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Accel Solutions and Veego today announced the integration of Veego's Artificial Intelligence and machine learning solution with Bezeq, Israel's largest Telecom. The integration will enhance Bezeq's ability to provide its subscribers with improved Internet quality of experience and mitigate network malfunctions. Bezeq will integrate Veego's solution in their consumer line of Be-Routers. The Veego solution provides Bezeq the ability to identify and mitigate connectivity malfunctions remotely, attain a broad overview of the network and improve the overall experience for its customers.

Niv Berkner, Head of Services and Product Innovation at Bezeq indicated "I have no doubt that the integration of the Veego solution in our Be-Routers will allow us to provide our customers an optimal quality of experience. The Veego solution will allow us to understand the interaction between all the devices connected in the home, and as such, provide Bezeq the ability to identify, anticipate and mitigate network related malfunctions remotely, without the customers involvement and/or being aware."

"Veego provides ISPs and CSPs the ability to leverage data and provide them with insights that alleviate churn, while constantly improving the customer experience." outlined Amir Kotler, Veego's CEO.

"The integration of Veego's AI and ML capabilities enable Telcos to actually experience what the customer experiences when he has an internet malfunction that disrupts a healthy Internet process," Kotler added "Veego's solution enables ISP to predict the issue, resolve it in autonomic ways and as a result, improves operational efficiency, increases revenues and reduces churn."

Ronen Shor, CEO of Accel Solutions stated, "The Bezeq - Veego agreement is another step in our continuous enhancement efforts on the products sold to Bezeq and a significant technological upgrade offered by Bezeq to its customers. Accel Solutions considers Veego as a strategic partner with tremendous potential in the international market.

Source:https://accelsolutionsllc.com/

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Veegos Artificial Intelligence and Machine Learning Solution Integrated with Israels Largest Telecom - AZoRobotics

The advisory and climate tech-led sustainability solution has opened a new London HQ after raising $5m in a pre-Series A funding round, to support growing demand from commercial and industrial UK real estate owners striving to meet net zero carbon targets

Ecolibriums Head of Commercial Real Estate Yash Kapila (left) and CEO Chintan Soni (right) will lead the business UK expansion from its new London HQ. Image credit: Max Lacome

UK expansion builds on considerable success in Asia Pacific, where Ecolibrium's technology has been deployed across 50 million sq ft by globally renowned brands including Amazon, Fiat, Honeywell, Thomson Reuters, Tata Power, and the Delhi Metro

The $5m pre-Series A funding round was co-led by Amit Bhatia's Swordfish Investments and Shravin Bharti Mittal's Unbound venture capital firm

Launches in the UK today having already signed its first commercial contract with Integral, real estate giant JLL's engineering and facilities service business

LONDON, June 13, 2022 /PRNewswire/ -- Machine learning-led decarbonisation platform Ecolibrium has today launched its revolutionary sustainability solution in the UK, as the race to reduce carbon emissions accelerates across the built environment.

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.

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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: ecolibrium@fticonsulting.com, +44 (0) 2037271000

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

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Machine learning-led decarbonisation platform Ecolibrium launches in the UK - Yahoo Finance

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

PALO ALTO, Calif. and TORONTO, June 14, 2022 (GLOBE NEWSWIRE) -- Today, Cohere For AI, a non-profit research lab and community, announced its official launch. Dedicated to contributing open source, fundamental machine learning research, the lab will focus on solving some of the most complex challenges in the field of machine learning.

Sara Hooker will serve as Head of Cohere For AI, bringing a wealth of knowledge across AI and machine learning, with a specialty in deep learning. Prior to Cohere For AI, Sara was a Research Scientist at Google Brain where she focused on training models that go beyond top-line metrics to effectively demonstrate ability to be interpretable, compact, fair, and robust. She also founded Delta Analytics, a non-profit that brings together researchers, data scientists, and software engineers to volunteer their skills for non-profits around the world.

In order to realise the potential of machine learning, we need to make sure were working across a diverse set of people, disciplines, backgrounds, and geographies, said Aidan Gomez, CEO and Cofounder at Cohere. Im so excited to have Sara at the helm of Cohere For AI and cant wait to build the community together.

Cohere For AI aims to create open collaboration with the broader machine learning community. The lab is committed to supporting fundamental research on machine learning topics, while also prioritizing good stewardship of open source scientific practices.

This is the lab I wish had existed when I entered the field, said Hooker, Head of Cohere For AI. Depending on where youre located, theres often a lack of opportunities in machine learning. Cohere For AI aims to reimagine how, where, and by whom research is done. Im inspired by the opportunity to make an impact in ways that dont just advance progress on machine learning research, but also broadens access to the field.

In addition to contributions to fundamental research, Cohere For AI will support a machine learning community where members can connect with each other, discover new colleagues, and spur open discussion and collaboration. The lab and community will work to create new points of entry to machine learning research and will, ultimately, reflect the diversity of its members experiences and interests.

To get involved, browse our open research positions at jobs.lever.co/cohere, and stay in the loop on new programs and lab developments by signing up here.

About Cohere For AICohere For AI is a non-profit research lab and community dedicated to contributing fundamental research in machine learning, working to solve some of the field's most challenging problems. It supports responsible research across machine learning, while also prioritizing good stewardship of open source scientific practices. As a borderless research lab, Cohere For AI is community-driven and motivated by the opportunity to establish an inclusive, distributed community made up of brilliant research and engineering talent from across the globe.

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Cohere For AI Announces Non-Profit Lab Dedicated to Open Source Fundamental Research - GlobeNewswire

As schools and workplaces begin resuming in-person operations, we project a permanent increase in the volume of online meetings and calls. And while communication and collaboration solutions have played a critical role in enabling continuity during these unprecedented times, early stress tests have revealed opportunities to improve and enhance meeting and call quality.

Disruptive echo effects, poor room acoustics, and choppy video are some common issues that hinder the effectiveness of online calls and meetings. Through AI and machine learning, which have become fundamental to our strategy for continual improvement, weve identified and are now delivering innovative enhancements in Microsoft Teams that improve such audio and video challenges in ways that are both user-friendly and scalable across environments.

Today, were announcing the availability of new Teams features including echo cancellation, adjusting audio in poor acoustic environments, and allowing users to speak and hear at the same time without interruptions. These build on AI-powered features recently released like expanding background noise suppression.

During calls and meetings, when a participant has their microphone too close to their speaker, its common for sound to loop between input and output devices, causing an unwanted echo effect. Now, Microsoft Teams uses AI to recognize the difference between sound from a speaker and the users voice, eliminating the echo without suppressing speech or inhibiting the ability of multiple parties to speak at the same time.

In specific environments, room acoustics can cause sound to bounce, or reverberate, causing the users voice to sound shallow as if theyre speaking within a cavern. For the first time, Microsoft Teams uses a machine learning model to convert captured audio signal to sound as if users are speaking into a close-range microphone.

A natural element of conversation is the ability to interrupt for clarification or validation. This is accomplished through full-duplex (two-way) transmission of audio, allowing users to speak and hear others at the same time. When not using a headset, and especially when using devices where the speaker and microphone are very close to each other, it is difficult to remove echo while maintaining full-duplex audio. Microsoft Teams uses a model trained with 30,000 hours of speech samples to retain desired voices while suppressing unwanted audio signals resulting in more fluid dialogue.

Each of us has first-hand experience of a meeting disrupted by the unexpected sounds of a barking dog, a car alarm, or a slammed door. Over two years ago, we announced the release of AI-based noise suppression in Microsoft Teams as an optional feature for Windows users. Since then, weve continued a cycle of iterative development, testing, and evaluation to further optimize our model. After recording significant improvements across key user metrics, we have enabled machine learning-based noise suppression as default for Teams customers using Windows (including Microsoft Teams Rooms), as well as Mac and iOS users. A future release of this feature is planned for Teams Android and web clients.

These AI-driven audio enhancements are rolling out and are expected to be generally available in the coming months.

We have also recently released AI-based video and screen sharing quality optimization breakthroughs for Teams. From adjustments for low light to optimizations based on the type of content being shared, we now leverage AI to help you look and present your best.

The impact of presentations can often depend on an audiences ability to read on-screen text or watch a shared video. But different types of shared content require varied approaches to ensure the highest video quality, particularly under bandwidth constraints. Teams now uses machine learning to detect and adjust the characteristics of the content presented in real-time, optimizing the legibility of documents or smoothness of video playback.

Unexpected issues with network bandwidth can lead to a choppy video that can quickly shift the focus of your presentation. AI-driven optimizations in Teams help adjust playback in challenging bandwidth conditions, so presenters can use video and screen sharing worry-free.

Though you cant always control the surrounding lighting for your meetings, new AI-powered filters in Teams give you the option to adjust brightness and add a soft focus for your meetings with a simple toggle in your device settings, to better accommodate for low-light environments.

The past two years have made clear how important communication and collaboration platforms like Microsoft Teams are to maintaining safe, connected, and productive operations. In addition to bringing new features and capabilities to Teams, well continue to explore new ways to use technology to make online calling and meeting experiences more natural, resilient, and efficient.

Visit the Tech Community Teams blog for more technical details about how we leverage AI and machine learning for audio quality improvements as well as video and screen sharing optimization in Microsoft Teams.

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How Microsoft Teams uses AI and machine learning to improve calls and meetings - Microsoft