Today, Defiance ETFs launched The Big Data ETF ($BIGY). Listed on the New York Stock Exchange, BIGY will give investors exposure to companies involved in Data Science and Analytics.

“Big Data, big potential opportunity. Data science is an emerging trend that has already taken hold. The race is on to extract actionable data from Big Data, thereby releasing business value and opening up previously unimagined capabilities. The companies at the heart of this process are at the heart of BIGY,” says Sylvia Jablonski, Co-founder and Chief Investment Officer of Defiance ETFs.

About Defiance: Founded in 2018, Defiance is a FinTech asset-manager and an exchange-traded funds (ETFs) sponsor focused on the next generation of investors. $BIGY joins Defiance’s suite of disruptive ETFs which includes the Psychedelics ETF ($PSY), Next Gen H2 ($HDRO), the first SPAC ETF ($SPAK), the first 5G ETF ($FIVG) and $CRUZ, the Hotels, Airlines and Cruise ETF – “the travel reopening trade”.

Investing involves risk. Principal loss is possible. As an ETF, the fund may trade at a premium or discount to NAV. Shares of any ETF are bought and sold at market price (not NAV) and are not individually redeemed from the Fund. Brokerage commissions will reduce returns. The Fund is not actively managed and would not sell a security due to current or projected under performance unless that security is removed from the Index or is required upon a reconstitution of the Index.

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Deep learning software specialist Intellegens has enhanced its solution for Additive Manufacturing (AM) with the launch of a new Alchemite™ AM Package. The ready-to-go bundle of machine learning software, analysis tools, and implementation services is designed to help AM teams extract value from their data, optimise build parameters and ensure more repeatable AM processes, while greatly reducing the need for testing. The launch of the Alchemite™ AM Package follows Intellegens’ success at the recent AM Innovation Awards, organised by the American Society of Mechanical Engineers (ASME). Intellegens’ Alchemite™ technology is unique in its capability to extract value from sparse and noisy experimental datasets, such as those generated during AM projects. These projects seek to understand the subtle combined effects of material properties, machine parameters, and operating conditions on the consistency and performance of AM parts. Such understanding helps to get parts to market faster, fulfilling the promise of AM for more flexible delivery of stronger, lighter manufactured products. For further information see the IDTechEx report on 3D Printing and Additive Manufacturing 2020-2030: COVID Edition.

The potential of Alchemite™ as a game-changer in AM development was recognised at ASME’s AM Tech Forum event in June, where Intellegens scooped both the Best-in-Class Software and Startup Innovation Awards. Intellegens was selected from over forty organisations, which presented technical solutions, with an expert judging panel making the final decision in combination with attendee votes at the event. Alchemite™ has been validated in a range of customer projects and through Project MEDAL, an AM collaboration with the UK Advanced Manufacturing Research Centre and global aerospace giant Boeing, supported by the National Aerospace Technology Exploitation Program (NATEP). Intellegens is also working in partnership with engineering simulation leader Ansys to embed Alchemite™ within its AM data management solution. The Alchemite™ AM Package builds on the knowledge developed through this work. It delivers the right combination of software and expert advice to ensure that new user organisations get up-and-running quickly as they apply machine learning to accelerate the delivery of AM processes.

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Also: PainChek’s app picks up European and Australian regulatory clearances; Digital health access as a social determinant of health.

AI isn’t ready for COVID-19 prime time. A systematic review of published this week in nature machine intelligence warns that new models using machine learning to review chest radiographs and chest computed tomographies for COVID-19 have major methodical deficiencies or underlying biases.

Among the 62 published or pre-print papers outlining these approaches, the authors wrote that not a single one was of potential clinical use. Many were hampered by low-quality data, and in particular the high likelihood of duplicated images across different sources that result in so-called “Frankenstein datasets.” All the proposed models also suffered some degree of bias, they wrote, such as including samples from nonrepresentative populations.

“Despite the huge efforts of researchers to develop machine learning models for COVID-19 diagnosis and prognosis, we found methodological flaws and many biases throughout the literature, leading to highly optimistic reported performance,” the reviewers wrote.

“Higher-quality datasets, manuscripts with sufficient documentation to be reproducible and external validation are required to increase the likelihood of models being taken forward and integrated into future clinical trials to establish independent technical and clinical validation, as well as cost-effectiveness.”

Easy med refills for psychiatric patients. Today marked the launch of New York-based Minded, a digital service that helps those taking psychiatric medications renew, adjust, refill and order delivery of their prescriptions.

The startup, which has raised more than $5 million from investors, aims to cut down the burden and cost of regular visits to a traditional provider for assessment and prescription renewal.

Through its app-based platform, users can instead complete a five-minute online assessment regarding their mental health and a 10-minute video consultation. If appropriate, they can either have their prescription filled at a local pharmacy or delivered to their home for free.

The subscription service costs $30 per month plus $5 for each medication, and includes 24/7 access to the company’s care team and other long-term medication management support.

“Once I found what worked for me, I did not want to go to the doctor every 90 days to pay $300 for a five-minute appointment. I wanted to take the frustrating, time-consuming, and expensive process of renewing my prescription and make it magically simple,” David Ronick, Minded cofounder and CEO, said in a statement. “We’re tackling the critical issues of access and affordability facing millions of Americans.”

Regulatory wins for pain measurement app. PainChek, the maker of a pain assessment and monitoring app for smartphones, announced this week that it’s received a CE Mark and a Therapeutic Goods Administration clearance for its Universal Pain Assessment Solution.

Designed for caretakers and others providers, the tool helps assess pain severity among those who cannot adequately describe it, or otherwise document quantified pain levels for those who can self-report. With these, the company said that it’d be rolling out the app in the U.K. and Australia next month, and then moving onto the rest of Europe and other international markets.

“PainChek can become a single, simple and rapid point-of-care solution for healthcare professionals in assessing and documenting pain across all their patients, in a broad range of settings including the larger home care and hospital care markets,” CEO Philip Daffas said in a statement. “Based on initial market feedback, we expect this novel solution will be well received by our existing users and attract a wider global audience.”

Not everyone has a smartphone. A comment letter published today in NPJ Digital Medicine makes the case that access to digital tools, and subsequently mobile health technologies, is increasingly important for healthcare stakeholders to view as another social determinant of health (SDOH).

Economic access, Internet connectivity and general tech literacy are becoming core issues as care delivery is digitized and novel tools are built using software or devices, they wrote. As such, they recommended that health systems adopt “a digital-inclusion-informed strategy regarding mobile health” that not only takes access into account, but works to assess and support patients as they learn digital skills.

“Mobile health technologies hold significant promise to increase the efficiency of care and improve health outcomes. Yet, we must be cognizant of their potential to increase health disparities,” they wrote.

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DataRobot’s AI platform makes it easy to build predictive models to identify infection hotspots

A new data-driven project is launching with the ambitious aim of resolving the COVID-19 pandemic in 60 days. 

ContagionNET has been designed by DataRobot, a global enterprise AI company that enables easy building and deployment of predictive models. Aimed at solving the data sharing problem that has plagued the COVID-19 pandemic response, the not-for-profit initiative will help determine when a patient is at their most contagious.

ContagionNET combines affordable antigen checks performed at home, anonymous data collection, and an AI platform. With these tools DataRobot are aiming to identify the most contagious areas in a community and encourage people to take preventative action. The goal is to identify people earlier than traditional testing (i.e., when they are most infectious) to disrupt the chain of transmission. 

ContagionNET can also predict how many people need to participate on a county-by-county basis by measuring the impact of different participation levels and testing frequency. This localised approach allows those with the highest viral load to self-isolate earlier, preventing further spread of the virus. 

“The reality is that those most likely to spread COVID-19 aren’t usually aware they are contagious” said Sally Embrey, DataRobot’s VP of Public Health and Health Technologies. 

“With the proliferation of frequent, easy-to-use at home antigen checks, ContagionNET is poised to inform the most contagious of their risk and help them make lifestyle modifications that will significantly reduce spread of the virus.”

DataRobot has been involved in pandemic response since early 2020. Working with the US government, DataRobot’s forecasting helped vaccine manufacturers select the right participants and prioritise enrollment in the highest risk locations over each vaccine trial period. 

The organisation has also used modeling to improve testing distribution, equity, and diagnostic reporting, all of which have informed its approach to ContagionNET. 

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NIIT University (NU) has introduced four new bachelor’s degree programmes in the new academic year 2021 — B.Tech in Communication and Computer Engineering, B.Tech in Data Science, B.Tech in Cyber Security, and Bachelors in Business Administration. 

To establish a vision to bring about innovation in higher education and learning in emerging areas of the knowledge society, these programmes focus on training students for employability and incorporating new-age skills for the future of work. According to the official release, these programmes will make students future-ready for the new world of work, through multidisciplinary courses.

The course curriculum has been specifically designed to bring in a holistic learning environment while keeping students at par with technological advancements. Thus, these programmes will ensure that the students become ready for employment in today’s dynamic environment, right after their graduation. The four core principles that NIIT University works on include — industry-linkage, technology, research-driven and seamless education.

When asked about these new programmes, Prof. Parimal Mandke, the Acting President of NIIT University stated in the official release that in the current era, it has become imperative for every individual to learn to adapt and change with times to ensure relevancy. 

He added, “Keeping in mind the growing demand for new-age skills, these new programmes offer the best in learning pedagogy, through our outstanding faculty, while enabling students to prepare for the future and offer recession-proof careers in today’s evolving work environment.”

Programmes at NIIT University — 

B.Tech in Data Science degree (four-year undergraduate programme) — built-in line with the growing demand for data science experts worldwide. The programme aims to deploy data sets models to solve real-world problems. The programme emphasises providing industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.

B.Tech in Communication and Computer Engineering (four-year undergraduate programme) — dedicated to carry out ICT based management and integrate telecom systems with associated software in networking, enabling students to gain expertise in digital and distribution controls, latest devices in internet-based communication networks, AT, CS, cloud and edge computing, etc.

B.Tech in Cybersecurity degree (four-year undergraduate programme ) — designed for those students who are keen to explore and exploit the latest trends in cybersecurity technologies. It aims to bridge the skill gap between the manpower needs and available talent pool by developing trained professionals for this fast-growing area.

The Bachelors in Business Administration degree (three-year undergraduate programme) — designed for students to build a theoretical foundation and acquire new-age skills in business analytics, digital marketing and finance, banking and insurance technology. This programme aims to develop entrepreneurial skills in students with NU’s specialisation in industry-relevant skills and knowledge.

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Datawire this week launched Ambassador Edge Stack 1.0, which combines an open source application programming interface (API) gateway optimized for Kubernetes with a Level-7 load balancer, Kubernetes Ingress controllers, monitoring capabilities and a developer portal into a single platform.

Company CEO Richard Li says Ambassador Edge Stack 1.0 enables IT organizations to provision these tools in a few minutes rather than having to configure each separately.

Ambassador Edge Stack 1.0 also advances best DevOps practices because, via that portal, developers can apply security, resilience and traffic management policies to the services they develop on their own.

Each of those services can be secured using an automatic HTTPS configuration capability that supports ACME protocols, OAuth/OpenID Connect authentication, rate limiting and fine-grained access controls.

Developers can also configure automatic retries, timeouts and circuit breakers for their APIs, in addition to accessing an auto-updated API catalog and API documentation generated from a Swagger/OpenAPI specification.

Traffic management controls such as traffic shadowing, canary routing and cross-origin resource sharing can also be applied across a wide variety of protocols including TCP, HTTP/1.x, HTTP/2, gRPC, gRPC-Web and WebSockets traffic.

Finally, Ambassador Edge Stack 1.0 provides native support for distributed tracing, metrics collection and logging.
By bringing all these capabilities into a single platform, Li says Datawire is enabling organizations to reduce costs and operational overhead.

Kubernetes clusters require a different type of gateway than most organizations use today to manage APIs within a monolithic application environment, Li says. Microservices in Kubernetes environments require a gateway that makes it easier to create APIs at scale as microservices are developed and reduces latency by using a stateless architecture that is integrated natively with Kubernetes APIs. Ambassador Edge Stack 1.0 is also tightly integrated with the open source Envoy proxy server for easier deployment on-premises or in a cloud computing environment, he adds.

It’s not clear who within an IT organization will take care of API gateways today and in the future. However, Li says that as microservices continues to mature, a separation of duties between developers and IT operations teams is becoming clear. IT operations teams can use Ambassador Edge Stack 1.0 to provide developers access to a graphical user interface (GUI) to apply policies and controls to the APIs and services they develop.

Longer term, Datawire will use the Ambassador Edge Stack 1.0 platform to deliver additional services in a way that is streamlined alongside Kubernetes clusters.

It’s too early to say to what degree the rise of Kubernetes will force organizations to rethink the way they manage and secure APIs. However, as the number of microservices in any of those environments increases, it’s apparent the number of APIs being dynamically generated may require a different approach.

Ambassador Edge Stack is available for free as part of Datawire’s early access program. It’s scheduled to be generally available later this month in both free Community and Enterprise editions.

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According to a recent press release, “GreenSky, Inc., a leading financial technology company Powering Commerce at the Point of Sale®, today announced the launch of a newly established Data Science division to boost the Company’s consumer protection program. The company is investing in artificial intelligence and machine learning to more accurately identify suspicious activity, alert consumers faster, and remediate situations more effectively. Marty Smith, former GreenSky Chief Information Officer, is leading this division. Prior to joining GreenSky, Mr. Smith held multiple executive-level technology positions with IPG, ChoicePoint, and The Home Depot. ‘Our investment in Data Science underscores the importance that GreenSky places upon employing the most advanced technologies available to protect our Program borrowers,’ said David Zalik, GreenSky Chairman and CEO. ‘I have complete confidence in Marty’s leadership to assume this critical role for GreenSky as part of our ongoing efforts to detect and eliminate consumer fraud’.”

The release continues, “GreenSky has a relentless focus on eliminating fraud at the point of sale and is constantly exploring new ways to build upon its top-notch consumer protection program. The Company currently leverages AI to create identity verification scores and creates fraud models to identify risky merchants and transaction patterns. GreenSky will require consumer borrowers to authorize pending transactions via “text back” to GreenSky. Leveraging the Company’s innovative real-time text back technology will empower a consumer to allow a charge to post to the consumer’s account or to immediately decline the transaction, in which case the transaction and the presenting merchant can be flagged for immediate investigation.”

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A former executive from payment platform PayPal has launched a new deep learning health intelligence platform, Global Care Analytics, to provide claims-and-cost clinical data and predictive analytics for healthcare companies.

The company’s president, Scott Guilfoyle, formerly served as CTO of PayPal, as well as CIO of LendingTree, and other major companies. The move underscores the growing interest in the AI in healthcare space and the emergence of more companies leveraging AI to solve healthcare management issues.

“The CEO, COO or CFO can execute precisely targeted, complex queries on massive data sets with real-time or near-real-time responses by dragging and dropping preset queries into the engine,” Guilfoyle said of the company’s platform. “We have a patented hyper-ingestion engine that can take in a million datasets a minute, which is amazingly fast and accurate. Then our hyper-digestion process uses neural networks to analyze the oceans of data and become more and more accurate as it learns to refine its ability to make connections.”

One of the goals of the founders was to leverage healthcare data that is currently underutilized and “trapped” within organizations, according to CEO Kevin Sullivan.

“When executive management has desktop power to identify gaps in care or delivery of care services, outcome metrics, and the most complete real-time picture of the health of their patient populations, they can speed up more knowledgeable decision making,” he said.

According to Guilfoyle, the company, which plans to follow the analytics technology with Global Care Pay to provide a frictionless billing-claims-reimbursement system, could help eliminate waste in administrative duties, which add up to $147 billion to $510 billion.

The company, Global Care Administrators, is two years old and is raising capital.

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Since 205, September has become Destiny’s favourite month. It’s the month wherein the game world that Bungie has created evolves, updating its experience to give Guardians a new threat to face and more worlds to explore. Last year saw a two-for-one deal in the Forsaken expansion, as Guardians scoured the Reef in a quest for revenge against Uldren Sov and then jetted off to the Dreaming City to face an ironic wish-granting dragon from beyond reality (I swear I’m not making this up).

This year? Players are returning to the Moon as the Hive have begun regrouping and have assembled a new army with which to finally strike back at the Vanguard during their most dangerous hour. After the death of Crota, Oryx and Zol, the Hive are hungry for revenge and only you can stop then in Shadowkeep. An expansion that has been leaked a few hours early thanks to an errant listing on the Microsoft store.

Before it was taken down, a few details were snagged from the page (cheers, True Achievements). For starters, Shadowkeep will be available regardless of how much Destiny 2 content you own. Don’t possess the season pass or Forsaken? Fret not you can still play it. Yes, you heard me: Players will not need to own any previous DLC expansion in order to play Shadowkeep or any future content.

In addition to that, the expansion features the usual goodies:

• New quests
• New Dungeons
• A new Raid
• New weapons
• New gear

And here’s the flavour text for the story!

BUT WAIT THERE’S MORE! Shadowkeep will be available in the usual vanilla flavour, as well as a digital deluxe edition which includes the following extras:

• Four Season Passes*, each offering a unique set of exclusive Seasonal activities, artifacts, and rewards
• Exclusive Eris Morn themed items:
• Exotic Emote
• Exotic Ghost Shell
• Emblem

There’ll probably be a fancy pants trailer shown off tonight at 7PM CAT, so stick around to see that. Meanwhile, I’ll be hoping back into the game and getting my best exotics ready for the fight to come. I’ve managed to kill several Hive gods over the last couple of years. I’m ready to finish the job when the scaly bastards gear up for another attack.

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New Delhi: Intel on Friday launched the Movidius Neural Compute Stick, a USB-based deep learning inference kit and self-contained artificial intelligence (AI) accelerator that delivers dedicated deep neural network processing capabilities to a wide range of host devices at the edge.

Designed for product developers and researchers, the Movidius Neural Compute Stick aims to reduce barriers to developing, tuning and deploying AI applications by delivering dedicated high-performance deep-neural network processing in a small form factor.

As more developers adopt advanced machine learning approaches to build innovative applications and solutions, Intel is committed to providing the most comprehensive set of development tools and resources to ensure developers are retooling for an AI-centric digital economy.

Whether it is training artificial neural networks on the Intel Nervana cloud, optimising for emerging workloads such as artificial intelligence, virtual and augmented reality, and automated driving with Intel Xeon Scalable processors, or taking AI to the edge with Movidius vision processing unit (VPU) technology, Intel offers a comprehensive AI portfolio of tools, training and deployment options for the next generation of AI-powered products and services.

“The Myriad 2 VPU housed inside the Movidius Neural Compute Stick provides powerful, yet efficient performance – more than 100 gigaflops of performance within a 1W power envelope – to run real-time deep neural networks directly from the device. This enables a wide range of AI applications to be deployed offline,” said Remi El-Ouazzane, VP and general manager of Movidius, an Intel company.

Machine intelligence development is fundamentally composed of two stages- training an algorithm on large sets of sample data via modern machine learning techniques, and running the algorithm in an end-application that needs to interpret real-world data.

This second stage is referred to as “inference,” and performing inference at the edge – or natively inside the device – brings numerous benefits in terms of latency, power consumption and privacy.

Layer-by-layer performance metrics for both industry-standard and custom-designed neural networks enable effective tuning for optimal real-world performance at ultra-low power. Validation scripts allow developers to compare the accuracy of the optimised model on the device to the original PC-based model.

Unique to Movidius Neural Compute Stick, the device can behave as a discrete neural network accelerator by adding dedicated deep learning inference capabilities to existing computing platforms for improved performance and power efficiency.

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