The global voice assistant market is driven by increasing popularity of connected devices and high demand for self-service applications.These factors have helped shape the voice assistant market and are expected to boost the growth.Companies in the voice assistant market could also face challenges such as limited integration of voice assistants and lack of content in regional languages.Request a Free Sample @  Competitive Outlook: The voice assistant market is supported by personalized services triggered with voice commands and easy integration of voice assistants in connected devices.The voice assistant market research report also provides company profiles of major companies.On the basis of technology, the market for voice assistant is segmented based on speech recognition, natural language processing, text to speech recognition, voice recognition.
The global Artificial Intelligence (AI) in Cyber Security Market presents comprehensive information that makes it a valuable source of insightful data for business strategists during 2021-2026.Given the technological innovations in the market, the industry is likely to emerge as a complementary platform for investors in the emerging market.A thorough competitive analysis covering insightful data on industry leaders is intended to help potential market entrants and competing existing players to reach their decisions in the right direction.Growth between segments over the period 2021-2026 provides accurate calculations and forecasts of revenue by type and application in terms of volume and value.This analysis can help you expand your business by targeting eligible niches.Product Segment Analysis:Machine Learning, Natural Language Processing, OthersApplication Segment Analysis:BFSI, Government, IT & Telecom, Healthcare, Aerospace and Defense, OthersThe market research report also discusses the numerous development strategies and plans that the Artificial Intelligence (AI) in Cyber Security industry follows to expand to a global level.Details related to the dynamic change in the segment are provided in the research report.: study conducts a SWOT analysis to evaluate the strengths and weaknesses of key players in the Artificial Intelligence (AI) in Cyber Security market.
While visual ‘no code‘ tools are helping businesses get more out of computing without the need for armies of in-house techies to configure software on behalf of other staff, access to the most powerful tech tools — at the ‘deep tech’ AI coal face — still requires some expert help (and/or costly in-house expertise). This […]
New York, NY 09 Apr 2021: The global IBM Watson services market size is expected to reach USD 16.5 billion by 2027 according to a new study by Polaris Market Research.The report “IBM Watson Services Market Share, Size, Trends, Industry Analysis Report, By Service Type (Watson Language, Watson Data Insights, Watson Speech, and Watson Vision Services); By End Use (Healthcare, BFSI, Retail, Discrete & Process Manufacturing, Telecom, Media & Entertainment, Transportation & Logistics, Government, Travel & Tourism, Education, and Others); By Regions; Segment Forecast, 2020 –2027” gives a detailed insight into current market dynamics and provides analysis on future market growth.The IBM Watson is a disruptive technology which ensures higher efficiency and agility for the enterprises.IBM Watson services power advertisements for aiding them in generating authentic content, which includes food ingredient-based customized recipe by assessing taste trends of consumers worldwide.Request For Sample Copy @ technology across the world is changing at a rapid pace, with the advent of machine learning and artificial intelligence to take quicker informed decisions by key stakeholders in the industry.With the use of natural language processing (NLP), data mining, and advanced text analytics, cognitive systems have been assisting doctors in diagnosing diseases and making faster decisions.They are also optimizing patient selection for clinical trials with intelligence matching.
So, here are the 10 important 2021 SEO trends: Optimization Focused on the UserGoogle regularly has updates.SEOs need to have a strategy in place for reaching customers through new access points.The update also showcased one of the most important changes in Google’s strategy for content search.It is now showing importance to intent over keywords.Keywords show us what a customer is searching, whereas intent is all about knowing why a customer is searching something particular.Natural language processing & deep learning are making strong headway into technology, so intent will get precedence on keywords.So, you need to completely forget about keyword stuffing, rewording, and article spinning.Long-tail keywords that are grammatically correct will also get renewed importance.
Clarifai, a leading AI lifecycle platform provider for managing unstructured image, video, text and audio data expands its product offerings in Q1 2021.Over the last three months, Clarifai has significantly advanced its portfolio of AI products and services.The portfolio works seamlessly together on its end-to-end platform to help its customers use AI to increase revenue, decrease expenses and minimize risk.“We have seen accelerated growth in Q1 as more and more enterprise and public sector organizations adopt AI,”  said Dr. Matt Zeiler, founder and CEO of Clarifai.“I’m incredibly proud of the suite of products, models and workflows that we built to support our Computer Vision, Natural Language Processing and automated data labeling capabilities.”Clarifai’s new product lineup includes the following:Scribe Label: A data labeling platform or fully managed data labeling service that uses AI automation to speed productivity of high-quality training datasets by 100x with 10x less data needed.It searches for visually similar images and custom concepts in images, video and textual data and includes an intuitive user interface for bulk operations, sorting, and filtering data.Spacetime allows for deeper search into multilingual text inputs, including custom concept search and text similarity search.Enlight Train: A rich suite of pre-trained models used to train and produce highly accurate custom models with support for a variety of different training types such as transfer learning and deep training.Neural networks can be built in minutes as complexities are abstracted away, exposing only the “key” essentials.Armada Predict: A tool that  analyzes unstructured image, video and text data using multiple prediction types to gain insights with fast time-to-accuracy.
Artificial Intelligence Expert Discusses How to Address Baumol’s Cost Disease in HealthcareAKASA, the only Unified Automation™ company for revenue cycle management in healthcare, announced that its AI Technology Lead, Byung-Hak Kim, Ph.D., is leading a discussion today at 3:10 pm ET on how to address Baumol’s cost disease in healthcare with machine learning.Baumol’s cost disease is the rise of salaries in jobs that have experienced no or low increase of labor productivity, in response to rising wages in other jobs that have experienced higher labor productivity growth.The Baumol effect has been a significant driver of costs in healthcare for decades with no clear path to reversing these effects in our healthcare system.In his talk, Kim presents the recent progress of harnessing state-of-the-art deep learning techniques in automating how medical bills are processed and paid in healthcare revenue cycle management.Making the billing process more efficient allows health systems to redirect investment into patient care while minimizing wasteful spending.These advancements can help health systems and hospitals increase productivity, maximize the value delivered by their administrative staff, and minimize the impact of Baumol’s cost disease on their organization so they can invest more in patient care.Byung-Hak Kim, PhD, has focused on machine learning research and development in real-world applications in the challenging areas of human health, education, and speech.Kim holds a bachelor’s and master’s degree in Electrical Engineering from Korea University and a doctorate degree in Electrical & Computer Engineering at Texas A University. 
Market OverviewGlobal Computational Creativity Market is expected to reach USD 1.1497 Billion by 2026, registering a CAGR of 25.42% during the forecast period.In this report, Market Research Future (MRFR) includes the segmentation and dynamics of the global computational creativity market to offer a better glimpse of the coming years.Global Computational Creativity Market has been segmented based on Technology, Components, and Application.Based on the technology, the global computational creativity market has been segmented into natural language processing (NLP), machine learning and deep learning (ML and DL), and computer vision.Furthermore, the segment is anticipated to emerge as the fastest-growing segment over the forecast period owing to the increasing adoption of machine learning & deep learning algorithm for implementing various applications of computational creativity.The growing demand for the improvement of the creative process and efficiency of creative professionals contributes to the rapid growth of the segment in the computational creativity market.The natural language processing segment is a subfield of artificial intelligence that deals with the interaction between computers and humans using natural language.The computer vision segment is a branch of artificial intelligence that instruct computers to interpret and understand the visual world.Based on components, the global computational creativity market has been segmented into solutions and services.
The global AI in manufacturing market size is expected to rise owing to increasing demand for collaborative robots and growing semiconductor industry.According to Fortune Business Insights, its latest report, titled “Artificial Intelligence (AI) in Manufacturing Market Size, Share & COVID-19 Impact Analysis, By Offering (Hardware, Software, and Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, and Context Awareness), By Application (Process Control, Production Planning, Predictive Maintenance & Machinery Inspection, Logistics and Inventory Management, Quality Management, and Others), By Industry (Automotive, Medical Devices, Semiconductor , Energy & Power, Heavy Metal & Machine Manufacturing, and Others), and Regional Forecast, 2020-2027.”, observes that the market will hit USD 9.89 Billion by 2027, while exhibiting a promising 24.2% CAGR between 2020 and 2027.This market is expected to witness substantial growth owing to the COVID-19 impact and hence the 2020-2027 CAGR is high/very high, as a large section of industry would look to adopt AI in order to automate the operation with less human intervention.Artificial intelligence (AI) is believed to be a game-changing modern technology for the manufacturing industry.Adoption of AI in manufacturing provides multi-faceted benefits such as accurate and rapid data-driven decisions, minimizing of operational costs, optimizing several processes, and improving the overall experience of customer-satisfaction.In addition to this, AI can be easily embedded to the existing products and services offered by the companies to render them reliable, effective, and safe.For instance, in the automotive industry, AI-based technology such as computer vision is used to accurately detect obstructions to prevent road fatalities, while promoting safe driving.List of the Companies Proliferating in the Market:• Microsoft Corporation (United States)• Google LLC (United States)• IBM Corporation (United States)• Inc. (United States)• NVIDIA Corporation (United States)• Siemens AG (Germany)• GENERAL ELECTRIC (United States)• SAP SE (Germany)• Rockwell Automation, Inc. (United States)• Mitsubishi Electric Corporation (Japan)Regional Analysis:Increasing Investment for AI-based Platform in Asia-Pacific to Drive the MarketAmong the regions, the market in Asia-Pacific that hit USD O.68 Billion in 2019 is expected to hold the highest global AI in manufacturing market revenue during the projected horizon.
Market Analysis: Global Autonomous Agents Market Global autonomous agents market is expected to rise to an estimated value of 7254.13 million by 2026 witnessing a healthy CAGR in the forecast period of 2019-2026.The rise in the market value can be attributed to the rising applicability of AI, cloud based technology and technological advancements.Global Autonomous Agents Market By Deployment Type (Cloud, On-Premises), Organization Size (SMEs, Large Enterprises), Vertical (BFSI, IT & Telecom, Manufacturing, Healthcare, Transportation & Mobility, Others), Geography (North America, South America, Europe, Asia-Pacific, Middle East and Africa) – Industry Trends and Forecast to 2026Get More Insights about Autonomous Agents Market, Request Sample @ Definition: Global Autonomous Agents Market Autonomous agents are intelligent agents that are programming elements performing certain set of tasks on the benefit of the owner with freedom, without any interference from the owner.They are smart software entities that automatically act depending on the scenario of the environment, in the reach of its own goal or agenda.The rising scope of AI applications boosts the development and growth of autonomous agents·       Fast pace improvements in cloud technology and technological advancements fosters the growth of this market·       Rising access and use of parallel computational resources·       Rising costs of security and maintenance of on-premises solution stimulates the growth of autonomous agents, as they reduce the operational and maintenance costs·       Growing size and complexity of data sets boosts the need for autonomous agents·       Rising improvements and use of Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning (ML)·       Use of autonomous agents improves performance, with enhanced scalability and efficiency by access to real time informationMarket Restraints:·       Absence of skilled workers and proper standards of performance·       Huge initial cost of setup and heavy investments retrains the growth of this marketTo Know more visit report Analysis: Global Autonomous Agents Market Global autonomous agents market is highly fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market.The report includes market shares of autonomous agents market for global, Europe, North America, Asia Pacific, South America and Middle East & Africa.Key Market Competitors: Global Autonomous Agents Market Few of the major competitors currently working in the autonomous agents market are Oracle, IBM Corporation, SAP SE, Amazon Web Services, Inc., SAS Institute Inc., Infosys Limited, Nuance Communications, Inc., Fair Isaac Corporation, Fetch.AI, Affectiva., Intel Corporation,, inc., Aptiv., Google, Talla, Inc., Microsoft and AOS Group amongst others.Get Access Report @ Methodology: Global Autonomous Agents Market Data collection and base year analysis is done using data collection modules with large sample sizes.Apart from this, other data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Top to Bottom Analysis and Vendor Share Analysis.
No doubt Artificial Intelligence is impacting medical and healthcare as the use of chatbots in this industry has recently become popular.And why are chatbots being adopted by the healthcare industry as telehealth software solutions?Chatbots are interactive software designed to imitate human-like chats in real-time.These are developed using Machine Learning algorithms, including natural language processing.A chatbot assists the user via text messages within applications or websites.Chatbots have already been applied in retail, social media, customer service, and banking.Currently, chatbots are ready to make a mark in the healthcare industry.Application of Chatbots in HealthcareHere we discuss the possible advantages that these chatbots promise to medical service providers, doctors, and patients:  Health TrackingDoctors are always willing to help their patients and they understand that how important it is to be available if the patient is in urgent need of medical attention.
Market HighlightsThe increasing adoption of deep learning and NLP (Natural Language Processing) in social media and marketing are majorly driving the market.However, lack of data security in the cloud is hindering the market growth.The global AI in social media market is segmented into component, deployment, technology, tools, vertical, and region.Key playersSome of the key players in this market are Oracle Corporation (U.S.), IBM Corporation (U.S.), Adobe Systems (U.S.), SAS Institute (U.S.), Google LLC (U.S.), SAP SE (Germany), Alice Technologies (U.S.), NVIDIA Corporation (U.S.), Micron Technology, Inc. (U.S.), Albert Technologies Ltd. (U.K) and many others.Some of the key innovators in the global AI in social media market are Twitter (U.S.), (U.S.), Persado (U.S.), Talkwalker Alerts (Luxembourg), Darktrace (U.K), Autodesk, Inc. (U.S.), Renoworks Software (Canada), Bentley Systems Inc. (U.S.), Beyond Limits (U.S.), HPE (U.S.), Amazon Web Services (U.S.) and many others.Get Free Sample Copy Report Of The Market @ have been recent mergers and acquisitions among the key players, where the business entities expect to strengthen their reach to their customers.Regional AnalysisBy geography, the market is studied in North America, Europe, Asia Pacific, and the rest of the world.Among these regions, Asia Pacific is projected to show high growth rate in the forecast period.The rise in demand for cloud-based applications and growth in big data is driving organizations to deploy AI in social media in this region.On the other hand, Europe, the Middle East & Africa is expected to show a decent growth considering the AI in the social media market.The adoption of AI to improve customer service is driving the market in this region.However, the North America region is expected to register a significant market share throughout the forecast period.
AI in Insurance Market-OverviewThe penetration of AI in insurance processes, especially in developed economies, is estimated to bolster the in the insurance market 2020.The ICT industry reports are produced by Market Research Future, which highlights market options for expansion.An impressive CAGR is forecasted for the global market in the forecast period.The requirement of staying competitive in the market is forecasted to spur the AI in Insurance Market Share in the future.The escalating quantity and pace of data generation are anticipated to benefit AI in the insurance market in the approaching period.Segmental Analysis The segmental review of the AI in the insurance market has been carried out on the basis of application, technology, deployment, component, and sector.Based on the technology, the AI in the insurance market has been segmented into natural language processing (NLP), machine vision, machine learning, robotic automation, and deep learning.The AI in insurance market in the Middle Eastern & African and South American regions is also anticipated to develop at a considerable rate throughout the forecast period.Complete Report Details @ AnalysisThe stress on enhancing the production potential and upgradation of the workforce are the top priorities to reinvigorate the development potential of the market in the coming period.
Industry InsightThe take of global artificial intelligence in manufacturing market market 2020 recorded by Market Research Future reveals that the market can hit 47.09% to the net worth with USD 14.77 billion by 2024 amid the long-term impact of COVID-19.The years of growth is calculated to be from 2019-2024.Top Grossing FactorsThe global artificial intelligence in the manufacturing industry has gathered pace in its growth amid COVID-19 breakthrough with rapidly evolving industrial automation and IoT, at present.Artificial intelligence is allied with human intelligence with similar characteristics such as understanding, problem-solving, reasoning, language, and learning.All these factors are cheering the adoption of artificial intelligence solutions among the manufacturers to process the data and extract actionable insights.Furthermore, the factor of enhancement in automation in the manufacturing industry and the rise in demand for big data integration boost the escalation of artificial intelligence in the manufacturing industry.With this, prevalent usage of machine vision cameras in manufacturing applications, such as material movement, machinery inspection, quality control, and field service, is also to drive the growth of artificial intelligence in the manufacturing industry for the forecast period.Segmentation of Market: Artificial Intelligence in ManufacturingThe study by MRFR also digs some segmentation of the global artificial intelligence in the manufacturing industry, which has been done through the component, technology, application, and vertical.In terms of component segment, the market has included software, hardware, and services.In the last segment, the services segment also has a breakdown into support & maintenance and deployment & integration.In terms of the technology segment, the market has included natural language processing, machine learning & deep learning, computer vision, and context-aware computing.In terms of the application segment, the market has included supply chain management, predictive maintenance, field services, IT management, robotics, quality control, and others.In terms of vertical segment, the market has included aerospace & defense, automobile, semiconductor & electronics, energy & power, pharmaceuticals, food & beverage, and others.Complete Report Details @ AnalysisMarket Research Future (MRFR) study has covered some key countries in the regional analysis of artificial intelligence in manufacturing market market—North America, Europe, Asia-Pacific, the Middle East & Africa, and South America in the rest of the world.Artificial intelligence in the manufacturing industry is currently led by the Asia-Pacific region as the primary economic countries such as India, China, the Philippines, and South Korea are the major manufacturing centers of electronics, semiconductors, pharmaceuticals, and energy & power.
Moreover, it aids with diverse aspects of clinical trial operations.This blog is about some of the technologies fit within the clinical trial system and the way it will influence future clinical trial designs.Use of AI in Three AreasIn the clinical research industry, clinical trials are such an area which has a great potential for optimization.Research also supports this fact as only 12% of drug development programs ended in success in a 2000-2019 study according to recent research.Therefore, vendors will focus on the use of AI-based software in three main areas: information engines, patient stratification, and clinical trial operations.Information Engines Natural Language Processing will be used in this area.Professionals mainly concentrate on enhancing the quality, efficiency and success rate of clinical trials.Furthermore, it is also ensured that their drug responses are kept in track to ensure that conclusions can be drawn from a trial.
(University of California - Santa Barbara) As we rely more on natural language processing to help us navigate our world, it's more important than ever that these artificial intelligence models -- used increasingly in applications such as caption generation for the visually impaired -- remain true to reality.
In this article, I am going to talk about the most important libraries of Python used in the field of data science.Libraries are collection of functions and methods that enable you to perform a wide variety of actions without writing the code yourself.First of all, there are over 137.000 libraries in Python.In this article we are going to learn : Scientific Computing Libraries in PythonVisualization Libraries in Python High-Level Machine Learning and Deep Learning Libraries in Python Deep Learning Libraries in PythonPython Libraries for NLP ( Natural Language Processing )   Before we start explaining all of them, Let’s learn what data science is and why we use python programming language in this field.Click here to go to the article.  
Sentiment Analytics Market, By Components (Software, Services, By Deployment (Cloud, On-Premise), By Organization Size (SMEs, Large Enterprises), By Vertical (Retail, BFSI, Healthcare & Life Science) - Forecast 2023OverviewSentiment analytics determines the emotional tone behind a series of words and analyses human emotions, sentiments with the help of consumer data (primarily social media feeds), deep learning capabilities and natural language processing (NLP).The global sentiment analytics market is anticipated to grow at a CAGR of 14% and reach a valuation of USD 6 Bn over the forecast period of 2017-2023, asserts Market Research Future (MRFR) in a detailed research report.Growing popularity of social media platforms is one of the preliminary factors spurring the growth of the global sentiment analytics market.Advances made in the field of artificial intelligence (AI) which allows contemplation of human behavior and emotions also drives the market for sentiment analytics.Sentiment analytics is gaining traction among various industry verticals such as healthcare, FMCG, telecom, retail, media & entertainment, and others.Sentiment analytics allows a deep understanding of consumer’s needs, expectations and extending customer base which can aid businesses to plan their business strategies accordingly.The emergence of big data is a crucial factor in boosting the growth of the global sentiment analytics market.Availability of colossal amounts of data allows enterprises to leverage it to get actionable insights.Growing adoption of cloud computing is also a major factor driving the growth of the global sentiment analytics market.Other drivers include seamless integration and up gradation, and cost saving on infrastructure.
Cognitive Cloud Market, By Technology (NLP, Machine Learning, Automated Reasoning), By Service (Managed, Professional), By End User (SMEs, Large Enterprises) and By Vertical - Forecast 2023Industry InsightMarket Research Future provides a short-term assessment of the impact of COVID-19 on the global cognitive cloud market 2020.It offers a clear assessment of the projected market fluctuations during the forecast period (2017–2023) with USD 3.42 Billion in valuation.In this daunting time where businesses are struggling to keep up with their infrastructure needs, the global cognitive cloud market is anticipated to achieve a milestone of high percent uptime of a stable growth graph.While COVID-19 has had a noteworthy impact on the worldwide cognitive cloud market, organizations realize that cloud services are necessarily a good fit for unprecedented uncertainties ensuring business continuity amidst physical lockdowns.These factors are assessed to be beneficial for the market of the cognitive cloud to expand in the forecast period.As the global cognitive cloud market encompasses technologies such as machine learning, natural language processing, information retrieval, and automated reasoning for translating unstructured data to sense, these are creating meticulous opportunities for new players to invest in and take the market’s valuation to the next level.At the same time, globally, several companies are rapidly adopting cognitive cloud technologies to gain a competitive edge in the market.These companies are incessantly innovating their products and services to overcome large and complex data challenges as compared to other database solutions.Furthermore, the rise in concern among all the major business organizations to study the extensive volume of data to assess the risk associated with any strategic initiative is further instrumental in accelerating the cognitive cloud market growth.In healthcare, the cognitive cloud assists with assembling the available information and integrating that data with patient information, which, in turn, helps in presenting more personalized services.
The market report study titled ‘Natural Language Processing (NLP) in Healthcare and Life Sciences published by Reports and Data offers in-depth and comprehensive research describing the scope of the market and market insights until 2026.The report will include details about potential opportunities, new projects, financial situations, constructive business strategies, and an outlook on the industry forecast.The COID-19 crisis has dynamically changed the economic scenario on a global level.The report is updated with the latest COVID-19 incidence, economic landscape, and present and future impact of COVID-19 on the market.The research report further studies the growth driving and restraining factors impacting the regional market and competitive landscape of the business sphere.The study also offers deeper insights into the challenges and hurdles the established companies and new entrants might face in the Natural Language Processing (NLP) in Healthcare and Life Sciences industry.Get a sample of the report @ Analysis of the Natural Language Processing (NLP) in Healthcare and Life Sciences Market:The Natural Language Processing (NLP) in Healthcare and Life Sciences Market is further segmented into key players operating in the Natural Language Processing (NLP) in Healthcare and Life Sciences industry.The major companies profiled in the report include Cerner Corporation, 3M, Nuance Communications, Inc., IBM Corporation, Heath Fidelity, Microsoft Corporation, Linguamatics, Apixio, Clinithink Inc., and Mmodal IP PLC.The Natural Language Processing (NLP) in Healthcare and Life Sciences offers a detailed analysis of the product portfolio, key trends, applications, and a thorough value chain analysis.