, Intelligence, Space, European Space Agency, ADR, Australian Space Agency, Space Race, Organization, BrainChip

This collaboration represents a significant milestone as it aims to introduce the first space-grade SoC worldwide with incorporated true artificial intelligence (AI) capabilities.

Key Points: 
  • This collaboration represents a significant milestone as it aims to introduce the first space-grade SoC worldwide with incorporated true artificial intelligence (AI) capabilities.
  • These next generation microprocessors would include BrainChip’s AI processing capabilities, thereby enabling a considerable step forward in the computing resources available for space-borne systems.
  • “Adding AI capabilities to our next generation microprocessors would set a new standard for modern space-grade computing devices,” said Sandi Habinc, General Manager at Frontgrade Gaisler.
  • A collaboration between Frontgrade Gaisler and BrainChip to utilize such advanced technologies for space is therefore very encouraging.”
    “When we say that we are dedicated to growing AI everywhere, we mean it,” said Sean Hehir, CEO of BrainChip.

VeriSilicon NPU IP is Shipped in Over 100 Million AI-Enabled Chips Worldwide

Retrieved on: 
Thursday, February 29, 2024
Technology, Semiconductor, IOT (Internet of Things), Security, Other Technology, Telecommunications, Software, Audio, Video, VoIP, Networks, Internet, Mobile, Wireless, Hardware, Electronic Design Automation, Data Management, Consumer Electronics, Artificial Intelligence, Dai, Transformer, Algorithm, Acuity, NPU, Processor (computing), Architecture, TensorFlow, AI, IPS, Internet of things, Electronics, Convolutional neural network, GM, Recursive neural network, LLM, CNN, ONNX, ISP, DDR, Memory, SDK, GPU, IP, Television, PyTorch, Tablet, Software development kit

VeriSilicon’s NPU IP is a high-performance AI processor IP designed with a low-power, programmable, and scalable architecture.

Key Points: 
  • VeriSilicon’s NPU IP is a high-performance AI processor IP designed with a low-power, programmable, and scalable architecture.
  • It can be easily configured to meet licensees’ requirements for chip sizes and power budgets, making it a cost-effective neural network acceleration engine.
  • VeriSilicon’s latest VIP9000 series NPU IP offers scalable and high-performance processing capabilities for both Transformer and Convolutional Neural Network (CNN).
  • VeriSilicon is leveraging our highly efficient AI computing capabilities and vast experience in deploying over 100 million AI-enabled chips to bring server-level AIGC capabilities to embedded devices.”

VeriSilicon Unveils the New VC9800 IP for Next Generation Data Centers

Retrieved on: 
Monday, January 8, 2024
Semiconductor, Hardware, Data Management, Technology, Artificial Intelligence, Dai, Artificial neural network, Consumer Electronics Show, Data center, GM, Recursive neural network, VPU, Data, AI, GPU, IP, Cloud computing, VVC, NPU, CES, Video game

The newly launched series IP caters to the advanced requirements of next generation data centers including video transcoding servers, AI servers, virtual cloud desktops, and cloud gaming.

Key Points: 
  • The newly launched series IP caters to the advanced requirements of next generation data centers including video transcoding servers, AI servers, virtual cloud desktops, and cloud gaming.
  • The VC9800 series of VPU IP boasts high performance, high throughput, and server-level multi-stream encoding and decoding capabilities.
  • Through Rapid Look Ahead encoding, the VC9800 series IP improves video quality significantly with low memory footprint and encoding latency.
  • The VC9800 series of VPU IP can seamlessly interface with Neural Network Processor (NPU) IP, enabling a complete AI-video pipeline.

Wearable Devices Releases Mudra Developer Kit for Its Gesture Control Technology

Retrieved on: 
Thursday, January 4, 2024
Recursive neural network, MDK, IOS, Gesture, Electronics, Original equipment manufacturer, Android, Sport, Translation, API, Intelligence, Application, SDK, Algorithm, WLDS, Finger

YOKNEAM ILLIT, ISRAEL, Jan. 04, 2024 (GLOBE NEWSWIRE) -- Wearable Devices Ltd. (the “Company” or “Wearable Devices”) (Nasdaq: WLDS, WLDSW), a technology growth company specializing in artificial intelligence (AI)-powered touchless sensing wearables, today announced the launch of the Mudra Developer Kit (MDK), a pioneering technology in wristband neural gesture control, set to redefine how we interact with our devices.

Key Points: 
  • YOKNEAM ILLIT, ISRAEL, Jan. 04, 2024 (GLOBE NEWSWIRE) -- Wearable Devices Ltd. (the “Company” or “Wearable Devices”) (Nasdaq: WLDS, WLDSW), a technology growth company specializing in artificial intelligence (AI)-powered touchless sensing wearables, today announced the launch of the Mudra Developer Kit (MDK), a pioneering technology in wristband neural gesture control, set to redefine how we interact with our devices.
  • With the capability of interpreting neural signals intended for the fingers, the Mudra Developer Kit signifies a leap forward in the human-device interaction domain.
  • The MDK deciphers the neural impulses into accurate Mudra 'Air-Touch' gestures which are translated into digital commands, offering an unmatched level of control.
  • For further details on the Mudra Developer Kit and to explore its potential, please visit https://www.wearabledevices.co.il/mdk .

Global Water Treatment Market Insights and Forecast (2023-2028): Integration of AI, Growing Demand for IoT Solutions and Increasing Adoption of Nanotechnology - ResearchAndMarkets.com

Retrieved on: 
Thursday, November 23, 2023
Other Natural Resources, Natural Resources, Recursive neural network, Artificial intelligence, Water, CNN, Metal, DT, Recycling, Investment, Recurrent neural network, Water supply, Drinking water, Development finance institution, RNN, Water resources, Automation, Nutrient, Seawater, Nanotechnology, Growth, Pesticide, AI, UNICEF, Knowledge, CAF, Sewage treatment

So, rising concerns regarding ground water depletion, low availability of naturally available drinking water and increasing adoption of the concept of recycling & reusing water by companies will continue to boost the growth of global water treatment market.

Key Points: 
  • So, rising concerns regarding ground water depletion, low availability of naturally available drinking water and increasing adoption of the concept of recycling & reusing water by companies will continue to boost the growth of global water treatment market.
  • So with increasing competition and reduced margins, the companies aren't seeking such substantial investments needed to build water treatment plants, impeding the growth of global water treatment market.
  • Therefore, increasing integration of AI in water treatment processes is expected to boost the growth of global water treatment market in the forecasted period.
  • The market for water treatment has been fragmented due to the presence of numerous international, regional and local players in the market.

Water Treatment Market Poised to Reach $325.41 Billion by 2023: Uncovering Key Trends & Challenges

Retrieved on: 
Monday, November 20, 2023
Recursive neural network, Artificial intelligence, Pressure, Water, CNN, Water quality, Metal, DT, Recycling, Urbanization, Investment, Application, Co-production (public services), Recurrent neural network, Water supply, Drinking water, Disinfectant, Veolia, Development finance institution, RNN, Water resources, Fresh water, Automation, Nutrient, Seawater, Swimming, Nanotechnology, Sewage, Growth, Pesticide, Population growth, AI, UNICEF, Knowledge, Public, CAF, Sewage treatment

The global water treatment market is expected to reach US$325.41 billion in 2023, progressing at a CAGR 7.20% over the projected period.

Key Points: 
  • The global water treatment market is expected to reach US$325.41 billion in 2023, progressing at a CAGR 7.20% over the projected period.
  • So with increasing competition and reduced margins, the companies aren't seeking such substantial investments needed to build water treatment plants, impeding the growth of global water treatment market.
  • Therefore, increasing integration of AI in water treatment processes is expected to boost the growth of global water treatment market in the forecasted period.
  • Services water treatment market is both the largest and the fastest growing segment of global water treatment market owing to increasing manufacturing activities, rapid urbanization, increasing company focus on building technologically advanced water treatment facilities and growing need for maintenance of existing sewage treatment plants.

Pioneering a Counterfeit-Free Future: Global ETS LLC's Revolutionary AI Technology Showcased at SMTA

Retrieved on: 
Monday, October 23, 2023
San Francisco Bay Area, Hope, Quality control, Recursive neural network, Particle swarm optimization, Artificial intelligence, CNN, Trust, IC, Risk, Rnn (software), Genetic algorithm, Classification, Electronics, Algorithm, Culture, ETS, Video game, Sales

The Surface Mount Technology Association (SMTA), a global nexus of industry professionals, champions the cause of curbing this malaise.

Key Points: 
  • The Surface Mount Technology Association (SMTA), a global nexus of industry professionals, champions the cause of curbing this malaise.
  • Global ETS LLC 's innovation is a testament to the firm's enduring commitment to elevating industry standards.
  • Amidst a backdrop where counterfeit chip detection remains a pressing challenge, Global ETS LLC technology resonated profoundly within the SMTA community.
  • Wensheng Chen from Global ETS LLC remarked, 'The response from the SMTA community to our innovative hybrid AI technology has been overwhelmingly positive.

WiMi Developed a Deep Learning-Based Approach to Personalized Video Recommendations

Retrieved on: 
Friday, October 13, 2023
Cloud, Online, Holography, Deep learning, Algorithm, RNN, Social network analysis, Intelligence, Virtual reality, WIMI, Communication, CNN, Heart, Recursive neural network, SGD, Augmented reality, AR, Social, Learning, LSTM, Social media, Research, Overfitting, Video game, Mobile phone, Online shopping

BEIJING, Oct. 13, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that it developed a personalized video recommendation system based on deep learning according to the development needs of the industry, providing new ideas and directions for the research of personalized video recommendation under deep learning.

Key Points: 
  • BEIJING, Oct. 13, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that it developed a personalized video recommendation system based on deep learning according to the development needs of the industry, providing new ideas and directions for the research of personalized video recommendation under deep learning.
  • In personalized video recommendation, different types of neural network models are used to model the association between the user and the video.
  • Feature Representation Learning: In a personalized video recommendation system, effective feature representations are critical to the performance of the model.
  • WiMi's deep learning-based personalized video recommendation technology solves information overload, personalizes user needs, improves user experience, and promotes market development in the online video industry.

Explainable-AI Image Recognition achieves precise 3D descriptions of objects for US Air Force, a major AI breakthrough

Retrieved on: 
Tuesday, September 5, 2023
Medical imaging, California Institute of Technology, National Medal of Technology and Innovation, University of California, Berkeley, USAF, Z-transform, Binocular Rivalry Described by Quantum Formalism, Engineering, United States Air Force, 3D, Recursive neural network, UTSA, Fuzzy logic, ML, National Medal, Doctor of Philosophy, Invention, GAN, Explainable artificial intelligence, Cornell University, CPU, Machine learning, Algorithm, Artificial intelligence, Cognition, AI, ResNet, GPU, 3D printing, LASIK, ZAC, MD, Physics, Research

This is in sharp contrast to the other algorithms in industry (e.g., statistical algorithms, Neural Net, Deep CNN, ResNet, and GAN), which are not able to describe and measure 3D objects at all.

Key Points: 
  • This is in sharp contrast to the other algorithms in industry (e.g., statistical algorithms, Neural Net, Deep CNN, ResNet, and GAN), which are not able to describe and measure 3D objects at all.
  • In addition, the other algorithms in industry also require thousands to billions of training samples, trained on large GPU servers.
  • ZAC algorithms can describe and measure 3D objects from any viewpoint, for full "Explainability" of 3D objects.
  • "ZAC algorithms can describe and measure 3D objects from any viewpoint, for full Explainability of 3D objects," emphasized Dr. Bijan Tadayon, CEO of ZAC.

Novel Application of Machine Learning Approaches Predicts Gait Dysfunction in Parkinson's Disease

Retrieved on: 
Sunday, August 27, 2023
Average absolute deviation, Rectifier (neural networks), Magnetic resonance imaging, DTI, Disease, MLP, Perceptron, Recursive neural network, Department of Neurology, Xuanwu hospital, Movement disorder, Movement, DWI, Parkinson's disease, Patient, HIV disease progression rates, Machine learning, AUC, Neurology, UPDRS, International Congress on Tuberculosis, Medical imaging, PD

COPENHAGEN, Denmark, Aug. 27, 2023 /PRNewswire-PRWeb/ -- A machine learning approach from diffusion tensor imaging (DTI) multi-spectral diffusion weighted imaging (DWI) showed prediction of gait dysfunction in PD according to a study released today at the International Congress of Parkinson's Disease and Movement Disorders® in Copenhagen, Denmark.

Key Points: 
  • COPENHAGEN, Denmark, Aug. 27, 2023 /PRNewswire-PRWeb/ -- A machine learning approach from diffusion tensor imaging (DTI) multi-spectral diffusion weighted imaging (DWI) showed prediction of gait dysfunction in PD according to a study released today at the International Congress of Parkinson's Disease and Movement Disorders® in Copenhagen, Denmark.
  • Several neuroimaging studies in Parkinson's disease (PD) suggest an altered interplay between cortical and subcortical brain areas at a structural and functional level each that contributes to gait dysfunction in PD.
  • This study used 7 different quantitative DTI measures from 43 PD patients along with UPDRS III, to develop a prediction model for gait dysfunction using different machine learning approaches and 60 template regions of interest (ROIs).
  • "This study suggests that a machine learning approach of DTI analysis may have potential in predicting gait dysfunction in PD patients if confirmed by larger confirmative studies.