LSTM

Syntiant Unveils NDP250 Neural Decision Processor with Next-Gen Core 3 Architecture

Retrieved on: 
Tuesday, April 9, 2024
Cortex, TTS, Speech, 2D, Environment, LSTM, M12, Embedded, GRU, ASR, Classification, PLL, Human, Life, Deep learning, Language, Privacy, GOPS, NDP, Computer data storage

IRVINE, Calif., April 09, 2024 (GLOBE NEWSWIRE) -- Syntiant Corp., a leader in low power edge AI deployment, today introduced its Syntiant® NDP250 Neural Decision Processor™ (NDP), the company’s most powerful chip that delivers 5x the tensor throughput than its previous generation of deep learning hardware.

Key Points: 
  • IRVINE, Calif., April 09, 2024 (GLOBE NEWSWIRE) -- Syntiant Corp., a leader in low power edge AI deployment, today introduced its Syntiant® NDP250 Neural Decision Processor™ (NDP), the company’s most powerful chip that delivers 5x the tensor throughput than its previous generation of deep learning hardware.
  • Built using the Syntiant Core 3™ programmable deep learning architecture, the NDP250 is designed for numerous imaging, speech and sensor applications in power-constrained devices, such as person detection, object classification, automatic speech recognition (ASR), text to speech (TTS) and motion tracking, among others.
  • “Our NDP250 builds on two generations of neural network architectures to deliver 30 GOPS, making it our fastest, highest-performing chip yet,” said Kurt Busch, CEO of Syntiant.
  • Syntiant will be demonstrating the NDP250 and various hardware-agnostic deep learning vison models at Embedded World 2024 (Hall 2 – Booth 2-238), April 9-11 in Nuremberg, Germany.

WiMi Developed Efficient Prediction Models for Cryptocurrency Markets Based on Machine Learning

Retrieved on: 
Tuesday, February 27, 2024
Cloud, Bitcoin, EMD, Algorithm, Artificial intelligence, WIMI, VMD, Overalls, Holography, Face, ELM, Extreme learning machine, Machine learning, Augmented reality, Deep learning, LSTM, Cryptocurrency

Based on machine learning, deep learning and other techniques, it focuses on developing efficient forecasting models applicable to the cryptocurrency market.

Key Points: 
  • Based on machine learning, deep learning and other techniques, it focuses on developing efficient forecasting models applicable to the cryptocurrency market.
  • Therefore, WiMi chose a multi-scale analysis approach, matching different machine learning algorithms with corresponding multi-scale components to construct a more comprehensive cryptocurrency price prediction model.
  • WiMi put its emphasis on the hybrid LSTM-ELM model that combines advanced methods such as multi-scale analysis, artificial intelligence, and signal decomposition.
  • Deep learning algorithms enhanced data learning capabilities for the model, allowing it to better understand and adapt to the nonlinear characteristics of the cryptocurrency market.

WiMi Developed an LSTM-based Data Analysis System

Retrieved on: 
Monday, January 22, 2024
Cloud, RNN, Learning, Holography, Architecture, Natural language processing, Social media, Policy, Deep learning, Memory, Feedback, LSTM, Environment, Data analysis, Long short-term memory, Augmented reality, WIMI, Cryptocurrency

Traditional data analysis methods make it difficult to handle such complex data, but the LSTM algorithm can solve this problem.

Key Points: 
  • Traditional data analysis methods make it difficult to handle such complex data, but the LSTM algorithm can solve this problem.
  • The system uses a variety of data sources, including historical prices, transaction volumes, social media data, and more.
  • WiMi utilizes the LSTM algorithm to build an efficient data analysis system that is capable of deep learning from historical Bitcoin transaction data to extract key factors that influence price trends.
  • The system mainly includes the following modules:
    Data pre-processing: Processing raw data to ensure the quality of the data.

BAM.money Introduces Game-Changing Trading Tool That Empowers Investors to Compete with Industry Giants

Retrieved on: 
Thursday, January 4, 2024
Barclays, Hallucination, Risk management, LSTM, Goldman Sachs, JPMorgan Chase, Environment

This groundbreaking tool uses objective-driven AI, ML, and human expertise to turn complex data into clear signals that unlock alpha for professional traders.

Key Points: 
  • This groundbreaking tool uses objective-driven AI, ML, and human expertise to turn complex data into clear signals that unlock alpha for professional traders.
  • Many investment firms face challenges using alternative data and advanced technology to enhance decision-making, mainly due to constraints on expertise and costs.
  • This means focused, objective-driven tools are critical to help investors see the whole picture and avoid getting lost in the parts."
  • With a 21-day free trial, see for yourself how BAM's TradingPulse levels the playing field with price-focused, objective-driven AI/ML at https://BAM.money .

WiMi Announced Hybrid Recurrent Neural Network Architecture-Based Intention Recognition for Human–Robot Collaboration

Retrieved on: 
Monday, December 18, 2023
Cloud, Architecture, CNN, Classification, Probability, Research, LSTM, WIMI, Human, Augmented reality, Speech, Holography, GRU, RNN, Computer data storage

Hybrid recurrent neural network architecture is a model that combines recurrent neural network (RNN) and convolutional neural network (CNN).

Key Points: 
  • Hybrid recurrent neural network architecture is a model that combines recurrent neural network (RNN) and convolutional neural network (CNN).
  • Hybrid recurrent neural network combines the advantages of RNN and CNN, which can better capture sequence information and local features, and can better handle intention recognition for human-robot collaboration.
  • Using hybrid recurrent neural network architecture for human-robot collaboration intention recognition can greatly improve the efficiency and quality of human-robot collaboration.
  • WiMi will try to fuse multi-modal information into a hybrid recurrent neural network architecture-based human-robot collaboration intention recognition.

MicroAlgo Inc. Announced Bitcoin Trading Prediction Algorithm Based on Machine Learning and Technical Indicators

Retrieved on: 
Tuesday, December 26, 2023
Bollinger Bands, Learning, Classification, Forecasting, Fintech, Movement, Deep learning, LSTM, SVM, Tree (graph theory), RSI, Machine learning, Growth, Intelligence, Algorithm, Cryptocurrency

BEIJING, Dec. 26, 2023 /PRNewswire/ -- MicroAlgo Inc. (NASDAQ: MLGO) (the "Company" or "MicroAlgo"), today announced a Bitcoin trading prediction algorithm based on machine learning and technical indicators.

Key Points: 
  • BEIJING, Dec. 26, 2023 /PRNewswire/ -- MicroAlgo Inc. (NASDAQ: MLGO) (the "Company" or "MicroAlgo"), today announced a Bitcoin trading prediction algorithm based on machine learning and technical indicators.
  • MicroAlgo Inc.'s Bitcoin trading prediction algorithm based on machine learning and technical indicators utilizes a large amount of market data to train a model to predict the future movement of the Bitcoin price.
  • MicroAlgo Inc.'s Bitcoin trading prediction algorithm based on machine learning and technical indicators plays a crucial role in the construction of the technical foundation with data processing and feature engineering.
  • By incorporating machine learning models, technical indicator analysis, and advanced quantitative trading strategies, a Bitcoin trading prediction algorithm based on machine learning and technical indicators from MicroAlgo Inc. has demonstrated superior performance on historical data.

WiMi Developed Explainable Artificial Intelligence (XAI)-based fNIRS Neuroimage Classification

Retrieved on: 
Thursday, December 7, 2023
Cloud, Classification, Brain, Research, CNN, BCI, Augmented reality, Virtual reality, Data analysis, Artificial intelligence, Holography, Infrared spectroscopy, Human, WIMI, LSTM, Medical imaging

BEIJING, Dec. 7, 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 explainable artificial intelligence (XAI)-based fNIRS neuroimage classification, bringing a breakthrough in the development of BCI technology.

Key Points: 
  • BEIJING, Dec. 7, 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 explainable artificial intelligence (XAI)-based fNIRS neuroimage classification, bringing a breakthrough in the development of BCI technology.
  • WiMi's XAI-based fNIRS neuroimage classification system consists of several key modules that work together to process, analyze, and interpret data for accurate brain activity classification and interpretation.
  • WiMi's XAI-based fNIRSfNIRS neuroimage classification system employs two key classification modules, i.e., a one-dimensional sliding-window-based convolutional neural network (CNN) and a long short-term memory (LSTM) neural network.
  • The research and application of WiMi's XAI-based fNIRSfNIRS neuroimage classification system brings new insights to the field of brain science.

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.

Flow Security Unveils the First DSPM Solution to Harness LLM in Unstructured Data Classification

Retrieved on: 
Wednesday, August 2, 2023
Data Management, Technology, Professional Services, Business, Other Technology, Apps, Applications, Data Analytics, Software, Artificial Intelligence, Other Professional Services, Internet, NER, LLM, GDPR, CCPA, OCR, Human, PCI-DSS, Multimedia, Classification, HIPAA, LSTM, Algorithm, Cryptocurrency, Mobile phone, Book

With a focus on unstructured data, this technology can identify over 150 distinct data types with unprecedented accuracy.

Key Points: 
  • With a focus on unstructured data, this technology can identify over 150 distinct data types with unprecedented accuracy.
  • View the full release here: https://www.businesswire.com/news/home/20230802897459/en/
    Flow was quick to recognize the potential LLMs have to conquer some of our biggest data security challenges, including data classification.
  • Flow Security was the first DSPM vendor to realize that LLMs could take data classification technology to a whole new level.
  • Its latest offering is bringing about a revolution in the understanding and classification of unstructured data.

Cisco Launches Full-Stack Observability Platform

Retrieved on: 
Tuesday, June 6, 2023
Unify, Cloud, DevOps, KPI-driven code analysis, Forecasting, Secop, ARIMA, ML, Risk, Metric, LSTM, FSO, LAS, Organization, Platform, Root cause analysis, CISCO, CSCO, Ecosystem, Telemetry, Network equipment provider, Risk management, Cisco

LAS VEGAS, June 6, 2023 /PRNewswire/ -- CISCO LIVE -- Cisco (NASDAQ: CSCO) announced the launch of a new Full-Stack Observability Platform—a vendor-agnostic solution that harnesses the power of the company's full portfolio. It delivers contextual, correlated, and predictive insights that allow customers to resolve issues more quickly and optimize experiences, while also minimizing business risk.

Key Points: 
  • Ecosystem of Partners Enable New, Extensible Observability Use Cases to Unify and Secure Digital Experiences
    New vendor-agnostic Cisco Full-Stack Observability (FSO) Platform brings data together from multiple domains at scale.
  • Powerful new platform delivers unparalleled insights, optimizing experiences and minimizing business risk for customers
    LAS VEGAS, June 6, 2023 /PRNewswire/ -- CISCO LIVE -- Cisco (NASDAQ: CSCO) announced the launch of a new Full-Stack Observability Platform—a vendor-agnostic solution that harnesses the power of the company's full portfolio.
  • The Cisco FSO Platform is also designed as a unified, extensible platform, allowing developers to build their own observability solutions, empowering an ecosystem of customers and partners.
  • Cloud Native Application Observability is the premier solution delivered on Cisco FSO Platform.