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Microsoft researchers tap AI for anonymous data sharing for health care providers

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The use of images to build diagnostic models of diseases has become an active research topic in the AI community. But capturing the patterns in a condition and an image requires exposing a model to a rich variety of medical cases. It’s well-known that images from a source can be biased by demographics, equipment, and means of acquisition, which means training a model on such images would cause it to perform poorly for other populations.

In search of a solution, researchers at Microsoft and the University of British Columbia developed a framework called Federated Learning with a Centralized Adversary (FELICIA). It extends a family of a type of model called a generative adversarial network (GAN) to a federated learning environment using a “centralized adversary.” The team says FELICIA could enable stakeholders like medical centers to collaborate with each other and improve models in a privacy-preserving, distributed data-sharing way.

GANs are two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples. As for federated learning, it entails training algorithms across decentralized devices holding data samples without exchanging those samples. Local algorithms are trained on local data samples and the weights, or learnable parameters of the algorithms, are exchanged between the algorithms at some frequency to generate a global model.

With FELICIA, the researchers propose duplicating the discriminator and generator architectures of a “base GAN” to other component generator-discriminator pairs. A privacy discriminator is selected to be nearly identical in design to the other discriminators, and most of the optimization effort is dedicated to training the base GAN on the whole training data to generate realistic — but synthetic — medical image scans.

In experiments, the researchers simulated two hospitals with different populations, considering a “very restrictive” regulation preventing sharing images, as well as models have that had access to images. The team used a dataset of handwritten digits (MNIST) to see whether FELICIA could help generate high-quality synthetic data even when both data owners have biased coverage. They also sourced a more complex dataset (CIFAR10) to show how the utility could be significantly improved when a certain type of image was underrepresented in the data. And they tested FELICIA in a federated learning setting with medical imagery using a popular skin lesion image dataset.

According to the researchers, the results of the experiments show that FELICIA has potentially wide application in health care research settings. For example, it could be used to augment an image dataset to improve diagnostics, like the classification of cancer pathology images. “The data from one research center is often biased toward the dominating population of the available data for training. FELICIA could help mitigate bias by allowing sites from all over the world to create a synthetic dataset based on a more general population,” the researchers wrote in a paper describing their work.

In the future, the researchers plan to implement FELECIA with a GAN that can generate “highly complex” medical images, such as CT scans, X-rays, and histopathology slides in real-world federated learning settings with “non-local” data owners.

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Source: https://venturebeat.com/2021/01/20/microsofts-felicia-taps-ai-to-enable-health-providers-to-share-data-anonymously/

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Digital ID Verification Service IDnow Acquires identity Trust Management AG, a Global Provider of ID Software from Germany

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IDnow, a provider of identity verification-as-a-service solutions, will be acquiring identity Trust Management, a global provider of digital and offline ID verification software from Germany.

IDnow confirmed that it would continue to maintain identity Trust Management’s Düsseldorf location and will retain its employees as well.

The acquisition of Identity Trust Management should help IDnow with further expanding into new verticals while offering its services to a larger and potentially more diverse client base in Germany and other areas.

The combined product portfolio will aim to provide comprehensive ID verification methods, ranging from automated to human-assisted and from being purely online to point-of-sale. All these ID verification methods will be accessible through the IDnow platform.

Identity Trust Management has established its operations in Germany’s identity industry during the past 10 years, with a solid reputation and portfolio of clients focused on telecommunications and insurance services.

Andreas Bodczek, CEO at IDnow, stated:

“Identity Trust Management AG has built an impressive company both in terms of product portfolio and client relationships. We have known the leadership team for years and have established a partnership rooted in deep loyalty and mutual understanding. We are excited to welcome identity Trust Management AG’s talented team to the IDnow family and look forward to combining the strengths of both companies to create a unified, market-leading brand.”

Uwe Stelzig, CEO at identity Trust Management AG, remarked:

“This combination unites the power of IDnow’s innovative technology with identity Trust Management AG’s diverse set of capabilities to create a differentiated identity verification platform. Together, we will be well-positioned to achieve our joint vision of providing clients with a unique, one-stop solution for identity verification.”

This is reportedly IDnow’s second acquisition in just the past 6 months following that of Wirecard Communication Services in September of last year.

As covered in December 2020, the European Investment Bank (EIB) had decided to provide €15 million of growth funding to Germany-based identity verification platform, IDnow. Founded in 2014, IDnow covers a wide range of use cases both in regulated sectors in Europe and for completely new digital business models worldwide.

The platform allows the identity flow to be adapted to different regional, legal, and business requirements on a per-use case basis.

As explained by the IDnow team:

“IDnow uses Artificial Intelligence to check all security features on ID documents and can therefore reliably identify forged documents. Potentially, the identities of more than 7 billion customers from 193 different countries can be verified in real-time. In addition to safety, the focus is also on an uncomplicated application for the customer. Achieving five out of five stars on the Trustpilot customer rating portal, IDnow technology is particularly user-friendly.”

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Source: https://www.crowdfundinsider.com/2021/03/172910-digital-id-verification-service-idnow-acquires-identity-trust-management-ag-a-global-provider-of-id-software-from-germany/

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China five-year plan aims for supremacy in AI, quantum computing

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China’s tech industry has been hit hard by US trade battles and the economic uncertainties of the pandemic, but it’s eager to bounce back in the relatively near future. According to the Wall Street Journal, the country used its annual party meeting to outline a five-year plan for advancing technology that aids “national security and overall development.” It will create labs, foster educational programs and otherwise boost research in fields like AI, biotech, semiconductors and quantum computing.

The Chinese government added that it would increase spending on basic research (that is, studies of potential breakthroughs) by 10.6 percent in 2021, and would create a 10-year research strategy.

China has a number of technological advantages, such as its 5G availability and the sheer volume of AI research it produces. This is one of the few countries where completely driverless taxis are serving real customers. In that light, the country is really cementing some of its strong points.

However, this may also be a matter of survival. US trade restrictions have hobbled companies like Huawei and ZTE, in part due to a lack of cutting-edge chip manufacturing. The US also leads in overall research, and the Biden administration is boosting spending on advancements for 5G, AI and electric cars. As experienced as China is in some areas, it risks slipping behind if it doesn’t counter the latest American efforts.

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Source: https://www.engadget.com/china-five-year-plan-for-technology-225618577.html

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How Machine Learning is Being Applied to Software Development

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When Elon Musk proposed the idea of autonomous vehicles, everyone assumed it to be a hypothetical dream and never took it seriously. However, the same vehicles are now on the roads, being one of the top-selling cars in the United States.

The applications of artificial intelligence and machine learning are visible in all areas, from Google Photos in your smartphone to Amazon’s Alexa at your home, and software development is no exception. AI has already changed the way iOS and Android app developers work.

Machine learning can enhance the way a traditional software development cycle works. It allows a computer to learn and improve from the experiences without the need for programming. The sole purpose of AI and ML is to allow computers to learn automatically.

Moreover, being a software developer, you might need to specify minute details to let your computer know what it has to do. Developing software integrated with machine learning can help you make a significant difference in your developing experience.

Machine Intelligence is the last invention that humanity will ever need to make!

When it comes to how machine learning and AI help developers, only the sky’s the limit. Taking it even broader, AI has always transformed every industry it has ever entered. Here’s a quick rundown of stats that convey the same:

As the figures stated, artificial intelligence and machine learning are surely transforming the world, and the development industry is no exception. Let’s have a look at how it can help you write flawless code, deploy, and rectify bugs.

AI and ML in Development – How Does This Benefit Software Developers?

Whether you’re a person working as an android app developer or someone who writes codes for a living, you might have wondered what AI has in it for you. Here’s how developers can harness the capabilities of machine learning and AI:

1. Controlled Deployment of Code

AI and machine learning technologies help in enhancing the efficiency of code deployment activities required in development. In the development spectrum, the deployment mechanisms include a development phase where you need to upgrade your programs and applications to a newer version.

However, if you fail to execute the process properly, you need to face several risks including corruption of the software or application. With the help of AI, you can easily prevent such vulnerabilities and upgrade your code with ease.

2. Bugs and Error Identification

With the advancements in Artificial intelligence, the coding experience is getting even better and improved. It allows developers to easily spot bugs in their code and fix them instantly. They don’t have to read their code, again and again, to find potential flaws in their code anymore.

Several machine learning algorithms can automatically test your software and suggest changes.

AI-powered testing tools are certainly saving a plethora of time to developers and help them deliver their projects faster.

3. Secure Data Storage

With the ever-growing transfer of data from numerous networks, cybersecurity experts often find it complex and overwhelming to monitor every activity going on in the network. Due to this, there might be a threat or breach that may go away unnoticed, without producing any alerts.

However, with the capabilities of artificial intelligence, you can avoid issues such as delayed warnings and get notified about bugs in your code as soon as possible. These tools gradually lessen the time it takes a company to get notified about a breach.

4. Strategic Decision Making and Prototyping 

It’s a habit for a developer to go through a hefty and endless list of what needs to be included in a project or code they’re making. However, technological solutions driven by machine learning and AI are capable of analyzing and evaluating the performance of existing applications.æ

With the help of this technology, both business leaders and engineers can work on a solution that cuts down the risk and maximizes the impact. By using natural language and visual interfaces, technical domain experts can develop technologies faster.

5. Skill Enhancement

To keep evolving with the upcoming technology, you need to evolve with the advancement in technology. For the freshers and young developers, AI-based tools help them to collaborate on various software programs and share insights with fellow team members and seniors to learn more about the programming language and software.

Parting Words

While machine learning and AI simplify numerous tasks and activities related to software development, it doesn’t mean that testers and developers are going to lose their jobs. A hired android app developer will still write codes in a faster, better, and more efficient environment, supported by AI and machine learning.

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Source: https://hackernoon.com/how-machine-learning-and-ai-are-helping-developers-6g2s33w6?source=rss

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Future of Mobile Apps: Here’s Everything that’s Worth the Wait

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@devansh-khetrapalDevansh Khetrapal

Devansh writes all about tech. He mainly talks about AI, Machine Learning and Software Development.

This year has been really rough on everyone and I guess we’ve seen enough of that already, but what we’ve also seen during this period are some amazing technological inventions. With phones, however, it’s kinda gotten boring. 

Every year the mobile users are excited because of the new Snapdragon processors and other bleeding-edge specs that these devices are pumping so they can insanely outperform the previous generation smartphones, but are the mobile apps in these phones evolving as congruently?

From the most interactive social media and messaging apps like Facebook, Instagram, WhatsApp, etc, it seems like there isn’t anything beyond that. So what’s next? Well, that’s exactly what we’re going to talk about.

Here’s the Future of Mobile Apps

When we say future of mobile apps, we don’t completely mean that these technologies aren’t already here. In fact, several of these are being incorporated right now. It’s just that these are in their primitive stages of development.

Here they are:

IoT (Internet of Things)

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It’s projected that by 2023, the global spending on IoT technology will be $1.1 trillion. Through Machine Learning and integrated Artificial Intelligence (AI), it has the potential to not just enable billions of devices simultaneously but also leverage the huge volumes of actionable data that can automate diverse business processes.

What does this entail for the future of mobile apps? Well, get ready to be able to control your car, thermostats, and kitchen appliances through your mobile devices. The IoT is being presently used in Manufacturing, Transportation, Healthcare, Energy, and many other industries.

Artificial Intelligence

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AI will single handedly change the future of mobile app design.

Mobile apps are coded to operate within the constraints of certain parameters, the implications of which have to be predefined. Simply put, if you’re browsing for a homestay on Airbnb, the results you see are based on predetermined parameters like your location, your size, and amenity requirements.

Those predetermined parameters, with the assistance of AI, can evolve to a point where you’ll be able to get results based on your preferences that it learned along the way, such as the kind of accommodation you usually prefer, the kind of facilities you need, and may even suggest you buy a place because your favourite restaurant is nearby. 

Augmented Reality (AR) / Virtual Reality (VR)

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AR and VR are attracting a high amount of investments and are forecasted to reach $72.8 billion by 2024. We can already see their success in the gaming and entertainment industry with Pokemon Go, Sky Siege, Google Cardboard, iOnRoad, and Samsung Gear VR.

Brands like Jaguar Land Rover and BMW have already started using VR to conduct design and engineering evaluation sessions to finalize their visual design before they spend any money on manufacturing the parts physically.

Gradually, you’ll be able to make more immersive simulations that can revolutionize any form of architecture involved in it.

Cross-Platform Development

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The future of mobile apps will definitely make native app development obsolete. Currently, React Native offers exceptional flexibility while developing Android and iOS apps. This will save tons of time since you won’t have to develop 2 separate apps.

More importantly, cross-platform app development will eliminate the downside of having to compromise on certain nuanced features. All of this will gradually make the app development process a lot cheaper, simpler, and time-saving.

5G

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Imagine if you could download an entire Netflix series in about 10 seconds. That’s how great the potential of 5G is. Theoretically, it has the potential to reach speeds of 10 Gigabits per second and not just high speeds, but low latency. Even in its infancy, we can witness 5-6 Gigabits per second on our smartphones in the US.

Speaking of the future of mobile apps, well, fast internet would mean faster download and upload speeds, which changes everything from Augmented and Virtual Reality, IoT, supply chain, transportation, smart cities, because everything can happen in real-time because of the latency of merely 2 – 20 milliseconds.

Blockchain

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Blockchain is a term being thrown around a lot lately. Well, it’s a technology that allows data to be stored globally on thousands of servers. Now because it’s decentralized, completely transparent, and immutable, it becomes difficult for one user to gain control over the network.

This means that it’s almost impossible for anyone to hack into blockchain and make changes. The future of app development depends highly on blockchain technology because of its ability to deliver highly secure mobile apps.

Wearable Devices

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You see wearables, or “smartwatches”, being popularly used as fitness bands these days. They’re smart in the sense that they’re able to tell you your heart rate, blood oxygen, count steps, are able to notify you in case of irregular heart rhythms. And of course, it does tell time.

The tech, when combined with IoT, opens up so many doors. Be it checking appointments, making calls, sending messages, getting reminders, it’s just scratching the surface. This tech has a huge potential to evolve and can eventually eliminate the need to use a smartphone. 

Wrapping Up

It’s pretty assuring that the future of mobile apps is ridiculously exciting. We can only imagine how the user experience is going to unfold. 

Be it data visualization with the help of VR and AR, or maximization of convenience with the help of wearables, they’re all going to bring about a massive change in the mobile app development trends. Hopefully, we’ve helped you scratch that itch of curiosity and you got to learn about how our interaction with the world is about to change.

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