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SAN FRANCISCO, Sept. 16, 2021 /PRNewswire/ -- MetricStream, the industry leader in supporting the Governance, Risk, and Compliance (GRC) space, and Golden Gate University, announced the successful completion of the first phase of their "DeepEdge" project, using emerging technologies to bring innovation to business solutions.

The project started in 2019 with the goal of letting GGU faculty and graduate students in the MS in Business Analytics and MS in Information Technologies programs partner with MetricStream employees to develop new risk management solutions. The teams set out to use emerging model-based AI augmented with Machine Learning, Elastic Edge Computing, Agile methodologies maturing to DevOps, and Zero-touch Self-Managing service orchestration. The teams have successfully implemented the first application to assess and mitigate risk in enterprise contract management process, resulting in MetricStream adopting it as a part of their product suite.

"Contracts are legally binding agreements," said Vidya Phalke, Chief Technology Evangelist at MetricStream. "Knowing the obligations for every contract, monitoring and assuring compliance is labor-intensive process and error-prone. The DeepEdge project uses model-based AI, machine learning and automation of extracting the knowledge of the obligations for every contract. It integrates with processes already in place and improves monitoring and contract obligation fulfillment at scale. This type of industry-academia collaboration is what is needed to power what is next in the post-pandemic world."

Judith Lee, Business Innovation & Technology department chair, said the project "allowed graduate students and GGU faculty to work jointly with MetricStream to push the boundaries of machine learning and edge computing technologies."

"We chose edge computing for security and data privacy reasons, and the deployment was facilitated by a zero-touch operations environment supported by Platina Systems," said Ross Millerick, program director, MS/IT Management. "It allowed us to remotely access the infrastructure at MetricStream during the Covid pandemic, when our laboratory on campus was not available."

"Bringing together thought leadership in AI that goes beyond deep learning and edge computing allows us to teach our students how to push the boundaries with federated AI and edge computing" said Rao Mikkilineni, distinguished adjunct professor.

The project spanned five terms and a succession of students. The students completed their capstone obligation with the project output with support from MetricStream. The project will continue to drive innovation in various enterprise business processes. Its vision is to build a long-term mutually beneficial partnership between the GGU business school and MetricStream, to inform the surrounding business community about the importance of GRC, and to provide an ongoing local forum for dialogue and education.

Leveraging the power of AI, MetricStream is the global market leader in Governance, Risk, and Compliance and Integrated Risk Management solutions, providing the most comprehensive solutions for Enterprise and Operational Risk, Regulatory Compliance, Internal Audit, IT and Cyber Risk and Third-Party Risk Management on one single integrated platform.

Golden Gate University, a private nonprofit, has been helping adults achieve their professional goals by providing undergraduate and graduate education in accounting, law, taxation, business and related areas since 1901. Programs offer maximum flexibility with evening, weekend and online options. GGU is accredited by the American Bar Association (ABA) and the WASC Senior College and University Commission.

Media Contacts: For MetricStream Amy Rhodes, [emailprotected]; For GGU: Judith Lee [emailprotected],edu,Michael Bazeley, [emailprotected]

SOURCE Golden Gate University

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Artificial Intelligence (AI) and Machine Learning (ML) will change the way we live, and virtual cloud-enabled seamless data connectivity would usher in a digital revolution by 2040, said D. Narayana Rao, Pro-Vice Chancellor of SRM University.

A senior scientist in the field of Atmospheric Science Research and Radar Technology and former Director, National Atmospheric Research Laboratory, Dr. Narayana Rao said that just as the world has seen revolutionary changes between 2000 and 2020, current technologies would become obsolete by the year 2040.

AI and MI are some of the future technologies that are going to shape our lives in the next two decades, Dr. Narayana Rao said during the celebrations of Engineers Day on September 15, held to mark the birth anniversary of Bharat Ratna Mokshagundam Visvesvaraya.

Data and information will be available virtually as air. Everything on the go will take on a literal meaning and the word connect will be meaningless for most of our gadgets. Data will just move seamlessly whether you are in an elevator, car or an aeroplane, he said.

AI and ML will make us believe that the world revolves around us. As we talk, discuss, act, AI will surround us with actions and suggestions and actionable inputs at a wink. AI will resemble Real Intelligence (RI). Driverless and automated intelligent cars will move around by themselves and self-park. Peoples job profiles will change. They will need to work less and most routine and hazardous work will be carried out by robots. Typing on gadgets will be redundant and will be replaced by voice commands, gestures and even thought controls. Natural Language Processing (NLP) will remove the language barriers in trade and travel. NLP will do the translation of spoken language and will ensure a global world, Dr. Narayana Rao said.

Space tourism will turn from fantasy into a reality. Holiday tours to Switzerland, Bali, and Seychelles will be replaced by tours to Venus, Mars and the moon, he said, adding that 3D printing technology will be used to construct buildings, structures and several products within a few hours/days which presently takes months and years to do.

When our country became independent, India was the poorest of the poor countries with a literacy rate of just around 12% and a life expectancy of 32 years. Today, in 70 years, India has become one of the top five economies in the world. What made this remarkable transformation possible was the application of science and technology in building the nation, Dr. Narayana Rao said.

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AI, machine learning will change the way we live - The Hindu

Applications of AI And Machine Learning In Computer Science and Electrical Engineering

Technologically, we are evolving with every passing day. Progress in the field of Artificial intelligence and machine learning has transformed our lives for the better. Today, these magnificent technologies are used to optimize systems and meet the desired organizations goals. AI and machine learning not only boost the performance of the system but also address the problems of the business like never before. Additionally, problems are addressed efficiently and faster than before. All in all, implementing the latest applications of AI and machine learning might end up being a path for achieving greater heights. Computer engineering systems and electrical engineering systems generate huge volumes of data. Thus, we can apply data mining to discover new relationships in these systems. With the advent of deep neural networks thanks to the advancement in technology, we can learn new mappings between inputs and output of these systems. On that note, have a look at some of the greatest applications of AI and machine learning in the field of Computer engineering and electrical engineering that have simplified our lives.

Power systems

One of the best applications of AI when it comes to computer engineering has been on power systems. Right from identifying malfunctions to forecasting, AI has covered it all. Artificial intelligence has done a magnificent job in reducing the workload of human operators by taking up tasks such as data processing, routine maintenance, training, etc.

Application of Artificial intelligence in Electrical Equipment

First things first, we all know how complex the electrical equipment structure is. In reality, it not only needs knowledge pertaining to electronics, circuits, electromagnetic fields, motors, automation, etc. but also the necessity to understand the generators, sensors and other components of the role and mechanism. It is here that AI turns out to be no less than a saviour. Through programming and operation by computer technology, AI can realize the automatic operation of electrical equipment and replace human labour as well, thereby reducing the labour cost to a large extent. Additionally, Artificial intelligence technology greatly improves the speed and precision of the work.

Fault diagnosis

Artificial intelligence can be used in the logic of fuzzy neural network expert systems timely. With this, it is not only possible to accurately detect the faults, but also used to determine the cause of the failure, type and location of thefailure, and timely control of fault repair.

More secure systems

With the help of advanced search algorithms, Artificial intelligence and machine learning, identifying potential threats and data breaches in real-time has become easier than ever. Well, this is not it there is more to this. These advanced technologies also provide the necessary solutions to avoid those issues in the future. Well, there is no denying that when it comes to computer science, data security becomes way more relevant, right?

Server optimization

We all know that hosting servers have millions of inbound requests on a day-to-day basis. However, a point of concern is that due to the continuous flow of queries, some of these servers may end up slowing down and become unresponsive. Well, Artificial intelligence to the rescue it is! AI holds the potential of optimizing the host server and enhancing the operations, thereby boosting customer service.

What everything boils down to is the fact that AI and machine learning are changing many sectors, particularly IT/computer and electrical engineering because of the amount of data sets it can process at greater speeds and ability to learn faster than the human brain.

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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Applications of AI And Machine learning In Computer Science and Electrical Engineering - Analytics Insight

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Register now!

Women in the AI field are making research breakthroughs, spearheading vital ethical discussions, and inspiring the next generation of AI professionals. We created the VentureBeat Women in AI Awards to emphasize the importance of their voices, work, and experience and to shine a light on some of these leaders. In this series, publishing Fridays, were diving deeper into conversations with this years winners, whom we honored recently at Transform 2021. Check out last weeks interview with a winner of our AI rising star award.

No one got more nominations for a VentureBeat AI award this year than Katia Walsh, a reflection of her career-long effort to mentor women in AI and data science across the globe.

For example, Mark Minevich, chair of AI Policy at International Research Center of AI under UNESCO, said, Katia is an impressive, values-driven leader [who has] been a diversity champion and mentor of women, LGBTQ, and youth at Levi Strauss & Co, Vodafone, Prudential, Fidelity, Forrester, and in academia over many years. And Inna Saboshchuk, a current colleague of Walshs at Levi Strauss & Co, said, a single conversation with her will show you how much she cares for the people around her, especially young professionals within AI.

In particular, these nominators and many others highlighted Walshs efforts to upskill team members. Most recently, she launched a machine learning bootcamp that allowed people with no prior experience to not only learn the skills, but apply them every day in their current roles.

VentureBeat is thrilled to present Walsh with this much-deserved AI mentorship award. We recently caught up with her to learn more about the early success of her latest bootcamp, the power of everyday mentorship, and the role it can play in humanizing AI.

This interview has been edited for brevity and clarity.

VentureBeat: You received a ton of nominations for this award, so clearly youre making a real impact. How would you describe your approach to AI mentorship?

Katia Walsh: My approach is not specific to AI mentorship, but rather overall leadership. I consider myself to be a servant leader, and I see my job as serving the people on my teams, my partners teams, and at the companies that I have the privilege to work for. My job is to remove barriers to help them grow, learn, engage, and mobilize others to succeed. So that extends to AI, but its not limited to that alone.

VentureBeat: Can you tell us about some of the specific initiatives youve launched? I know at Levi Strauss & Co, for example, you recently created a machine learning bootcamp to train more than 100 employees who had no prior machine learning experience, most of them women. Thats amazing.

Walsh: Absolutely. So we are still in the process. We just started our first cohort between April and May, where we took people with absolutely no experience in coding or statistics from all areas of the company including warehouses, distribution centers, and retail stores and sought to make sure we gave people across geographies and across the company the opportunity to learn machine learning and practice that in their day job, regardless of what that day job was.

So we trained the first cohort with 43 people, 63% of whom were women in 14 different locations around the world. And thats very important because diversity comes in so many different ways, including cultural and geographic diversity. And so that was very successful; every single one of those employees completed the bootcamp. And now were about to start our second cohort with 60 people, which will start in September and complete in November.

VentureBeat: Im glad you mentioned those different aspects of diversity, because the industry is full of conversations around diversity, inclusion efforts, and ethical AI some of them more genuine than others. So how does AI mentorship ladder up to all that?

Walsh: I see it as just yet another platform to make an impact. AI is such an exciting field, but it can also be seen as intimidating. Some people dont know if its technology or business, but the answer is both. In fact, AI is actually part of our personal lives as well. One of my goals is to humanize the field of AI so that everyone understands the benefits and feels the freedom and the power to contribute to it. And by feeling that, they will in turn help make it even more diverse. At the end of the day at this point, at least AI is the product of human beings, with all of human beings mindsets, capabilities, and limitations. And so, its also imperative to ensure that when we create algorithms, use data, and deliver digital products, we do our very best to really reflect the world we live in.

VentureBeat: We talked about initiatives, but of course mentorship is also about those everyday mentorship-like interactions, such as with ones manager or an industry connection. How important are these not just for personal development, but also running a business and being part of a team?

Walsh: Thats actually probably the most important stage. Our daily lives revolve around what might be considered the mundane meetings, tasks, assignments, deadlines and thats actually where we can make the most impact. Mentorship is really not about doing something special and extra, but rather making sure that as part of our daily lives and daily responsibilities and jobs, we ensure we think about if were being equitable, fair, and doing everything we can to bring diversity. But it cant be a box to check; it has to become a part of how we think and act every hour in every single day.

VentureBeat: Are there any misconceptions about mentorship you think are important to clear up, or often overlooked aspects of mentorship you think everyone should know about?

Walsh: One thing that comes to mind is this idea that women can only be mentored by other women. Thats actually not the case. And in my own experience, Ive had the great privilege of working with men who have themselves taken the chance on me, given me opportunities, and given me responsibilities even before I felt ready. And I really appreciate that. So everyone can be a mentor to women and all genders including fluid genders regardless of their own gender, job, or role.

VentureBeat: And do you have any advice for everyone, but especially business leaders, about how they can be better mentors? Or what about advice for people looking to be mentored about how to make the most out of those relationships and everyday interactions?

Walsh: Ill address the mentee question first. Ive really been impressed with people who, even at a very young age, have had the courage, incentive, and initiative to reach out and say, I want to learn from you. Can you spend a few minutes with me? I always take the call. So I really encourage people to feel that strength and to take that initiative to reach out to people they think they can learn from. And I encourage those who are mentors to also take that call and to proactively encourage others to stay connected with them. One of the things I did was actually give my cell phone number to everyone in my company. Its not commonly done, but Ive put it in our own town hall chat because I want people to feel that connection. I dont want anyone to feel intimidated by a title or where someone sits in a company. AI, data, and digital are truly transversal. Theyre horizontal and cut across everything in a company. So its part of what I do in my function, but its also part of really wanting to contribute to diversity and mentorship.

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How to upskill your team to tackle AI and machine learning - VentureBeat

Meet Taktile, a new startup that is working on a machine learning platform for financial services companies. This isnt the first company that wants to leverage machine learning for financial products. But Taktile wants to differentiate itself from competitors by making it way easier to get started and switch to AI-powered models.

A few years ago, when you could read machine learning and artificial intelligence in every single pitch deck, some startups chose to focus on the financial industry in particular. It makes sense as banks and insurance companies gather a ton of data and know a lot of information about their customers. They could use that data to train new models and roll out machine learning applications.

New fintech companies put together their own in-house data science team and started working on machine learning for their own products. Companies like Younited Credit and October use predictive risk tools to make better lending decisions. They have developed their own models and they can see that their models work well when they run them on past data.

But what about legacy players in the financial industry? A few startups have worked on products that can be integrated in existing banking infrastructure. You can use artificial intelligence to identify fraudulent transactions, predict creditworthiness, detect fraud in insurance claims, etc.

Some of them have been thriving, such as Shift Technology with a focus on insurance in particular. But a lot of startups build proof of concepts and stop there. Theres no meaningful, long-term business contract down the road.

Taktile wants to overcome that obstacle by building a machine learning product that is easy to adopt. It has raised a $4.7 million seed round led by Index Ventures with Y Combinator, firstminute Capital, Plug and Play Ventures and several business angels also participating.

The product works with both off-the-shelf models and customer-built models. Customers can customize those models depending on their needs. Models are deployed and maintained by Taktiles engine. It can run in a customers cloud environment or as a SaaS application.

After that, you can leverage Taktiles insights using API calls. It works pretty much like integrating any third-party service in your product. The company tried to provide as much transparency as possible with explanations for each automated decision and detailed logs. As for data sources, Taktile supports data warehouses and data lakes as well as ERP and CRM systems.

Its still early days for the startup, and its going to be interesting to see whether Taktiles vision pans out. But the company has already managed to convince some experienced backers. So lets keep an eye on them.

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Taktile makes it easier to leverage machine learning in the financial industry - TechCrunch