Federated learning

Provdotnet Acquires USA Assets from CloudSigma, Launches Alpha 3 Cloud Services, and Joins the HPE Partner Ready Service Provider Program

Retrieved on: 
Wednesday, June 29, 2022
Cloud, Security, Rest, Computing, Solution, CEO, Technology, Silicon, Infrastructure as a service, Ecosystem, Industry, Service, Hewlett Packard Enterprise, Platform as a service, Economics, Compliance, Privacy, Alpha, Public sector, Federated learning, LLC, NYSE, Organization, SGX, Intel, Blockchain, PRSP, HPE, Storage, Confidentiality, Customer, Service provider, Infrastructure, Software, Video game console, Software

PROVIDENCE, R.I., June 29, 2022 /PRNewswire/ -- Alpha 3 Cloud®, a high-performance cloud service provider, today announced that it has acquired the USA Cloud Operations and Infrastructure Assets of CloudSigma a premier cloud services provider headquartered in Zug Switzerland.  The USA Cloud operations that were acquired are located in Northern VA, and Silicon Valley. The company also announced it has joined the HPE Partner Ready Service Provider (PRSP) program as a Confidential Computing IaaS and PaaS cloud provider for thousands of HPE partners and customers. Alpha 3 Cloud® becomes the first PRSP member to offer the Confidential Computing Cloud delivered as a service.

Key Points: 
  • PROVIDENCE, R.I., June 29, 2022 /PRNewswire/ -- Alpha 3 Cloud, a high-performance cloud service provider, today announced that it has acquired the USA Cloud Operations and Infrastructure Assets of CloudSigma a premier cloud services provider headquartered in Zug Switzerland.
  • The company also announced it has joined the HPE Partner Ready Service Provider (PRSP) program as a Confidential Computing IaaS and PaaS cloud provider for thousands of HPE partners and customers.
  • Alpha 3 Cloud becomes the first PRSP member to offer the Confidential Computing Cloud delivered as a service.
  • Alpha 3 Cloud and HPE bring to market a suite of hybrid cloud solutions as a service, enabled by HPE GreenLake.

More Than 2 Billion Shipments of Devices with Machine Learning will Bring On-Device Learning and Inference Directly to Consumers by 2027

Retrieved on: 
Wednesday, May 25, 2022
Smartphone, Research, AI, Federated, Learning, Privacy, Technology, Distributed learning, Intel, Federated learning, Intelligence, Artificial intelligence, GRAI, Medical device, NVIDIA, Qualcomm

NEW YORK, May 25, 2022 /PRNewswire/ -- Artificial Intelligence (AI) is all around us, but the processes of inference and learning that form the backbone of AI typically take place in big servers, far removed from consumers. New models are changing all that, according to ABI Research, a global technology intelligence firm, as the more recent frameworks of Federated Learning, Distributed Learning, and Few-shot Learning can be deployed directly on consumers' devices that have lower compute and smaller power budget, bringing AI to end users.

Key Points: 
  • This might well prove to be an attractive proposition for many, as it does not involve uploading data onto a cloud server, making for more secure and private data.
  • The shift will take place in more powerful consumer devices, such as autonomous vehicles and robots, before making its way into the likes of smartphones, wearables, and smart home devices.
  • These findings are from ABI Research's Federated, Distributed and Few-Shot Learning: From Servers to Devices application analysis report.This report is part of the company's AI and Machine Learning research service, which includes research, data, and ABI Insights.
  • For more information about ABI Research's services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com .

More Than 2 Billion Shipments of Devices with Machine Learning will Bring On-Device Learning and Inference Directly to Consumers by 2027

Retrieved on: 
Wednesday, May 25, 2022
Smartphone, Research, AI, Federated, Learning, Privacy, Technology, Distributed learning, Intel, Federated learning, Intelligence, Artificial intelligence, GRAI, Medical device, NVIDIA, Qualcomm

NEW YORK, May 25, 2022 /PRNewswire/ -- Artificial Intelligence (AI) is all around us, but the processes of inference and learning that form the backbone of AI typically take place in big servers, far removed from consumers. New models are changing all that, according to ABI Research, a global technology intelligence firm, as the more recent frameworks of Federated Learning, Distributed Learning, and Few-shot Learning can be deployed directly on consumers' devices that have lower compute and smaller power budget, bringing AI to end users.

Key Points: 
  • This might well prove to be an attractive proposition for many, as it does not involve uploading data onto a cloud server, making for more secure and private data.
  • The shift will take place in more powerful consumer devices, such as autonomous vehicles and robots, before making its way into the likes of smartphones, wearables, and smart home devices.
  • These findings are from ABI Research's Federated, Distributed and Few-Shot Learning: From Servers to Devices application analysis report.This report is part of the company's AI and Machine Learning research service, which includes research, data, and ABI Insights.
  • For more information about ABI Research's services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com .

NICE Actimize Releases 2022 Fraud Insights Report Identifying Threat Patterns Emerging Across Financial Institutions

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Monday, May 16, 2022
Hardware, Security, Data Management, Consumer Electronics, Technology, Finance, Banking, Professional Services, Other Technology, Telecommunications, Software, Networks, VoIP, Internet, Mobile, Wireless, Risk, CX, Company, Fraud, Private Securities Litigation Reform Act, U.S. Securities and Exchange Commission, AI, Atos, Federated, ACH, Acceleration, NASDAQ, Solution, NICE, COVID-19, Marketing, NICE Ltd., Forward-looking statement, Communication, Technology, Organization, Federated learning, Intelligence, SEC, Prevalence, Growth, Annual report, CEO, Pharmaceutical industry, Cryptocurrency, Online shopping, P2P

NICE Actimize, a NICE (NASDAQ: NICE) business, has released "The 2022 NICE Actimize Fraud Insights Report" that identifies and analyzes the leading fraud threats and patterns that impacted leading global financial institutions in 2021.

Key Points: 
  • NICE Actimize, a NICE (NASDAQ: NICE) business, has released "The 2022 NICE Actimize Fraud Insights Report" that identifies and analyzes the leading fraud threats and patterns that impacted leading global financial institutions in 2021.
  • NICE Actimize currently employs these techniques across leading financial institutions to monitor and stay aware of advancing fraud threats.
  • The Fraud Insights Report aggregated and synthesized fraudulent activity patterns seen across a range of global financial institutions.
  • The NICE Actimize 2022 Fraud Insights report showed that increased utilization of mobile devices for everyday purposes, such as banking, shopping, and communication, heavily impacted the fraud landscape in 2021.

Bairong Inc. Wins Three Patents for Federated Learning and Voice Interruption

Retrieved on: 
Friday, December 17, 2021
Solution, Federated learning, FSP, Company, Data analysis, Feedback, Federated, Speech recognition, Recursive neural network, Adoption, AI, Risk, CEO, Patent, Efficiency, Multimedia, Risk management, Compliance, Technology, Natural language, Privacy, View, Mobile phone, Pharmaceutical industry, Cryptocurrency, Customer service

BEIJING, Dec. 17, 2021 /PRNewswire/ -- Bairong Inc ("Bairong" or "the Company", 6608.HK), a leading independent AI-powered technology platform in China, was recently granted three national invention patents in China, including two for Federated Learning technologies and one for "voice interruption method and device."

Key Points: 
  • BEIJING, Dec. 17, 2021 /PRNewswire/ -- Bairong Inc ("Bairong" or "the Company", 6608.HK), a leading independent AI-powered technology platform in China, was recently granted three national invention patents in China, including two for Federated Learning technologies and one for "voice interruption method and device."
  • The two Federated Learning patents are "a prediction method and system based on an isolated forest training of Vertical Federation" and "a mobile device credit anti-fraud prediction method and system based on Federated Learning."
  • For the second Federated Learning patent, Bairong has developed an anti-fraud technical solution between users' mobile devices and financial institutions with privacy protection on both sides.
  • Under various financial scenarios, the AI voice robot can provide superior customer service experience and support the digital transformation of financial services.

Owkin Enters Into Agreement to Build Innovative Methods With the Potential to Enhance AI-Enabled External Control Arms

Retrieved on: 
Wednesday, September 15, 2021
Janssen Pharmaceuticals, Artificial intelligence, Biology, Biomarker, Heart, AI, Drug development, Janssen, Federated, Nobel Prize, Pulmonary hypertension, Degenerative disease, Patient, Pressure, Algorithm, Clinical trial, Development, Machine learning, Academic health science centre, MD, Drug, Blood, GLOBE, PAH, Intelligence, Johnson & Johnson, Bias, Diagnosis, Research, Life expectancy, Federated learning, Pharmaceutical industry, Medical device

The aim of this initial project with Janssen's R&D Data Science team is to investigate innovative machine learning-based methods for the estimation of treatment effect in clinical trials involving real-world data sources.

Key Points: 
  • The aim of this initial project with Janssen's R&D Data Science team is to investigate innovative machine learning-based methods for the estimation of treatment effect in clinical trials involving real-world data sources.
  • Owkin and Janssen's R&D Data Science team will focus on innovative double/debiased machine learning-based approaches that enable adjustment for high-dimensional confounders to overcome important challenges of standard methods, such as bias and confounding.
  • Detecting efficacy with small trials and external control cohorts, which is often the case for rare diseases, is a challenge.
  • Owkin leverages life science and machine learning expertise to make drug development and clinical trial design more targeted and cost-effective.

Global Federated Learning Market Report 2021: Strategic Partnerships for Accelerating Technology Development to Meet Substantial Market Demand

Retrieved on: 
Monday, August 23, 2021
Machine learning, Strategy, ML, Privacy, Federated learning, Federated, Medical device

DUBLIN, Aug. 23, 2021 /PRNewswire/ -- The "Federated Learning: New Approach to Building AI Models" report has been added to ResearchAndMarkets.com's offering.

Key Points: 
  • DUBLIN, Aug. 23, 2021 /PRNewswire/ -- The "Federated Learning: New Approach to Building AI Models" report has been added to ResearchAndMarkets.com's offering.
  • Federated learning is a distributed ML architecture that enables a global model to be trained using decentralized data.
  • To help companies gain valuable insights about this emerging technique, this report offers an overview of the federated learning industry, market dynamics, key market players, research directions, key application areas, and recent developments.
  • Attracted to this powerful privacy-protecting technique, a growing number of market participants, academics, and end-use industries are adopting federated learning at an unprecedented rate.

Bairong Inc. Launches Indra, a Secure AI-Powered Multi-Party Computing Platform

Retrieved on: 
Monday, July 19, 2021
Computing, Software, Free software, Federated learning, Machine learning, Big data, Wire

BEIJING, July 19, 2021 /PRNewswire/ -- Bairong Inc. ("Bairong", 6608.HK), a leading independent AI-powered technology platform in China, has officially launched Indra, a groundbreaking secure multi-party computing platform that meets key privacy protection needs in the process of data development.

Key Points: 
  • BEIJING, July 19, 2021 /PRNewswire/ -- Bairong Inc. ("Bairong", 6608.HK), a leading independent AI-powered technology platform in China, has officially launched Indra, a groundbreaking secure multi-party computing platform that meets key privacy protection needs in the process of data development.
  • We built the platform upon the foundations of secure multi-party computing and Federated Learning, while tailoring its features specifically to the needs of big data applications in the finance sector.
  • Founded in March 2014, Bairong is a leading independent AI-powered technology platform in China serving more than 4,800 financial services provider clients.
  • Bairong also provides big data marketing and distribution services that enable FSP clients to reach and serve their target customers more effectively.

Global Federated Learning Solutions Market (2020 to 2028) - Growing Need to Increase Learning Between Devices and Organization is Driving the Industry

Retrieved on: 
Thursday, April 22, 2021
Federated learning, Machine learning, Federated

b'5 Federated Learning Solutions Market, by Application\n6 Federated Learning Solutions Market, by Vertical\n6.3.1 Large Pool of Applications, Multiple Research Initiatives, and Collaborations Among Technology Vendors and Healthcare and Life Sciences Organizations to Drive Market Growth\n6.3.2 Healthcare and Life Sciences: Forecast 2023-2028 (Optimistic/As-Is/Pessimistic)\n7 Federated Learning Solutions Market, by Region\n'

Key Points: 
  • b'5 Federated Learning Solutions Market, by Application\n6 Federated Learning Solutions Market, by Vertical\n6.3.1 Large Pool of Applications, Multiple Research Initiatives, and Collaborations Among Technology Vendors and Healthcare and Life Sciences Organizations to Drive Market Growth\n6.3.2 Healthcare and Life Sciences: Forecast 2023-2028 (Optimistic/As-Is/Pessimistic)\n7 Federated Learning Solutions Market, by Region\n'

The Worldwide Federated Learning Solutions Industry is Projected to Grow to $201 Million by 2028 - ResearchAndMarkets.com

Retrieved on: 
Monday, April 19, 2021
Technology, Software, Computing, Technology, Science and technology, Industrial automation, Industrial Internet of Things, Internet of things, Federated learning, Compound annual growth rate, UST, Big data

The healthcare and life sciences vertical is expected to account for the largest market size during the forecast period.

Key Points: 
  • The healthcare and life sciences vertical is expected to account for the largest market size during the forecast period.
  • Moreover, the manufacturing vertical is expected to grow at the highest CAGR during the forecast period.
  • With the increasing focus on Industrial Internet of Things (IIoT) and the rise in competition, manufacturing companies are prioritizing the analysis of data collected from numerous sources, including web, mobile, stores, and social media.\nThe federated learning solutions market in APAC is projected to grow at the highest CAGR from 2023 to 2028.
  • The increase in the adoption of emerging technologies, such as big data analytics, AI, and IoT, and ongoing developments to introduce data regulations, as well as focus on hyper-personalization and contextual recommendation in support of budding e-Commerce markets in key countries such as China, India, and Japan are expected to drive the growth of federated learning solutions in the region.\n'