AI & Machine Learning News. 03, February 2020

The Artificial Intelligence and Machine Learning Newsletter by CloudQuant

The Artificial Intelligence and Machine Learning News clippings for Quants are provided algorithmically with CloudQuant’s NLP engine which seeks out articles relevant to our community and ranks them by our proprietary interest score. After all, shouldn’t you expect to see the news generated using AI?


Play Which Face is Real?!

Which Face Is Real?

Defenses Emerge to Combat Adversarial AI

As threats like deep fakes and data poisoning lurk, momentum is building for deploying trusted, pre-trained AI models with embedded security and defenses against the emerging threat known as adversarial AI.

Adversarial AI attacks that can corrupt data used to train AI models are on the rise as companies seek to scale AI applications. In response, the consulting firm Booz Allen Hamilton launched an enterprise AI software product late last year designed to accelerate deployment and management of trusted AI models at scale.
2020-01-30 00:00:00 Read the full story…
Weighted Interest Score: 5.6088, Raw Interest Score: 2.4624,
Positive Sentiment: 0.0000, Negative Sentiment 0.5472

CloudQuant Thoughts : The idea that one can create an image that looks either like random noise or a well know object, add it to an image either algorithmically or by placing it within the captured image and completely fool an ML system is an idea that should give us all pause. These changes can be imperceptible to the human eye. Check out this  great Stanford lecture online here (1h 22m) or this very simple example if you want to get caught up on Adversarial AI.

Web scraping is now legal – Here’s what that means for Data Scientists

In late 2019, the US Court of Appeals denied LinkedIn’s request to prevent HiQ, an analytics company, from scraping its data. The decision was a historic moment in the data privacy and data regulation era. It showed that any data that is publicly available and not copyrighted is fair game for web crawlers. But commercial use of scraped data is still limited
The decision does not, however, grant HiQ or other web crawlers the freedom to use data obtained by scraping for unlimited commercial purposes. For example, a web crawler would be allowed to search Youtube for video titles, but it could not re-post the Youtube videos on its own site, since the videos are copyrighted. In general, the copyright for data, including data for media files like video or music, is still enforceable regardless of how the data was obtained.

Some forms of web scraping are also still illegal. The decision also does not grant web crawlers the freedom to obtain data from sites that require authentication.

CloudQuant Thoughts : Tread Carefully! But this is great news for anyone who does their own web scraping for data.

IIT Delhi Startup Creates Buddhi Kit To Make AI Learning A Child’s Play

An IIT-Delhi startup has created a first-of-its-kind interactive DIY education kit based on artificial intelligence (AI). Buddhi AI DIY kit can be used to quickly and easily learn the basics of AI and build AI-based solutions for real-world problems. The kit will also help people without having any prior domain knowledge or training. The idea is to assist young students, tinkerers, makers, innovators, hobbyists, teachers, educationists, artists, parents and professionals from any background.

Buddhi (Build, understand, design, deploy human-like intelligence) kit was launched at IIT Delhi. An IIT statement read — “Buddhi kit helps users develop core skills such as problem-solving, creative thinking and ability to work in teams. With the kit, creative possibilities are endless as it can be used to easily introduce AI in any existing STEAM (science technology, engineering, arts & maths) project.”

2020-01-30 12:54:41+00:00 Read the full story…
Weighted Interest Score: 3.9588, Raw Interest Score: 1.3069,
Positive Sentiment: 0.4356, Negative Sentiment 0.1188

CloudQuant Thoughts : Kits that teach kids how AI works are my favorite things at the moment. This one looks excellent, I would also recommend the “build your own Smart Speaker” kit from ChatterBox.

Top 10 AI Trends for 2020

The rise of artificial intelligence in the workplace to enable and sustain the digital workforce is an apparent trend for 2020.

Artificial intelligence, machine learning, neural networks or whatever other fancy terms industry is coming out with for what is defined as the sophisticated computer technology that is becoming widely utilized to understand and improve business and customer experiences. I assume, you have heard of it before, but they way it is defined today is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans…

2020-02-03 14:11:32.361000+00:00 Read the full story…
Weighted Interest Score: 3.1000, Raw Interest Score: 1.5680,
Positive Sentiment: 0.3877, Negative Sentiment 0.1292

CloudQuant Thoughts : A lightweight blog post but interesting in the observation that “there will be an AI for every worker”! This reminds me of Bill Gates vision of “A computer on every desk and in every home.” which was regarded as extremely unlikely at the time as most people had no concept of what a computer could be used for. But that goal has arguably been achieved, at least in the western world. An AI per person is the 2020 version of that vision. The idea that each of us will be accompanied by an AI assistant for our personal and our work life is actually less difficult for modern humans to imagine than Bill Gates’ vision from the mid 70s. We all interact with AI daily, from Siri to our car navigation to automated banking. This is going to be a wild future!

Top Machine Learning Projects Launched By Google In 2020

It may be that time of the year when new year resolutions start to fizzle, but Google seems to be just getting started.The tech giant has been building tools and services to bring in the benefits of artificial intelligence (AI) to its users. The company has begun upping its arsenal of AI-powered products with a string of new releases this month alone.

Here is a list of the top products launched by Google in January 2020…
2020-02-03 11:30:00+00:00 Read the full story…
Weighted Interest Score: 2.8066, Raw Interest Score: 1.6357,
Positive Sentiment: 0.2431, Negative Sentiment 0.0663

CloudQuant Thoughts : Keeping up with the Googles… Meena is a 2.6 billion parameter end-to-end trained neural conversational model that can conduct conversations that are more sensible and specific than existing state-of-the-art chatbots.

Xignite Now Available in AWS Data Exchange

SAN MATEO, Calif., /PRNewswire/ — Xignite, Inc. announced their financial data APIs are now available in AWS Data Exchange, a new service that makes it easy for millions of Amazon Web Services (AWS) customers to securely find, subscribe to, and use third-party data in the cloud. Xignite is providing AWS Data Exchange customers with end-of-day and historical equities and ETFs trading on North American exchanges: In addition to closing prices, the data includes open, high, low, volume, and simple corporate actions data such as dividend amounts and split ratio for the securities.

Xignite is an Advanced Technology Partner in the AWS Partner Network (APN) and has achieved AWS Financial Competency status . Xignite was also one of the first market data distribution offerings available on the cloud, launching on AWS in 2009. Xignite financial data APIs have been listed in AWS Marketplace since 2014. These designations recognize Xignite for providing deep expertise and relevant technical proficiency delivering solutions seamlessly on AWS.

2020-01-31 02:43:36+00:00 Read the full story…
Weighted Interest Score: 5.1564, Raw Interest Score: 2.6282,
Positive Sentiment: 0.2120, Negative Sentiment 0.0424

Crayon Data to demo maya.ai at FinovateEurope 2020

Singapore/Chennai, January 31, Crayon Data announced today that it will participate in Finovate Europe – one of the largest fintech events in Europe. Crayon will also exhibit and demo their flagship product, maya.ai at the event.

Finovate is a global conference series, focused on financial services technology. This is the first time the annual FinovateEurope conference will take place in Germany. More than 1,200 senior attendees,half of whom are from financial institutions,and more than 150 speakers and 60 demoing companies will be in attendance. FinovateEurope 2020 will be held between Feb 11 -13th, 2020 at the Intercontinental Berlin Hotel in Berlin.

Crayon Data is a big data and AI startup, based out of Singapore. It’s product AI-led personalization product, maya.ai equips top tier enterprises, across industries like banking, e-commerce and travel and hospitality, to have personalized conversations with each of their customers. Across all channels. maya.ai, comes equipped with richly curated vast external datasets, backed by cutting-edge artificial intelligence, delivered through a series of easy-to-use APIs that cater to the needs of the portfolio, campaigns, analytics and alliances teams within an enterprise.

2020-01-31 08:21:11+00:00 Read the full story…
Weighted Interest Score: 4.7734, Raw Interest Score: 1.8322,
Positive Sentiment: 0.2411, Negative Sentiment 0.0000

Investing 2020: The Future of Finance

It’s hard to believe that the first iPhone came out just a little over 12 years ago. It’s even harder to imagine life without our smartphones. The past decade has seen a tornado of innovation that’s mixed our personal lives and our digital lives in an inseparable cocktail that will define this century and beyond. Nowhere has this combination been so powerful than in our wallets.

The finance industry has always been at the forefront of innovation through technology, and for good reason. From open outcry trading at physical exchanges to high-frequency and algorithmic trading via ultra-fast networks; from paper savings account passbooks to robo-advisors that track our spending and investing, technological innovation has been a priority for financial institutions and consumers alike, both eager to make their transactions as fluid as possible.
2020-01-29 17:13:49.654000+00:00 Read the full story…
Weighted Interest Score: 4.6772, Raw Interest Score: 1.9440,
Positive Sentiment: 0.1647, Negative Sentiment 0.0988

Two Sigma’s private-equity arm is building out a data team — it’s a big move that could serve as a case study for PE firms that are behind the ball on AI

Two Sigma’s private-equity arm has plans to build out its data capabilities, recruiting engineers, and data scientists to help provide insights to investment professionals and portfolio companies, Business Insider has learned.

The private-equity arm of hedge fund Two Sigma, known as Sightway Capital, is building out a team of data scientists and engineers to provide deeper insights to investment professionals and portfolio companies, two sources with direct knowledge of the matter have told Business Insider. The goal is to bring its tech-oriented professionals closer in number to its investment professionals, one of these sources said. Sightway Capital’s website lists 17 investment professionals, not counting operating, legal and compliance staff. Meanwhile, there are two data scientists displayed.

Another source said that Sightway Capital will focus on “measured” growth, with not all positions filled immediately. New roles will range from people who will mine data about companies and industries, to project managers who interface with portfolio companies, to software developers, who create dashboards and tools to equip companies with data visualizations created by Sightway Capital.

2020-02-03 00:00:00 Read the full story…
Weighted Interest Score: 4.3572, Raw Interest Score: 2.0898,
Positive Sentiment: 0.0536, Negative Sentiment 0.0536

Unlocking Data Silos to Reach the Promised Land of Smart Data Analytics

With mountains of market data, historical prices, and transactions data stored in disparate systems, securities and investment firms are shifting from a focus on collecting data to extracting value from it. A December 2019 paper by capital markets consultancy GreySpark Partners examined the potential for buy-side and sell-side firms to transform large quantities of big data into actionable intelligence – producing what is known as ‘smart data – through specialized analytics.

The move comes as electronic trading has generated massive data sets across equities, fixed income and currencies. Firms are hiring data scientists and coding analytics to mine this data for trading opportunities or to identify patterns that help lower transaction costs. In the report, titled “Smart Data Analytics Set to Play Key Role in Reducing Buy Side and Sell Side Trading Costs,” GreySpark predicts that smart data inputs and data analytics will become more significant in the next three-to-five years in terms of client performance analytics, competitive differentiation, and value creation.

2020-02-03 14:22:56+11:00 Read the full story…
Weighted Interest Score: 4.2167, Raw Interest Score: 2.2246,
Positive Sentiment: 0.1055, Negative Sentiment 0.1247

Reflections on AI from Davos 2020 – World Economic Forum

What do you say to a Nobel Prize winner when discussing how to make AI explainable in a deep neural network with over one billion parameters? This was my first trip to Davos and it coincided with the World Economic Forum’s (WEF) celebration of its 50th annual meeting. The setting was picture perfect: an idyllic mountain town framed by snow-capped mountains under crystal clear blue skies. The world’s elite were out in force in their designer sunglasses. I spotted senior government ministers, billionaires, tech titans and rock stars all within an hour. And here I was talking to the Nobel Prize winner, Joseph Stiglitz, and making sure that our boutique AI management consultancy, Best Practice AI, was represented at the highest level. We discussed AI explainability, the words that are on everyone’s lips. While Professor Stiglitz has concerns from an academic point of view, I deal with the issue from a different perspective: bringing practical tools to boards who are grappling with AI ethics and how to evidence the management of AI risks.
2020-02-02 13:08:02.392000+00:00 Read the full story…
Weighted Interest Score: 4.1787, Raw Interest Score: 1.4770,
Positive Sentiment: 0.3630, Negative Sentiment 0.2629

3 Top Artificial Intelligence Stocks to Watch in February

Though artificial intelligence (AI) has been a hot topic among technologists for quite some time, it’s only in recent years that semiconductor, software, and cloud capabilities have gotten to the point where companies are now deploying AI on a wider basis.

AI is so powerful because it can help companies on every part of the income statement. It can identify the best leads and better satisfy customers through recommendation engines, helping to boost revenue. AI can also help automate many back office tasks, saving companies on their selling, general, and administrative costs. And perhaps most exciting, AI can also help research and development departments find new solutions or correct flaws in highly technological manufacturing processes, benefiting both research and development as well as costs of goods sold.

February is shaping up to be a crucial month for these three AI leaders across cloud, memory hardware, and software-based analytics. Here’s what investors should watch…

2020-02-03 00:00:00 Read the full story…
Weighted Interest Score: 3.8242, Raw Interest Score: 1.6567,
Positive Sentiment: 0.1999, Negative Sentiment 0.1999

Market contemplates AI standards amidst regulatory pressure

An industry-led artificial intelligence (AI) standard may be forthcoming according to Bill Wardwell, vice president of strategy and product at Bottomline Technologies.

“I think looking at AI and machine learning at this point from a technology provider standpoint, what you’re going to continue to see is probably more of an industry framework related to guidance around AI,” says Wardwell.

“We’ve seen other firms release plans or infor…
2020-01-29 00:00:00 Read the full story…
Weighted Interest Score: 3.7606, Raw Interest Score: 1.4771,
Positive Sentiment: 0.1257, Negative Sentiment 0.0629

Data Freedom- The Path To Unlocking True Enterprise Intelligence

Today, companies across the globe are redefining their business models and seeking innovative ways to extract data, connect it and employ it for meaningful insights and learning. But for any enterprise to become intelligent, they should have the freedom to efficiently utilise all data they are creating and consuming to make smarter business decisions. The smart insights have to be entirely driven by data, not human judgement, or assumptions. This is precisely where the philosophy of Data Freedom comes in.

The concept of Data Freedom is about good-quality data being available within the enterprise in good quality, on an agile platform to all operational users. This includes IT and DevOps, analytical users like data scientists, decision-makers like business executives, and external users who are part of the business value chain.

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2020-01-27 13:13:00+00:00 Read the full story…
Weighted Interest Score: 3.7082, Raw Interest Score: 1.9605,
Positive Sentiment: 0.4711, Negative Sentiment 0.1064

Britain’s AI industry could boom post-Brexit by escaping damaging Brussels moves

Britain’s artificial intelligence sector could get a boost from Brexit if the country can escape from “poorly-constructed” regulations being drafted in the EU, experts have said.

Already the UK is seen as the third leading geography for AI, behind only China and the US, thanks to its world-class universities where some of the most advanced research is taking place.

European countries have been discussing how to regulate the emerging industry over recent years, with the EC saying it would want to implement rules to make AI “trustworthy and human”.
2020-01-31 00:00:00 Read the full story…
Weighted Interest Score: 3.6904, Raw Interest Score: 1.2613,
Positive Sentiment: 0.1802, Negative Sentiment 0.1802

40 Interview Questions On Statistics For Data Scientists

We frequently come out with resources for aspirants and job seekers in data science to help them make a career in this vibrant field. Cracking interviews especially where understating of statistics is needed can be tricky. Here are 40 most commonly asked interview questions for data scientists, broken into basic and advanced.

Here are some other interview questions resources for data scientists.

2020-02-02 07:20:14+00:00 Read the full story…
Weighted Interest Score: 3.6623, Raw Interest Score: 2.1120,
Positive Sentiment: 0.1014, Negative Sentiment 0.5349

2020 is the Year for Enterprise Data Connectivity

Expect this in 2020: Data will come to the forefront of enterprise priorities. The consumerization of IT and democratization of data have triggered a dramatic shift in data control across small and large organizations. Data control – once the sole domain of the CIO or CTO via the IT department – is increasingly in the hands of users.

The proliferation of applications created a shift within IT departments. Fewer and fewer companies look to IT to control data and instead, these organizations are governing data. Furthermore, with few exceptions, data is now firmly in the hands of business units given the propagation of cloud-based enterprise and functional and departmental applications. Today, organizations are continuously installing new applications to gain a competitive advantage and are establishing yet another source of data with each one. Our enterprise data truth is that digital information is now created by and accessible to the average non-technical user of applications and systems, without having to require the involvement of IT.

But what are those users – and the enterprises they represent – missing? They’re most often missing access to the right data, when and where they need it … in part due to the data fragmentation resulting from the multitudes of departmental apps, data in the cloud, and the diversity of enterprise systems. A Gartner forecast indicated that this year more than 40% of data-based tasks will be automated to bring higher productivity and more democracy to the data user community. Taken together, these trends further escalate the need to solve the massive data fragmentation problem, and the subsequent demand for comprehensive data access.

Consider three key tips for Enterprise Data Management success in 2020:

2020-02-03 08:35:22+00:00 Read the full story…
Weighted Interest Score: 3.6155, Raw Interest Score: 1.9649,
Positive Sentiment: 0.2090, Negative Sentiment 0.1254

Five Ways Artificial Intelligence Improves Contract Management

Cast aside apocalyptic visions of malevolent androids usurping our throne. Artificial intelligence is designed to act as an effective aid for specific tasks that were previously performed by decision-making humans.
If a university professor were scouring students’ essays for plagiarism, for instance, it would be difficult to detect every traceable amount of stolen information in each essay in a reasonable amount of time.

However, an artificially intelligent plagiarism detection service can check submitted documents against its database and the content of other websites to provide a detailed originality score in a matter of minutes or hours, allowing our collegiate example to focus exclusively on the content of those essays. The point is this: AI does not replace the duties of employed human beings, rendering our workforce obsolete. Instead, it assists professionals in performing the myriad of demands of their roles so that their positions can be streamlined into more strategy-based ones.

Recent AI’s machine learning is fostered by the data fed into it by live, human coordinators. This applies to organizations leveraging contract management software as well.
2020-02-03 12:27:57.337000+00:00 Read the full story…
Weighted Interest Score: 3.5681, Raw Interest Score: 2.2382,
Positive Sentiment: 0.3247, Negative Sentiment 0.1740

The human impact of data literacy

As the amount of data continues to grow year on year, a business’s ability to compete will increasingly be driven by how well it can extract insight, apply analytics and implement new technologies. That’s key to stay competitive in today’s ever-changing economy, leveraging rich datasets to get a deeper understanding of their customers, operations and the markets they operate in.

Dealing with an increased amount of data requires an adaptive, agile approach. The organisations that succeed are those that can make sense of the data, spotting the opportunities and assessing ideas quickly. But, before data can be used, it needs to be interpreted and understood properly.

2020-01-31 18:18:45 Read the full story…
Weighted Interest Score: 3.5227, Raw Interest Score: 1.7330,
Positive Sentiment: 0.4830, Negative Sentiment 0.1989

New Library Adds Causality to ML Models

A new open source library is designed to help data scientists and domain experts jointly develop machine learning models based on causal relationships rather than just data correlations. The developers of the new CausalNex library argue that running machine learning projects without considering causality can lead to faulty conclusions.

QuantumBlack, a data analytics unit of McKinsey & Co., said CausalNex is its second open source release after Kedro, a library aimed at production ML code. Its new machine le…
2020-01-28 00:00:00 Read the full story…
Weighted Interest Score: 3.5166, Raw Interest Score: 2.1510,
Positive Sentiment: 0.1218, Negative Sentiment 0.1218

AI And BI Are Vibrantly Sparking New Trends In Affiliate Marketing

The market for affiliate marketing is expected to reach $8.2 billion by 2022. AI is making it easier than ever to succeed in this growing field.

The application of Artificial intelligence and Business Intelligence in affiliate marketing has been actively discussed for quite a time. No wonder, more or less but the majority of marketers have already applied them both at their campaigns. Companies like Propel Media are using machine learning to del…
2020-01-27 16:46:56+00:00 Read the full story…
Weighted Interest Score: 3.4986, Raw Interest Score: 1.4467,
Positive Sentiment: 0.2704, Negative Sentiment 0.2569

Why Is Active Learning Important For Machine Learning

The lack of labelled data is one of the peskiest challenges in machine learning. A classifier that is put to identify spam from proper mails, cats from dogs or any other classifying tasks need to be fed with appropriate annotated data for accurate decision making.

However, this is not the case always; the real-world problems that ML models are tasked with solving come with uncertainties and deficiencies. So, keeping the model updated, in other words, making the model smar…
2020-01-27 05:22:56+00:00 Read the full story…
Weighted Interest Score: 3.3608, Raw Interest Score: 2.1888,
Positive Sentiment: 0.3060, Negative Sentiment 0.3295

Explainable Deep Learning in Breast Cancer Prediction

Explainable Deep Learning in Breast Cancer Prediction

Understanding Convolutional Neural Network Prediction Results in Healthcare

Advanced machine learning models (e.g., Random Forest, deep learning models, etc.) are generally considered not explainable [1][2]. As described in [1][2][3][4], those models largely remain black boxes, and understanding the reasons behind their prediction results for healthcare is very important in assessing trust if a doctor plans to take actions to treat a disease (e.g., cancer) based on a prediction result. In [2], I …
2020-02-02 22:59:20.051000+00:00 Read the full story…
Weighted Interest Score: 3.3558, Raw Interest Score: 1.5307,
Positive Sentiment: 0.0882, Negative Sentiment 0.0401

Can We Use Medicines Designed By AI On Humans Just Yet

Artificial intelligence has been assisting humans in finding patterns in biological data in order to predict potential diseases. In a few cases, it is even outperforming prominent doctors in determining the ailments. However, with the latest advancements, pharma companies have turned towards AI to expedite the drug discovery. Sooner rather than later, we will be witnessing medicines developed by AI that are used on huma…
2020-02-01 08:30:00+00:00 Read the full story…
Weighted Interest Score: 3.2567, Raw Interest Score: 1.0302,
Positive Sentiment: 0.3115, Negative Sentiment 0.4552

China’s AI Champion IFlyTek Says 2019 Revenue Will Exceed US$1.4 Billion As It Downplays Impact Of Tech War

he US escalated

China’s voice recognition champion iFlyTek said on Monday that its 2019 revenue is expected to surpass 10 billion yuan (US$1.4 billion) on the back of healthy development in its core artificial intelligence business.

Despite being added to a US trade blacklist last October, iFlyTek said it will report a net profit of 732 million to 894 million yuan for 2019, representing year-on-year growth of between 35 to 65 per cent amid a “complicated international and domestic economic environment”, according to a company statement.

Last year was a challenging one for Chinese tech companies as the tech cold w…
2020-02-02 23:15:31-05:00 Read the full story…
Weighted Interest Score: 3.2456, Raw Interest Score: 1.7341,
Positive Sentiment: 0.1806, Negative Sentiment 0.2529

Apple cancels preexisting military drone Pentagon contract after acquiring AI company

Less than three weeks after quietly acquiring artificial intelligence company Xnor.ai, Apple has swiftly canceled the company’s preexisting contract with the Pentagon that would have seen its tech used in the controversial “Project Maven” military drone operation.

That’s according to a report from The Information, citing a person familiar with the matter. Project Maven is the Pentagon’s initiative to use artificial intelligence to identify objec…
2020-01-30 09:26:07 Read the full story…
Weighted Interest Score: 3.2432, Raw Interest Score: 1.4771,
Positive Sentiment: 0.0985, Negative Sentiment 0.4924

Deploying ‘industry 4.0’ technologies in treasury

As a growing number of financial operations move to ‘real-time’, treasurers need to rethink how they organise and manage treasury functions ensuring that investment in technology can support seamless processes, efficiently.

According to BCG’s research “70 percent of treasurers have yet to embrace digitisation in a meaningful way”. Many rely on fragmented data, outdated modeling and analytical tools to optimise balance sheet and risk management. …
2020-01-28 00:00:00 Read the full story…
Weighted Interest Score: 3.1516, Raw Interest Score: 2.0431,
Positive Sentiment: 0.3715, Negative Sentiment 0.0743

Microsoft launches $40M initiative to solve global health challenges with AI

Microsoft launched a major health research initiative Wednesday to address some of the medical world’s most confounding challenges using artificial intelligence.

The $40 million AI for Health initiative will focus on three core areas:

Studying, preventing, and treating diseases

Studying mortality and longevity around the world to protect against the next global health crisis

Reducing inequity in global healthcare

Microsoft will provide grants, data science experts, technology, and other resources to help partner organizations tackle health projects …
2020-01-29 17:30:18+00:00 Read the full story…
Weighted Interest Score: 3.1240, Raw Interest Score: 1.4300,
Positive Sentiment: 0.2328, Negative Sentiment 0.3658

Microsoft Health Innovation Awards 2020 are now open for submission

Accelerating innovation for better experiences, better insights, and better care

There’s never been a more demanding time in healthcare, with many factors driving the need for innovation to solve the industry’s most prevalent and persistent challenges. There has been considerable progress made in this space as we all strive to achieve healthier lives. With that, the submissions for the Microsoft Health Innovation Awards 2020 are now being accept…
2020-01-30 00:00:00 Read the full story…
Weighted Interest Score: 3.0380, Raw Interest Score: 1.3519,
Positive Sentiment: 1.3519, Negative Sentiment 0.1690

Importance of data in the digital age

It isn’t an understatement to say that a day won’t go by when digital transformation isn’t talked about – whether on Twitter, LinkedIN, or in the business press. Whilst too much focus is often put on the technology aspect of a digital transformation or being digital, a key foundation and enabler for the digital age has to be data. A recent Forbes article stated “companies that aren’t continuously reinventing their business – with data at the core – will end up watching from the sidelines while their market is disrupted”. A key industry where this statement is true has to be financial services.
2020-02-02 19:30:46 Read the full story…
Weighted Interest Score: 2.9249, Raw Interest Score: 1.8176,
Positive Sentiment: 0.2773, Negative Sentiment 0.1848

Jumio provides digital onboarding for CIMB mobile customers

Jumio, the leading provider of AI-powered end-to-end identity verification and authentication solutions, has partnered with CIMB Bank Philippines to provide a simple, hassle-free and convenient digital onboarding solution to Filipinos.

In its first full year of formal operations, CIMB Bank Philippines signed in 1.7 million Filipinos via the CIMB Bank PH mobile app, 30% of which are first-time bankers, making CIMB Bank PH the faste…
2020-02-03 11:39:00 Read the full story…
Weighted Interest Score: 2.9032, Raw Interest Score: 1.6144,
Positive Sentiment: 0.2306, Negative Sentiment 0.0000

The Advent And Scope Of AI Marketing In 2020 And Beyond

When it comes to bridging the existing gap between data science and its usage, targeting better marketing results, nothing beats the utilitarian nature of AI. While artificial intelligence alone is capable of sifting through humongous data sets for analyzing the relevant ones, AI marketing is slowly but steadily shaping up into a venture that comes with a host of benefits over the conventional ways of promoting a product or service.

That said, b…
2020-02-03 00:00:00 Read the full story…
Weighted Interest Score: 2.8694, Raw Interest Score: 1.2849,
Positive Sentiment: 0.4007, Negative Sentiment 0.0691

StreamSets Now Integrates with Microsoft SQL Server 2019 Big Data Clusters

StreamSets, provider of a DataOps platform, is supporting and integrating its platform for Microsoft’s recently announced SQL Server 2019 Big Data Clusters.

With this integration, SQL users are empowered to design and operationalize data pipelines for big data workloads without the complexities of coding for big data systems.

With StreamSets DataOps Platform’s new capabilities for Big Data Clusters, SQL developers can accelerate their analytics use cases by:

Design and operate continuous data flows with intuitive, visual tools, eliminati…
2020-01-30 00:00:00 Read the full story…
Weighted Interest Score: 2.8249, Raw Interest Score: 1.6949,
Positive Sentiment: 0.2511, Negative Sentiment 0.0628

Why we’re failing to regulate the most powerful tech we’ve ever faced

Alphabet CEO Sundar Pichai said artificial intelligence is “more profound than fire or electricity.” Author and historian Yuval Noah Harari said, “If you have enough data about me, enough computing power and biological knowledge, you can hack my body, my brain, my life, and you can understand me better than I understand myself.” And a recent Brookings Institution report prophesied that the country or region leading in AI in 2030 will rule the planet u…
2020-02-01 00:00:00 Read the full story…
Weighted Interest Score: 2.8165, Raw Interest Score: 1.1238,
Positive Sentiment: 0.2847, Negative Sentiment 0.3296

How To Write Movie Reviews with AI

How To Write Movie Reviews with AI

Fine-Tuning GPT-2 for Short-Form Nonfiction

Photo by Felix Mooneeram on Unsplash

Imagine collaborating on a Medium article with an artificial intelligence that has read every single word you’ve ever written — a language model that learned from your posts, essays, dictated notes, early drafts, scanned diary entries, research files, favorite quotes, and every other scrap of thought that makes your writing unique.

Your AI writing partner could deliver a smart critique of your essay and make suggestions about how to improve your argument. It could sur…
2020-02-03 06:09:31.163000+00:00 Read the full story…
Weighted Interest Score: 2.8144, Raw Interest Score: 1.3034,
Positive Sentiment: 0.1955, Negative Sentiment 0.3258

StreamSets Announces Support for New Microsoft SQL Server 2019 Big Data Clusters

According to a new press release, “StreamSets®, provider of the industry’s first DataOps platform, announced today support and platform integration for Microsoft’s recently announced SQL Server 2019 Big Data Clusters. With this integration, SQL users are empowered to design and operationalize data pipelines for big data workloads without the complexities of coding for big data systems. Announced at Ignite conference last November, Microsoft SQL Server 2019 Big Data Clusters allows users to deploy scalable clusters of SQL Server, Apache Spark and HDFS containers running on Kubernetes.”

The release co…
2020-01-31 08:05:21+00:00 Read the full story…
Weighted Interest Score: 2.8087, Raw Interest Score: 1.6969,
Positive Sentiment: 0.2341, Negative Sentiment 0.0585

Five Data Ethics Considerations for 2020

During the past two years, data theft and privacy concerns have emerged as a heavy counterweight to the benefits of big data and data analytics. Data ethics, the right or wrong conduct related to handling data, is in daily public discourse. Professionals who work in data-related fields are rethinking long-held beliefs about its management and use. The debate centers on the responsibility of companies to ethically protect the rights of data source…
2020-01-30 00:00:00 Read the full story…
Weighted Interest Score: 2.8033, Raw Interest Score: 1.4835,
Positive Sentiment: 0.2522, Negative Sentiment 0.4747

AI Driving Personalization Efforts at Restaurants; Dynamic Drive-Thru Menus Coming

ample, is incorporating AI into its mobile app used by five million customers, through a partnership with Certona, a personalization engine, according to a recent account in Forbes. The app relies on machine learning to present content to users based on their individual behavior. It can differentiate menu items and pricing based on geographic region.

“Instead of displaying generic, or static, product recommendations, we use Certona’s AI engine to determine what the best products are to display to a customer,” stated Derrick Chan, Taco Bell’s director of e-commerce. “So, for example, if it is a first-time use…
2020-01-30 22:30:23+00:00 Read the full story…
Weighted Interest Score: 2.7267, Raw Interest Score: 1.1585,
Positive Sentiment: 0.3724, Negative Sentiment 0.0000

Dice 2020 Salary Report: Which Cities, Skills, and Occupations Paid the Most?

Welcome to the 2020 edition of the Dice Salary Report. In order to obtain the latest data on the top technology salaries, we surveyed more than 12,800 technologists over two months. Whether you’re brand-new to the industry or a longtime veteran, there’s data in here that’s relevant to your current career and future goals. Let’s jump in!

Certain skills saw a significant year-over-year bump, suggesting heightened demand by employers, and certain c…
2020-01-29 00:00:00 Read the full story…
Weighted Interest Score: 2.5744, Raw Interest Score: 1.8039,
Positive Sentiment: 0.2627, Negative Sentiment 0.0350

Expanding Your Data Science and Machine Learning Capabilities

Expanding Your Data Science

and Machine Learning Capabilities

SPECIAL DBTA ROUNDTABLE WEBINAR THURSDAY, JUNE 25, 2020 – 11:00 am PT / 2:00 pm ET

Surviving and thriving with data science and machine learning means not only having the right platforms, tools and skills, but identifying use cases and implementing processes that can deliver repeatable, scalable business value. The challenges are numerous, from selecting dat…
2020-06-25 00:00:00 Read the full story…
Weighted Interest Score: 2.5744, Raw Interest Score: 1.7004,
Positive Sentiment: 0.2429, Negative Sentiment 0.0810

Modern Data Warehousing: Enterprise Must-Haves

Modern Data Warehousing:

Enterprise Must-Haves

SPECIAL DBTA ROUNDTABLE WEBINAR THURSDAY, NOVEMBER 19, 2020 – 11:00 am PT / 2:00 pm ET

To fit into modern analytics ecosystems, legacy data warehouses must evolve – both architecturally and technologically – to deliver the agility, scalability and flexibility that business need to thrive in today’s data-driven economy. Alongside new architectural approaches, a variety of technologies have emerge…
2020-11-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5448, Raw Interest Score: 1.6053,
Positive Sentiment: 0.0944, Negative Sentiment 0.0000

Data Lake Modernization for Speed, Scale and Agility

DBTA ROUNDTABLE WEBINAR THURSDAY, MARCH 19, 2020 – 11:00 am PT / 2:00 pm ET

Data lake adoption has more than doubled over the past three years. Currently in use by 45% of DBTA subscribers to support data science, data discovery and real-time analytics initiatives, data lakes are still underpinned by Hadoop in many cases, although cloud-native approaches are on the rise. The technologies and best practices surrounding data lakes continue to evolve, as well as the challenges, from data governance and security, to integration and architecture. Join us for a special roundtable webinar on March 19th to learn …
2020-03-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5355, Raw Interest Score: 1.6227,
Positive Sentiment: 0.2028, Negative Sentiment 0.1014

Unlocking the Power of DataOps

DBTA ROUNDTABLE WEBINAR THURSDAY, MAY 7, 2020 – 11:00 am PT / 2:00 pm ET

A new methodology is on the rise at insights-hungry enterprises looking to bring improved quality and reduced cycle times to data analytics. Borrowing from Agile Development, DevOps and statistical process control, DataOps is poised to revolutionize data analytics with its eye on the entire data lifecycle, from data preparation, to reporting. However, improving the flow of data between managers and consumers within an organization through greater communication, integration and automation is no simple task, and it requires cultural ch…
2020-05-07 00:00:00 Read the full story…
Weighted Interest Score: 2.5234, Raw Interest Score: 1.4953,
Positive Sentiment: 0.6542, Negative Sentiment 0.0000

The Secret to Data and Analytics Success Is…People

One of the most astonishing facts culled from the data and analytics field is the persistently high rate of failure. Despite the billions of dollars and millions of hours invested, the majority of data analytics projects simply do not succeed. There are many reasons for this, of course. Sometimes the technology is not up to par, and the data is almost always dirty. But arguably, the biggest factor is a lack of investment in people.

There’s a growing realization that people are the key to data and analytics success. Of course, every organization that fancies itself to be “data-driven” would like to have …
2020-01-30 00:00:00 Read the full story…
Weighted Interest Score: 2.5152, Raw Interest Score: 1.2424,
Positive Sentiment: 0.2222, Negative Sentiment 0.2727

Saving Penguins with AI

Penguin populations (like those of most adorable animals) are threatened by looming environmental catastrophes, including climate change – but, as in the case of whales, protecting those populations first requires that we understand them and the challenges they are encountering. Now, Intel and Gramener are highlighting new research that uses AI to analyze Antarctic penguin populations, paving the way for better protection of their fragile ecosyst…
2020-01-29 00:00:00 Read the full story…
Weighted Interest Score: 2.5103, Raw Interest Score: 1.0116,
Positive Sentiment: 0.1499, Negative Sentiment 0.3747

On the Radar: Promethium, StreamNative, Inzata

Welcome to On the Radar, a new Datanami feature about interesting new startups in the big data and analytics space. In this week’s edition, we explore three vendors making news, including Promethium, NativeStreams, and Inzata.

Promethium, a provider of AI-powered data management software that’s based in Menlo Park, California, has landed on our radar with a $6 million round of funding led by .406 Ventures. The round, which the company tells us is a pre-Series A round, comes on the heels o…
2020-01-29 00:00:00 Read the full story…
Weighted Interest Score: 2.4160, Raw Interest Score: 1.4103,
Positive Sentiment: 0.0261, Negative Sentiment 0.0783


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