AI accelerator

BrainChip Goes Virtually Everywhere at AI Everywhere Forum 2021

Retrieved on: 
Tuesday, September 28, 2021
Data Management, Security, Technology, Other Technology, Internet, Hardware, Taste, Exhibition, Aircraft, Solution, Home automation, Privacy, Data center security, Device, AI accelerator, Carbon, SOC, PDT, Acquisition, IOT, ASX, Intelligence, Brain, Learning, Security operations center, Machine learning, Robotics, Intellectual property, Technical, Data center, OTCQX, Medical device

A live chat hosted by the BrainChip team will be answering questions during each virtual presentation.

Key Points: 
  • A live chat hosted by the BrainChip team will be answering questions during each virtual presentation.
  • In this session, attendees will learn how to easily apply efficient AI in edge devices by implementing Akida IP into their SOC or as stand-alone silicon.
  • As AI becomes more prevalent in these systems, there remains a need to bring processing to devices at the edge through on-chip learning.
  • The conference will focus on AI in the Data Center, at the Edge, in the Device and for the IoT.

BRIDGEi2i Named in Gartner's Market Guide for Artificial Intelligence Service Providers, 2021

Retrieved on: 
Tuesday, September 21, 2021
Cobham Analytic Solutions, Organization, Acceleration, Entrepreneurship, Solution, AI, AI accelerator, Medical device, Customer service

FREMONT, Calif., Sept. 21, 2021 /PRNewswire/ --BRIDGEi2i Analytics Solutions announced its inclusion in Gartner's Market Guide for Artificial Intelligence Service Providers, 2021.

Key Points: 
  • FREMONT, Calif., Sept. 21, 2021 /PRNewswire/ --BRIDGEi2i Analytics Solutions announced its inclusion in Gartner's Market Guide for Artificial Intelligence Service Providers, 2021.
  • The Gartner report compiles a list of service providers that represent the breadth of offerings in the AI market.
  • Being featured in the Gartner's Market Guide for Artificial Intelligence Service Providers, 2021, takes us one step further on the journey of making AI real for enterprises.
  • Source: Gartner Market Guide for Artificial Intelligence Service Providers, Published 26 July 2021

NVIDIA Turbocharges Extreme-Scale AI for Argonne National Laboratory’s Polaris Supercomputer

Retrieved on: 
Wednesday, August 25, 2021
Aurora, Industry, Hewlett Packard Enterprise, Transport, GPU, Growth, Engineering, NVIDIA, GLOBE, A100, Science, AI accelerator, Research, Machine learning, AI, Intelligence, U.S. Department of Defense Strategy for Operating in Cyberspace, Physics, NASDAQ, Government, Algorithm, Cryptocurrency, Video game console

The Polaris supercomputer, hosted at the laboratorys Argonne Leadership Computing Facility (ALCF), will supercharge research and discovery with extreme scale for users algorithms and science.

Key Points: 
  • The Polaris supercomputer, hosted at the laboratorys Argonne Leadership Computing Facility (ALCF), will supercharge research and discovery with extreme scale for users algorithms and science.
  • Accelerated by 2,240 NVIDIA A100 Tensor Core GPUs , the system can achieve almost 1.4 exaflops of theoretical AI performance and approximately 44 petaflops of peak double-precision performance.
  • Polaris, to be built by Hewlett Packard Enterprise, will combine simulation and machine learning by tackling data-intensive and AI high performance computing workloads, powered by 560 total nodes, each with four NVIDIA A100 GPUs.
  • Polaris is a powerful platform that will allow our users to enter the era of exascale AI, said ALCF Director Michael E. Papka.

CVEDIA Joins the NVIDIA Metropolis Program, Focusing on Synthetic Data to Accelerate Edge AI Applications

Retrieved on: 
Thursday, July 29, 2021
Computing, Computer engineering, Artificial intelligence, Technology, Graphics hardware, GPGPU, Application-specific integrated circuits, Virtual reality, Nvidia, Graphics processing unit, Applications of artificial intelligence, AI accelerator

CVEDIA is announcing a suite of custom tools including synthetic training data generation, deep learning analytics, algorithm optimization, and hardware fitting to accelerate development for edge AI applications.

Key Points: 
  • CVEDIA is announcing a suite of custom tools including synthetic training data generation, deep learning analytics, algorithm optimization, and hardware fitting to accelerate development for edge AI applications.
  • Synthetic data generated from simulations provide an inexpensive alternative to the real-world data used to train AI algorithms.
  • Metropolis partners have the opportunity to gain early access to NVIDIA platform updates to enhance and accelerate their AI application development efforts.
  • "We're looking forward to providing AI developers with data and algorithms built ready to deploy on NVIDIA GPU-accelerated systems and applications," said Arjan Wijnveen, CEO and co-founder of CVEDIA.

GBT Considers Using an AI Accelerator for its xCalibre (internal project name) Pattern Recognition Technology

Retrieved on: 
Wednesday, July 28, 2021
Academic disciplines, Articles, Computational neuroscience, Technology, Application-specific integrated circuits, Computer optimization, Artificial intelligence, Cybernetics, AI accelerator, Accelerator, Artificial general intelligence

GBT is now evaluating to accompany xCalibre with a complementary AI accelerator hardware.

Key Points: 
  • GBT is now evaluating to accompany xCalibre with a complementary AI accelerator hardware.
  • An AI accelerating system is a high-performance hardware that is designed to work in conjunction with an AI algorithm, enabling ultra-fast data processing.
  • A high level of processing optimization can be achieved by using a combination of AI programming with specifically designed hardware for it.
  • GBT evaluates adapting its AI algorithms with accelerating hardware targeting to significantly boost its xCalibre imaging performance.

ZTE launches its new-generation under-display camera smartphone Axon 30

Retrieved on: 
Tuesday, July 27, 2021
Smartphones, Mobile phones, Telecommunications, Technology, ZTE, Smartphone

Today, we bringournew-generationunder-displaycamera smartphone ZTE Axon 30.With further reinforcedperformance and comprehensive upgrades, the ZTE Axon 30 provesa leap-forward improvement and bringsour users a revolutionary full-screen visual experiencecompared tothe previous generation."

Key Points: 
  • Today, we bringournew-generationunder-displaycamera smartphone ZTE Axon 30.With further reinforcedperformance and comprehensive upgrades, the ZTE Axon 30 provesa leap-forward improvement and bringsour users a revolutionary full-screen visual experiencecompared tothe previous generation."
  • The ZTE Axon 30 is also the first under-display camera smartphone,with a screen of120Hz refresh rate and 360Hz touch sampling rate.
  • The ZTE Axon 30 continues this trendequipped with the AI quad-camera,includinga 64 megapixel main camera, a 120-degree wide-angle camera, a 3cm macro lens and a depth-of-field lens.
  • In the wave of technological innovation, The ZTE Axon 30 is on a continuous exploration of under-display camera technology.

Maxim Integrated Teams with Xailient to Provide World's Fastest and Lowest-Power IoT Face Detection

Retrieved on: 
Tuesday, July 27, 2021

"Advanced applications include person, vehicle and object counting, presence or obstruction detection, as well as path mapping and footfall heatmaps."

Key Points: 
  • "Advanced applications include person, vehicle and object counting, presence or obstruction detection, as well as path mapping and footfall heatmaps."
  • Maxim Integrated, an engineer's engineering company, exists to solve the designer's toughest problems in order to empower design innovation.
  • We've built the world's smallest and fastest object detector to fit on extremely tiny devices running on exceptionally low power.
  • Xailient, making it possible to see what matters using the world's fastest Computer Vision AI.

Maxim Integrated's Hand-Held Camera Cube Reference Design Enables Artificial Intelligence at the Edge for Vision and Hearing Applications

Retrieved on: 
Tuesday, July 20, 2021
Articles, Science and technology, Technology, Emerging technologies, Application-specific integrated circuits, Ambient intelligence, Digital technology, Internet of things, Technology assessment, Artificial intelligence, AI accelerator, Accelerator

The MAXREFDES178# enables ultra-low-power internet of things (IoT) devices to implement hearing and vision and showcases the MAX78000 low-power microcontroller with neural network accelerator for audio and video inferences.

Key Points: 
  • The MAXREFDES178# enables ultra-low-power internet of things (IoT) devices to implement hearing and vision and showcases the MAX78000 low-power microcontroller with neural network accelerator for audio and video inferences.
  • But the MAXREFDES178# camera cube demonstrates how AI can live on a low-power budget, enabling applications that are time- and safety-critical to operate on even the smallest of batteries.
  • The MAX78000's AI accelerator slashes the power of AI inferences up to 1,000x for vision and hearing applications, as compared to other embedded solutions.
  • Maxim Integrated, an engineer's engineering company, exists to solve the designer's toughest problems in order to empower design innovation.

Data Center Accelerator Market worth $65.3 billion by 2026 - Exclusive Report by MarketsandMarkets™

Retrieved on: 
Thursday, July 15, 2021
Computing, Concurrent computing, Technology, Coprocessors, Data management, Technology forecasting, Nvidia, Artificial intelligence, Big data, AI accelerator

The key factors contributing to the growth of the data center accelerator market include growth of cloud-based services, focus on parallel computing in AI data center and deep learning usage in big data analytics, However, The burgeoning application of AI in various sectors has enhanced consumer perception and expectations from AI technologies.

Key Points: 
  • The key factors contributing to the growth of the data center accelerator market include growth of cloud-based services, focus on parallel computing in AI data center and deep learning usage in big data analytics, However, The burgeoning application of AI in various sectors has enhanced consumer perception and expectations from AI technologies.
  • Various AI technologies built to date have failed to make a larger impact in the AI market.
  • For instance, owing to the high cost of data center accelerators such as NVIDIA Tesla products, a majority of data center manufacturers are reluctant about adopting those accelerators in their products.
  • With the exponential data growth, data center operators have to establish a balance between the need for the performance at scale and the operational efficiencies.

Data Center Accelerator Market worth $65.3 billion by 2026 - Exclusive Report by MarketsandMarkets™

Retrieved on: 
Thursday, July 15, 2021
Computing, Concurrent computing, Technology, Coprocessors, Data management, Technology forecasting, Nvidia, Artificial intelligence, Big data, AI accelerator

The key factors contributing to the growth of the data center accelerator market include growth of cloud-based services, focus on parallel computing in AI data center and deep learning usage in big data analytics, However, The burgeoning application of AI in various sectors has enhanced consumer perception and expectations from AI technologies.

Key Points: 
  • The key factors contributing to the growth of the data center accelerator market include growth of cloud-based services, focus on parallel computing in AI data center and deep learning usage in big data analytics, However, The burgeoning application of AI in various sectors has enhanced consumer perception and expectations from AI technologies.
  • Various AI technologies built to date have failed to make a larger impact in the AI market.
  • For instance, owing to the high cost of data center accelerators such as NVIDIA Tesla products, a majority of data center manufacturers are reluctant about adopting those accelerators in their products.
  • With the exponential data growth, data center operators have to establish a balance between the need for the performance at scale and the operational efficiencies.