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Exam Code: P2065-013 Practice test 2022 by Killexams.com team
IBM Intelligent Operations Center Technical Mastery Test v1
IBM Intelligent answers
Killexams : IBM Intelligent answers - BingNews https://killexams.com/pass4sure/exam-detail/P2065-013 Search results Killexams : IBM Intelligent answers - BingNews https://killexams.com/pass4sure/exam-detail/P2065-013 https://killexams.com/exam_list/IBM Killexams : Here's How Consumers Can Now Use Watson No result found, try new keyword!Questions Watson is equipped to answer include “What is the ... “Through this experience, we expect to learn how intelligent assistants like IBM Watson can help service members who may not ... Fri, 22 Jul 2022 12:00:00 -0500 en-us text/html https://www.thestreet.com/technology/heres-how-you-can-finally-use-watson-12782116 Killexams : Cybersecurity - what’s the real cost? Ask IBM
(Pixabay)

Cybersecurity has always been a concern for every type of organization. Even in normal times, a major breach is more than just the data economy’s equivalent of a ram-raid on Fort Knox; it has knock-on effects on trust, reputation, confidence, and the viability of some technologies. This is what IBM calls the “haunting effect”.

A successful attack breeds more, of course, both on the same organization again, and on others in similar businesses, or in those that use the same compromised systems. The unspoken effect of this is rising costs for everyone, as all enterprises are forced to spend money and time on checking if they have been affected too.

But in our new world of COVID-19, disrupted economies, climate change, remote working, soaring inflation, and looming recession, all such effects are all amplified. Throw in a war that’s hammering on Europe’s door (with political echoes across the Middle East and Asia) and it’s a wonder any of us can get out of bed in the morning.

So, what are the real costs of a successful cyberattack – not just hacks, viruses, and Trojans, but also phishing, ransomware, and concerted campaigns against supply chains and code repositories?

According to IBM’s latest annual survey, breach costs have risen by an unlucky 13% over the past two years, as attackers, which include hostile states, have probed the systemic and operational weaknesses exposed by the pandemic.

The global average cost of a data breach has reached an all-time high of $4.35 million – at least, among the 550 organizations surveyed by the Ponemon Institute for IBM Security (over a year from March 2021). Indeed, IBM goes so far as to claim that breaches may be contributing to the rising costs of goods and services. The survey states:

Sixty percent of studied organizations raised their product or services prices due to the breach, when the cost of goods is already soaring worldwide amid inflation and supply chain issues.

Incidents are also “haunting” organizations, says the company, with 83% having experienced more than one data breach, and with 50% of costs occurring more than a year after the successful attack.

Cloud maturity is a key factor, adds the report:

Forty-three percent of studied organizations are in the early stages [of cloud adoption] or have not started applying security practices across their cloud environments, observing over $660,000 in higher breach costs, on average, than studied organizations with mature security across their cloud environments.

Forty-five percent of respondents run a hybrid cloud infrastructure. This leads to lower average breach costs than among those operating a public- or private-cloud model: $3.8 million versus $5.02 million (public) and $4.24 million (private).

That said, those are still significant costs, and may suggest that complexity is what deters attackers, rather than having a single target to hit. Nonetheless, hybrid cloud adopters are able to identify and contain data breaches 15 days faster on average, says the report.

However, with 277 days being the average time lag – an extraordinary figure – the real lesson may be that today’s enterprise systems are adept at hiding security breaches, which may appear as normal network traffic. Forty-five percent of breaches occurred in the cloud, says the report, so it is clearly imperative to get on top of security in that domain.

IBM then makes the following bold claim :

Participating organizations fully deploying security AI and automation incurred $3.05 million less on average in breach costs compared to studied organizations that have not deployed the technology – the biggest cost saver observed in the study.

Whether this finding will stand for long as attackers explore new ways to breach automated and/or AI-based systems – and perhaps automate attacks of their own invisibly – remains to be seen. Compromised digital employee, anyone?

Global systems at risk

But perhaps the most telling finding is that cybersecurity has a political dimension – beyond the obvious one of Russian, Chinese, North Korean, or Iranian state incursions, of course.

Concerns over critical infrastructure and global supply chains are rising, with threat actors seeking to disrupt global systems that include financial services, industrial, transportation, and healthcare companies, among others.

A year ago in the US, the Biden administration issued an Executive Order on cybersecurity that focused on the urgent need for zero-trust systems. Despite this, only 21% of critical infrastructure organizations have so far adopted a zero-trust security model, according to the report. It states:

Almost 80% of the critical infrastructure organizations studied don’t adopt zero-trust strategies, seeing average breach costs rise to $5.4 million – a $1.17 million increase compared to those that do. All while 28% of breaches among these organizations were ransomware or destructive attacks.

Add to that, 17% of breaches at critical infrastructure organizations were caused due to a business partner being initially compromised, highlighting the security risks that over-trusting environments pose.

That aside, one of the big stories over the past couple of years has been the rise of ransomware: malicious code that locks up data, enterprise systems, or individual computers, forcing users to pay a ransom to (they hope) retrieve their systems or data.

But according to IBM, there are no obvious winners or losers in this insidious practice. The report adds:

Businesses that paid threat actors’ ransom demands saw $610,000 less in average breach costs compared to those that chose not to pay – not including the ransom amount paid.

However, when accounting for the average ransom payment – which according to Sophos reached $812,000 in 2021 – businesses that opt to pay the ransom could net higher total costs, all while inadvertently funding future ransomware attacks.”

The persistence of ransomware is fuelled by what IBM calls the “industrialization of cybercrime”.

The risk profile is also changing. Ransomware attack times show a massive drop of 94% over the past three years, from over two months to just under four days. Good news? Not at all, says the report, as the attacks may be higher impact, with more immediate consequences (such as destroyed data, or private data being made public on hacker forums).

My take

The key lesson in cybersecurity today is that all of us are both upstream and downstream from partners, suppliers, and customers in today’s extended enterprises. We are also at the mercy of reused but compromised code from trusted repositories, and even sometimes from hardware that has been compromised at source.

So, what is the answer? Businesses should ensure that their incident responses are tested rigorously and frequently in advance – along with using red-, blue-, or purple-team approaches (thinking like a hacker, a defender, or both).

Regrettably, IBM says that 37% of organizations that have IR plans in place fail to test them regularly. To paraphrase Spinal Tap, you can’t code for stupid.

Wed, 27 Jul 2022 20:21:00 -0500 BRAINSUM en text/html https://diginomica.com/cybersecurity-whats-real-cost-ask-ibm
Killexams : How Much Is Microsoft Worth? No result found, try new keyword!By 1980, the company had struck a deal to provide the operating system for IBM computers ... Productivity and Business Processes, Intelligent Cloud and More Personal Computing. Mon, 01 Aug 2022 10:43:00 -0500 text/html https://www.nasdaq.com/articles/how-much-is-microsoft-worth Killexams : Death Of The Turing Test In An Age Of Successful AIs

IBM has come up with an automatic debating system called Project Debater that researches a topic, presents an argument, listens to a human rebuttal and formulates its own rebuttal. But does it pass the Turing test? Or does the Turing test matter anymore?

The Turing test was first introduced in 1950, often cited as year-one for AI research. It asks, “Can machines think?”. Today we’re more interested in machines that can intelligently make restaurant recommendations, drive our car along the tedious highway to and from work, or identify the surprising looking flower we just stumbled upon. These all fit the definition of AI as a machine that can perform a task normally requiring the intelligence of a human. Though as you’ll see below, Turing’s test wasn’t even for intelligence or even for thinking, but rather to determine a test subject’s sex.

The Imitation Game

Turing test with machine
Turing test with machine

The Turing test as we know it today is to see if a machine can fool someone into thinking that it’s a human. It involves an interrogator and a machine with the machine hidden from the interrogator. The interrogator asks questions of the machine using only keyboard and screen. The purpose of the interrogator’s questions are to help him to decide if he’s talking to a machine or a human. If he can’t tell then the machine passes the Turing test.

Often the test is done with a number of interrogators and the measure of success is the percentage of interrogators who can’t tell. In one example, to supply the machine an advantage, the test was to tell if it was a machine or a 13-year-old Ukrainian boy. The young age excused much of the strangeness in its conversation. It fooled 33% of the interrogators.

Imitation game with a machine and a man
Imitation game with a machine and a man

Naturally Turing didn’t call his test “the Turing test”. Instead he called it the imitation game, since the goal was to imitate a human. In Turing’s paper, he gives two versions of the test. The first involves three people, the interrogator, a man and a woman. The man and woman sit in a separate room from the interrogator and the communication at Turing’s time was ideally via teleprinter. The goal is for the interrogator to guess who is male and who is female. The man’s goal is to fool the interrogator into making the wrong decision and the woman’s is to help him make the right one.

The second test in Turing’s paper replaces the woman with a machine but the machine is now the deceiver and the man tries to help the interrogator make the right decision. The interrogator still tries to guess who is male and who is female.

But don’t let that goal fool you. The real purpose of the game was as a replacement for his question of “Can a machine think?”. If the game was successful then Turing figured that his question would have been answered. Today, we’re both more sophisticated about what constitutes “thinking” and “intelligence”, and we’re also content with the machine displaying intelligent behavior, whether or not it’s “thinking”.  To unpack all this, let’s take IBM’s recent Project Debater under the microscope.

The Great Debater

IBM’s Project Debater is an example of what we’d call a composite AI as opposed to a narrow AI. An example of narrow AI would be to present an image to a neural network and the neural network would label objects in that image, a narrowly defined task. A composite AI, however, performs a more complex task requiring a number of steps, much more akin to a human brain.

Debate format

Project Debater is first given the motion to be argued. You can read the paper on IBM’s webpage for the details of what it does next but basically it spends 15 minutes researching and formulating a 4-minute opening speech supporting one side of the motion. It also converts the speech to natural language and delivers it to an audience. During those initial 15 minutes, it also compiles leads for the opposing argument and formulates responses. This is in preparation for its later rebuttal. It then listens to its opponents rebuttal, converting it to text using IBM’s own Watson speech-to-text. It analyzes the text and, in combination with the responses it had previously formulated, comes up with its own 4-minute rebuttal. It converts that to speech and ends with a summary 2-minute speech.

All of those steps, some of them considered narrow AI, add up to a composite AI. The whole is done with neural networks along with conventional data mining, processing, and analysis.

The following video is of a live debate between Project Debater and Harish Natarajan, world record holder for the number of debate competitions won. Judge for yourself how well it works.

Does Project Debater pass the Turing test? It didn’t take the formal test, however, you can judge for yourself by imagining studying a transcript of what Project Debater had to say. Could you tell whether it was produced by a machine or a human? If you could mistake it for a human then it may pass the Turing test. It also responds to the human debater’s argument, similar to answering questions in the Turing test.

Keep in mind though that Project Debater had 15 minutes to prepare for the opening speech and no numbers are given on how long it took to come up with the other speeches, so if time-to-answer is a factor then it may lose there. But does it matter?

Does The Turing Test Matter?

Does it matter if any of today’s AIs can pass the Turing test? That’s most often not the goal. Most AIs end up as marketed products, even the ones that don’t start out that way. After all, eventually someone has to pay for the research. As long as they do the job then it doesn’t matter.

IBM’s goal for Project Debater is to produce persuasive arguments and make well informed decisions free of personal bias, a useful tool to sell to businesses and governments. Tesla’s goal for its AI is to drive vehicles. Chatbots abound for handling specific phone and online requests. All of them do something normally requiring the intelligence of a human with varying degrees of success. The test that matters then is whether or not they do their tasks well enough for people to pay for them.

Maybe asking if a machine can think, or even if it can pass for a human, isn’t really relevant. The ways we’re using them require only that they can complete their tasks. Sometimes this can require “human-like” behavior, but most often not. If we’re not using AI to trick people anyway, is the Turing test still relevant?

Mon, 01 Aug 2022 12:00:00 -0500 Steven Dufresne en-US text/html https://hackaday.com/2021/04/06/death-of-the-turing-test-in-an-age-of-successful-ais/
Killexams : AI Lawyer "Ross" Has Been Hired By Its First Official Law Firm

Law firm Baker & Hostetler has announced that they are employing IBM’s AI Ross to handle their bankruptcy practice, which at the moment consists of nearly 50 lawyers. According to CEO and co-founder Andrew Arruda, other firms have also signed licenses with Ross, and they will also be making announcements shortly.

Ross, “the world’s first artificially intelligent attorney” built on IBM’s cognitive computer Watson, was designed to read and understand language, postulate hypotheses when asked questions, research, and then generate responses (along with references and citations) to back up its conclusions. Ross also learns from experience, gaining speed and knowledge the more you interact with it.

“You ask your questions in plain English, as you would a colleague, and ROSS then reads through the entire body of law and returns a cited answer and topical readings from legislation, case law and secondary sources to get you up-to-speed quickly,” the website says. “In addition, ROSS monitors the law around the clock to notify you of new court decisions that can affect your case.”

Ross also minimizes the time it takes by narrowing down results from a thousand to only the most highly relevant answers, and presents the answers in a more casual, understandable language. It also keeps up-to-date with developments in the legal system, specifically those that may affect your cases.

Click to View Full Infographic

Baker & Hostetler chief information officer Bob Craig explains the rationale behind this latest hire: “At BakerHostetler, we believe that emerging technologies like cognitive computing and other forms of machine learning can help enhance the services we deliver to our clients.”

“BakerHostetler has been using ROSS since the first days of its deployment, and we are proud to partner with a true leader in the industry as we continue to develop additional AI legal assistants,” he added.


Mon, 11 Jul 2022 10:46:00 -0500 text/html https://futurism.com/artificially-intelligent-lawyer-ross-hired-first-official-law-firm
Killexams : Data-centric Security Market Size, Share, Growth Rate Report, Forecast Between 2022 to 2028

New Jersey, United States – Data-centric Security Market 2022 – 2028, Size, Share, and Trends Analysis Research Report Segmented with Type, Component, Application, Growth Rate, Region, and Forecast | key companies profiled -Broadcom, Forcepoint, IBM, and others.

Data-Centric security is tied in with getting information where it is put away and taken care of, as opposed to zeroing in on security controls for servers, applications and organization foundation. Data-Centric security likewise assists associations with defeating the separation between IT security innovation and the business methodology goals by interfacing security benefits straightforwardly to the information they totally safeguard. Data Centric security assists associations with chopping down within dangers, dangers presented by programmers, and other pernicious assaults. It ceaselessly notices the movement of classified information. Data Centric models likewise adopt a zero-trust strategy that lessens digital gamble as the client demands restricted admittance just when required. Data Centric security gives numerous different advantages, for example, getting information transmissions, keeping up with information trustworthiness and security, guaranteeing consistency, and safeguarding unapproved access.

According to our latest report, the Data-centric Security market, which was valued at US$ million in 2022, is expected to grow at a CAGR of approximate percent over the forecast period.

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The worldwide Data Centric security market size is projected to develop from an expected worth of USD 4.2 billion in 2022 to USD 12.3 billion by 2028, a growth from 2022 to 2028. The need to find, order, secure, and track the most delicate information all through its whole lifecycle; government compliances and guidelines; and developing information break episodes is driving the development of Data Centric security market across the globe. Information is becoming quicker and allowed to stream everywhere imaginable in the cloud as the need might arise. In 2020, organizations like IBM, Microsoft, and Google overwhelmed the cloud market and executed different cutting-edge innovations, like AI and ML, to examine information. Huge and little undertakings expanding need to safeguard information on the cloud is supposed to drive the Data Centric security market. For example, Informatica gives Intelligent Cloud ServicesSM, which gives information assurance as failover server farms, client confirmation, and access controls, encryption at the working system, data set, and application levels.

Data-Centric security arrangements supply a far-reaching method for safeguarding ventures information consistence and protection. These arrangements can be applied to information very still, information on the way, and information being used, and can include a few cycles, for example, information characterization and disclosure, information insurance by means of encryption, tokenization and concealing, and information administration and consistence. These arrangements are worried about the protection and security of information as opposed to the security of organizations, endpoints, and applications. Besides, expansion in occasions of cyberattacks is making Data Centric security arrangements a fundamental component in associations to safeguard strategic information. The worldwide Data-Centric security market is in the development stage, attributable to ascend in worries of information security among end clients.

Segmentation

Developing interest for Data-Centric security answers for cloud-based information security and expanding chances looked by big business information because of abuse of enormous information investigation, computerized reasoning, and AI is assessed to drive the Data Centric security market during the conjecture time frame. Severe guidelines, for example, the government data handling norms, and installment card industry information security principles are empowering endeavors to execute Data-Centric security, which is assessed to help the Data Centric security market during the estimate time frame.

The medical care and drug fragment is projected to observe the quickest development pace of during the gauge time frame. The medical care vertical covers individual wellbeing data and basic information about a patient that needs high security; thusly, information security has been of most extreme significance to this vertical. The developing need to shield the inside medical care information of an association is likewise of most extreme significance since most medical services associations center around client information secure and don’t zero in on the assurance of the interior information.

Access the Premium Data-centric Security market research report 2022 with a full index.

Regional analysis

The Asia Pacific district ruled the worldwide Data-Centric security market with the biggest offer because of the fast reception of encryption advances and unrivaled Data-Centric security arrangements by arising economies like India, China, Japan, Singapore, and Australia. SMEs and organizations in the Asia Pacific locale are broadly taking on Data-Centric security answers for shielding critical and touchy business information from digital dangers, business secret activities, and abuse of information.

The Data-Centric security market in North America is projected to extend at a fast speed during the gauge time frame. This can be credited to the presence of larger part of the market players and the developing need to ensure information security, predominance, and heredity across organizations.

Key Players

Broadcom
Forcepoint
IBM
Egnyte
Fasoo
Informatica
Netwrix
NextLabs Inc.
Imperva
Protegrity
Seclore
Talend
Microfocus
NetApp
Orange Cyberdefense
Varonis Systems

The following are some of the reasons why you should Buy a Data-centric Security market report:

  • The Report looks at how the Data-centric Security industry is likely to develop in the future.
  • Using Porter’s five forces analysis, it investigates several perspectives on the Data-centric Security market.
  • This Data-centric Security market study examines the product type that is expected to dominate the market, as well as the regions that are expected to grow the most rapidly throughout the projected period.
  • It identifies recent advancements, Data-centric Security market shares, and important market participants’ tactics.
  • It examines the competitive landscape, including significant firms’ Data-centric Security market share and accepted growth strategies over the last five years.
  • The research includes complete company profiles for the leading Data-centric Security market players, including product offers, important financial information, current developments, SWOT analysis, and strategies.

Click here to download the full index of the Data-centric Security market research report 2022

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Tue, 02 Aug 2022 00:40:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/data-centric-security-market-size-share-growth-rate-report-forecast-between-2022-to-2028
Killexams : Edge AI Software Market Status and Segments Forecast 2022-2027 | IBM, Imagimob, Microsoft, Nutanix,

Astute Analytica released a new research report on the global Edge AI Software Market The worldwide Edge AI Software Market report 2027 is a thorough investigation that examines the current Edge AI Software Market trends. The report consists of market definitions, market segmentation, end-use applications, and industry chain analysis. In addition, it offers a succinct overview of the market. The study on the global market offers an overview of the market encompassing the competitive environment, current market developments, and industry trends.

The global Edge AI Software market held a market value of USD 1,300.0 Million in 2020 and is forecasted to reach USD 8,049.8 Million by the year 2027. The market is expected to register a CAGR of 29.8% during the forecast period.

The competition study provides information about the major players in the Chinese market in terms of their financials, company profiles, product portfolios, and capacity. Along with the important development trends and sales channel research, the report also offers upstream raw material analysis and downstream demand analysis. The global research study also covers the investment opportunity areas.

Request To download demo of This Strategic Report: – https://www.astuteanalytica.com/request-sample/edge-ai-software-market

Despite the driving factors, security and privacy concerns coupled with vulnerability to cyber attacks are expected to hinder the market growth. During the COVID-19 pandemic, the healthcare segment using edge AI software witnessed positive growth as the software led to growing funding and research for keeping businesses safe and secure across the value chain.

Growth Influencers:

Advancements in AI powered IoT (Internet of Things) for intelligent systems and smart applications

Artificial intelligence sector is experiencing the emergence of a range of applications in various verticals. All these applications need massive computing power for performing activities, such as capture and process data in real time. While functioning with the cloud technology, artificial intelligence applications undergo various latency issues and lead to difficulties in offering quick responses. Edge AI software help in keeping the resources at the edge of the network. This helps the applications to work with high bandwidth and low latency. Hence, advancements in AI powered IoT (Internet of Things) for intelligent systems and smart applications are anticipated to boost the market growth.

Segments Overview:

The global Edge AI Software market is segmented into component, data source, application, and end-users.

By Component

  • Solutions
  • Software Tools
  • Platform
  • Services
  • Training and Consulting Services
  • System Integration and Testing
  • Support and Maintenance

The solutions segment is estimated to account for the largest market share of around 80% owing to its high demand. The services segment is expected to grow at the fastest CAGR of 30.6% owing to slowly increasing adoption of training and consulting services. The support and maintenance segment is held a market size of USD 337.3 million in 2020.

By Data Source

  • Biometric Data
  • Mobile Data
  • Sensor Data
  • Speech Recognition
  • Video and Image Recognition

The sensor data is anticipated to hold the largest market share of around 26% owing to high product availability in this segment. The biometric data is estimated to grow at the fastest rate of about 30.4% owing to growing adoption of biometric technology in various industries.

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By Application

  • Access Control
  • Autonomous Vehicles
  • Energy Management
  • Predictive Maintenance
  • Remote Monitoring
  • Telemetry
  • Video Surveillance
  • Others

The energy management segment is expected to account for the dominant share of the market owing to growing number of edge AI software applications in this industry. The video surveillance segment is estimated to hit a market value of around USD 500 million by 2025.

By End-Users

  • Advanced Industries
  • Banking and Insurance
  • Chemicals and Agriculture
  • Consumer
  • Cross-Vertical
  • Energy and Materials
  • Healthcare
  • Infrastructure
  • Media and Entertainment
  • Public Sector and Utilities
  • Retail
  • Travel, Transport and Logistics

The travel, transport, and logistics segment accounted for the largest market share of about 21% owing to growing adoption of healthcare IT in the travel, transport, and logistics sector. The cross-vertical sector is estimated to witness a growth rate of around 30.3% and the consumer segment is expected to surpass a market value of around USD 262.4 million by 2025.

Regional Overview:

On a regional basis, the global Edge AI Software market is segmented into Europe, North America, Asia Pacific, Middle East & Africa, and South America.

The Asia Pacific region held the largest market share of about 38% owing to increasing adoption of technologically advanced solutions in the market and growing travel industry in countries, such as India and Japan. The North American witnessed a growth rate of around 30.9% owing to the growing healthcare IT industry in the U.S. and Canada.

Competitive Landscape:

Key players operating in the global Edge AI Software market include Alef Edge, Inc., Anagog Ltd., AWS, Azion Technologies, Bragi.Com, Chaos Prime, Inc., Clearblade, Inc., Foghorn Systems, Inc., Google, Gorilla Technology Group, Inc., IBM, Imagimob, Microsoft, Nutanix, Octonion, Sixsq Sarl, Synaptics, TACT.AI, TIBCO Software, Veea Inc., and other prominent players.

Major 2 players in the market hold about 25-30% of the market share. These players are engaged in product launches, mergers & acquisitions, and collaboration, among others. For instance, in January 2021, TIBCO Software, Inc. acquired Information Builders, hence advancing its connected intelligence platform by addition of Information Builders’ data management and analytics capabilities.

The global Edge AI Software market report provides insights on the below pointers:

  • Market Penetration: Provides comprehensive information on the market offered by the prominent players
  • Market Development: The report offers detailed information about lucrative emerging markets and analyzes penetration across mature segments of the markets
  • Market Diversification: Provides in-depth information about untapped geographies, recent developments, and investments
  • Competitive Landscape Assessment: Mergers & acquisitions, certifications, product launches in the global Edge AI Software market have been provided in this research report. In addition, the report also emphasizes the SWOT analysis of the leading players.
  • Product Development & Innovation: The report provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The global Edge AI Software market report answers questions such as:

  • What is the market size and forecast of the Global Edge AI Software Market?
  • What are the inhibiting factors and impact of COVID-19 on the Global Edge AI Software Market during the assessment period?
  • Which are the products/segments/applications/areas to invest in over the assessment period in the Global Edge AI Software Market?
  • What is the competitive strategic window for opportunities in the Global Edge AI Software Market?
  • What are the technology trends and regulatory frameworks in the Global Edge AI Software Market?
  • What is the market share of the leading players in the Global Edge AI Software Market?
  • What modes and strategic moves are considered favorable for entering the Global Edge AI Software Market?

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Astute Analytica is a global analytics and advisory company that has built a solid reputation in a short period, thanks to the tangible outcomes we have delivered to our clients. We pride ourselves in generating unparalleled, in-depth, and uncannily accurate estimates and projections for our very demanding clients spread across different verticals. We have a long list of satisfied and repeat clients from a wide spectrum including technology, healthcare, chemicals, semiconductors, FMCG, and many more. These happy customers come to us from all across the globe.

They are able to make well-calibrated decisions and leverage highly lucrative opportunities while surmounting the fierce challenges all because we analyze for them the complex business environment, segment-wise existing and emerging possibilities, technology formations, growth estimates, and even the strategic choices available. In short, a complete package. All this is possible because we have a highly qualified, competent, and experienced team of professionals comprising business analysts, economists, consultants, and technology experts. In our list of priorities, you-our patron-come at the top. You can be sure of the best cost-effective, value-added package from us, should you decide to engage with us.

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The MarketWatch News Department was not involved in the creation of this content.

Jun 29, 2022 (Market Insight Reports) -- The latest Intelligent Video (IV) Market Analysis is designed to help clients Improve their market position, and in line with this, this report provides a detailed analysis of several leading Intelligent Video (IV) market Key Players including IBM, Cisco Systems, Inc., Robert Bosch GmbH, Axis Communications AB, Siemens, Honeywell International, Inc., Panasonic, Verint Systems, Avigilon, Agent Video Intelligence, Inc., Objectvideo, Inc., Advantech, Infinova, Qognify, PureTech Systems, IntelliVision, VCA Technology, and Others. Also, the Intelligent Video (IV) market analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.

Our Experts will help you get valuable insights about Intelligent Video (IV) market share, size, and regional growth prospects. Available Other Related Market Research Reports

Sample PDF Report at- https://reportsinsights.com/sample/593507

Intelligent Video (IV) Market showcases an in-depth analysis of the overall Intelligent Video (IV) market in terms of market size, upstream situation, price & cost, industry environment, segmentation for Intelligent Video (IV) providers, end-users, geographies, and analysis up to 2028. In addition, the report outlines the factors driving industry growth and the description of market channels.

This has brought along several changes in this report also covers the impact of COVID-19 on the global market.

The market research report covers the analysis of key stakeholders of the Intelligent Video (IV) market. Some of the leading players profiled in the report include: IBM, Cisco Systems, Inc., Robert Bosch GmbH, Axis Communications AB, Siemens, Honeywell International, Inc., Panasonic, Verint Systems, Avigilon, Agent Video Intelligence, Inc., Objectvideo, Inc., Advantech, Infinova, Qognify, PureTech Systems, IntelliVision, VCA Technology

The research insights presented in this report are backed by a deep understanding of key insights gathered from both secondary and primary research. The opinions and insights presented in the Intelligent Video (IV) market report were influenced by discussions held with several players in this industry. the Intelligent Video (IV) market report highlights the key players and manufacturers and the latest strategies including new product launches, partnerships, joint ventures, technology, segmentation in terms of region and industry competition, profit and loss ratio, and investment ideas. A precise evaluation of effective manufacturing techniques, advertisement techniques, Intelligent Video (IV) market share, size, growth rate, revenue, sales, and value chain analysis.

The 'Global Intelligent Video (IV) Market Research Report' is a comprehensive and informative study on the current state of the Global Intelligent Video (IV) Market industry with emphasis on the global industry. The report presents key statistics on the market status of the global Intelligent Video (IV) market manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.

Major Product Types covered are:
Camera-based Systems

Server-based Systems

Major Applications of Intelligent Video (IV) covered are:
BFSI Sector

Government and Public Sector

Industrial Sector

Retail Sector

Transport and Logistics Sector

Others

Regional Intelligent Video (IV) Market (Regional Output, Demand & Forecast by Countries):-
North America (United States, Canada, Mexico)
South America ( Brazil, Argentina, Ecuador, Chile)
Asia Pacific (China, Japan, India, Korea)
Europe (Germany, UK, France, Italy)
Middle East Africa (Egypt, Turkey, Saudi Arabia, Iran) And More.

Access full Report Description, TOC, Table of Figures, Chart, etc. at-https://www.reportsinsights.com/industry-forecast/intelligent-video-iv-markets-growth-trends-593507

The report is useful in providing answers to several critical questions that are important for the industry stakeholders such as manufacturers and partners, end-users, etc., besides allowing them in strategizing investments and capitalizing on market opportunities.

Reasons to Purchase Global Intelligent Video (IV) Market Report:

1. Important changes in Intelligent Video (IV) market dynamics
2. What is the current Intelligent Video (IV) market scenario across various countries?
3. Current and future of Global Intelligent Video (IV) market outlook in the developed and emerging markets.
4. Analysis of various perspectives of the market with the help of Porter's five forces analysis.
5. The segment that is expected to dominate the Global Intelligent Video (IV) market.
6. Regions that are expected to witness the fastest growth during the forecast period.
7. Identify the latest developments, Global Intelligent Video (IV) market shares, and strategies employed by the major market players.
8. Former, ongoing, and projected 90 market analysis in terms of volume and value

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