Archive for the ‘Artificial Intelligence’ Category

Top Remarkable Artificial Intelligence Developments that Happened in 2021 – Analytics Insight

Highlights in the use of artificial intelligence in 2021

The year 2021 was profoundly challenging for citizens, companies, and governments around the world. As covid-19 spread, requiring far-reaching health and safety restrictions, artificial intelligence (AI) applications played a crucial role in saving lives and fostering economic resilience. Research and development (R&D) to enhance core AI capabilities, from autonomous driving and natural language processing to quantum computing, continued unabated.

It typically takes years, if not decades, to develop a new vaccine. But by March 2020, vaccine candidates to fight covid-19 were already undergoing human tests, just three months after the first reported cases. The record speed of vaccine development was partly thanks to AI models that helped researchers analyze vast amounts of data about coronavirus.

There are tens of thousands of subcomponents to the outer proteins of a virus. Machine learning models can sort through this blizzard of data and predict which subcomponents are the most immunogenici.e., capable of producing an immune responseand thereby guide researchers in designing targeted vaccines. The use of AI in vaccine development may revolutionize the way all vaccines are created in the future.

Autonomous driving technology continued to mature in 2021, with the industrys leading companies testing driverless cars and opening up robotaxi services to the public in various cities. Fully automated driving, which enables rides without a human safety driver on board, will be necessary for the scalability and commercialization of autonomous driving.

In 2021, natural language systems became significantly more advanced at processing aspects of human language like sentiment and intent, generating language that aligns with human speaking and writing patterns, and even visual understanding, meaning the capability to express understanding about an image through language. These natural language models are powering more accurate search results and more sophisticated chatbots and virtual assistants, leading to better user experiences and creating value for businesses. Visual understanding lays the foundation for computer systems to physically interact in everyday scenes, as it involves both understanding visual content and expressing it through language. It will be crucial for improving the quality of human-machine interaction.

Quantum computing made significant inroads in 2021, including the Jiuzhang computers achievement of quantum supremacy. This carries significance for AI, since quantum computing has the potential to supercharge AI applications compared to binary-based classical computers. For example, quantum computing could be used to run a generative machine learning model through a larger dataset than a classical computer can process, thus making the model more accurate and useful in real-world settings. Advanced technologies such as deep learning algorithms are also playing an increasingly critical role in the development of quantum computing research.

AI hardware continued to develop in 2020, with the launch of several AI chips customized for specialized tasks. While an ordinary processor is capable of supporting AI tasks, AI-specific processors are modified with particular systems that can optimize performance for tasks like deep learning. As AI applications become more widespread, any increase in performance or reduction in cost can unlock more value for companies that operate a wide network of data centers for commercial cloud services, and can facilitate the companys internal operations.

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Top Remarkable Artificial Intelligence Developments that Happened in 2021 - Analytics Insight

Edge Artificial Intelligence Market Research Report by Processor, by Component, by Source, by End-Use, by Application, by Region – Global Forecast to…

Edge Artificial Intelligence Market Research Report by Processor (ASIC, CPU, and GPU), by Component (Services and Solution), by Source, by End-Use, by Application, by Region (Americas, Asia-Pacific, and Europe, Middle East & Africa) - Global Forecast to 2026 - Cumulative Impact of COVID-19

New York, Dec. 06, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Edge Artificial Intelligence Market Research Report by Processor, by Component, by Source, by End-Use, by Application, by Region - Global Forecast to 2026 - Cumulative Impact of COVID-19" - https://www.reportlinker.com/p06168877/?utm_source=GNW

The Global Edge Artificial Intelligence Market size was estimated at USD 572.00 million in 2020 and expected to reach USD 701.73 million in 2021, at a CAGR 23.35% to reach USD 2,014.99 million by 2026.

Market Statistics:The report provides market sizing and forecast across five major currencies - USD, EUR GBP, JPY, and AUD. It helps organization leaders make better decisions when currency exchange data is readily available. In this report, the years 2018 and 2019 are considered historical years, 2020 as the base year, 2021 as the estimated year, and years from 2022 to 2026 are considered the forecast period.

Market Segmentation & Coverage:This research report categorizes the Edge Artificial Intelligence to forecast the revenues and analyze the trends in each of the following sub-markets:

Based on Processor, the market was studied across ASIC, CPU, and GPU.

Based on Component, the market was studied across Services and Solution. The Services is further studied across Support & Maintenance, System Integration & Testing, and Training & Consulting. The Solution is further studied across Platform and Software Tools.

Based on Source, the market was studied across Biometric Data, Mobile Data, Sensor Data, Speech Recognition, and Video & Image Recognition.

Based on End-Use, the market was studied across Automotive, Energy and Utilities, Government & Public Sector, Healthcare, Manufacturing, and Telecom.

Based on Application, the market was studied across Access Management, Autonomous Vehicles, Energy Management, Precision Agriculture, Remote Monitoring & Predictive Maintenance, Smart Wearables, Telemetry, and Video Surveillance.

Based on Region, the market was studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, and Thailand. The Europe, Middle East & Africa is further studied across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Cumulative Impact of COVID-19:COVID-19 is an incomparable global public health emergency that has affected almost every industry, and the long-term effects are projected to impact the industry growth during the forecast period. Our ongoing research amplifies our research framework to ensure the inclusion of underlying COVID-19 issues and potential paths forward. The report delivers insights on COVID-19 considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The updated study provides insights, analysis, estimations, and forecasts, considering the COVID-19 impact on the market.

Competitive Strategic Window:The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies to help the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. It describes the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period.

FPNV Positioning Matrix:The FPNV Positioning Matrix evaluates and categorizes the vendors in the Edge Artificial Intelligence Market based on Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Market Share Analysis:The Market Share Analysis offers the analysis of vendors considering their contribution to the overall market. It provides the idea of its revenue generation into the overall market compared to other vendors in the space. It provides insights into how vendors are performing in terms of revenue generation and customer base compared to others. Knowing market share offers an idea of the size and competitiveness of the vendors for the base year. It reveals the market characteristics in terms of accumulation, fragmentation, dominance, and amalgamation traits.

Competitive Scenario:The Competitive Scenario provides an outlook analysis of the various business growth strategies adopted by the vendors. The news covered in this section deliver valuable thoughts at the different stage while keeping up-to-date with the business and engage stakeholders in the economic debate. The competitive scenario represents press releases or news of the companies categorized into Merger & Acquisition, Agreement, Collaboration, & Partnership, New Product Launch & Enhancement, Investment & Funding, and Award, Recognition, & Expansion. All the news collected help vendor to understand the gaps in the marketplace and competitors strength and weakness thereby, providing insights to enhance product and service.

Company Usability Profiles:The report profoundly explores the recent significant developments by the leading vendors and innovation profiles in the Global Edge Artificial Intelligence Market, including Adlink Technology, Inc., Amazon Web Services Inc., Anagog Ltd., Cato Networks, Ltd., ClearBlade, Inc., Cloudera, Inc., Edge Intelligence Software, Inc., EdgeConneX, EdgeIQ, Eta Compute Inc., FogHorn Systems, Google LLC by Alphabet Inc., Gorilla Technology Inc., Hewlett Packard Enterprise Company, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Nutanix, Inc., Octonion SA, Saguna, Synaptics Incorporated, Tata Elxsi Limited, TIBCO Software Inc., Vapor IO, and Vector ITC.

The report provides insights on the following pointers:1. Market Penetration: Provides comprehensive information on the market offered by the key players2. Market Development: Provides in-depth information about lucrative emerging markets and analyze penetration across mature segments of the markets3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The report answers questions such as:1. What is the market size and forecast of the Global Edge Artificial Intelligence Market?2. What are the inhibiting factors and impact of COVID-19 shaping the Global Edge Artificial Intelligence Market during the forecast period?3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Edge Artificial Intelligence Market?4. What is the competitive strategic window for opportunities in the Global Edge Artificial Intelligence Market?5. What are the technology trends and regulatory frameworks in the Global Edge Artificial Intelligence Market?6. What is the market share of the leading vendors in the Global Edge Artificial Intelligence Market?7. What modes and strategic moves are considered suitable for entering the Global Edge Artificial Intelligence Market?Read the full report: https://www.reportlinker.com/p06168877/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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Healthcare Artificial Intelligence (AI) Market Size to Reach Revenues of USD 44.5 Billion by 2026 – Arizton – PRNewswire

CHICAGO, Dec. 1, 2021 /PRNewswire/ -- In-depth analysis and data-driven insights on the impact of COVID-19 included in this global healthcare artificial intelligence (AI) market report.

The healthcare artificial intelligence (AI) market is expected to grow at a CAGR of over 46.21% during the period 20202026.

Key Highlights Offered in the Report:

1. Software & services in healthcare AI is expected to witness high growth rate due to the evolution in digital health technologies such as EMR/EHR, telehealth, e-prescribing in healthcare services. The software and services segment accounted for 73.92% of healthcare AI market share in 2020.

2. Artificial intelligence in drug discovery and clinical decision-making leads to new path of speedy workflow in pharmaceutical drug & dosage management. This emerging trend of advancements in drug discovery is incorporated widely as it is cost and time efficient.

3. The growth and acceptance of AI in hospital workflow management witnessed streamlined and efficient patient care offered by the healthcare facilities. Hospital workflow management accounted for 38.41% of healthcare AI market in 2020 and expected to retain its market dominance in coming years.

4. North America captured a dominant position in the market and generated maximum revenue in compared to rest. Additionally, Europe and APAC are likely to see the top line growth in adoption of AI and healthcare information technology solutions in healthcare facilities.

5. Vendors from the market are rising the investment in digital solutions for healthcare. In recent years, the number of collaborations between IT companies and healthcare providers have been made to adopt new technologies and incorporating to better outcomes.

6. Machine learning is widely applied in and adopted in the healthcare services because of its algorithmic more accurate results. In application segment machine learning accounted a major share of 41.16% of healthcare AI market in 2020.

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Healthcare Artificial Intelligence (AI) Market Segmentation

Healthcare Artificial Intelligence (AI) Market by Category

Healthcare Artificial Intelligence (AI) Market by Application

Healthcare Artificial Intelligence (AI) Market by Technology

Healthcare Artificial Intelligence (AI) Market by End-users

Healthcare Artificial Intelligence (AI) Market Dynamics

Global key vendors from the pharmaceutical and biotech industry, such as Amgen, BASF, LEO, Eli Lilly, AstraZeneca, Bayer, Novartis, J&J, and Merck, are now a part of machine learning for pharmaceutical discovery. These vendors are making remarkable growth as AI-driven solutions are easy for the user interface and are creating analytical bookmarks on key drivers in sales to determine investments. For example, the collaboration of GSK with Exscientia identified a small compound for targeted therapeutics and its characteristics toward the specific target using AI platforms. Gilead Sciences and Insitro partnered to research on non-alcoholic steatohepatitis patients. Using machine learning and human genetics, Insitro identified discovery & development in therapeutics.

Key Drivers and Trends fueling Market Growth:

Healthcare Artificial Intelligence (AI) Market Geography

North America captured a dominant position in healthcare artificial intelligence (AI). The presence of a large patient population, coupled with better adoption of digital healthcare with the latest advancements in artificial intelligence (AI), is the primary factor for its high market share. The strong presence of key healthcare IT players is also another reason for the high uptake of healthcare artificial intelligence (AI) in North America. The rise in the adoption of AI technologies in drug discovery & development and patient-centric treatment procedures are expected to drive the market growth during the forecast period. New artificial intelligence (AI) technologies can help companies create more value for their patients and communities by turning time-consuming, labor-intensive, and often ineffective functions into actionable insights for better results. Forward-thinking hospital and healthcare system executives view AI as the most effective path to a more productive, efficient, and better performing healthcare organization.

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Healthcare Artificial Intelligence (AI) Market by Geography

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Healthcare Artificial Intelligence (AI) Market Size to Reach Revenues of USD 44.5 Billion by 2026 - Arizton - PRNewswire

Artificial Intelligence in financial sector will boost security of companies – GhanaWeb

AI will boost the security of companies and help keep out cyber attacks according to the expert

Dr Pius Gadossey, Lecturer, Lancaster University says the use of Artificial Intelligence (AI) in the financial space will boost the security companies by alerting institutions of any discrepancies or unusual activity for prompt actions.

Dr Gadossey said the AI in the financial sector ensured that clients and financial institutions' monies and their personal information were safe and secured as well as prevented cyber-attacks.

"AI is not biased and can decide on loan eligibility quickly and more accurately", he said.

The Lecturer said this on Saturday at a lecture and graduation ceremony of which eight members were Chartered as Compliance and Cyber Analyst.

The programme was organised by the Institute of Compliance and Cyber Studies (ICCS).

AI is the ability of a computer programme or a machine to think or learn. It provides human-like interventions with software and offers decision support for specific tasks.

Speaking on the "Relevance of AI in the Financial Industry", he said banks were using machine learning algorithms not only to determine a person's loan eligibility but also to provide personalized options.

"Machine learning can help experts use data to project trends, identify risks, conserve manpower and ensure better information for future planning," he said.

Dr Gadossey said AI fraud detection systems analyses a person's buying behaviour and trigger an alert if something seems out of the ordinary or contradicted traditional spending patterns.

"The use of applications like chatbot and virtual have reduced the need to spend time on the phone waiting to speak with a customer service representative", he said.

The Bank of America chatbot "Erica" has served more than 10 million users. As of mid-2019, Erica was able to understand almost 500,000 question variations.

Mr Eebenezer Domesew, Board Member of Institute of Compliance and Cyber Studies touching on the "Relevance of Risk-Based Auditing in the Financial Industry" said competitiveness had been toughened in the face of the increased presence of multinational companies which have embraced the advantages of technology.

He stated that adopting risk management practices gives higher financial performance and a highly competitive edge in the world market.

The graduands were presented with a certificate for successfully graduating from the course.

Mr Jude Apoore Azure won the best Governance and Ethics award while Mr Richard Nyarko emerged as the Audit and Tax Compliance award winner.

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Artificial Intelligence in financial sector will boost security of companies - GhanaWeb

Sydney and Newcastle use artificial intelligence and edge computing to improve road mobility – iTWire

Sydney and Newcastle are deploying artificial intelligence and edge computing technology in a trial to improve customer journey, safety, and increase transport service reliability.

Minister for Transport and Roads Rob Stokes says the transport for NSW trials are connecting several buses, ferries, and light rail vehicles, and then using real-time data to help identify improvements for customers.

Weve partnered with Cisco to investigate how a real-time view of vehicle supply and customer demand and performance can guide future network decisions and monitor road conditions to identify where repair work is needed, Stokes says.

Pitt Street near Central Station is using artificial intelligence, Wi-Fi, and edge computing to capture real time data and identify high-risk events.

Well be able to keep a close eye on vehicle movements as more commuters and pedestrians head back to Sydneys busiest transport hubs as COVID-19 restrictions continue to ease, Stokes claims.

Transport for NSW deputy secretary of customer, strategy, and technology Joost de Kock says road user movements are tracked at several intersections in Newcastle using intelligent sensors to help improve overall road safety.

In another trial, we are also using advanced sensors on buses, ferries, and light rail to provide instant feedback on the comfort of customer journeys and improve real-time customer information, de Kock says.

Buses equipped with this technology can also monitor asset and road conditions and provide us with real-time information on vehicles.

Both cities are also trialling Ciscos technologies including:

Internet of Things (IoT) - enabling physical objects to be digitised and connected to the network via sensors

Edge Computing - taking real-time data from connected objects and allowing for faster decision making

Artificial Intelligence assists with data and automating the process, which will help to transform the data into useful insights.

Cisco Australia and New Zealand general manager for transport and infrastructure Simon Young says Transport for NSW is the only agency in the world trialling their AI system.

These trials represent the strength of the partnership between Cisco and Transport for NSW to co-innovate and use technology to solve some of the most pressing and challenging problems facing transport agencies, Young says.

The cost of congestion in Sydney, the Hunter, and Illawarra is forecast to double to $15.7 billion by 2031, according to a 2019 report by Infrastructure Australia.

This puts Transport for NSW in a position to make this new technology invaluable by helping to support a more efficient road and transport network.

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