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Automated testing initiatives still lag behind in many organizations as increasingly complex testing environments are met with a lack of skilled personnel to set up tests.
Recent research conducted by Forrester and commissioned by Keysight found that while only 11% of respondents had fully automated testing, 84% percent of respondents said that the majority of testing involves complex environments.
For the study, Forrester conducted an online survey in December 2021 that involved 406 test operations decision-makers at organizations in North America, EMEA, and APAC to evaluate current testing capabilities for electronic design and development and to hear their thoughts on investing in automation.
The complexity of testing has increased the number of tests, according to 75% of the respondents. Sixty-seven percent of respondents said the time to complete tests has risen too.
Those that do utilize automated testing often have difficulty making the tests stable in these complex environments, according to Paulina Gatkowska, head of quality assurance at STX Next, a Python software house.
One such area where developers often find many challenges is in UI testing in which the tests work like a user: they use the browser, click through the application, fill fields, and more. These tests are quite heavy, Gatkowska continued, and when a developer finishes their test on a local environment, sometimes it fails in another environment, or only works 50% times, or a test works the first week, and then starts to be flaky.
“What’s the point of writing and running the tests, if sometimes they fail even though there is no bug? To avoid this problem, it’s important to have a good architecture of the tests and good quality of the code. The tests should be independent, so they don’t interfere with each other, and you should have methods for repetitive code to change it only in one place when something changes in the application,” Gatkowska said. “You should also attach great importance to ‘waits’ – the conditions that must be met before the test proceeds. Having this in mind, you’ll be able to avoid the horror of maintaining flaky tests.”
Then there are issues with the network that can impede automated tests, according to Kavin Patel, founder and CEO of Convrrt, a landing page builder. A common difficulty for QA teams is network disconnection, which makes it difficult for them to access databases, VPNs, third-party services, APIs, and certain testing environments, because of shaky network connections, adding needless time to the testing process. The inability to access virtual environments, which are typically utilized by testers to test programs, is also a worry.
Because some teams lack the expertise to implement automated testing, manual testing is still used as a correction for any automation gaps. This creates a disconnect with the R&D team, which is usually two steps ahead, according to Kenny Kline, president of Barbend, an online platform for strength sports training and nutrition.
“To keep up with them, testers must finish their cycles within four to six hours, but manual testing cannot keep up with the rate of development. Then, it is moved to the conclusion of the cycle,” Kline said. “Consequently, teams must include a manual regression, sometimes known as a stabilization phase, at the end of each sprint. They extend the release cadence rather than lowering it.”
Forrester’s research also found that 45% of companies say that they’re willing to move to a fully automated testing environment within the next three years to increase productivity, gain the ability to simulate product function and performance, and shorten the time to market.
The companies that have implemented automated testing right have reaped many rewards, according to Michael Urbanovich, head of the testing department at a1qa, an international quality assurance company. The ones relying on robotic process automation (RPA), AI, ML, natural language processing (NLP), and computer vision for automated testing have attained greater efficiency, sped up time to market, and freed up more resources to focus on strategic business initiatives. RPA alone can lower the time required for repetitive tasks up to 25%, according to research by Automation Alley.
For those looking to gain even more from their automation initiatives, a1qa’s Urbanovich suggests looking into continuous test execution, implementing self-healing capabilities, RPA, API automation, regression testing, and UAT automation.
Urbanovich emphasized that the decision to introduce automated QA workflows must be conscious. Rather than running with the crowd to follow the hype, organizations must calculate ROI based on their individual business needs and wisely choose the scope for automation and a fit-for-purpose strategy.
“To meet quality gates, companies need to decide which automated tests to run and how to run them in the first place, especially considering that the majority of Agile-driven sprints last for up to only several weeks,” Urbanovich said.
Although some may hope it were this easy, testers can’t just spawn automated tests and sit back like Paley’s watchmaker gods. The tests need to be guided and nurtured.
“The number one challenge with automated testing is making sure you have a test for all possibilities. Covering all possibilities is an ongoing process, but executives especially hear that you have automated testing now and forget that it only covers what you actually are testing and not all possibilities,” said David Garthe, founder of Gravyware, a social media management tool. “As your application is a living thing, so are the tests that are for it. You need to factor in maintenance costs and expectations within your budget.”
Also, just because a test worked last sprint, doesn’t mean it will work as expected this sprint, Garthe added. As applications change, testers have to make sure that the automated tests cover the new process correctly as well.
Garthe said that he has had a great experience using Selenium, referring to it as the “gold standard” with regard to automated testing. It has the largest group of developers that can step in and work on a new project.
“We’ve used other applications for testing, and they work fine for a small application, but if there’s a learning curve, they all fall short somewhere,” Garthe said. “Selenium will allow your team to jump right in and there are so many examples already written that you can shortcut the test creation time.”
And, there are many other choices to weave through to start the automated testing process.
“When you think about test automation, first of all you have to choose the framework. What language should it be? Do you want to have frontend or backend tests, or both? Do you want to use gherkin in your tests?,” STX Next’s Gatkowska said. “Then of course you need to have your favorite code editor, and it would be annoying to run the tests only on your local machine, so it’s important to configure jobs in the CI/CD tool. In the end, it’s good to see valuable output in a reporting tool.”
Choosing the right tool and automated testing framework, though, might pose a challenge for some because different tools excel at different conditions, according to Robert Warner, Head of Marketing at VirtualValley, a UK-based virtual assistant company.
“Testing product vendors overstate their goods’ abilities. Many vendors believe they have a
secret sauce for automation, but this produces misunderstandings and confusion. Many of us don’t conduct enough study before buying commercial tools, that’s why we buy them without proper evaluation,” Warner said. “Choosing a test tool is like marrying, in my opinion. Incompatible marriages tend to fail. Without a good test tool, test automation will fail.”
In the next three years 52% of companies that responded to the Forrester report said they would consider using AI for integrating complex test suites.
The use of AI for integrated testing provides both better (not necessarily more) testing coverage and the ability to support agile product development and release, according to the Forrester report.
Companies are also looking to add AI for integrating complex test suites, an area of test automation that is severely lacking, with only 16% of companies using it today.
A1qa’s Urbanovich explained that one of the best ways to cope with boosted software complexity and tight deadlines is to apply a risk-based approach. For that, AI is indispensable. Apart from removing redundant test cases, generating self-healing scripts, and predicting defects, it streamlines priority-setting.
“In comparison with the previous year, the number of IT leaders leveraging AI for test prioritization has risen to 43%. Why so?” Urbanovich continued, alluding to the World Quality Report 2021-2022. “When you prioritize automated tests, you put customer needs FIRST because you care about the features that end users apply the most. Another vivid gain is that software teams can organize a more structured and thoughtful QA strategy. Identifying risks makes it easier to define the scope and execution sequence.”
Most of the time, companies are looking to implement AI in testing to leverage the speed improvements and increased scope of testing, according to Kevin Surace, CTO at Appvance, an AI-driven software testing provider.
“You can’t write a script in 10 minutes, maybe one if you’re a Selenium master. Okay, the machine can write 5,000 in 10 minutes. And yes, they’re valid. And yes, they cover your use cases that you care about. And yes, they have 1,000s of validations, whatever you want to do. And all you did was spend one time teaching it your application, no different than walking into a room of 100 manual testers that you just hired, and you’re teaching them the application: do this, don’t do this, this is the outcome, these are the outcomes we want,” Surace said. “That’s what I’ve done, I got 100 little robots or however many we need that need to be taught what to do and what not to do, but mostly what not to do.”
Appvance’s Surace said that the overall place of where testing needs to go is to be completely hands off from humans.
“If you just step back and say what’s going on in this industry, I need a 4,000 times productivity improvement in order to find essentially all the bugs that the CEO wants me to find, which is find all the bugs before users do,” Surace said. “Well, if you’ve got to increase productivity 4,000 times you cannot have people involved in the creation of very many use cases, or certainly not the maintenance of them. That has to come off the table just like you can’t put people in a spaceship and tell them to drive it, there’s too much that has to be done to control it.”
Humans are still good at prioritizing which bugs to tackle based on what the business goals are
because only humans can really look at something and say, well, we’ll just leave it, it’s okay, we’re not gonna deal with it or say this is really critical and push it to the developers side to fix it before release, Surace continued.
“A number of people are all excited about using AI and machine learning to prioritize which tests you should run, and that entire concept is wrong. The entire concept should be, I don’t care what you change in application, and I don’t understand your source code enough to know the impacts and on every particular outcome. Instead, I should be able to create 10,000 scripts and run them in the next hour, and give you the results across the entire application,” Surace said. “Job one, two, and three of QA is to make sure that you found the bugs before your users do. That’s it, then you can decide what to do with them. Every time a user finds a bug, I can certain you it’s in something you didn’t test or you chose to let the bug out. So when you think about it, that way users find bugs and the things we didn’t test. So what do we need to do? We need to test a lot more, not less.”
A challenge with AI is that it is a foreign concept to QA people so teaching them how to train AI is a whole different field, according to Surace.
First off, many people on the QA team are scared of AI, Surace continued, because they see themselves as QA people but really have the skillset of a Selenium tester that writes Selenium scripts and tests them. Now, that has been taken away similar to how RPA disrupted many industries such as customer support and insurance claims processing.
The second challenge is that they’re not trained in it.
“So one problem that we see that we have is you explain how the algorithms work?,” Surace said. “In AI, one of the challenges we have in QA and across the AI industry is how do we make people comfortable that here’s a machine that they may not ever be able to understand. It’s beyond their skillset to actually understand the algorithms at work here and why they work and how neural networks work so they now have to trust that the machine will get them from point A to point B, just like we trust the car gets from point A to point B.”
However, there are some areas of testing in which AI is not as applicable, for example, in a form-based application where there is nothing else for the application to do than to guide you through the form such as in a financial services application.
“There’s nothing else to do with an AI that can add much value because one script that’s data-driven already handles the one use case that you care about. There are no more use cases. So AI is used to augment your use cases, but if you only have one, you should write it. But, that’s few and far between and most applications have hundreds of 1,000s of use cases perhaps or 1,000s of possible combinatorial use cases,” Surace said.
According to Eli Lopian, CEO at Typemock, a provider of unit testing tools to developers worldwide, QA teams are still very effective at handling UI testing because the UI can often change without the behavior changing behind the scenes.
“The QA teams are really good at doing that because they have a feel for the UI, how easy it is for the end user to use that code, and they can see the thing that is more of a product point of view and less of doesn’t work or does it not work point of view, which now is really it’s really essential if you want to an application to really succeed,” Lopian said.
Dan Belcher, the co-founder at mabl, said that there is still plenty of room for a human in the loop when it comes to AI-driven testing.
“So far, what we’re doing is supercharging quality engineers so human is certainly in the loop, It’s eliminating repetitive tasks where their intellect isn’t adding as much value and doing things that require high speed, because when you’re deploying every few minutes, you can’t really rely on a human to be involved in that in that loop of executing tests. And so what we’re empowering them to do is to focus on higher level concerns, like do I have the right test coverage? Are the things that we’re seeing good or bad for the users?,” Belcher said.
One area where AI/ML in testing excels at is in unit testing on legacy code, according to Typemock’s Lopian.
“Software groups often have this legacy code which could be a piece of code that maybe they didn’t do a unit test beforehand, or there was some kind of crisis, and they had to do it quickly, and they didn’t do the test. So you had this little piece of code that doesn’t have any unit tests. And that grows,” Lopian said. “Even though it’s a difficult piece of code, it wasn’t built for testability in mind, we have the technology to both write those tests for those kinds of code and to generate them in an automatic manner using the ML.”
The AI/ML can then make sure that the code is running in a clean and modernized way. The tests can refactor the code to work in a secure manner, Lopian added.
AI-driven testing is also beneficial for UI testing because the testers don’t have to explicitly design the way that you reference things in the UI, you can let the AI figure that out, according to mabl’s Belcher. And then when the UI changes, typical test automation results in a lot of failures, whereas the AI can learn and Excellerate the tests automatically, resulting in 85-90% reduction in the amount of time engineers spend creating and maintaining tests with AI.
In the UI testing space, AI can be used for auto healing, intelligent timing, detecting visual changes automatically in the UI, and detecting anomalies and performance.
According to Belcher, AI can be the vital component in creating a more holistic approach to end-to-end testing.
“We’ve all known that the answer to improving quality was to bring together the insights that you get when you think about all facets of quality, whether that’s functional or performance, or accessibility, or UX. And, and to think about that holistically, whether it’s API or web or mobile. And so the area that will see the most innovation is when you can start to answer questions like, based on my UI tests, what API tests should I have? And how do they relate? So when the UI test fails? Was it an API issue? And then, when a functional test fails, did anything change from the user experience that could be related to that?,” Belcher said. “And so the key is to do this is we have to bring kind of all of the kind of end-to-end testing together and all the data that’s produced, and then you can really layer in some incredibly innovative intelligence, once you have all of that data, and you can correlate it and make predictions based on that.”
The MarketWatch News Department was not involved in the creation of this content.
Jul 28, 2022 (Heraldkeepers) -- The Global Integrated Playout Automation market research report includes profiles of more than the top major competitors in addition to global and regional statistics that can be used to assess market potential. For company leaders in particular, the worldwide Integrated Playout Automation market research offers a basic evaluation of information and strategies.
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The report has been compiled through extensive primary research (through interviews, surveys, and observations of seasoned analysts) and secondary research (which entails reputable paid sources, trade journals, and industry body databases). The report also features a complete qualitative and quantitative assessment by analyzing data gathered from industry analysts and market participants across key points in the industry's value chain.
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Never before have clinical researchers had more options at their fingertips when designing a study. As technology leaps ahead, companies are sending more notifications, collecting larger amounts of data, and adding more apps, wearables, and ePROs to studies. But researchers need to be considerate about the fact that many potential participants are dealing with burnout, and uncertainty after more than two years of pandemic life.
During the pandemic, about four in ten adults in the U.S. have reported symptoms of anxiety or depressive disorder, which is a significant rise from the one in ten adults who reported these symptoms from January to June 2019. And for patients suffering from new health issues or struggling with existing conditions, the pandemic has caused delayed diagnoses, postponed surgeries, and more uncertainty.
All said, many potential participants are tired and stressed. Some may even be wary of adding another commitment by joining a clinical trial. Therefore, research studies need to prioritize simplicity, authenticity, and practicality to earn patient trust for better enrollment and retention.
Human-centric recruitment and enrollment
Informed consent shouldn’t read like a Ph.D. thesis. It should be simple, most likely in the form of eConsent using a phone, tablet, or computer. This remote approach lowers enrollment barriers by reducing travel costs, eliminating possible exposure to Covid-19 risks, and allowing greater participant flexibility with their schedule. It increases comprehension and retention of information since complex procedures or study treatments can be shown visually and explained out loud. It allows study participants to choose their preferred method of learning and functionalities can be included to help vulnerable populations (e.g., visually impaired, pediatrics).
eConsent also simplifies recruitment efforts by reaching and engaging with patients on the platforms they use. Social media platforms such as TikTok, Snapchat, and Instagram have user-friendly advertising interfaces that position recruitment materials in front of a greater proportion of eligible participants. Clinical researchers can streamline their search efforts to accelerate efforts to identify the right participants.
A decentralized approach to recruitment can reach underserved minority populations who are underrepresented in clinical research. This supports hiring remote study staff who are representative of the patient population or who have cultural competency expertise in communicating scientific concepts to populations who have experienced deprivation of autonomy. Using video chat, staff members can guide participants through the informed consent process. eConsent offers more engagement with the consenting process and can offer participants empowerment, ownership, and autonomy—often a significant step in overcoming hesitation in joining a study.
Technology consolidation for improved patient data
Another key to streamlined, patient-centric trials is automation. In particular, APIs can overcome the need for patients to juggle multiple apps. Researchers should explore intuitive software that offers excellent UX and helpful features. This has previously been a challenge since the regulatory and development background created a very commoditized environment with research tools that were all more alike than different. But now, innovative companies are offering new solutions—and researchers should select the optimal research platform that offers the best patient experience while supporting quality clinical research.
Another way to leverage technology to Excellerate participant experience is direct-to-patient devices. Sending participants a Bluetooth-connected medical device shipped with a phone preloaded with an appropriate telehealth product for easy visits is one idea. This approach also helps alleviate work for the study site, as sending participants pre-configured devices (rather than BYOD models) decreases help desk staffing needs. Ideally, participants should use the shipped device or phone for various tasks within the study, such as reporting outcomes and communicating with researchers.
Harnessing the power of RWD
Real-world data will play an even larger role in clinical trials in the near future— to the benefit of all participants. If a researcher can show that a measurement (e.g. heart rate) can infer the same thing as a more complicated measurement (e.g. electrocardiogram) this paves the way for further study design simplification. For example, if a study involves a chronic condition the participant must visit a physician to manage, such as blood pressure, then the real-world data from the physician’s office could be used for the study rather than taking the same measurement twice. In other cases, participants can use a wearable to collect and transmit data to the study site in real-time. This kind of efficiency can boost both enrollment and retention rates in studies and allows for more data to be acquired consistently.
Let’s push for simple, authentic, and practical studies – and give participants a break! Let’s meet people where they are and put their needs first. By doing so, we’ll recruit more participants and hopefully keep them engaged and hold on to them throughout the entire study. Let’s work together to develop new cures for a better tomorrow.
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They’re not airplanes. They’re not helicopters. What skills will pilots need to fly eVTOLs?
WOBURN, Mass., Aug. 08, 2022 (GLOBE NEWSWIRE) -- Electric Vertical Takeoff and Landing (eVTOL) aircraft will soon transform the skies above. But who will fly these new and novel vehicles, what skills will they need, and how will they be trained to operate platforms that feature new levels of automation?
To help answer those questions, Aptima, Inc., has been awarded a contract by the US Air Force to assist the Air Education and Training Command’s Detachment 62 (Det 62) to determine the pilot proficiencies and training needed for eVTOL operators. Det 62 supports the AFWERX Agility Prime program and is charged with developing the curriculum for eVTOL pilots and driving certification standards for an emerging market that is expected to transform civil air mobility and select military missions.
Using simulators of various eVTOL prototypes, Aptima will assess and identify the pilot competencies needed for proficient flight, including how pilots learn and perform on eVTOL platforms that have varying levels of automation. “The learnability study will help us not only understand the baseline pilot skills and competencies needed for proficient eVTOL flight, but also the impact of automation on pilot performance,” said Samantha Emerson, Training, Learning & Readiness Scientist at Aptima, and project manager for the contract. “Both experienced and novice pilots will bring unique sets of skills and capacities based on their experiences and abilities. We’ll assess how these differences affect performance in aircraft with various levels of automation”.
EVTOL prototypes range from having moderate levels of automation, that still fly like typical aircraft, to higher orders of automation, thus raising questions about the skills and training required to fly them.
In more heavily automated platforms, where pilots mostly control flight settings rather than the aircraft itself, preliminary research suggests experienced pilots tend to have more difficulty adjusting to automation than novice pilots. This is why we will look to see if experienced pilots tend to “overcontrol” of the aircraft.
“Even though a more experienced pilot may possess greater ability in controlling aircraft, not all those skills may be useful or even desired in platforms with more automation and augmentation. In fact, it may require an ‘unlearning’ and re-training of behaviors to prevent interference or conflict with automated operations,” Emerson added.
Aptima, a leader in human-machine teaming and training, will help evaluate how automation affects pilots in different eVTOLs, which existing skills will be transferable, and what new skills will require training.
Applying AFRL Technologies to eVTOL Training
To assess pilot learning and performance, Aptima will use technologies and techniques it has developed with the Air Force Research Laboratory (AFRL) over the past 15 years to measure, analyze, understand, and optimize Airman performance. These include the Performance Evaluation Training System, or PETS, which harvests data from simulators to provide objective, system-based measures, and SPOTLITE, Aptima’s handheld tool used by subject matter experts to provide observer-based measures of performance.
“Together, the objective measures from simulators and the subjective measures from what experts recognize as “good flying” produce a more complete picture of pilot learning and performance.” These findings will help Det 62 test and evaluate its eVTOL training assumptions. The findings could also influence how aircraft manufacturers design platforms in the future as we discover which aspects of flight benefit most from improved automation.
This work is funded by the U.S. Air Force via the General Services Administration under Solicitation Number 47QFLA22Q0077 / GSA ID# 47QFLA19K0069-0006 entitled, “AETC Det 62 eVTOL: Agility Prime Training Assessment Technologies for Electric Vertical Takeoff and Landing (eVTOL) Vehicles,” funded by Col Don “Stryker” Haley and Dr. Stephen B. Ellis, whom the authors wish to thank for their support.
CONTACT: Media Contact: Joel Greenberg DCPR firstname.lastname@example.org 202-363-1065 | 202-669-3639 cell
Boeing (Chicago, Ill., U.S.) is strengthening its partnership with Japan by opening a new Boeing Research and Technology (BR&T) center, according to an Aug. 1 announcement. The facility will focus on sustainability and support a newly expanded cooperation agreement with Japan’s Ministry of Economy, Trade and Industry (METI).
Boeing and METI have agreed to broaden the 2019 Cooperation Agreement so that it includes a focus on sustainable aviation fuels (SAF), electric and hydrogen powertrain technologies, and future flight concepts that will promote zero climate impact aviation. This is in addition to exploring electric and hybrid-electric propulsion, batteries and composites manufacturing that will enable new forms of urban mobility.
“We are excited to open our latest global research and technology center here in Japan,” Greg Hyslop, Boeing chief engineer and executive vice president of Engineering, Test and Technology, says. “Working with partners like METI, the new center will expand upon Boeing-wide initiatives in sustainable fuels and electrification, and explore the intersection of digitization, automation and high-performance aerospace composites for greater sustainability in our future products and production systems.”
The BR&T — Japan Research Center will be located in Nagoya, which is already home to many of Boeing’s major industrial partners and suppliers. The facility will further expand Boeing’s research and development (R&D) footprint in the region, which includes centers in Australia, China and Korea.
Boeing is fully committed to supporting Japan’s SAF industry and has been accepted as the latest member of ACT FOR SKY, a voluntary organization of 16 companies that works to commercialize, promote and expand the use of SAF produced in Japan. It was founded by Japan-based Boeing airline customers All Nippon Airways (ANA) and Japan Airlines (JAL), along with global engineering company JGC Holdings Corp. and biofuel producer Revo International.
In addition to becoming partners in ACT FOR SKY, Boeing has a long history of innovating with ANA and JAL on sustainable aviation, which includes pioneering SAF-powered flights and launching the 787 Dreamliner. Recently, the aerospace company has signed an agreement with ANA and JAL to work together to study advanced sustainable technologies, including electric, hybrid, hydrogen and other novel propulsion systems in an endeavor to reduce the carbon footprint of aircraft.
“To ensure the enormous societal benefits of aviation remain available for generations to come, we must continue to partner with capable innovators and leaders to support the industry’s commitment to net-zero carbon emissions by 2050,” Boeing Chief Sustainability Officer Chris Raymond adds. “We are humbled to join ACT FOR SKY and collaborate with other members to share global best practices and help with the scale-up and demand of SAF in Japan. And we are honored to open the Japan Research Center and expand our work with airline customers ANA and JAL on advanced technologies to realize zero climate impact aviation.”
When buying a home, it’s important to get the best deal possible. Working with a real estate agent will help you do just that. Agents have years of experience and know the market inside and out. They can help you find the right home and negotiate a fair price. Plus, agents are familiar with the paperwork and procedures involved in buying a home. This can save you time and money in the long run.
Recently, research has shown that those who worked with a real estate agent were able to save on their home purchase. The study found that those who worked with an agent were able to get a better deal on their home, as well as reduce the amount of time it took to find a home. The study showed that working with a real estate agent can help you avoid costly mistakes. By having an expert on your side, you can be sure that you are making the best decisions for your property and getting the best deals possible. Agents have extensive knowledge of the market, and they can help you navigate through complicated transactions with ease. They can also help you find the right property for your needs and budget.
A real estate agent can help you to negotiate the best possible price for your home. By providing expert advice and market knowledge, as well as being your advocate during the negotiation process, a real estate agent can help you get the best deal on your home purchase. Real estate agents typically receive commissions from the seller, so they have a vested interest in getting the seller the best possible price for their home. Because of this, agents will often recommend that their clients list their home at a higher price than what they may be willing to accept, in the hopes that they will receive an offer closer to their desired price. While this may not always result in the best deal for the seller, it is important to remember that agents are working in their best interests.
A real estate agent who specializes in your desired area can help you save time by doing all of the necessary research for you. They will have a comprehensive understanding of the current market conditions, latest sales data, and neighborhood information. This knowledge will allow them to quickly identify potential homes that fit your criteria and schedule viewings for you. Additionally, they can provide expert advice on pricing, negotiations, and the home buying process.
Advice: A real estate agent can provide you with expert advice on what to look for in your dream home.
When looking for a new home, it is important to have expert advice. A real estate agent can provide you with all the information you need to find your dream home. They can tell you what to look for in terms of location, size, and features. A real estate agent can help you negotiate a good price for a property and guide you through the buying process. Real estate agents have knowledge of the market and can help you find the right property for your needs. They can also assist you in the negotiation process, and provide advice on home inspections, financing, and title searches.
A real estate agent typically has access to many resources that a potential home buyer may not have. These resources can include but are not limited to: information about latest sales in the area, a list of reputable contractors, and a network of professionals who can help with the buying or selling process. By leveraging these resources, a real estate agent is often able to provide an unmatched level of service and support to their clients.
Agents have expertise in all aspects of buying and selling homes. They are experts in the real estate market, and know how to get the best price for their clients. They also have knowledge of the legal process involved in a real estate transaction, and can guide their clients through it. Property agents are experts in home decoration and staging. This can help a home sell faster by making it more appealing to potential buyers. Property agents often have a lot of experience with different types of décor and know how to make a home look its best. They may also be able to recommend furniture, paint colours, and other changes that can help a home sell quickly.
When working with a real estate agent, you are tapping into that professional’s years of training and experience in order to have someone looking out for your best interests. The agent is there to help you navigate the complicated process of buying or selling a home, from finding the right property to getting the best possible deal. Real estate agents can provide valuable insights into the local market due to their understanding of the area and their connections with other industry professionals. By talking with a real estate agent, homebuyers can gain a better understanding of what is available in the market and learn about any latest sales that may have an impact on the asking price of a home. Additionally, real estate agents can provide guidance on preparing a home for sale and negotiating a purchase agreement.
In conclusion, working with a real estate agent is the best way to get the best deal on your dream home. They have years of experience and knowledge in the industry, which means they can help you navigate through the process and find the right property for you. Not to mention, they can also help you negotiate a better price. So if you’re looking to buy a home, be sure to work with a real estate agent.
By Christos Makridis
Remote learning might’ve gotten a bad rap during the pandemic, but education is about to move into the metaverse. And, experts say, it will be better than in-person instruction.
The costs of higher education have been growing, racking up more debt for students, and the post-college economic returns have been flattening. But learning has never been more important, especially in an era of rapid technological and growing automation.
Unfortunately, traditional higher educational institutions are not equipped to handle the scale of the challenge. “The class of institutions we need going forward isn’t fully fleshed out yet,” said Michael Crow, president of Arizona State University. “Redesigning research universities will require innovative institutional models that creatively use learning technologies to cooperate rather than compete with other universities, and forming strategic partnerships that include business and industry and government agencies,” Crow said.
But in the interim, new educational technology companies are rising to the challenge. Following a $700 million valuation with over four million people accessing its content, Scaler just announced that it is launching programs in the United States to build learning communities designed for the future of work. “Higher education’s learning environment with physical buildings is not designed to scale,” said Abhimanyu Saxena, co-founder of Scaler.
But designing content that can scale is only one piece of the puzzle. “It is a necessary part, but it is rarely the full picture,” said Saxenda. Researchers have long recognized that a large portion of the economic returns to a college education come from the social and network effects of peers, and these effects can be persistent over time. Scaler uses interactive learning with live lectures to incentivize engagement among their students, coupled with community hubs where students can work and live together for the duration of the roughly one-year program. Students are also matched with mentors who share similar backgrounds but are slightly more advanced in their fields.
Traditional higher educational institutions recruit faculty based on their publication within academic journals. However, all instructors in Scaler are leading practitioners at some of the largest and most profitable technology companies. “It doesn’t work… that is why we have such a scarcity of engineers,” Saxena said. The instructors are practitioners who have a pulse on the latest techniques and demands of the marketplace, providing timely instruction to students.
Software development, cloud technologies, proactive security, information technology automation, and artificial intelligence and machine learning are five of the most disruptive skills demanded by the technology sector, according to a 2020 report by Emsi Burning Glass. “Since our 2020 study, the trends we observed have accelerated… the average job has seen 37% of its top skills replaced just over the past five years but the pace of change has been much faster since the start of the pandemic,” said Matt Sigelman, president of the Burning Glass Institute.
But the skill requirements are increasing across the board. “It’s not only a matter of technology change but also a phenomenon of skills intersecting jobs from across domains. Overall, four secular trends are leading this disruption: digital skills in non-digital roles, soft skills in digital roles, the growing demand for visual communication, and the integration of social media skills into a broad range of occupations,” Sigelman said.
These “softer skills” are harder to teach through purely online material—at least some in-person interaction is required. Less than half of the U.S. population report that they have a “great deal” or “quite a lot” of confidence in higher education, according to a 2018 survey by Gallup. Moreover, at least some of these attitudes are driven by the growing cost of higher education: over half of unenrolled adults report the cost of a college degree as a very important reason they have not continued their education, according to a 2022 report by Gallup.
But cost is not the only part of the equation. Universities are some of the “least engaged workplaces in the world,” and only 34% of university faculty are engaged at their jobs, according to Gallup.
Enter a metaverse-based upgrade to traditional higher education: merging augmented and virtual reality with the expansion of distributed ledger technologies provides new ways for students and instructors to interact with each other. Edverse announced a partnership with Polygon MATIC , an Ether ETH eum scaling platform, to build a metaverse dedicated exclusively to education. The first-of-its-kind virtual education firm aims to “decentralize and democratize education” using blockchain technology.
“We envision an education landscape where we completely re-write the rules and definitions of the four key stakeholders – educators, students, creators and the promoters of education,” said Gautam Arjun, co-founder & CEO of Edverse. Redefining the way that people interact with each other has the potential to unlock new levels of engagement and understanding.
Whether it be educators or students, none seem to be engaged in the entire process… with a metaverse experience we are fostering a playful, yet purposeful, education space – the one that accelerates intelligence and advances the human race ahead, ensuring the students achieve and grasp more in the time the dedicate to educating themselves, while ensuring that the journey is enjoyable and enriching,” said Alok Patni, co-founder and CFO CFO of Edverse.
Since the metaverse is scalable and allows for the incorporation of both “learn to earn” and “wear to earn” approaches to tokenization, there is the potential to flip the switch on the traditional model of funding higher education, which relies on student tuition and donors. There is also the potential to “self-sponsor your entire higher education, without even paying a penny,” Patni said.
Some traditional institutions of higher education are also beginning to pilot metaverse initiatives with virtual reality, such as Arizona State University through its Dreamscape Immersive and University of Nicosia’s Open Metaverse Initiative.
To be sure, the future of higher education requires scalable solutions that leverage technology as a tool, rather than an end in and of itself. Virtual and metaverse spaces are beginning to revolutionize the educational landscape — and traditional schools may soon have to play catch-up.
STAMFORD, Conn.--(BUSINESS WIRE)--Jul 26, 2022--
Information Services Group ( ISG ) (Nasdaq: III ), a leading global technology research and advisory firm, has launched a research study examining human capital management (HCM) platforms that enterprises use to optimize the human side of their business for competitive advantage.
The study results will be published in a comprehensive ISG Provider Lens™ report, called HCM Technology Platforms 2022, scheduled to be released in December. The report will cover companies offering technology solutions for core HCM functions, talent management and recruiting.
Enterprise buyers will be able to use information from the report to evaluate their current vendor relationships, potential new engagements and available offerings, while ISG advisors use the information to recommend providers to the firm’s buy-side clients.
With the current tight market for skilled resources and evolving expectations around work, human capital management is increasingly vital to achieving strategic goals and competitive advantage. HCM technology solutions can help organizations become more agile, train or retrain workers and offer a superior employee experience. They can also maximize the productivity of the workforce, which usually makes up the largest cost component of an operating budget.
“Enterprises need effective people management more than ever,” said Jan Erik Aase, partner and global leader, ISG Provider Lens Research. “HCM technology platforms support the decisions of people managers to attract and retain great employees, resulting in significant value creation.”
ISG has distributed surveys to approximately 50 HCM platform providers. Working in collaboration with ISG’s global advisors, the research team will produce three quadrants representing the digital services and products the typical enterprise is buying, based on ISG’s experience working with its clients. The three quadrants are:
A report produced from the study will cover the global HCM technology platform market and examine available products and services. ISG analysts Saskia Goods, Stacey Cadigan, Steve Goldberg and Akshay S Hiremath will serve as authors of the report.
An archetype report will also be published as part of this study. This report, unique to ISG, is the study of typical buyer types of HCM services as observed by ISG advisors.
A list of identified providers and vendors and further details on the study are available in this digital brochure. Companies not listed as HCM technology providers can contact ISG and ask to be included in the study.
All 2022 ISG Provider Lens™ evaluations now feature new and expanded customer experience (CX) data that measures real enterprise experience with specific provider services and solutions, based on ISG’s continuous CX research. Enterprise customers wishing to share their experience about a specific provider or vendor are encouraged to register here to receive a personalized survey URL. Participants will receive a copy of this report in return for their feedback.
About ISG Provider Lens™ Research
The ISG Provider Lens™ Quadrant research series is the only service provider evaluation of its kind to combine empirical, data-driven research and market analysis with the real-world experience and observations of ISG’s global advisory team. Enterprises will find a wealth of detailed data and market analysis to help guide their selection of appropriate sourcing partners, while ISG advisors use the reports to validate their own market knowledge and make recommendations to ISG’s enterprise clients. The research currently covers providers offering their services globally, across Europe, as well as in the U.S., Canada, Brazil, the U.K., France, Benelux, Germany, Switzerland, the Nordics, Australia and Singapore/Malaysia, with additional markets to be added in the future. For more information about ISG Provider Lens research, please visit this webpage.
A companion research series, the ISG Provider Lens Archetype reports, offer a first-of-its-kind evaluation of providers from the perspective of specific buyer types.
ISG (Information Services Group) (Nasdaq: III ) is a leading global technology research and advisory firm. A trusted business partner to more than 800 clients, including more than 75 of the world’s top 100 enterprises, ISG is committed to helping corporations, public sector organizations, and service and technology providers achieve operational excellence and faster growth. The firm specializes in digital transformation services, including automation, cloud and data analytics; sourcing advisory; managed governance and risk services; network carrier services; strategy and operations design; change management; market intelligence and technology research and analysis. Founded in 2006, and based in Stamford, Conn., ISG employs more than 1,300 digital-ready professionals operating in more than 20 countries—a global team known for its innovative thinking, market influence, deep industry and technology expertise, and world-class research and analytical capabilities based on the industry’s most comprehensive marketplace data. For more information, visit www.isg-one.com.
View source version on businesswire.com:https://www.businesswire.com/news/home/20220726005893/en/
Will Thoretz, ISG
+1 203 517 3119
email@example.comJulianna Sheridan, Matter Communications for ISG
KEYWORD: CONNECTICUT UNITED STATES NORTH AMERICA
INDUSTRY KEYWORD: CONSULTING TECHNOLOGY PROFESSIONAL SERVICES SECURITY OTHER TECHNOLOGY DATA ANALYTICS SOFTWARE NETWORKS INTERNET MOBILE/WIRELESS HUMAN RESOURCES
SOURCE: Information Services Group, Inc.
Copyright Business Wire 2022.
PUB: 07/26/2022 12:01 PM/DISC: 07/26/2022 12:02 PM
ORONO — A new lab to study how the latest artificial intelligence tools and techniques could bolster advanced manufacturing in northern New England will be launched with a $6 million award from the National Science Foundation to the University of Maine.
UMaine will collaborate with the University of New Hampshire, University of Vermont, Southern Maine Community College, Dartmouth College and Vermont Technical College to create the Northeast Integrated Intelligent Manufacturing Lab, funded by a Research Infrastructure Improvement Track-2 Focused EPSCoR Collaboration award.
The lab, based at UMaine, will be used to investigate new technologies to increase advanced manufacturing efficiency, scalability, capability and safety by incorporating AI, robotics and 3D metal printing.
The research team behind the lab will explore the efficacy of various AI techniques for advanced manufacturing, including interpretable machine learning models, physics-guided and multitask learning, and unsupervised domain adaptation. In collaboration with industry partners, researchers plan to develop new AI models for advanced manufacturing that are more interpretable and adaptable, AI-guided design for additive metal manufacturing that reduces unnecessary trial-and-error, self-aware computer numerical control machines for subtractive manufacturing and industrial robots to support cellular manufacturing.
Through these studies, the lab and its scientists aim to help northern New England manufacturers evolve their businesses by providing research, education and workforce development. For example, researchers could devise learning techniques that factory workers could use to teach their robots new skills.
“This is an example of the interdisciplinary innovation and partnership that an R1 research university provides,” says UMaine President Joan Ferrini-Mundy. “UMaine has long led advanced manufacturing research and development that helps to impact economic development. This award builds on those efforts to support a manufacturing industry in transition for the future and continues UMaine’s nationally recognized leadership in innovation.”
Yifeng Zhu, UMaine Libbey Professor of Electrical and Computer Engineering, is leading the project alongside co-principal investigators Chaofan Chen, UMaine assistant professor of computer science; Brett Ellis, UMaine associate professor of mechanical engineering technology; Se Young Yoon, UNH associate professor of electrical and computer engineering; and Nick Cheney, UVM assistant professor of computer science.
Other UMaine researchers involved in the project include Liping Yu, assistant professor of physics; Vikas Dhiman, assistant professor of electrical and computer engineering; John Belding, director of the Advanced Manufacturing Center; Bruce Segee, professor of electrical and computer engineering; Todd Gabe, professor of economics; Andrew Crawley, assistant professor of regional economic development; Rebecca Colannino, director of Upward Bound; and Matthew Dube, an aspirations instructor and research mentor for UMaine’s Upward Bound and an assistant professor of computer information systems appointed at the University of Maine at Augusta.
“The brilliant faculty and students at the University of Maine are conducting cutting-edge research and making promising discoveries in a wide variety of fields,” said Sens. Susan Collins and Angus King in a joint statement. “This funding will help UMaine continue to build on its groundbreaking achievements that are powering our economy today and into the future. We welcome this investment that will support Maine businesses, help create good jobs in our state, and solidify UMaine’s leadership in advanced manufacturing research.”
Infusing artificial intelligence into manufacturing can bring a lot of benefits to business, says Zhu. “We will actively work with local manufacturers to build prototype test beds to evaluate and deploy our AI-powered technologies.”
Maine industry is extremely eager to be able to use advanced Industry 4.0 technologies to Excellerate manufacturing productivity, says Belding. “All of the work AMC is completing with Maine companies involve automation, robotics, multi-axis machining, laser machining and metal additive manufacturing. Having AI as another tool in the toolbox allows us to cover even more of Maine industry needs,” he says.
John Murray, director of business development for Progress Engineering, says his Manchester, Maine-based company “is excited at the prospect of working with the University of Maine on using AI programs on several known applications in the forest products industry here in our state.
“We congratulate UMaine on receiving this AI development grant,” Murray says. “Progress Engineering envisions this being a huge benefit to the wood products industry as it applies to development of cost-effective, automatic wood grading systems for our smaller companies.”
“Yale Cordage needs to continuously ensure the top quality we are known for in each rope we produce,” says Glenn Jameson, director of design and development for Yale Cordage in Saco, Maine. “We would like to make this inspection process more robust. We believe advanced technologies such as AI and cameras can help us achieve this goal to add leading-edge production and jobs to our growth in the state of Maine.”
NIIM will utilize research infrastructure, community partnerships, faculty expertise and other existing investments across the participating institutions to support the project, including the UMaine Advanced Research Computing, Security, and Information Management (ARCSIM). The team at ARCSIM will work with Segee to launch federated supercomputing resources in Maine, New Hampshire and Vermont.
“For this project, UMaine ARCSIM is enabling senior research personnel by ensuring adequate access to high-performance computational resources,” says Shane Moeykens, director of ARCSIM and Maine EPSCoR. ARCSIM supports the research computing needs of the university research community and its collaborators, and is associated with Coordinated Operating Research Entities (CORE), which is overseen by the Office of the Vice President for Research and Dean of the Graduate School.
To ensure the lab provides tools and knowledge that are relevant to the priorities of the northern New England manufacturing sector, the team will collaborate with manufacturing extension partnership programs (MEPs) in the three states, an industrial advisory board, industry partners, and the U.S. Economic Development Administration University Center for Economic Development.
Funding from the award will allow the team to recruit a postdoctoral associate and other professionals, graduate and undergraduate student researchers; and purchase a collaborative robot, 3D metal printing and other advanced manufacturing materials.
The lab and the research it generates also will yield new educational materials for UMaine’s Upward Bound program, which provides opportunities to low-income high school students that help prepare them for college; UNH’s Northeast Passage, which supports disabled students and workers at community and technical colleges; and community colleges across the three northern New England states.
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