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Architectural Engineering And Construction Solutions (AECS) Market Size to grow by USD 6.41 Bn, Driven by the Increasing Need for Managing Large-Scale…

NEW YORK, Oct. 17, 2022 /PRNewswire/ -- Technavio has been monitoring the architectural engineering and construction solutions (AECS) market, operating in the IT software industry. The report estimates it to register an incremental growth of USD 6.41 billion,at a CAGR of 11.7% during the forecast period. The global AECS market is characterized by the presence of well-diversified international and regional vendors. Competitors have to focus on performance, innovation, cost, and financial stability to strengthen their foothold in the market. Market vendors also have to leverage the existing growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments. Request Free Sample Report.

Technavio has announced its latest market research report titled Global Architectural Engineering and Construction Solutions (AECS) Market 2022-2026

Architectural Engineering and Construction Solutions (AECS) Market Vendors

We provide a detailed analysis of around 25 vendors operating in the Architectural Engineering and Construction Solutions (AECS) Market, including some of the vendors such as vendors Backed with competitive intelligence and benchmarking, our research reports on the Architectural Engineering and Construction Solutions (AECS) Market are designed to provide entry support, customer profile and M&As as well as go-to-market strategy support.

4M Group

ACCA software Spa

ANSYS Inc.

Autodesk Inc

AVEVA Group Plc

Bentley Systems Inc.

CYPE Ingenieros SA

Dassault Systemes SE

Esri

GEOTEC Software Inc.

Hexagon AB

Innovaya LLC

Integrated Environmental Solutions Ltd.

Nemetschek SE

Newforma Inc.

Oracle Corp.

Procore Technologies Inc.

Trimble Inc.

Virtual Build Technologies

Construsoft B.V.

Find additional highlights on the growth strategies adopted by vendors and their product offerings, Download a Sample Report.

Architectural Engineering and Construction Solutions (AECS) Market Driver

The increasing need for managing large-scale projects is notably driving the architectural engineering and construction solutions (AECS) market growth.Currently, organizations are focusing on cultivating and managing the resources necessary for efficient product output, which increases the need for efficient solutions for themanagement of large-scale construction projects. The primary purpose ofAECS is to automate processes to ensure maximizedoutputby managing resources and maintaining regular follow-up. Automated services increase connectivity so that organizations can handle project-related inquiries easily and effectively. Also, automation decreases response time and increases productivity, which ensures efficient process management. By using AEC solutions, revenue possibilities can be rapidly increased by calculating conversion ratios and running reports to track the metrics detailed as per customer demand. These features reduce the operating time. Thus, such benefits associated with the adoption of AECS will drive the growth of the market in focus during the forecast period.

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Architectural Engineering and Construction Solutions (AECS) Market Challenge

Thechallenges associated with open-source platforms is the major challenge impeding thearchitectural engineering and construction solutions (AECS) market growth.With the rising demand for digitalization in the current market scenario, the demand for open-source software has increased in the market. Open-source vendors provide a wide range of business analytics tools and applications. These types of feature-rich software are freely available on the Internet. Hence, several small and emerging enterprises use them, as the purchasing and licensing costs of commercial software are high. Also, the primary and common features that are provided in the proprietary are available in most of the open-source AECS. Open-source software can be downloaded and run on all platforms, posing stiff competition to commercial BIM software. Free BIM viewer, Standard office application-based BIM, BIM software toolkit, BIM as a bolt-on for CAD software, BIMx from GRAPHISOFT, BuildTools, eSUB, Estimator Application, and GenieBelt are some of the common open-source AEC solutions available in the market. Open-source platforms can be easily tested before implementation, and this makes them suitable for rapid prototyping and experimentation. In addition, open-source platforms are peer-reviewed software, which leads to better reliability. Thus, such factors might hamper the growth of the global AECS market during the forecast period.

To know about the additional drivers and challenges. Request a Sample Report

Architectural Engineering and Construction Solutions (AECS) Market 2022-2026: Segmentation

Based on geographic segmentation, 35%of the market's growth originated from North America during the forecast period. In addition, software led the growth of the product segment. This report provides an accurate prediction of the contribution of all the segments to the growth of the superfood powders market size.

Product

Deployment

Geography

Architectural Engineering and Construction Solutions (AECS) Market 2022-2026: Scope

Architectural Engineering and Construction Solutions (AECS) Market 2022-2026: Key Highlights

CAGR of the market during the forecast period 2022-2026

Detailed information on factors that will assist architectural engineering and construction solutions (AECS) marketgrowth during the next five years

Estimation of the architectural engineering and construction solutions (AECS) marketsize and its contribution to the parent market

Predictions on upcoming trends and changes in consumer behavior

The growth of the architectural engineering and construction solutions (AECS) market

Analysis of the market's competitive landscape and detailed information on vendors

Comprehensive details of factors that will challenge the growth of the architectural engineering and construction solutions (AECS) market, vendors

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Oil and Gas Engineering Services Market by Type and Geography Forecast and Analysis 2022-2026

Architectural Engineering And Construction Solutions (AECS) Market Scope

Report Coverage

Details

Page number

120

Base year

2021

Forecast period

2022-2026

Growth momentum & CAGR

Accelerate at a CAGR of 11.7%

Market growth 2022-2026

USD 6.41 billion

Market structure

Fragmented

YoY growth (%)

10.58

Regional analysis

North America, Europe, APAC, South America, and Middle East and Africa

Performing market contribution

North America at 35%

Key consumer countries

US, China, Japan, UK, and France

Competitive landscape

Leading companies, competitive strategies, consumer engagement scope

Companies profiled

4M Group, ACCA software Spa, ANSYS Inc., Autodesk Inc, AVEVA Group Plc, Bentley Systems Inc., CYPE Ingenieros SA, Dassault Systemes SE, Esri, GEOTEC Software Inc., Hexagon AB, Innovaya LLC, Integrated Environmental Solutions Ltd., Nemetschek SE, Newforma Inc., Oracle Corp., Procore Technologies Inc., Trimble Inc., Virtual Build Technologies, and Construsoft B.V.

Market Dynamics

Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and future consumer dynamics, and market condition analysis for the forecast period.

Customization purview

If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized.

Table of Contents:

1 Executive Summary

2 Market Landscape

3 Market Sizing

4 Five Forces Analysis

5 Market Segmentation by Product

6 Market Segmentation by Deployment

7 Customer Landscape

8 Geographic Landscape

9 Drivers, Challenges, and Trends

10 Vendor Landscape

11 Vendor Analysis

12 Appendix

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contact

Technavio ResearchJesse MaidaMedia & Marketing ExecutiveUS: +1 844 364 1100UK: +44 203 893 3200Email: media@technavio.comWebsite: http://www.technavio.com/

Global Gastrointestinal Stromal Tumors Therapeutics Market 2022-2026 (PRNewsfoto/Technavio)

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How AI-driven digitalisation is transforming the engineering sector – Gulf Business

We live in a progressively more digital world. As digitalisation ramps up in various industrial sectors, so does the need for companies to rethink how they implement products, services, and engagement strategies. For over two decades, industry 4.0 has been on the horizon, and then in its infancy. This transition had previously been gradual. Engineering firms were discussing their future digital transformation initiatives. If they already had roadmaps, they were mapped out across anywhere from a year to over a decade.

Accelerating the evolutionary process Over time, evolution has accelerated significantly with the recent rapid change in engineering practices, a key example. For many years, the different engineering disciplines operated alone, focusing only on their specific fields. And that worked! But recently, market dynamics have forced process engineers to look at the bigger picture, to optimise their process by integrating different engineering disciplines and improving collaboration.

Across the globe, firms have identified millions of dollars in lost opportunities that can be attributed to a lack of collaboration. Enhanced workflows that enable better communication and sharing of information between process engineers, project engineers, estimators, and safety and energy specialists deliver the potential to capture those opportunities. Local initiatives such as the UAEs Fourth Industrial Revolution Strategy aims to improve the UAEs position as a global hub and to develop its contribution to the economy, by advancing modernisation and future technologies.

In terms of digital transformation itself though, most engineering firms were either initiating or contemplating initiatives to improve engineering productivity and reduce project and financial risk. These initiatives were being undertaken, in large measure, to consolidate and connect their portfolios of engineering software and technology in support of new, streamlined, digitalised workflows spanning departments, disciplines, and offices. Anticipated business benefits include shorter cycle times, lower cost, and higher-quality designs, as well as fewer errors and problems encountered during design, construction, and handover.

The pandemic has acted as a further catalyst for digital transformation in the engineering sector. Supply chains globally were exposed to cracks that led to empty shelves and pandemic-induced panic. Engineering firms had to embrace industrial digitalisation for new ways to maintain customer engagement and recover from supply chain disruptions. Roadmaps from companies that already had a digital strategy underway were shortened drastically. What was once mapped across a year, or more was narrowed down to weeks and days.

Delivering new opportunities through AIToday, a growing number of engineering firms are extending their digital initiatives into new areas to take advantage of escalating business opportunities. Artificial intelligence (AI) often lies at the heart of these opportunities. Indeed, senior executives are now prioritising AI to reduce setup and programming overheads that are commonly required for individual tasks. If reports are to be believed will contribute $96bn in 2030 (13.6 per cent GDP) to the UAE economy. In line with this, we have seen several examples of AI-driven digitalisation delivering benefits across the industry.

The use of AI-driven digital twin technology, in particular, can bring high value to these companies clients, as it captures real-time data of the asset once it is in operation. Additionally, being in a position to leverage digital design and engineering data during handover provides greater potential for offering value-added services during operations and maintenance, making the firm less reliant on capital spending alone.

AI can also play an important role in supporting and outlining an engineering approach to a project, the constructibility of a design, and the planning of how materials, equipment, and labour are organised. This early planning approach has been proven to reduce costs and speed up schedules.

Risk and best-case scenarios evaluationThe use of first-principle models for defining and predicting a projects performance and its outcomes is standard in process industries. However, there are some processes that are more difficult to predict. Often these are managed through less-precise techniques such as operator experience or rules of thumb, but this can lead to less than expected performance levels.

However, AI can simulate thousands of design options which very quickly narrow down the options that not only best meet the owners requirements, but are the safest, most environmentally friendly, and most cost-effective. A new capability, known as multi-case analysis, offers engineering firms the opportunity to transform the way these early decisions are made. Previously, engineers would define these critical parameters using limited data from a limited number of operating cases and conditions. Imagine designing an iPad with such a limited set of data, never mind a bespoke $10bn process plant. Yet that has been standard practice in the past.

Multi-case analysis helps to optimise early design decisions based on the consideration of hundreds or even thousands of operating conditions and cases. Leveraging AI and high-performance computing, either in the cloud or on a desktop, allows designers to rely on a significantly broader set of data to adjust and fine-tune their designs.

From the many different grades of crude oil to varying ambient weather conditions, this improvement in understanding how a potential design would perform in real conditions can result in improvements across the board, from construction materials, and the size of equipment to the type of utilities and even the location of the plant. These decisions will often have a major impact on the plants capital and operating costs, its risk analysis, as well as the overall fit for its intended purpose.

A multi-case analysis is undoubtedly a key area of focus for engineering firms using AI-driven digitalisation today. However, in speaking with customers across all regions, the highest priority area to be addressed under digitalisation is the consolidation of engineering software and technology portfolios, followed by the digitalisation of remaining applications and business processes. Critical to this effort is the ability to find and re-use data across the organisation, and eventually across their ecosystem of vendors, sub-contractors, and consultants.

There is so much to be gained (some companies estimate there is an opportunity for double-digit improvement in engineering and estimating productivity alone) that those who do not move forward risk being less competitive in the future.

Positive prospectsLooking ahead to the future of the engineering sector, digital transformation will inevitably accelerate and bring about significant improvements. While the path of change was already firmly established prior to the arrival of Covid-19, the pandemic has acted as a catalyst to speed this up. For engineering firms to succeed it is imperative that they adopt the advanced technology that is now available to them which includes AI tools. This will ensure they achieve operational efficiencies across the end-to-end value chain, giving them that all-important competitive edge. That, in turn, will position them well as they look to migrate beyond Industry 4.0 to the rapidly emerging fifth industrial revolution, or Industry 5.0, which takes the existing paradigm one step further by highlighting operational excellence and innovation as key drivers for change.

Sonali Singh is the VP Product Management at AspenTech

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Reverse-Engineering A Display Protocol To Repair A Roland Synthesizer – Hackaday

Repairing electronic devices isnt as hard as it used to be. Thanks to the internet, its easy to find datasheets and application notes for any standard component inside your gadget, and once youve found the faulty one, you simply buy a replacement from one of a million web shops assuming you dont end up with a fake, of course. When it comes to non-standard components, however, things get more difficult, as [dpeddi] found out when a friend asked him for help in repairing a Roland Juno-G synthesizer with a broken display.

The main issue here was the fact that the display in question was a custom design, with no replacement or documentation available. The only thing [dpeddi] could figure out from the service manual was the basic pinout, which showed a parallel interface with two lines labelled chip select an indication that the display contained two separate controllers. But the exact protocol and data format was not documented, so [dpeddi] brought out his logic analyzer to try and decode the signals generated by the synthesizer.

After a bit of trial and error, he was able to figure out the protocol: it looked like the display contained two KS0713-type LCD controllers, each controlling one half of the screen. Finding a compatible replacement was still proving difficult, so [dpeddi] decided instead to decode the original signals using a microcontroller and show the picture on a modern LCD driven by SPI. After some intial experiments with an ESP32, it turned out that the task of reading two reasonably fast parallel buses and driving an even faster serial one was a bit too much for the ESP, so [dpeddi] upgraded to a Raspberry Pi Pico. This worked a treat, and thanks to a 3D-printed mounting bracket, the new display also fit snugly inside the Rolands case.

The Picos code is available on [dpeddi]s GitHub page, so if youve also got a dodgy display in your Juno-G you can simply download it and use it to plug in a brand-new display. However, the method of reverse-engineering an existing display protocol and translating it to that of a new one is pretty universal and should come in handy when working with any type of electronic device: say, a vintage calculator or multimeter, or even another synthesizer.

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Reverse-Engineering A Display Protocol To Repair A Roland Synthesizer - Hackaday

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Sarnia event aims to encourage diversity in engineering – Sarnia and Lambton County This Week

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An event encouraging girls in elementary and high school to consider careers in engineering returns Saturday to Sarnia.

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Go ENG Girl is open to Grade 7 to 10 youth identifying as girls and non-binary and is being held at the Western Sarnia-Lambton Research Park Saturday morning with hands-on activities, information for youth and their parents, and a presentation by Abbey Slawich, an engineer in training at Nova chemicals.

The events have been held annually in Sarnia for several years but switched to virtual events during the pandemic.

Go ENG Girl is being presented in Sarnia by Western University, the Ontario Network of Women in Engineering and the research park so Grade 7 to 10 girls and non-binary youth can come and explore and be inspired by the wonderful world of engineering, said Samantha Fowler, outreach equity, diversity, and inclusion programs coordinator with Western University.

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The national organization, Engineers Canada, has set a target of increasing the proportion of newly licensed engineers who are women to 30 per cent by 2030. It said female-identifying engineers accounted for 20.6 per cent of newly licensed engineers in Canada in 2020.

Fowler said shes happy to see Go ENG Girl return to an in-person event.

Theres something about the energy in a classroom when students are actually coding or building something, she said. I missed it during the pandemic.

Organizers are expecting about 50 young people, plus parents, at the Sarnia event and the program is still taking registrations online at http://www.eng.uwo.ca/outreach.

Grade 7 to 10, research has shown, is really the age when students are starting to make decisions about their future, including whether or not to continue taking science and math courses in high school, Fowler said.

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Its still early enough for them to get their prerequisites they require to go on to engineering.

Fowler said she believes there has been progress in the support women feel in engineering, as well as in the number of women entering the profession.

One example of that support is a Women in Engineering student club for students at Western, which Slawich was a member of.

She graduated this year in electrical engineering and completed a 12-month co-op placement with Nova while at school.

Having those supports for women going through for engineering can make all the difference in finding your community and finding your passion, Fowler said.

Slawich will provide the prospective of a recent graduate, as well as someone doing really cool electrical engineering right now, Fowler said.

Fowler said one of her favourite reactions at outreach events is hearing girls who may not have been aware how creative and collaborative engineering is say, I can fit in here.

The hands-on portion of the morning will include coding with Microbit Rovers (small, handheld computers) and building electromagnetic dancers.

The day begins with registration at 8:30 a.m. and ends at noon with lunch. The event is free.

pmorden@postmedia.com

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How to Become a Cloud Engineer – Dice Insights

As businesses migrate more and more of their core operations to the cloud, the importance of cloud engineers only increases. If youre wondering how to become a cloud engineer, its important to learn not only the most popular cloud platforms and how they can best serve organizations, but also how to migrate any on-premises apps and services to a cloud-based environment, which is a key requirement for many cloud engineering jobs.

Successful cloud engineers not only have lots of technical knowledgethey also possess incredible soft skills such as empathy and communication, as they must effectively convey information (and secure buy-in) from multiple stakeholders throughout an organization, from software engineers to senior executives.

Here are some questions you might have if youre interested in how to become a cloud engineer:

On the technical side of things, the necessary skills often depend on the size the organization, the industry, and the size of the team. For starters, though, cloud engineers should have a solid grasp of the three major cloud platforms often utilized by businesses:

A cloud engineer is expected to understand the options available on each of these platforms, including storage (and how to deploy/manage it) and compute. During the interview process, a candidate for cloud engineering position will likely face some highly technical questions designed to test their cloud-platform knowledge, so its not something you can fake.

As more network functions migrate to the cloud, cloud engineers should also know as much as possible about cloud-based network management, from spinning up virtual networks and servers to security. (At moments, a cloud engineer job might seem virtually identical to a network engineer job, depending on the cloudiness of the organizations IT stack.)

Web services and APIs are also key, which means cloud engineers must be familiar with XML, SOAP, and how to automate processes.

Shira Shamban, CEO at Solvo, a security automation enabler for cloud development and production environments, suggests that, much like in other technical fields, degrees and certifications arent mandatory to become a professional in cloud engineering.

They are, however, useful in several cases like when youre looking for an entry-level position and want to have some kind of advantage, she says. This would show potential employers your motivation, ability to learn on your own, and prove to them you have some basic knowledge in the field.

Certifications can also be useful when you want or need very specific knowledge in a narrow, cloud-related domain like cybersecurity. These domains have a lot of nuances and just reading documentation wont help you get things done, she says. Of course, the ideal scenario would be working hands-on while getting some certifications, so you can implement and experiment with things that you learned in the lab.

For those who want to become a cloud engineer, theres always a more traditional route. Nathan Demuth, vice president of cloud services at Coalfire, says his career started with studying information systems in college. Cloud was just starting to gain traction at the time I finished my degree and represented an opportunity to get invested in a domain that even top professionals at the time didnt fully understand, and with nothing to lose, he explains.

There are also lots of online training camps, academies, and fast courses for you to improve your skills, whether or not you have a degree. Demuth points to a variety of training sources hes used, including formal training camps. These programs are often tiered, allowing you to access more basic or advanced content depending on your skill level.

These usually offered extensive videos, exercises, and materials to guide you through self-learning projects, he says. Some of these are also geared around a curriculum to pass CSP certifications.

On a more informal basis, forums such as Reddit and Discord are full of professionals who are often willing to provide advice. If you ask nicely, these technologists will often share their knowledge about everything from managing cloud resources to the processes and tools of a CI/CD pipeline.

The other skills that make a successful cloud engineer include having an understanding of every CSPs shared responsibility model, and how that does or does not impact your work and architectureespecially security responsibilities, Demuth adds.

Shamban believes a good cloud engineer doesnt wait for problems to occur. Planning in advance is really important, especially if you want to deliver the right solution at the right time (i.e., when problems are still small, and definitely before the production environment breaks).

The cloud as we know it today is very different from what it was five years ago, she says. So other than keeping yourself up-to-date with new technologies, cloud engineers need to have a good understanding about what a product and application in the cloud is doing in order to build the ideal infrastructure to support it.

In todays reality, she says cloud engineers also need to understand where their crown jewels are; that will allow them to secure the most valuable data and services from internal and external threats.

Demuth says a general knowledge of datacenter architecture and design principles is also important. Although many businesses are migrating to the cloud, many still rely on on-premises solutions; chances are good youll be working within a hybrid environment, including localized servers and hardware.

Dont be overwhelmed by the vastness of vendors, domains, and skills you see listed to become a cloud engineer, he advises. While it is a lot, it is absolutely doable if you take it one step at a time.

As you begin your training journey, Demuth recommends leveraging CSPs free tier to open accounts and build things. Find open-source projects and challenges to build out environments and complete them, he says. It doesnt matter if your work sucks at first, just start getting the experience.

If youre able to afford it, prioritize your budget for self-paced online learning courses and potentially a conference or two (if possible). And make sure to document all the projects you work on: when it comes time to apply for jobs, a portfolio of work can really impress a hiring manager and/or recruiter.

In terms of a portfolio, dont be afraid to show off your personal work, even if its just some code on GitHub. This will both make you think through what you did, and why, to reflect on your strengths and weaknesses, and will pay off later in interviews as you can share that work with potential employers to see your progression and commitment, Demuth says.

Shamban points out that all the big cloud providers have free training, labs, and workshops; some will even give you a few hundred dollars in credit to start exploring and playing around.

Take one of the labs and start building your projects, she says. But dont forget to shut down your cloud assets when youre done, because these bills add up.

Demuth notes its important to make sure you truly understand what value cloud offers over other types of systems and why. Ask yourself where and how it adds or subtracts value from the mission objectives youre working on and the problems youre trying to solve, he says. Understand alternatives, and when and why they may be more suitable.

Above all, he says, stay curious, and continue to set time aside throughout the weeks and years to keep up on whatever Amazon, Microsoft, Google, Oracle, and other vendors produce next. It may not be critical for you to become an overnight expert on everything new, but cloud is a rapidly changing landscape and you dont want to be fully caught off guard with changes, Demuth says.

Curious to find out more about the state of the tech job industry? Youve got the questions and weve got the answers. Tune in here.

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UH Mnoa engineering honored for excellence in education and workforce development | University of Hawaii System News – University of Hawaii

From left, Ed Barnabas, Booz Allen Hamilton; Song K. Choi, College of Engineering assistant dean; Kimberly Perez Hults, College of Engineering director of marketing and outreach relations; and Julie Morikawa, president of ClimbHI

The University of Hawaii at Mnoa College of Engineering was recognized as a top business in 2022 in education and workforce development by Hawaii nonprofit ClimbHI.

The inaugural ClimbHI Bridge Awards Brunch was held on October 12. The event recognized top participants on the ClimbHI Bridge online portal, which is used by 560 businesses across the state in an unprecedented public-private partnership. The bridge links educators, students, businesses and organizations to provide educational and workforce development opportunities.

Utilizing the ClimbHI platform this past year has allowed us to expand our outreach efforts to a wider swath of schools and classrooms throughout Hawaii and allow us to efficiently and effectively connect with STEM educators seeking classroom presenters, mentorship, expert judging, and other support for their students, said Kimberly Perez Hults, College of Engineering director of marketing and outreach relations. Our team of student ambassadors, along with other students, faculty and staff, have really stepped up to the plate to meet these requests, having logged many hours engaging in these activities both virtually and in person. We are thrilled to be a ClimbHI top contributor and appreciate everything they are doing to build these critical industry-to-education connections.

UH Mnoas College of Engineering joined 19 others in the top business category, including The Queens Health Systems, YMCA of Honolulu and HMSA.

These awardees and our hundreds of opportunity providers have helped reach nearly 57,000 students and 4,000 educators from 190 Hawaii schools statewide since the launch of ClimbHI Bridge in January 2021, said Julie Morikawa, president of ClimbHI. We are grateful for their continued support as we strengthen educational and career opportunities for our keiki right here in Hawaii.

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Stewart Kline named ‘Highway Engineer of the Year’ – wlfi.com

TIPPECANOE COUNTY, Ind. (WLFI)The Association of Indiana Counties recently named Stewart Kline its 2022 Engineer of the Year.

Kline has been executive director of the Tippecanoe County Highway Department since 2017.Before that, he owned a private engineering consulting firm.

In his 40-year career, Kline has been involved in many major road and bridge projects across the county.He says his favorite is Hog Point Bridge over the Tippecanoe River near Americus.The bridge is one of the few arch bridges in the area.

"It's a historic bridge and it was quite a project," Kline said. "Took the fill out of the old arches, rebuilt the light weight so we were able to widen the arches and restore them."

Kline also told News 18 that he also appreciates the artwork of the bridge.

"Transportation engineers, either in road or bridge, have a different take, see different things when you look at a bridge or road project," Kline said. "Most of the public just wants it to work and they miss the art. The beauty of the bridge."

The Association of Indiana Counties recognized Kline in South Bend during its annual conference.

Kline also thanked his dedicated staff at the highway department.

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Quantum Leap: "The big bang of quantum computing will come in this decade" – CTech

In the few images that IBM has released, its quantum computing lab looks like the engine room of a spaceship: bright white rooms with countless cables dangling from the ceiling down to a floating floor, pierced with vents. This technological tangle is just the background for the main show: rows of metal supports on which hang what look like... white solar boilers.

There, within these boilers, a historical revolution is taking shape. IBM, a computing dinosaur more than a century old, is trying to reinvent itself by winning one of the most grueling, expensive and potentially promising scientific races ever: the race to develop the quantum computer. "We are living in the most exciting era in the history of computing," says Dario Gil, Senior Vice President of IBM and head of the company's research division, in an exclusive interview with Calcalist. "We are witnessing a moment similar to the one recorded in the 40s & 50s of the last century, when the first classic computers were built." A few weeks after this conversation, his statements were further confirmed, when the Nobel Prize Committee announced the awarding of the prize in the field of physics to three researchers whose research served as a milestone in the development of the field.

The name Dario Gil shakes a lot of quanta and cells in the brains, and maybe even in the hearts, of physicists and computer engineers all over the world. This is the person who leads the most advanced effort in the world to develop a quantum computer. In September, when Gil landed in Tel Aviv for a short visit to give the opening lecture at the IBM conference, the hall was packed with senior engineers, researchers from the top universities in Israel, and representatives of government bodies - all enthralled by what Gil had to say.

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Dario Gil.

(Photo: Elad Gershgoren)

Gil (46) was born in Spain and moved to the United States to study at MIT University. He completed his doctoral studies there, and immediately after graduation began working at IBM in a series of research and development positions. Since 2019, he has been leading the company's research division, which has 3,000 engineers at 21 sites, including Israel. Under his management, in 2016, IBM built the first quantum computer whose services are available to anyone: if you have a complicated question, you can go to the IBM Quantum Experience website, remotely access one of the quantum computers through the cloud - and, perhaps, receive an answer. But as with everything related to quantum computing, it just sounds simple.

"Quantum computing is not just a name for an extremely fast computer," says Gill. In fact, he explains, the quantum computer is no longer a supercomputer that uses the same binary method that is accepted in every classical computer, but a completely new machine, another step in the evolution leading from strings of shells, through beaded invoices and calculating bars, to gear-based mechanical computers, to the electronic computer and now to the quantum computer. "Essentially, the quantum computer is a kind of simulator of nature, through which it is possible to simulate natural processes, and thus solve problems that previously had no solution," explains Gil. "If the classical computer is a combination of mathematics and information, then quantum computing is a combination of physics and information."

This connection makes it possible to solve certain types of problems with unprecedented speed: Google, which is also developing a quantum computer, claimed in 2019 that it had reached "quantum supremacy" a demonstration of a calculation that a quantum computer would perform more efficiently than a classical computer. The researchers at Google showed how a quantum computer performed in 200 seconds a calculation that they claim would have required a classical computer ten thousand years to complete. This claim has since been disproved by other researchers, who have presented an algorithm that allows a classical computer to perform the same calculation in a reasonable amount of timebut even this Google failure provides an idea of the enormous power a quantum computer will have.

"The quantum computer does not make the classical computer superfluous: they will live together, and each of them will solve different problems," explains Gil. "It's like asking you how to get from point A to point B: you can walk, ride a bicycle, travel by car or fly. If the distance between these points is 50 km, you won't fly between them, right? Accordingly, it is a mode suitable for a classic computer. A quantum computer allows you to fly, even to the moon, and quickly."

You will soon explain to me how it works, and in which areas exactly, but before that, let's start from the bottom line: what can we do with it?

"Quantum computing will make it possible to crack a series of problems that seemed unsolvable, in a way that will change the world. Many of these issues are related to energy. Others are related to the development of new and exciting materials. We tend to take the materials available to us for granted, but in the past there were eras that were defined by the materials that dominated them - The Stone Age', the 'Bronze Age', the 'Iron Age'. Quantum computing will help us develop materials with new properties, therefore the first sector that is already using it is industry, especially the car industry: the car manufacturers are interested in better chemistry, which will enable the production of more efficient and durable batteries for electric vehicles. For a normal computer this is a huge task, and to complete it we have to give up accuracy and settle for approximate answers only, but quantum computing can help quickly develop materials that will fit the task, even without entering the lab. The efficiency of a quantum computer when it comes to questions in chemistry is also used in the pharmaceutical industry, There they are beginning to make initial use of such computers to examine the properties of molecules, and in this way to speed up the development of new drugs; and also in the fertilizer industry, which will be able to develop substances whose production will not harm the environment.

The uses are not limited to the material world. "For the financial sector, for example, the quantum computer enables the analysis of scenarios, risk management and forecasting, and the industry is already very interested in such possible applications, which could provide the general public with dramatically improved performance in investment portfolios, for example.

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IBM.

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At the same time, there are industries that quantum computing will force to recalculate their course, and the information security industry is at the forefront. The modern encryption systems (mainly RSA, one of whose developers is the Israeli Prof. Adi Shamir) are asymmetric: each recipient publishes a code that allows the information sent to them to be encrypted ("public key"), which includes the product of two large prime numbers that are kept secret. To decipher the encrypted information, this product must be broken down into factors - but without knowing what the initial numbers are, "this task would require a normal computer to calculate for many years," explains Gil. "However, for the quantum computer, such a calculation can be a matter of seconds."

There is a real threat here to an entire industry, the logic behind which has been built since the 1970s, and now suddenly the ground is cracking under it.

"True, a normal computer needs ten thousand years to solve an encryption that a quantum computer would solve in an instant. That is why the quantum computer threatens the world of cyberspace and encryption, which are the basis of all global information security. This is an example that is not related to physics or nature, but simply to the stronger and faster computing power of the quantum computer.

The computer that works against all the rules of intuition

To understand the power of the quantum computer, this concept, "quantum computing", must first be broken down. The first step is to stop thinking in the familiar concepts of one and zero. Forget about bits and binaries. The key to understanding quantum computing is the recognition that this dichotomy is not there: instead of the bit, quantum computing relies on a basic unit of information called a qubit (short for "quantum bit"). The qubit is simultaneously one, zero and everything in between.

This is the moment to stop and explain the theory that underlies the quantum computer, and which seems to go against common sense. "Quantum theory makes it possible to explain the behavior of very, very small particles," Gil explains. "At school we are presented with a model of an atom that looks like a planet, with a nucleus and electrons moving around, but at the beginning of the 20th century, this model turned out to be not very accurate." This happened when physicists such as Max Planck and Albert Einstein realized that light, which until then physics saw as a wave, also behaves as a particle - and the energy of this particle can only be described in "quantum" jumps, that is, as discrete packets. In the decades that followed, this theory was developed more and more, and proved to be effective in describing a variety of phenomena in the world of particles. And yet, its deep meanings remain obscure even today.

Such is, for example, the idea that a particle is in more than one place. According to quantum theory, a particle moving between two points moves simultaneously in all the paths between them, a state called "superposition". It's not that we don't know its exact location: it just doesn't have one. Instead, it has a distribution of possible locations that coexist. In other words, reality is not certain, but probabilistic.

And this is not the only puzzle posed by quantum theory. Another confusing concept is "entanglement", a situation in which several particles exhibit identical physical values, and respond simultaneously to a change in one of them, even if they are at a great distance from each other. Gil suggests thinking of it as tossing two coins: anyone who has studied statistics knows that the probabilities of getting a "head" or a "tail" on each of them are independent. But in the quantum model, if the coins (representing particles here) are intertwined, then tossing one of them will result in the same result in the other. "Einstein didn't believe in interweaving, and hated these patterns," Gil says with a smile.

Measurements that affect the results? A reality that is not absolute but statistical? Particles that become twins even at infinite distance? If these ideas sound puzzling, incomprehensible or counter-intuitive to you, you are not alone: "Whoever comes across quantum theory and is not left stunned, has not understood it," said the physicist Niels Bohr, Einstein's contemporary and his great nemesis, who won the Nobel Prize for his contribution to the development of the theory (Einstein, by the way, had reservations about Bohr's interpretation of the theory's conclusions). Another physicist who won the Nobel Prize for his contribution to the theory, Richard Feynman, commented on this when he said: "If you think you have understood quantum theory, you have not."

The same Feynman is the father of quantum computing: he wanted to simulate the behavior of particles, but due to the probabilistic nature of the theory, a classical computer that would try to perform such a simulation would require an enormous amount of calculations, so that the simulation would become impractical. "Feynman, and like him other physicists, thought that the field of computing focused on mathematical horizons and moved too far away from nature, and that physics could be more connected to the world of information," explains Gil. "In a historic lecture he gave in 1981, Feynman claimed that there was nothing to give a classical computer to deal with particle simulation, because nature is not classical. He said, 'If we want to simulate nature, we need a machine that behaves like nature, in a quantum way.'" In 1998, this vision was realized, when the first quantum computer was built at the University of Oxford in Great Britain.

A quantum computer utilizes the enigmatic properties of quantum theory, those that are not fully understood by us, to perform calculation operations. In a normal computer, the basic unit of information is a "bit", which can have one of two values, 0 or 1; Using such bits makes it possible to perform any calculation imaginable - although some of these calculations may take a very long time. In a quantum computer, the qubit, thanks to superposition, represents not one absolute value, but a distribution of values. "You can think of it as a question of more dimensions: one and zero are just the ends, the poles of a coin for example, but it can also have a sideways tilt," explains Gil. Using statistical approaches it is possible to examine the state of the qubit and obtain useful results. This probabilistic approach is not suitable for every problem, but in solving certain problems it is infinitely more efficient than the classical computer's search for an absolute answer.

"Because of the entanglement effect, it is also possible to cause the qubits to influence each other," says Gil. And since each qubit represents an entire field of possibilities, each addition of a qubit increases the number of possible connections between the qubits with exponentially increasing power (in the classical computer, on the other hand, the addition of bits grows linearly). At the moment, IBM holds the record for qubits: last year it unveiled a quantum processor with 127 qubits, and its stated goal is to launch a processor with 433 qubits this year, and a processor with 1,021 qubits next year.

Three degrees colder than outer space

This ambition is more pretentious than it seems. It turns out that "building a machine that will behave like nature" is a complex story like no other: the qubits are very sensitive to outside influences, which makes building a computer a very complicated and expensive business. "The quantum computer is very powerful, but at the same time also very delicate," explains Gil: "It utilizes physical processes that occur in the world, but such processes are a system in which everything is connected, everything affects everything, and this can disrupt the results: if energy from the outside world goes inside and connect to the qubits, this will make them behave like normal bits, and thus the unique ability of quantum computation will be lost. Therefore, a quantum computer must be very isolated from the entire environment. The big challenge is to produce a system that is sufficiently isolated from the outside world, but not too isolated."

When I try to find out what the cost of building a quantum computer is - and IBM has already built 40 of them - Gil avoids a clear answer, but it is enough to hear what this effort entails: "There are several different approaches to building a quantum computer; IBM chose a cryogenic approach, meaning deep freezing, and the use of superconductors. The temperature in the computer is close to absolute zero: at the bottom of its case the temperature is minus 273 degrees Celsiusthree degrees less than the temperature of outer space, and less than one degree above absolute zero. The temperature should be close to absolute zero, but not reach it, because then there is no movement at all, Not even of the atoms."

The result is a cooling and protection case that resembles a water heater in its shape, and inside it has the calculation unit, whose shape gave it the nickname "chandelier" according to Gil and his team. "Inside the layers of protection there is a cylinder with the processor in it. Even if only a fraction of an energy particle enters the computer, literally a fraction of nothing, it will be enough to disrupt the results," Gil clarifies.

The great sensitivity, and the protection requirements derived from it, mean that the quantum computer is quite cumbersome: in the newest models, which try to include more and more qubits, the case already reaches a height of several meters. To some extent it is reminiscent of the first generations of classic computers, which looked like huge cabinets. Those classic computers kept getting smaller and smaller, until today we squeeze millions of times more computing power into a simple smartphone, but in the case of quantum computers, we cannot expect a similar process: "The quantum computer requires unique conditions that cannot be produced in a simple terminal device, and this will not change in the foreseeable future," Gil explains. "I believe that quantum computing will be a service that we can access remotely, as we access cloud services today. It will work similar to what IBM already enables today: the computer sits with us, and we make it possible to access the 'brain' and receive answers. Of the 40 computers we have built since 2016, today 20 are available to the public. About half a million users all over the world have already made use of the capabilities of the quantum computer we built, and based on this use, about a thousand scientific publications have already been published."

Google and Microsoft are heating up the competition

IBM is not the only company participating in the quantum computing race, but Gil exudes full confidence in its ability to lead it: according to him, most competitors only have parts of the overall system, but not a complete computer available to solve problems. Google, as mentioned, is a strong contender in this race, and it also allows remote access to its quantum computing service, Google Quantum AI; Microsoft is also working to provide a similar service on its cloud platform, Azure.

Meanwhile, quantum computing is a promise "on paper". The theoretical foundations for this revolution were laid already 40 years ago, the first proofs were presented more than 20 years ago, the industry has been buzzing around this field for several years - and we still haven't seen uses that would serve a regular person.

"If you go back to the 1940s, when the first computers were invented, you will see that even then the uses and advantages of the new invention were not clear. Those who saw the first computers said, 'Oh, great, you can use it to crack the code of encryption machines in wars, maybe even calculate routes of ballistic missiles, and that's it. Who's going to use it? Nobody,'" Gil laughs. "In the same way, the success of quantum computing will depend on its uses: how easy it will be to program, how large the community of users will be, what talents will get there. The quantum revolution will be led by a community, which is why education for this field is so important: we need more and more smart people to start to think 'how can I use quantum computing to advance my field'.

"What is beginning these days is the democratization phase of quantum computing, which will allow anyone to communicate with the computer without being an advanced programmer in the field: it will be possible to approach it with a question or a task that will be written in the classical languages of one or zero. That is why we are already seeing more use of quantum computing capacity today.

"There are also many startups that do not actually work to establish a quantum computer, but focus on various components of this world (for example, the Israeli company Quantum Machines, which develops hardware and software systems for quantum computers, and last July was selected by the Innovation Authority to establish the Israeli Quantum Computing Center). The activity of such companies creates a completely new ecosystem, thus promoting the industry and accelerating its development, just as is happening today in the field of ordinary computers. IBM will not rely only on itself either: we would like to benefit from the innovation of smart people in this field, of course also in Israel.

"I am convinced that the big bang of quantum computing will happen in this decade. Our ambition at IBM is to demonstrate 'quantum supremacy' already in the next three years. I believe that the combination of advances in artificial intelligence, together with quantum computing, will bring about a revolution in the industry of the kind that Nvidia made in its market (Nvidia developed unique processors for gaming computers, which made it the chip company that reached a billion dollar revenue the fastest.) Quantum computing can generate enormous value in the industry. It is phenomenally difficult, but it is clear to me that we will see the uses already in the current decade."

The Nobel Prize opens a new horizon for quantum computing

Quantum computing has ignited the imagination of researchers for many decades, but until now it has not left the confines of laboratories. However, the awarding of the Nobel Prize to three researchers in the field indicates that the vision is becoming a real revolution. Alain Aspect of France, the American John Clauser and Austrian Anton Zeilinger received the award for research they conducted (separately) since the 1970s, in which they examined the phenomenon of quantum entanglement (described in the article), proved its existence and laid tracks for its technological use.

The awarding of the Nobel Prize to the entanglement researchers proves that quantum computing is more than a mental exercise for a sect of physicists, and is a defining moment for companies that invest capital in the development of the field. They are pushed to this effort due to a fundamental change in the world in which they operate: in recent decades, the world of computing has operated according to "Moore's Law", which foresees that the density of transistors in computer processors will double every two years in a way that will increase the computing power of these chips. However, as the industry approaches the physical limit after which it will be impossible to cram more transistors onto a chip, the need to develop a quantum computer has become acute.

The numbers also signal that something is happening in the field. In 2020, the scope of the quantum computing market was less than half a billion dollars, but at the end of 2021, in a signal that the vision is beginning to be realized, the research company IDC published an estimate according to which in 2027 the scope of the market will reach $8.6 billion and investments in the field will amount to $16 billion (compared to $700 million in 2020 and $1.4 billion in 2021). IBM CEO Arvind Krishna also recently estimated that in 2027 quantum computing will become a real commercial industry.

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Quantum Leap: "The big bang of quantum computing will come in this decade" - CTech

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Podcast with Yianni Gamvros, Head of Business Development at QCWare – Quantum Computing Report

Yianni Gamvros, Head of Business Development at QCWare is interviewed by Yuval Boger. Yianni and Yuval talk about Q2B, the annual trade show that QCWare produces, intellectual property ownership when providing professional services, the importance of investments in software benchmarking, and much more.

Yuval: Hello, Yianni, and thanks for joining me today.

Yianni: Hi, Yuval. Its great to be here.

Yuval: So who are you, and what do you do?

Yianni: So my name is Yianni Gamvros. Im the head of business development for QCWare. So I handle all of sales and business partnerships and marketing for QCWare, and I also handle all of the decisions and all of the execution and the management that goes behind Q2B.

Yuval: So Q2B is a trade show that QCWare organizes, right? And this is now its fifth year? Sixth year?

Yianni: Its actually its sixth year. So actually, our CEO, Matt Johnson, started the show back in 2017. Back then, there were really no other business shows that dealt with quantum computing. So pretty much everyone that was interested in quantum computing would meet at the academic conferences. And those conferences are typically made for technical talks. And he had the insight to realize that we really need a place where business people can meet and can understand the value proposition for quantum computing at a high level and can understand potential use cases, ROI.

But obviously, the technical credibility of the show is also important, and having talks and speakers that are credible is also important. So Q2B tries to essentially be both a place for business people to understand the value proposition, but also we invite technical speakers and some technical talks to inform, essentially, on the technical aspects as well.

Yuval: How much has it grown? How many people were, if you know, on the first show, and how many do you expect this year?

Yianni: Yeah, so its been quite impressive, and it has really grown beyond our expectations. So the first show had about 250 attendees, and this last show that we did in Silicon Valley had 609 attendees.

It was the first in-person show we had after the virtual show in 2020. So the virtual show, obviously, had more attendees. We were up to a thousand, but we quickly returned back to an exclusively in-person format in 2021. It was actually a little bit aggressive to do it in 2021. We managed to do it even though it was a little bit risky, and we fell between the Delta and Omicron waves, but still had a very good attendance. And the show actually has grown now. For the first time this year in 2022, we went to a different geography. So we just had a successful show in Japan. So we had Q2B 22, Tokyo, which also had 370 attendees.

Yuval: So the show aside, how has the quantum computing industry changed, in your mind, over the last one or two years?

Yianni: Yeah, so its been unbelievable. The amount of new people coming into the industry, the startups, the announcements and the projections, its impressive. I think its much more professional. Were now getting to the point where we have projections and roadmaps from both software and hardware vendors. And I think thats interesting because now it means that people have a stake on the ground, and theyre making projections of what the technology will be able to do and what their products are going to be able to do. And now, its basically hard to say exactly where we are, but its always important to have these projections because you can always go back and look back at the last year or last two years and say, Okay, I know where the projections were two years ago, and I can see where we are today.

So I think thats going to play out over the next couple of years where were going to be able to say, Okay, well, these hardware roadmaps were good, or maybe they were too optimistic, or maybe they were pessimistic, or they were just about right. But well see.

Yuval: To me, Q2B is a great show and a great service that youre doing for the industry, but I know that QCWare does many other things except Q2B. So could you speak about those a little bit?

Yianni: Of course, of course. Yes.

So QCWare is primarily a quantum computing software startup. So we build quantum algorithms and quantum applications that run on quantum computers and deliver, essentially, the promised value of quantum computing. So Q2B, as you just said, its basically one of our three go-to-market areas and one of our three, essentially, business lines. The other two being professional services for quantum computing and software for quantum computing.

So for professional services, what we typically do is we talk to large enterprises, large industry end users in finance, pharma, automotive, aerospace, many other industries. And we advise them on how quantum computing will potentially disrupt their different business processes and what they can do to get ready for this upcoming computing disruption. And this might be in the form of a workshop, some educational workshop in the beginning, or use case discovery. It might be a little bit more advanced where we do some proof of concept, applying a known quantum algorithm to their data and looking at the results. Or the most advanced thing that we do for many of our clients are these joint development engagements where we effectively act as an augmented research R&D arm to their current R&D program. And we engage in active research, we try to break new ground, we try to do things that havent been done before, and design new algorithms that can run on quantum computers and deliver value.

And in many cases, these engagements have led to publications on very significant journals and have led to patents and have led to maybe also some press for both us and the customer. And so we are very happy to, basically, be able to do all these kinds of professional engagements for our customers.

So this was the professional services side that I just talked about. The other thing that I mentioned is software, because primarily we want to be a software company. And we already have a software product, its called QCWare Forge. And QCWare Forge right now runs on Amazon Braket. And its essentially an algorithmic layer, an application layer for quantum algorithms and quantum computing on top of Amazon Brakets platform as a service layer.

So we take all the algorithms and all the knowledge that we discovered during the professional service engagements that I just mentioned earlier, and we distill that into our software product. We package it, and we make it readily available for everyone thats coming fresh and new into quantum computing and even advanced users to, basically, see what weve done for other customers, see what the new algorithms can do and how they can execute and then use the Amazon Braket infrastructure to be able to run that either in simulators or on real hardware.

Yuval: When you spoke about the professional services, you mentioned that one of the outcomes sometimes are patents. And Im curious, what do you do with the IP? Meaning, when a customer brings you in, wouldnt they want to keep the IP thats generated from a project? Or is it somehow shared between QCWare and the customer?

Yianni: Great question. Yeah, so we always go in and we try to have this discussion as early as possible. Sometimes we have it on the very first call because this does come up. So everybody has this question, and its good to basically clear the air very, very early on.

So our position is that we like for the customer to be able to use the IP thats generated, for ground IP thats generated through a professional service engagement. But we also like to use the IP in any way, basically, that we want. So we like to be able to put the new IP into product and potentially resell it to other customers.

And obviously, this takes some negotiation with the procurement and the legal on the customer side, but its typically something that we can achieve because we are in such a niche space that our engagements with these customers are not treated as traditional professional services engagements. Were doing something thats very unique. We bring expertise to the table thats also very unique and very scarce, actually. And therefore, the customer realizes that they do want us to partner with them. And this is a red line that we are putting in there that, Hey, look, if we cant use the IP thats generated out of the engagement, then we are not basically going to engage.

Yuval: Excellent. Thank you for clarifying that. I wanted to ask both about the types of industries. Is there one or two industries that you see more often than others coming into quantum computing? And also curious about the stage. Do people come and say, Weve heard about quantum. We dont know for sure what its going to do for us, please help us. Or have they seen a competitor or seen an article someplace and say, Oh, this is the algorithm we need it implemented. Where do they come in and from? What verticals do they come in?

Yianni: Yes, yes, great question. So yeah, so I think the most mature industry is finance. So we see a lot of different finance players, basically, have very mature quantum computing programs. And we actually see new entrants, basically, coming to the market and very quickly set up dedicated quantum computing teams that are looking into quantum computing, basically, 100% of the time.

I think the next one potentially is automotive, where we again see several players having dedicated quantum computing programs. Maybe pharma comes next. And maybe then you have a few other places like energy, aerospace. To a lesser extent, you have materials, and to a lesser extent, you have pretty much every other industry like telcos, utilities, and everything else.

And to answer the second part of your question, we do see, in some cases, especially with finance and in some cases with pharma, companies coming in and actually dealing with it very strategically and putting in charge of a person thats going to be a quantum computing director, and they give this person headcount, and they can start setting up basically a program for the company. And in those cases, the discussion is more mature. They typically hire people with some quantum computing expertise, and you typically have discussions at a deeper technical level.

But as you say, there are some companies that are coming in fresh and just want to test the waters, and they might not have anyone thats dedicated. They might just have someone in the innovation department or R&D department that has a little bit of a budget to play around or is willing to play around with a vendor and some experiments. And in those cases we might do something thats a little bit simpler and a little bit more short-term just to give them an idea, basically, of what quantum computing looks like and what are the approaches, what can the hardware do at this stage and so on and so forth.

Yuval: Do you see customers preparing to use shrink wrap software? I mean, if there was sort of algorithm as a service, here is my route table and show me what the best traveling salesperson solution is. Or do they prefer to try and write their own software and their own algorithms? Which one do you see more common?

Yianni: Oh, we typically see a little bit of both because the two customers that I just described, the more mature ones, want to be more hands-on and want to design their own algorithms. And the ones that are just maybe testing the waters, maybe have an interest a little bit in also seeing the shrink wrap version and the black box version.

And frankly, my belief is that the shrink wrap version and the black box version is the one thats going to dominate and the one that we as an industry need to move towards. We cannot expect people to write quantum circuits. I think its absurd. And again, if you look back at the history of the computing space, obviously, thats how computing started by writing these very low-level statements. But it has quickly moved on, I think quantum computing will do the same in the future.

I guess I can conclude that by saying that in the meantime, quantum computing researchers need to have hands-on tools and basically dive deeper to technical tools and be hands-on on the code.

Yuval: Whats your best estimate of the time for quantum advantage? When people go beyond, Oh, Im playing with the technology, to, I can move it into production. Is it two years? Is it 10 years?

Yianni: Yes. So we do have a perspective on that. QCWare has a strong perspective on what will be the first application to exhibit quantum advantage. And we think thats in chemistry simulation. We think its going to take a few years, for sure. We think that with a few hundred qubits and several nines of fidelity on the operations for those qubits, we will be able to get to a point where we can do something that classical computers cannot. And we think in chemistry this is doable, as I said, with a few hundred qubits because there are some exotic chemistry simulation problems, some exotic materials that classical methods simply cannot simulate them. And so we think thats the most near-term application.

Then all the other applications that people talk about, we are still confident. I mean, were optimists, obviously, and thats why were in the space because we believe that quantum computing will change the world and it will impact other areas like optimization, machine learning, other simulations, Monte Carlo simulations, and partial differential equations. But we think those are a little bit further out. Probably in the five-plus year timeframe.

Yuval: Lets assume, for the sake of discussion, that the first application would be ready for production in three years. Thered be enough qubits, theyd be good enough, the software is there. What do you say to customers that say, Well, if its three years away, call me back in two years, and then well talk.

Yianni: Great. Yeah, great question. And it always comes up, and my answer is this. I always challenge back with another question to the customer where I ask them, Well, how long did your last digital transformation initiative take? And typically, when they think about that, the answer is actually 3, 4, 5, or more years. So if people think back to how long it took to bring in the right data scientists within their organization, essentially get those scientists situated, trained, expose those data scientists to different business processes, to business domain experts within the organization and let them build initial proof of concepts and then move those proof of concepts into production, then that takes a lot of time. That takes more than just three or four or five years.

And so in fact, for chemistry, our position is that, hey, look, if you want to actually be impactful when the first quantum computers arrive and be able to take advantage of that in the market, then in some sense, you might already be late. For machine learning and for, optimization and some of these other techniques, youre probably just in time. If you start now for chemistry, youre probably already a little bit behind if in fact happens in three years.

Yuval: As we get closer to the end of our conversation today, Im curious, if you had a magic wand, what would you want the industry to do that its not doing today? Is it more collaboration? Is it to work on something more than the other? Whats your wish for the industry?

Yianni: Yeah, great point. So I have a wish for the government organizations and the government policy, basically, that is supporting quantum computing in a big way. And actually, thats a great thing. But I think a lot of the focus for those initiatives goes into hardware. And obviously, yes, we do need the hardware. You cant run any of these things without the right hardware. And hardware does need to improve, and the faster it improves, the better off everyone is going to be. But obviously, being on the software side and seeing also the advances that software can make, I think there needs to be some proportional investment on the software side as well.

Many, many times we as a software company, we see that all these programs are really 100% dedicated to hardware. And there are many, many things, there are many, many open questions that software can answer, and there are many ways that software can, and software companies can benefit from the right policies and the right investment.

So thats the one thing on the government side. Now the other thing, potentially, also for these government or other consortium or maybe other vendors is the generation of use case-based benchmarks. So we again, we see a lot of benchmarks and a lot of metrics that concentrate on hardware qualities. And again, this is important. And its good to have multiple metrics. Its probably good to have diverse metrics and different metrics covering essentially different areas. Its impossible in a very complicated field like ours to have a single metric that covers everything. And its also important to have benchmarks for the hardware, specifically, for the hardware as well.

But its also very, very important to start having some use case-specific benchmarks where software vendors can also basically compete and say, Okay, we can do this better. We can load on a quantum computer an image of this size with our software, and the other company can load an image thats smaller maybe or larger and compete on that. Or, We can maybe train quantum neural network this quickly on so many steps and this is the accuracy we get on this quantum neural network. Or we can maybe price an asset, a derivative in so many steps to this accuracy and drive really to the specific metrics that the industry is looking to us to provide for specific guidance.

So the industry end users really dont care about number of qubits, they care about how big of a molecule I can simulate, how complex of a derivative I can price and so on and so forth. So we need to put the benchmarks, basically, in those terms and provide those kinds of benchmarks.

Yuval: Benchmarks. Very interesting. My next to last question, could you tell me about your personal journey? How did you get into quantum computing?

Yianni: Yeah, thats quite interesting. So I have a technical background. So I have a PhD in operations research. I started my career doing professional services, doing consulting for a company that built, basically, a software company that build an optimization solver. And I was one of the consultants that would go out and try to build decision support software for different types of industries, transportation systems and manufacturing. So we would build basically optimization solutions that would try to increase the throughput of a manufacturing plant or try to help with transportation dispatchers, basically, dispatching trucks or planes or what have you.

Then we got acquired by IBM. So this company, its name was ILOG, got acquired by IBM. And then, when we got acquired by IBM, I started moving, as I say to the dark side. So started going more into sales and business development. And slowly, within IBM, I moved to some sales leadership roles.

And at that time Im getting, out of the blue, a LinkedIn message from Matt Johnson, the CEO of QCWare saying, Hey, Im in Palo Alto, do you want to join me for coffee? And I look up this guy and hes a CEO for quantum computing startup. And that was so foreign at that time. I mean, that was maybe 2016 when there was very little in the news about quantum computing. IBM still not had not announced, basically, its quantum computing program. It was so, so, so early. And very, very few people were in quantum computing. It was not really the hype machine maybe that it is right now.

And I was this close to, basically, denying the invitation, but then I said, Okay, Ill go for coffee, doesnt hurt. And the first conversation was also not very promising. So basically, Matt explained to me, Hey, look, I know that youre positioning these optimization solutions to these big corporations and quantum computers will be able to solve these optimization problems in the future. And tell us how you basically talk to these corporate entities about what optimization can do and how you position the solutions and how you get customers.

And start to talking to them, but very quickly realized that theyre talking about very small problems. I mean, 10 variables. And this was in the beginning for me, it was incomprehensible that someone would try to set up a business where the biggest problem that can be solved is maybe 5 variables or 10 variables. And at the time, classical optimization could already solve problems of hundreds of thousands of variables. And those were the real problems that people wanted to solve. But then slowly we had a few more discussions. I started reading up more on quantum computing, and captured my imagination and the possibilities and all of that. And then, almost a year and a half, close to 2 years later, we talked about potentially moving over to QCWare to deal with sales and handle sales. And at the time, I had drank the Kool-Aid and was happy to join, basically.

Yuval: Excellent. So how can people get in touch with you to learn more about your work?

Yianni: Absolutely. My email is yianni.gamvros@qcware.com. You can reach out to me on Twitter or LinkedIn, Yianni Gamvros, or Y. Gamvros, @YGamvros or you can submit an info request on QCWares info page. They come to me actually, so youll be reaching directly into me if you actually just email info@qcware.com.

Yuval: Excellent. Well, thank you so much for joining me today.

Yianni: Yuval, thank you so much for the very, very exciting and very interesting questions. Thanks.

Yuval Boger is a quantum computing executive. Known as the Superposition Guy as well as the original Qubit Guy, he most recently served as Chief Marketing Officer for Classiq. He can be reached on LinkedIn or at this email.

October 16, 2022

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Podcast with Yianni Gamvros, Head of Business Development at QCWare - Quantum Computing Report

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Meet the 20 finalists for EIT Digital Challenge 2022; one of them is Dutch – Silicon Canals

Image credits: EIT Digital

EIT Digital, a pan-European organisation that promotes innovation, education, and entrepreneurship in digital technology, has announced this years 20 finalists across Europe for its EIT Digital Challenge.

The finalists will pitch in front of a jury of experts and investors, and participate in a matchmaking session with invited corporates and investors. The winners will be announced at an event on October 27.

The winners will receive a waived entry into the 12-month EIT Digital Accelerator programme worth 50,000. In addition, they will get dedicated services in international access to finance and business development from the EIT Digital Accelerator team.

The EIT Digital Accelerator provides tailor-made growth support by helping participants raise capital, find customers, and scale up internationally. This is done through a distributed team of business developers and fundraising experts from 10 European countries.

Since 2012, the EIT Digital Accelerator has supported startups and scaleups from 18 countries. Together, these startups have raised over 1B in investment. The Accelerator has also been recognised as the worlds top public Business Accelerator by UBI Global, and as one of the top three accelerator brands in Europe by Startup Heatmap Europe.

Here are the 20 selected finalists for the EIT Digital Challenge 2022.

HQ: Luxembourg

Anisoprint is a hardware startup producing carbon fibre 3D printers. The printers can manufacture carbon-reinforced plastic parts that can substitute metal parts in aerospace and engineering areas, cutting costs and increasing productivity. The company works with various clients in sports, robots, quadcopters, medical prostheses and orthoses, and sports goods.

HQ: Munich, Germany

Build38 provides mobile application protection solutions and services including artificial intelligence and robust app shielding technology. The company claims that its solutions are easy to integrate and can be done in minutes.

The company protects applications across various industries, including automotive, banking, insurance, public transportation, and healthcare.

Based out of Munich, the company has offices in Barcelona and Singapore.

HQ: Bressanone, Italy

Covision Quality is a spinoff of Covision Lab and works with its research and institutional partners. The company has developed software for automating and scaling visual inspection and defect detection on metals and plastics through computer vision and machine learning.

Covision claims that its customers can increase time to inline deployment by 20x and reduce pseudo scrap rates by up to 90%.

HQ: London, UK

Daye is a femcare startup offering healthcare products designed with women in mind. The companys new product is a tampon using CBD to handle period cramps, aka dysmenorrhea. CBD is an extract from the flower of the industrial hemp plant and is a legal marijuana relative.

HQ: London, UK

Elemendar has developed an Artificial Intelligence capability READ application that reads human-authored cyber threat intelligence and translates it into machine-readable industry-standard structured information (STIX & MITRE ATT&CK). The companys solution enables clients to understand and defend against new threats faster.

HQ: London, UK

Faradai Energy Intelligence Platform is an AI and cloud-based PaaS data analytics solution for commercial buildings, industrial facilities, and renewable energy plants. Through machine learning algorithms and big data analytics, Faradai provides energy saving, operational efficiency, energy procurement optimisation, predictive maintenance, solar energy, and sustainability management for its customers.

HQ: Eindhoven, the Netherlands

Founded by Mark Linders and Chantal Linders, Dutch company Greenhabit was launched within the EIT Digital Innovation Factory to help people with diabetes and cardiac conditions stick to their rehabilitation programmes.

The company employs a scientific approach to behavioural change. By providing daily activities and rewarding progress, the app employs gamification to keep users interested. In addition, Greenhabit can pinpoint patient requirements using AI to address the root cause of bad behaviour.

HQ: Vienna, Austria

Based out of Vienna, JENTIS is a server-side tracking tool that helps businesses extract complete, accurate, and consistent raw data to accelerate their growth. The Austrian company developed the SaaS solution to reduce errors and deviations in web analytics tools and to streamline operations.

HQ: Helsinki, Finland

Loupedeck manufactures customisable consoles designed to optimise productivity and maximise creativity through interactions with creative software.

The companys product line-up includes Loupedeck+, Loupedeck Live, and Loupedeck CT.

Each console is custom-designed to support various workflows, including photo and video editing, audio composition, graphic design, content creation, and live streaming.

HQ: Madrid, Spain

Based out of Madrid, Meep has developed MaaS solutions in the form of mobile applications in which all modes of transport available in a city, public and private, are integrated.

The company aims to combine traditional public transport services with new micro-mobility to put the citizen in the centre of public transport, radically improving their digital experience.

Through the app, the Spanish company provides digital solutions for Transit Authorities, Transit Operators, and Mobility Service Providers to create an interconnected mobility ecosystem.

HQ: Paris, France

Medicalib is an online portal that helps find health professionals, nurses, physiotherapists, and midwives in less than an hour.

HQ: London, UK

MiiCare is a social enterprise company that has developed a digital health coach, Monica, to support older adults (physically and emotionally) to live a healthier, safer, and happier life, and ease the pressure on their families and caregivers.

HQ: San Sebastin, Spain

Multiverse Computing provides software for companies from the financial industry to help them gain an edge with quantum computing. It combines quantum and quantum-inspired solutions to address complex open problems in finance by demonstrating industry use cases to bring value to financial institutions.

The companys flagship product, Singularity, enables financial professionals to run efficient quantum algorithms on any quantum computer from a simple spreadsheet to address highly complex problems such as portfolio optimisation and fraud detection without requiring any knowledge of quantum computers.

HQ: Barcelona, Spain

Outvise is an online talent marketplace for Business Tech freelance experts.

The platform connects companies with highly skilled freelance experts and management consultants to address their talent gaps across all functional areas, from strategy, marketing, and sales to operations, technology, and IT, in a fast and cost-effective way.

HQ: Berlin, Germany

Parloa is a Conversational AI platform for automating omni-channel customer services like phonebot and chatbots. The companys solution allows customer concerns, primarily on the phone, to be identified within seconds and repetitive tasks to be automated. Through this solution, Parloa aims to help every company worldwide to have better customer conversations.

HQ: Espoo, Finland

Sellforte is a marketing mix modelling platform serving companies to measure marketing ROI and plan scenarios for future media investments.

HQ: Stockholm, Sweden

Based out of Stockholm, Snafu is a full-service record label built on AI music discovery. To discover talent, the platforms proprietary algorithms analyse open platforms, including Spotify, SoundCloud, Youtube, and TikTok.

Then, as per the companys claims, the solution predicts which artists are likely to be popular, depending on sentiment analysis, song structure, decision trees, and neural networks.

HQ: Barcelona, Spain

Vottun focuses on helping companies adopt blockchain technology to improve their current business processes and create new business models.

The company has developed a platform that provides different blockchain ready-to-use solutions and APIs to create value. Currently, in the public blockchain, the company supports Ethereum, Stellar, Algorand, Ethereum Classic, Bitcoin, and Inmutable X (only for NFTs).

HQ: Warsaw, Poland

WorkTrips.com (previously Hotailors) is a next-gen AI-powered travel platform. The platform organises business travels that grant access to real-time offers from 2,000,000+ hotels and 700+ airlines worldwide. The company says that with its platform, businesses can easily control their travel policy, reduce spending and increase the efficiency of their company.

HQ: Rome, Italy

W.SENSE is a deep-tech telecommunication company, born as a spinoff of Sapienza University in Rome. It specialises in underwater monitoring and communication systems based on IoUT solutions.

Catch our interview with Paul Down, Head of Sales at Intigriti.

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Meet the 20 finalists for EIT Digital Challenge 2022; one of them is Dutch - Silicon Canals

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