The COVID-19 pandemic forced a shift to remote learning overnight for most higher-education students, starting in the spring of 2020. To complement video lectures and engage students in the virtual classroom, educators adopted technologies that enabled more interactivity and hybrid models of online and in-person activities. These tools changed learning, teaching, and assessment in ways that may persist after the pandemic. Investors have taken note. Edtech start-ups raised record amounts of venture capital in 2020 and 2021, and market valuations for bigger players soared.

A study conducted by McKinsey in 2021 found that to engage most effectively with students, higher-education institutions can focus on eight dimensionsof the learning experience. In this article, we describe the findings of a study of the learning technologies that can enable aspects of several of those eight dimensions (see sidebar Eight dimensions of the online learning experience).

In November 2021, McKinsey surveyed 600 faculty members and 800 students from public and private nonprofit colleges and universities in the United States, including minority-serving institutions, about the use and impact of eight different classroom learning technologies (Exhibit 1). (For more on the learning technologies analyzed in this research, see sidebar Descriptions of the eight learning technologies.) To supplement the survey, we interviewed industry experts and higher-education professionals who make decisions about classroom technology use. We discovered which learning tools and approaches have seen the highest uptake, how students and educators view them, the barriers to higher adoption, how institutions have successfully adopted innovative technologies, and the notable impacts on learning (for details about our methodology, see sidebar About the research).

Exhibit 1

Survey respondents reported a 19 percent average increase in overall use of these learning technologies since the start of the COVID-19 pandemic. Technologies that enable connectivity and community building, such as social mediainspired discussion platforms and virtual study groups, saw the biggest uptick in use49 percentfollowed by group work tools, which grew by 29 percent (Exhibit 2). These technologies likely fill the void left by the lack of in-person experiences more effectively than individual-focused learning tools such as augmented reality and virtual reality (AR/VR). Classroom interaction technologies such as real-time chatting, polling, and breakout room discussions were the most widely used tools before the pandemic and remain so; 67 percent of survey respondents said they currently use these tools in the classroom.

Exhibit 2

The shift to more interactive and diverse learning models will likely continue. One industry expert told us, The pandemic pushed the need for a new learning experience online. It recentered institutions to think about how theyll teach moving forward and has brought synchronous and hybrid learning into focus. Consequently, many US colleges and universities are actively investing to scale up their online and hybrid program offerings.

Some technologies lag behind in adoption. Tools enabling student progress monitoring, AR/VR, machine learningpowered teaching assistants (TAs), AI adaptive course delivery, and classroom exercises are currently used by less than half of survey respondents. Anecdotal evidence suggests that technologies such as AR/VR require a substantial investment in equipment and may be difficult to use at scale in classes with high enrollment. Our survey also revealed utilization disparities based on size. Small public institutions use machine learningpowered TAs, AR/VR, and technologies for monitoring student progress at double or more the rates of medium and large public institutions, perhaps because smaller, specialized schools can make more targeted and cost-effective investments. We also found that medium and large public institutions made greater use of connectivity and community-building tools than small public institutions (57 to 59 percent compared with 45 percent, respectively). Although the uptake of AI-powered tools was slower, higher-education experts we interviewed predict their use will increase; they allow faculty to tailor courses to each students progress, reduce their workload, and improve student engagement at scale (see sidebar Differences in adoption by type of institution observed in the research).

While many colleges and universities are interested in using more technologies to support student learning, the top three barriers indicated are lack of awareness, inadequate deployment capabilities, and cost (Exhibit 3).

Exhibit 3

More than 60 percent of students said that all the classroom learning technologies theyve used since COVID-19 began had improved their learning and grades (Exhibit 4). However, two technologies earned higher marks than the rest for boosting academic performance: 80 percent of students cited classroom exercises, and 71 percent cited machine learningpowered teaching assistants.

Exhibit 4

Although AR/VR is not yet widely used, 37 percent of students said they are most excited about its potential in the classroom. While 88 percent of students believe AR/VR will make learning more entertaining, just 5 percent said they think it will improve their ability to learn or master content (Exhibit 5). Industry experts confirmed that while there is significant enthusiasm for AR/VR, its ability to improve learning outcomes is uncertain. Some data look promising. For example, in a recent pilot study, students who used a VR tool to complete coursework for an introductory biology class improved their subject mastery by an average of two letter grades.

Exhibit 5

Faculty gave learning tools even higher marks than students did, for ease of use, engagement, access to course resources, and instructor connectivity. They also expressed greater excitement than students did for the future use of technologies. For example, while more than 30 percent of students expressed excitement for AR/VR and classroom interactions, more than 60 percent of faculty were excited about those, as well as machine learningpowered teaching assistants and AI adaptive technology.

Eighty-one percent or more of faculty said they feel the eight learning technology tools are a good investment of time and effort relative to the value they provide (Exhibit 6). Expert interviews suggest that employing learning technologies can be a strain on faculty members, but those we surveyed said this strain is worthwhile.

Exhibit 6

While faculty surveyed were enthusiastic about new technologies, experts we interviewed stressed some underlying challenges. For example, digital-literacy gaps have been more pronounced since the pandemic because it forced the near-universal adoption of some technology solutions, deepening a divide that was unnoticed when adoption was sporadic. More tech-savvy instructors are comfortable with interaction-engagement-focused solutions, while staff who are less familiar with these tools prefer content display and delivery-focused technologies.

According to experts we interviewed, learning new tools and features can bring on general fatigue. An associate vice president of e-learning at one university told us that faculty there found designing and executing a pilot study of VR for a computer science class difficult. Its a completely new way of instruction. . . . I imagine that the faculty using it now will not use it again in the spring. Technical support and training help. A chief academic officer of e-learning who oversaw the introduction of virtual simulations for nursing and radiography students said that faculty holdouts were permitted to opt out but not to delay the program. We structured it in a were doing this together way. People who didnt want to do it left, but we got a lot of support from vendors and training, which made it easy to implement simulations.

Despite the growing pains of digitizing the classroom learning experience, faculty and students believe there is a lot more they can gain. Faculty members are optimistic about the benefits, and students expect learning to stay entertaining and efficient. While adoption levels saw double-digit growth during the pandemic, many classrooms have yet to experience all the technologies. For institutions considering the investment, or those that have already started, there are several takeaways to keep in mind.

In an earlier article, we looked at the broader changes in higher education that have been prompted by the pandemic. But perhaps none has advanced as quickly as the adoption of digital learning tools. Faculty and students see substantial benefits, and adoption rates are a long way from saturation, so we can expect uptake to continue. Institutions that want to know how they stand in learning tech adoption can measure their rates and benchmark them against the averages in this article and use those comparisons to help them decide where they want to catch up or get ahead.

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Technology is shaping learning in higher education - McKinsey

The Industry 4.0 era of manufacturing depends so heavily on data-driven precision that artificial intelligence (AI) is playing an increasing role in harnessing that data to enhance the performance of machines including injection molders.

AI in manufacturing encompasses an array of technologies that allow machines to perform with intelligence that emulates that of humans. Machine learning and natural language processing help machines approximate the human capacity to learn, make judgments, and solve problems. Data-enhanced efficiency keeps processes moving faster and more cost-effectively.

AI is becoming increasingly important in mechanical engineering, not least because of the need to automate injection molding processes efficiently and flexibly despite ever smaller batch sizes and shorter product life cycles, said Werner Faulhaber, Director of Research and Development at Arburg. Application examples of AI include automatic programming of robotic systems, targeted malfunction remedying, and a spare parts system with intelligent image processing. Arburg is working on making injection molding more intelligent, step by step ensuring that the machine continuously learns, keeps itself stable, and can even optimize itself in the future.

Arburg forms flexible and controllable production systems by combining machines, automation, and proprietary IT solutions. The companys Gestica control system, with its intelligent assistant functions, is integral to those systems. All Kuka six-axis robots, for example, have been equipped with the new Gestica user interface as standard, Faulhaber noted. This simplifies programming, as well as the monitoring, storage, and evaluation of process data.

One application Arburg is working on is the automatic programming of its Multilift linear robotic systems. The idea is that the operator simply enters the destination, as with a car navigation device, and the system automatically calculates the optimal route. For robotic systems, this means that the operator simply enters the desired start and end positions, and the control system takes care of the rest.

Wittmann Battenfeld, which has fully embraced Industry 4.0 connectivity across its portfolio of injection molding and auxiliary machines over the past several years, employs AI with its robots to monitor cycle times and control robots speeds outside the molding machine.

The companys machine-learning capabilities HiQ Flow and CMS technology will be on display at this years K show on Oct. 19 to 26 in Dsseldorf, Germany. The speed of ROI can be as short as a few cycles with HiQ Flow, and the software can often be retrofitted to older injection molding machines equipped with a B8 machine control. A CMS Pro version will be available at a later date.

The technology draws new conclusions from current parameters and, thus, becomes increasingly intelligent as it monitors performance, said Product Manager Christian Glueck. We limit it to a methodical determination of parameters. Therefore, the time required to use the technology is minimal, as is the price.

Comparing AI and machine learning, Glueck said, AI actually requires a much higher time investment and, correspondingly, a higher financial investment. A large number of parameters must be recorded from a running process and the relevant parameters are determined on the basis of the deviations. These are compared with measurement data of the product.

Based on factors like changes in material, ambient temperature, machine wear, tool wear, and other influences, AI can determine which machine parameters need to be changed so that the product can be produced within its quality tolerances. This can take months, as errors first must occur in order to learn from them.

Wittmann co-funded such an assessment program with Austrias Montanuniversitt Leoben university, but we found that the time needed to make it workable for production had to be questioned because in addition to the long-term investigation of the process, you also need the manpower necessary to handle it.

The companys Eco-Mode saves wear and tear on the robot by ensuring it does not run faster than necessary ultimately saving maintenance and energy costs. Offered standard on many Wittmann robots, Eco-Mode requires no special programming or interface with the IMM or operator/programmer, said Jason Long, National Sales Manager for robots and automation for Wittmann USA. All the end user has to do is tell the robot how many seconds it should get back over the IMM before the mold opens.

Another Wittmann feature, Eco-Vac conserves energy by setting a few parameters on the robot and allowing the robot to turn its vacuum circuits off and on. The robot monitors the vacuum level of the circuit used for picking the part out of the mold. If the robot senses the vacuum has reduced to a level that it could drop the part before it is told to, the robot will turn the vacuum on until it reaches the safe level again, then shuts back off. This feature cuts the amount of compressed air each robot uses and could save customers hundreds of dollars a year per robot.

As AI and machine learning are further leveraged to improve injection molding operations, simply gathering data is not enough to optimize processes, Faulhaber cautioned. You also need the process expertise and domain knowledge. In the future, the evaluation of many data directly in the control unit will offer further added value.

Arburg uses AI to develop master models using experience and data collected over the years on process, material, and machinery, Faulhaber continued. The customer could then sharpen the provided master model on edge and optimize their processes. The in-house development Gestica control system, the Arburg host computer system, and the arburgXworld customer portal give an advantage here.

One of Arburg's medium-term goals is to develop a system for digital twins of customized injection molding machines. This will open up completely new possibilities for simulating the cycle and making energy predictions. In addition, 3D views and installation plans of the machine stored in the arburgXworld customer portal and in the control system support the operator, said Faulhaber.

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How Artificial Intelligence Is Transforming Injection Molding - Plastics Today

As artificial intelligence (AI) and machine learning (ML) continues to become more sophisticated, their profound impact has extended to virtually every industry in the world. The legal profession is no exception, and lawyers who fail to embrace AI and ML may soon find themselves at a disadvantage compared to their colleagues who do.

Lawyers can use AI in many ways to improve their efficiency and productivity. AI can provide indispensable help with managing caseloads, collecting data, researching cases, and more. In addition, AI can be used to serve and advise clients better. And yes, it can help to streamline various processes, including your contracts process. Lets take a closer look at some of the ways AI is changing the legal profession.

Managing Caseloads

One of the most time-consuming and daunting tasks for any lawyer is caseload management. The once-daunting task can be made much easier with the help of AI and ML. There are now AI- and ML-powered legal platforms that can quickly and easily identify relevant cases and documents. In addition, AI and ML adeptly manages deadlines, keeps track of dates, and more.

Collecting Data

Another area where AI and ML can be extremely helpful for lawyers is data collection. This is particularly true in the field of e-discovery and contracts, where AI and ML can sort through large volumes of data much faster than a human ever could. In addition, AI and ML can be used to analyze data in support of making more informed decisions.

Providing Better Client Service and Advice

Perhaps most importantly, AI and ML can help lawyers provide their clients with better service and advice by leveraging big data analytics and other advanced technologies. For example, AI- and ML-powered platforms can quickly identify the best possible strategies for given legal situations by sifting through an unprecedented amount of legal data to spot trends and patterns.

Staying Competitive

Ultimately, the key to thriving as a lawyer in todays digital age is being willing and able to embrace new technologies. Technology and innovation are here to stay. As such, it is crucial for lawyers to not only understand how AI works but also to stay up to date on new advances and developments in this rapidly changing field.

The full scope of the changes that AI and ML will bring to the legal profession is certain to be significant, but, by proactively embracing AI and ML, lawyers can ensure that they remain competitive and relevant despite any changes in the years to come.

As AI and ML continues to transform the legal profession, it is important for lawyers to embrace these changes and use them to their advantage. Whether lawyers turn to AI- and ML-powered platforms for managing caseloads, collecting data, or providing clients with better service and advice, staying up to date on new advances in AI and ML technology is the key to thriving as a lawyer.

The Bottom Line

Its clear that AI and ML is changing the legal profession in a number of ways. Lawyers who incorporate AI into their work will be better positioned to survive and thrive in the years to come. Those who dont may find themselves at a serious disadvantage. Embracing the seemingly endless possibilities of AI and ML technology is a necessary step for lawyers who want to stay competitive in the fast-changing legal landscape.

For more information on how AI and ML can drive lawyers in surviving and thriving in the legal profession, be sure to watch Season 4, Episode 12 of the Legal Talk Network podcast: Why Legal AI Needs Lawyers to Act Now with Wei Chen.

Olga V. Mack is the CEO ofParley Pro, a next-generation contract management company that has pioneered online negotiation technology. Olga embraces legal innovation and had dedicated her career to improving and shaping the future of law. She is convinced that the legal profession will emerge even stronger, more resilient, and more inclusive than before by embracing technology. Olga is also an award-winning general counsel, operations professional, startup advisor, public speaker, adjunct professor, and entrepreneur. She founded theWomen Serve on Boardsmovement that advocates for women to participate on corporate boards of Fortune 500 companies. She authoredGet on Board: Earning Your Ticket to a Corporate Board SeatandFundamentals of Smart Contract Security. You can follow Olga on Twitter @olgavmack.

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Embracing AI And Machine Learning To Survive And Thrive In The World Of Law - Above the Law

Founded in 2008 by entrepreneur brothers Chintan and Harit Soni at IIM Ahmedabad's Centre for Innovation, Incubation and Entrepreneurship in India, Ecolibrium provides expert advisory as well as technology-driven sustainability solutions to enable businesses in commercial and industrial real estate to reduce energy consumption and ultimately achieve their net zero carbon ambitions.

Relocating its global headquarters to London, Ecolibrium has raised $5m in a pre-Series A funding round as it looks to expand its international footprint to the UK. The round was co-led by Amit Bhatia's Swordfish Investments and Shravin Bharti Mittal's Unbound venture capital firm, alongside several strategic investors.

Ecolibrium launches in the UK today having already signed its first commercial contract with Integral, JLL's UK engineering and facilities service business.

The fundraising and UK expansion builds on Ecolibrium's considerable success in Asia Pacific, where its technology is being used across 50 million sq ft by more than 150 companies including Amazon, Fiat, Honeywell, Thomson Reuters, Tata Power, and the Delhi Metro. An annual reduction of 5-15% in carbon footprint has been achieved to date by companies which have deployed Ecolibrium's technology.

Ecolibrium has also strengthened its senior UK management team, as it prepares to roll-out its green platform across the UK, by hiring facilities and asset management veteran Yash Kapila as its new head of commercial real estate. Kapila previously held senior leadership positions with JLL across APAC and EMEA regions.

Introducing SmartSense

At the heart of Ecolibrium's offer is its sustainability-led technology product SmartSense, which assimilates thousands of internet of things (IoT) data points from across a facility's entire energy infrastructure.

This information is then channelled through Ecolibrium's proprietary machine learning algorithms, which have been developed over 10 years by their in-house subject matter experts. Customers can visualise the data through a bespoke user interface that provides actionable insights and a blueprint for achieving operational excellence, sustainability targets, and healthy buildings.

This connected infrastructure generates a granular view of an asset's carbon footprint, unlocking inefficiencies and empowering smart decision-making, while driving a programme of continuous improvement to deliver empirical and tangible sustainability and productivity gains.

Preparing for future regulation

Quality environmental data and proof points are also providing a distinct business advantage at this time of increasing regulatory requirements that require corporates to disclose ESG and sustainability performance. Ecolibrium will work closely with customers to lead the way in shaping their ESG governance.

According to Deloitte, with a minimum Grade B Energy Performance Certification (EPC) requirement anticipated by 2030, 80% of London office stock will need to be upgraded an equivalent of 15 million sq ft per annum.

Research from the World Economic Forumhas found that the built environment is responsible for 40% of global energy consumption and 33% of greenhouse gas emissions, with one-fifth of the world's largest 2,000 companies adopting net zero strategies by 2050 or earlier. Technology holds the key to meeting this challenge, with Ecolibrium and other sustainability-focused changemakers leading the decarbonisation drive.

Chintan Soni, Chief Executive Officer at Ecolibrium, said:"Our mission is to create a balance between people, planet and profit and our technology addresses each of these objectives, leading businesses to sustainable prosperity. There is no doubt the world is facing a climate emergency, and we must act now to decarbonise and protect our planet for future generations.

"By using our proprietary machine learning-led technology and deep in-house expertise, Ecolibrium can help commercial and industrial real estate owners to deliver against ESG objectives, as companies awaken to the fact that urgent action must be taken to reduce emissions and achieve net zero carbon targets in the built environment.

"Our goal is to partner with companies and coach them to work smarter, make critical decisions more quickly and consume less. And, by doing this at scale, Ecolibrium will make a significant impact on the carbon footprint of commercial and industrial assets, globally."

The UK expansion has been supported by the Department for International Trade's Global Entrepreneur Programme. The programme has provided invaluable assistance in setting up Ecolibrium's London headquarters and scaling in the UK market.

In turn, Ecolibrium is supporting the growth of UK innovation, promoting green job creation, and providing tangible economic benefits, as part of the country's wider transition to a more sustainable future.

Minister for Investment Lord Grimstone said: "Tackling climate change is crucial in our quest for a cleaner and green future, something investment will play an important part in.

"That's why I'm pleased to see Ecolibrium's expansion to the UK. Not only will the investment provide a revolutionary sustainability solution to reduce carbon emissions across various sectors, it is a continued sign of the UK as a leading inward investment destination, with innovation and expertise in our arsenal".

About Ecolibrium

Ecolibrium is a machine learning-led decarbonisation platform balancing people, planet and profit to deliver sustainable prosperity for businesses.

Founded in 2008 by entrepreneur brothers Chintan and Harit Soni, Ecolibrium provides expert advisory as well as technology-driven sustainability solutions to enable commercial and industrial real estate owners to reduce energy consumption and ultimately achieve their net zero carbon ambitions.

Ecolibrium's flagship technology product SmartSense is currently being used across 50 million sq ft by more than 150 companies including JLL, Amazon, Fiat, Honeywell, Thomson Reuters, Tata Power, and the Delhi Metro. SmartSense collects real-time information on assets, operational data and critical metrics using internet of things (IoT) technology. This intelligence is then channelled through Ecolibrium's proprietary machine learning algorithms to visualise data and provide actionable insights to help companies make transformative changes to their sustainability goals.

For more information, visit: http://www.ecolibrium.io

For press enquiries, contact: FTI Consulting: [emailprotected], +44 (0) 2037271000

Photo -https://mma.prnewswire.com/media/1837227/Ecolibrium_Yash_Kapila_and_Chintan_Soni.jpg

SOURCE Ecolibrium

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Machine learning-led decarbonisation platform Ecolibrium launches in the UK - PR Newswire

Teal members have found jobs with top companies, such as Google, Apple, TikTok, Spotify and Bumble.

The United States is heading into uncharted waters. After nearly two years of a steadily improving job market, better economy and optimism, it feels like America is losing some of the gains it has made. There have been a number of tech companiesranging from startups to big tech giants that have announced hiring freezes and layoffs. Its disconcerting that after talking about the Great Resignation and war for talent, workers are worried about holding onto their jobs.

On the positive side, there are still around 11.4 million jobs open, according to the U.S. Bureau of Labor Statistics. The Department of Labor also announced on Friday that the U.S. added 390,000 new jobs in May, and the unemployment rate is at 3.6%, a little higher than the 50-year low back in February 2020, prior to the pandemic.

Despite low unemployment and more jobs available than people to fill them, there are economic concerns. Runaway inflation, supply chain disruptions and the possibility of being sucked into a World War emanating from Russias invasion of Ukraine all create future uncertainty. When corporate executives are faced with the unknown, it's easier to hold off on doing anything, hunker down and wait for better clarity. This is the prime time when people need help and guidance.

Looking for a new job sometimes feels like a lonely pursuit. The companies have talent acquisition teams, the latest software, internal recruiters, human resources and a plethora of other personnel. You have to basically go it all alone. The matchup doesnt feel as if the odds are in your favor. However, there is a startup that can help level the playing field.

David Fano, founder and CEO of Teal, created a machine learning and AI- based careertech platform to help job seekers and people who want to advance their careers. Fano said, In the future of work, the employee is the enterprise."

As the head of a platform that offers the tech tools to empower people to take control over their career journey, the chief executive added, "Companies have HR teams, recruiters and sophisticated technology to manage their pipelines, but all that most job seekers have is a spreadsheet. Were leveling the playing field by building the infrastructure that helps people grow their careers with confidence.

To help professionals, Teal offers a free suite of web-based career tools.

To help professionals, Teal offers a free suite of web-based career tools. These features include a job tracker, rsum builder, Chrome extension and other tech tools. Members will receive prompts and guidance on the site to help with their career journey. There wont be any pushy salespeople, as the job seekers take control over their future.

More than 65,000 people have signed up to the program to help fast-track their careers. Fano shared that Teal members have found jobs with top companies, such as Google, Apple, TikTok, Spotify and Bumble.

Catherine Daneliak, a Teal member, said about her experience, Teal has brought all aspects of the job search together in one platform, which has enabled me to organize my job search and keep track of the status of each potential job.

Before Fano started Teal, he was on paternity leave when his then-employer, WeWork, conducted its first round of mass layoffs. At the time, Teal was an aspirational idea. Fano felt that he needed to help his former colleagues. Along with a group of ex-WeWorkers, Fano put together a career day. They offered free rsum reviews, networking opportunities and other career assistance.

He recognized that even experienced, knowledgeable professionals need resources to navigate layoffs and strategies on how to find a new job. Fano wrote in a LinkedIn post, For me, that was the big bang moment of why Teal needed to existto provide employees with the tools and infrastructure to take control of their careers. It was his big aha moment.

In light of the economic and geopolitical events that pushed both tech giants and startups to cut costs and enact hiring freezes, downsings and in the case of Coinbase, rescinding job offers, venture capital funding wont be as prolific for the foreseeable future. Teal fortunately raised a $6.3 million seed round before the window of opportunity started to close.

The latest funding will be used to develop Teals next phase of product initiatives. This will include a recommendations engine, matching members with relevant skills-based online courses to help them further their careers through upskilling and learning. The job hunters and career-focused individuals will be able to easily find and sign up to well-known online coursework with notable organizations, such as Coursera, General Assembly, Udemy and LinkedIn Learning.

"Teal is building the tools to help people navigate the future of work where career agility is more important than ever," said Jeff Rinehart, partner at City Light Capital and former chief marketing officer at 2U. We need a new category of technology that champions the candidatenot the companyempowering users to take control of their careers and develop the skills they need to excel long-term. Teals business model positions them to both do good and do well, and we couldnt be more excited to back them at this pivotal moment.

Teals seed round was led by City Light Capital with participation from Rethink Education, Human Ventures, Gaingels, Pareto Ventures, Basecamp Fund, Zelkova Ventures and angel investors, like Tom Willerer (former chief product officer at OpenDoor and Coursera). Previous investors include Flybridge, Lerer Hippeau and Oceans.

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Teal Is Revolutionizing The Career Journey With Tech, AI And Machine Learning - Forbes