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Parasoft C/C++test is honored for its leading technology to increase software engineer productivity and achieve safety compliance

MONROVIA, Calif., April 7, 2020 /PRNewswire/ --Parasoft, a global software testing automation leader for over 30 years, received the VDC Research Embedded Award for 2020. The technology research and consulting firm yearly recognizes cutting-edge Software and Hardware Technologies in the embedded industry. This year, Parasoft C/C++test, aunified development testing solution forsafety and securityof embedded C and C++ applications, was recognized for its new, innovative approach that expedites the adoption of software code analysis, increasing developer productivity and simplifying compliance with industry standards such as CERT C/C++, MISRA C 2012 and AUTOSAR C++14. To learn more about Parasoft C/C++test, please visit: https://www.parasoft.com/products/ctest.

Parasoft C/C++test is honored for its leading technology to increase software engineer productivity and achieve safety compliance

"Parasoft has continued its investment in the embedded market, adding new products and personnel to boost its market presence. In addition to highlighting expanded partnerships and coding-standard support, the company announced the integration of AI capabilities into its static analysis engine. While defect prioritization systems have been part of static analysis solutions for well over ten years, Parasoft's solution takes the idea a step further. Their solution now effectively learns from past interactions with identified defects and the codebase to better help users triage new findings," states Chris Rommel, EVP, VDC Research Group.

Parasoft's latest innovation applies AI/Machine Learning to the process of reviewing static analysis findings. Static analysis is a foundational part of the quality process, especially in safety-critical development (e.g., ISO26262, IEC61508), and is an effective first step to establish secure development practices. A common challenge when deploying static analysis tools is dealing with the multitude of reported findings. Scans can produce tens of thousands of findings, and teams of highly qualified resources need to go through a time-consuming process of reviewing and identifying high-priority findings. This process leads to finding and reviewing critical issues late in the cycle, delaying the delivery, and worse, allowing insecure/unsafe code to become embedded into the codebase.

Parasoft leaps forwardbeyond the rest of the competitive market by having AI/ML take into account the context of both historical interactions with the code base and prior static analysis findings to predict relevance and prioritize new findings. This innovation helps organizations achieve compliance with industry standards and offers a unique application of AI/ML in helping organizations with the adoption of Static Analysis. This innovative technology builds on Parasoft's previous AI/ML innovations in the areas of Web UI, API, and Unit testing - https://blog.parasoft.com/what-is-artificial-intelligence-in-software-testing.

"We are extremely honored to have received this award, particularly in light of the competition, VDC's expertise and knowledge of the embedded market," said Mark Lambert, VP of Products at Parasoft. "We have always been committed to innovation led by listening to our customers and leveraging capabilities that will help drive them forward. This creativity has always driven Parasoft's development and is something that has been in the company's DNA from its founding."

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About Parasoft (www.parasoft.com):Parasoft, the global leader in software testing automation, has been reducing the time, effort, and cost of delivering high-quality software to the market for the last 30+ years. Parasoft's tools support the entire software development process, from when the developer writes the first line of code all the way through unit and functional testing, to performance and security testing, leveraging simulated test environments along the way. Parasoft's unique analytics platform aggregates data from across all testing practices, providing insights up and down the testing pyramid to enable organizations to succeed in today's most strategic development initiatives, including Agile/DevOps, Continuous Testing, and the complexities of IoT.

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Parasoft wins 2020 VDC Research Embeddy Award for Its Artificial Intelligence (AI) and Machine Learning (ML) Innovation - Yahoo Finance

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Machine Learning in Healthcare Market to Witness Tremendous Growth in Forecasted Period 2020-2027 - Bandera County Courier

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About Us

Market Research Inc is farsighted in its view and covers massive ground in global research. Local or global, we keep a close check on both markets. Trends and concurrent assessments sometimes overlap and influence the other. When we say market intelligence, we mean a deep and well-informed insight into your products, market, marketing, competitors, and customers. Market research companies are leading the way in nurturing global thought leadership. We help your product/service become the best they can with our informed approach.

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Machine Learning as a Service Market: Indoor Applications Projected to be the Most Attractive Segment during 2020-2027 - Bandera County Courier

When Machines Design: Artificial Intelligence and the Future of Aesthetics

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Are machines capable of design? Though a persistent question, it is one that increasingly accompanies discussions on architecture and the future of artificial intelligence. But what exactly is AI today? As we discover more about machine learning and generative design, we begin to see that these forms of "intelligence" extend beyond repetitive tasks and simulated operations. They've come to encompass cultural production, and in turn, design itself.

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When artificial intelligence was envisioned during thethe 1950s-60s, thegoal was to teach a computer to perform a range of cognitive tasks and operations, similar to a human mind. Fast forward half a century, andAIis shaping our aesthetic choices, with automated algorithms suggesting what we should see, read, and listen to. It helps us make aesthetic decisions when we create media, from movie trailers and music albums to product and web designs. We have already felt some of the cultural effects of AI adoption, even if we aren't aware of it.

As educator and theorist Lev Manovich has explained, computers perform endless intelligent operations. "Your smartphones keyboard gradually adapts to your typing style. Your phone may also monitor your usage of apps and adjust their work in the background to save battery. Your map app automatically calculates the fastest route, taking into account traffic conditions. There are thousands of intelligent, but not very glamorous, operations at work in phones, computers, web servers, and other parts of the IT universe."More broadly, it's useful to turn the discussion towards aesthetics and how these advancements relate to art, beauty and taste.

Usually defined as a set of "principles concerned with the nature and appreciation of beauty, aesthetics depend on who you are talking to. In 2018, Marcus Endicott described how, from the perspective of engineering, the traditional definition of aesthetics in computing could be termed "structural, such as an elegant proof, or beautiful diagram." A broader definition may include more abstract qualities of form and symmetry that "enhance pleasure and creative expression." In turn, as machine learning is gradually becoming more widely adopted, it is leading to what Marcus Endicott termed a neural aesthetic. This can be seen in recent artistic hacks, such as Deepdream, NeuralTalk, and Stylenet.

Beyond these adaptive processes, there are other ways AI shapes cultural creation. Artificial intelligence hasrecently made rapid advances in the computation of art, music, poetry, and lifestyle. Manovich explains that AIhas given us the option to automate our aesthetic choices (via recommendation engines), as well as assist in certain areas of aesthetic production such as consumer photography and automate experiences like the ads we see online. "Its use of helping to design fashion items, logos, music, TV commercials, and works in other areas of culture is already growing." But, as he concludes, human experts usually make the final decisions based on ideas and media generated by AI. And yes, the human vs. robot debate rages on.

According to The Economist, 47% of the work done by humans will have been replaced by robots by 2037, even those traditionally associated with university education. The World Economic Forum estimated that between 2015 and 2020, 7.1 million jobs will be lost around the world, as "artificial intelligence, robotics, nanotechnology and other socio-economic factors replace the need for human employees." Artificial intelligence is already changing the way architecture is practiced, whether or not we believe it may replace us. As AI is augmenting design, architects are working to explore the future of aesthetics and how we can improve the design process.

In a tech report on artificial intelligence, Building Design + Construction explored how Arup had applied a neural network to a light rail design and reduced the number of utility clashes by over 90%, saving nearly 800 hours of engineering. In the same vein, the areas of site and social research that utilize artificial intelligence have been extensively covered, and examples are generated almost daily. We know that machine-driven procedures can dramatically improve the efficiency of construction and operations, like by increasing energy performance and decreasing fabrication time and costs. The neural network application from Arup extends to this design decision-making. But the central question comes back to aesthetics and style.

Designer and Fulbright fellow Stanislas Chaillou recently created a project at Harvard utilizing machine learning to explore the future of generative design, bias and architectural style. While studying AI and its potential integration into architectural practice, Chaillou built an entire generation methodology using Generative Adversarial Neural Networks (GANs). Chaillou's project investigates the future of AI through architectural style learning, and his work illustrates the profound impact of style on the composition of floor plans.

As Chaillou summarizes, architectural styles carry implicit mechanics of space, and there are spatial consequences to choosing a given style over another. In his words, style is not an ancillary, superficial or decorative addendum; it is at the core of the composition.

Artificial intelligence and machine learningare becomingincreasingly more important as they shape our future. If machines can begin to understand and affect our perceptions of beauty, we should work to find better ways to implement these tools and processes in the design process.

Architect and researcher Valentin Soana once stated that the digital in architectural design enables new systems where architectural processes can emerge through "close collaboration between humans and machines; where technologies are used to extend capabilities and augment design and construction processes." As machines learn to design, we should work with AI to enrich our practices through aesthetic and creative ideation.More than productivity gains, we can rethink the way we live, and in turn, how to shape the built environment.

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When Machines Design: Artificial Intelligence and the Future of Aesthetics - ArchDaily

Awarded to recognize Google Cloud partners who have made a positive impact on the world

Quantiphi, an award-winning applied artificial intelligence and data science software and services company, announced today that it has been named 2019 Social Impact Partner of the Year by Google Cloud. Quantiphi was recognized for its achievements for working with nonprofits, research institutions, and healthcare providers, to leverage AI for Social Good.

We are believers in the power of human acumen and technology to solve the worlds toughest challenges. This award is a recognition of our mission driven culture and our passion to apply AI for social good, said Asif Hasan, Co-founder, Quantiphi. Partnering with Google Cloud has given us the opportunity to work with the worlds leading nonprofit, healthcare and research institutions and we are truly humbled by this recognition.

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Were delighted to recognize Quantiphis commitment to social impact, said Carolee Gearhart, Vice President, Worldwide Channel Sales at Google Cloud. By applying its capabilities in AI and ML to important causes, Quantiphi has demonstrated how Google Cloud partners are contributing to positive change in the world.

A few initiatives that helped Quantiphi earn this recognition:

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Quantiphi previously earned the Google Cloud Machine Learning Partner of the Year twice in a row for 2018 and 2017 and is a premier partner for Google Cloud and holds Specializations in machine learning, data analytics and marketing analytics.

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Quantiphi Wins Google Cloud Social Impact Partner of the Year Award - AiThority