Category Archives: Big Data

Security Audits, Cyberattacks and other Potential Front Line Issues

Security Audits, Cyberattacks and other Potential Front Line Issues

Defending the Organization

When people talk about security audits in an organization, thoughts immediately go to malware, cyberattacks and other front line issues. These appear as the most obvious types of threats and are consequently given the greatest attention. As essential as these responses are, companies need additional layers of audit and defence further up the hierarchy if they are to build a culture of perpetual and successful self-governance. The problem is, internal compliance and control – the key elements of self-governance – are falling woefully behind the times thanks to traditions that have not yet received a full overhaul. This is bad news for business in the private and public sectors, since the enemies they face have already stepped up to the speed of “now.”

Traditionally, businesses have relied upon three lines of defence for standing up against risk. Called the “Combined Assurance Model,” it relies first on line managers to watch over the business processes. The second line belongs to internal risk managers and assurance providers, and then thirdly comes the internal and external auditors.

Security Audits

Such a structure has not always proven to be reliable. In 2013, Financial Times journalist Howard Davies quoted British lawmakers as suggesting the model “promoted a wholly misplaced sense of security.” He added, “Far from complementing each other as happy teammates, they think the second and third lines are in the chocolate teapot category of uselessness, with “the front line, remunerated for revenue generation, dominant over the compliance risk and audit apparatus.” 

These are the types of issues that worry Shrikant Deshpande, senior banking technology, risk and assurance professional and (ISC)2 Certified Cloud Security Professional. He suggests there seems to be a gap between Internal Audit, GRC (Governance, Risk management, and Compliance) and Cyber Security in terms of formalized methods of defining risks, monitoring and assurance. “There is certainly a meeting of minds and policy level agreement on objectives,” he states, “however a formal process of risk mapping and traceability of assurance outcomes to agreed high level risk needs to improve.

What this means in the most straightforward terms is that audit and GRC education must keep up with the times, and with the new technologies now impacting business globally, like cloud, big data and IoT. There needs to be greater investment in security monitoring technologies and in internal education, and this requires getting through to executive decision makers in a way that effectively conveys both urgency and importance.

Shrikant highlights the recommendations of a 2010 research paper published by the Institute of Chartered Accountants in Australia, outlining a process of continuous assurance for the digital world. Central to its thesis was the notion of “better matching internal and external auditing practices to the reality of the IT-enabled world, to provide stakeholders with more timely assurance.” The authors advocate “audit automation,” to move the audit process away from a “manual, periodic paradigm” to something more real-time.

Shrikant points out that a variety of cloud technology neutral assurance methods and processes already exist, such as COBIT, ISO 27k , ISO 30k, and NIST. The challenge is that audit and GRC professionals need to mature their skills and knowledge to apply these in specific technology environments like the cloud.

This is where a combination of techniques like assurance mapping, combined assurance and continuous auditing can coexist and assist.

He adds, “the gap between risk management stakeholders and those who are actually monitoring risk and creating assurance continues to exist. There is a legacy of division that must be overcome if businesses and organizations hope to thrive in the extremely fast-paced world of cyber-connected business.” His advice: formally engage. Organizations need formal programs, formal assurance mapping and an up-to-speed monitoring program. The luxury of waiting no longer exists.

For more on the CCSP certification from (ISC)2, please visit their website. Sponsored by (ISC)2.

By Steve Prentice

Wearable Device Tweaks – Better Security, Engagement and Fulfillment

Wearable Device Tweaks – Better Security, Engagement and Fulfillment

Wearable Device Tweaks

Wearable Device Tweaks

Though for many of us wearable tech still equates to the fitness monitor we had to have, loved for a month, and then forgot about, or perhaps the smartwatch that was going to revolutionize our lives but now just tells us the time, the adoption rates of this technology are increasing rapidly and perhaps we should thank a few forward-thinking developers for this trend. Though fitness monitors certainly have their place, and many athletes swear by them, the wearable tech coming out today promises far more for the everyman with the latest devices supporting third-party apps, offering relevant insights into our lives, and making the things we do every day more enjoyable. The next generation of wearable device tweaks promises better engagement and enhanced fulfillment through the activities that matter to us the most.

Data Gathering

Much excitement exists around the realm of Big Data and all that it promises, and wearable tech is one of the most personalized collectors of such data. No longer simply measuring primary health metrics such as heart rate and sleep, wearable tech is now able to track far more personal statistics such as locations visited, time spent on specific websites and applications, stress levels, comprehensive body functions, and much more. In fact, we’re reaching a stage where if you want to track it, somebody is probably developing a device so that you can. The value of this very specific and personalized data is, of course, customized insights that pertain directly to the user for enhanced engagement in everything they’re already doing.

Security

An area not often reflected on with regards to wearable tech, security is, in fact, at the fore of many of these devices. From GPS locators ensuring that children are safely where they should be to panic buttons that send emergency services location and trauma details, wearable tech is helping keep us safe and offering peace of mind. Of course, if you’re not a fan of Big Brother watching your every move you might have some reservations, but that’s a debate for another day.

Educational Tools

Though still an area in the earlier stages of development, wearable educational devices could soon be encouraging us to stay focused both through devices that track our awareness and mechanisms that enhance our engagement. Already virtual reality is being used to provide experience-style education systems in many schools, but it might not be long before the majority of classrooms are equipped with sensors that help educators understand how best to captivate students through the monitoring of vital statistics or devices that expertly train users in practical applications.

Just For Fun

And let’s not forget the most appealing part of our day; wearables further promote good ol’ fashioned fun, enhancing our downtime by finding ways to make our leisure activities even more amusing. The mind-boggling craze Pokémon GO is one point in case, though I’ll admit perhaps suggesting this leisure activity is ‘traditional’ might be going a bit far. Already the Pokémon GO developers are looking for new ways of boosting user engagement with the possibilities of augmented reality technology and wearable technology coming up trumps. For those less inclined to wander the streets searching for stray Pokémon, however, developers are producing leisure devices with many other functions; UV sensors that monitor sun exposure, shoes that steer you in the right direction, selfie drones, and even cocktail-making dresses. If you can think it…

No matter your preferences, there’s probably already a wearable device designed to enrich your life. Though Gartner observes that “most wearables are still exploratory products,” the next decade is likely to see an influx of gadgets that monitor and improve a variety of fields and maximize user engagement in real life.

By Jennifer Klostermann

Cloud Predictions 2017: Forrester Research Highlights 10 Trends

Cloud Predictions 2017: Forrester Research Highlights 10 Trends

Cloud Predictions 2017

By 2020 it’s projected by Gartner that corporate no-cloud policies will be as scarce as no-internet policies are today. Not surprising considering how valuable the cloud and cloud tools already are to many businesses across a range of industries. But although we’re seeing mainstream uptake of popular cloud products and services, cloud developers aren’t resting on their laurels; instead, we’re noting the development of existing and new cloud devices that are likely to keep the cloud top of mind and increasingly appreciated in the years to come.

Trends for 2017 and Beyond

Cloud Predictions 2017

Forrester Research has released a new report outlining cloud predictions for 2017 and highlighting ten trends for the coming year they believe necessary to act on. It’s expected that the cloud will be saving users money in many ways, not just through their traditional pay-per-use models, but also through the advancement of best practices optimizing costs. Expense transparency may also be realized through integrated cost management tools. And though Forrester says ‘size still matters,’ it’s clear that mega cloud providers will be balanced with niche providers. The public cloud option with its scalability and good economics continues to be a popular choice for enterprises averse to setting up their own private cloud networks, but the customization available through niche cloud provider services promises the smaller dedicated providers will also have a slice of the pie.

Furthermore, Forrester suggests that ‘hyper-converged infrastructure will help private clouds get real.’ These systems create integration of contrasting services on private cloud networks, and Forrester believes hyper-converged infrastructures should be the foundation for the development of private cloud networks, ensuring effortless and effective implementations. It’s also likely that containers will ‘shake up’ cloud platform and management strategies as Forrester predicts container-driven software code management will advance with Linux containers likely available in the majority of private and public cloud platforms early on in 2017. This, however, increases security challenges and is just one motive for the belief that cloud service providers will begin developing better security protocols into their offerings.

And further encouraging the cloud shift, Forrester believes that migration is going to become easier thanks to ‘lift-and-shift’ tools. Cloud migration applications are expected to be highly relevant in 2017, enabling smooth implementation and making the switch from public to private cloud, or vice versa, straightforward. Forrester does also expect enterprises to avoid large, complex and expensive cloud software suites, but also concludes that hybrid cloud networking will continue to create challenges for the hybrid cloud. We might also see SaaS moving towards regional and industry solutions instead of the prevalent one-stop-shops of today. Finally, Forrester suggests we keep an eye on what’s coming out of China as it’s expected that ‘Chinese firms will be key drivers of global cloud evolution.’

What the Cloud has in Store for Enterprises

Taking a look at enterprise advances, it’s suggested that the cloud market will accelerate more rapidly in 2017 as businesses attempt to improve efficiencies while scaling computing resources for better customer service. Says Forrester analyst Dave Bartoletti, “The number one trend is here come the enterprises. Enterprises with big budgets, data centers, and complex applications are now looking at cloud as a viable place to run core business applications.” Forrester recognizes Amazon Web Services as the originators of the first wave of cloud computing, launching basic storage and computing services back in 2006; ten years on and the results are mind-boggling. With 38% of surveyed North American and European enterprise infrastructure technology directors building private clouds and a further 32% securing public cloud services it’s evident that businesses are well into their cloud journey and nudging providers toward greater developments and innovations for the future.

By Jennifer Klostermann

How the Cloud Is Improving DNA Sequencing

How the Cloud Is Improving DNA Sequencing

DNA Sequencing

For many of us, the cloud is part of our daily lives.

We use these virtual storage servers to hold our pictures, our memories and our work documents, just to name a few. Cloud storage is also making its mark in the medical industry, with electronic health records making patient care easier no matter where you’re making your appointments.

This utilization of virtual information storage is also being used to improve the speed and accuracy of DNA sequencing. How can cloud storage change the way we look at DNA?

The Importance of DNA Sequencing

dna sequencingDNA, which stands for deoxyribonucleic acid, is the smallest building block of life. It’s found in almost all living things on the planet. Your DNA, found in every cell in your body, holds the blueprint that governs why you are the way you are.

Do you have red hair, or blue eyes? That’s written into your DNA. Are you tall, short, fat, skinny or athletic? You guessed it — that’s written into your DNA as well. Do you hate cilantro and think it tastes like soap? Believe it or not, that’s something that’s written into your DNA too.

In that DNA blueprint, there are answers to thousands of questions that we’ve been posing for centuries, including things like how long we’ll live, what diseases we may be predisposed to, and many others. That is where DNA sequencing comes in.

To stick with our same metaphor from a moment ago, you wouldn’t be able to read a blueprint without a key to tell you what different symbols mean, right? DNA sequencing provides researchers with the key to our DNA blueprint. By learning the order of the four base amino acids that make up DNA, researchers can determine which combinations of genes produce what result.

Old Tech, New Tech

Until now, DNA sequencing was performed on non-networked computers. While breakthroughs were being made, they were limited by the small subset of information available and the insufficient computer processing speeds. In other words, individual computers used for DNA sequencing are limited by the amount of processing power that they can possess.

Moore’s Law, coined by Gordon Moore — one of the founders of Intel — suggests that computers are limited by the number of transistors that can be placed on a single chip. He stated that this number would likely double every two years, and all current trends show that even with today’s advances, Moore’s Law still holds true.

Advances in DNA sequencing are appearing exponentially, and in many cases are only being limited by the available processing power.

Predictive Analytics

Predictive analytics, or the study of patterns to make predictions, has already made its way into the medical fields. When applied to DNA sequencing, it’s often dubbed Predictive Genomics. Cloud computing is a key component in the success of predictive genomics for a variety of reasons, including:

  • The amount of data — The sheer amount of data in one human being’s genome is almost mind-boggling. Each individual’s genome has up to 25,000 genes. These genes are made up of almost 3 million base pairs. When you break that down into digital data, you’re looking at upwards of 100 gigabytes of data per person.
  • The cost — Right now, having your personal genetic code sequenced costs between $1,500 and $4,000. This also plays a large role in the high cost of testing for specific genetic markers, like the BRCA1 and BRCA2 genes that indicate a higher chance of breast cancer.

The use of cloud computing and predictive genomics can reduce costs, ensure quality and improve accuracy throughout the world of DNA sequencing.

Amazon, our favorite online shopping mall, is doing what they can to help in the world of cloud computing and genomics. Amazon Web Services provides a cloud computing service that a number of companies, including DNAnexus and Helix, are using to improve the speed and accuracy of their genome sequencing.

There’s an App for That

While sending off a saliva-soaked q-tip to have your DNA tested isn’t a new concept, this is the first time it’s heading to both the cloud and the App Store.

A new startup from Silicon Valley named Helix has recently hit the DNA sequencing market with a new twist on the DNA game. Now, not only can you have your DNA tested for all sorts of information, but you can also have your genetic ancestry analyzed by the minds at National Geographic.

As the icing on the cake, all of your information will be stored on the cloud and accessible through Helix’s app.

Cloud computing is becoming an invaluable tool for a variety of different industries, with DNA sequencing as just the latest in a long line of innovations. As this advancement becomes more mainstream, only time will tell what secrets our DNA holds, and what we’ll be able to do with them once we find them.

By Kayla Matthews

Is Machine Learning Making Your Data Scientists Obsolete?

Is Machine Learning Making Your Data Scientists Obsolete?

Machine Learning and Data Scientists

In a recent study, almost all the businesses surveyed stated that big data analytics were fundamental to their business strategies. Although the field of computer and information research scientists is growing faster than any other occupation, the increasing applicability of data science across business sectors is leading to an exponential deficit between supply and demand.

When a 2012 article in the Harvard Business Review, co-written by U.S. chief data scientist DJ Patil, declared the role of data scientist “the sexiest job of the 21st century,” it sparked a frenzy of hiring people with an understanding of data analysis. Even today, enterprises are scrambling to identify and build analytics teams that can not only analyze the data received from a multitude of human and machine sources, but also can put it to work creatively.

One of the key areas of concern has been the ability of machines to gain cognitive power as their intelligence capacities increase. Beyond the ability to leverage data to disrupt multiple white-collar professions, signs that machine learning has matured enough to execute roles traditionally done by data scientists are increasing. After all, advances in deep learning are automating the time-consuming and challenging tasks of feature engineering.

While reflecting on the increasing power of machine learning, one disconcerting question comes to mind: Would advances in machine learning make data scientists obsolete?

The Day the Machines Take Over

machine

Advances in the development of machine learning platforms from leaders like Microsoft, Google, and a range of startups mean that a lot of work done by data scientists would be very amenable to automation — including multiple steps in data cleansing, determination of optimal features, and development of domain-specific variations for predictive models.

With these platforms’ increasing maturity and ability to create market-standard models and data-exchange interfaces, the focus shifts toward tapping machine-learning algorithms with a “black box” approach and away from worrying about the internal complexities.

However, as with any breakthrough technology, we need to recognize that the impact of the technology is limited unless it is well-integrated into the overall business flow. Some of the most successful innovations have been driven not by a single breakthrough technology but by reimagining an end-to-end business process through creative integration of multiple existing components. Uber and Netflix offer prime examples of intelligence gleaned from data being integrated seamlessly into a company’s process flow. Data scientists play a key role in this by leveraging data to orchestrate processes for better customer experience and by optimizing through continuous experimentation.

While organizations across industries increasingly see a more strategic role for data, they often lack clarity around how to make it work. Their tendency to miss the big picture by looking for “easy wins” and working with traditional data sources means that data scientists have an opportunity to help frame problems and to clearly articulate the “realm of the possible.

From Data to Strategy

It is easy to get carried away by the initial hype that machine learning will be a panacea that can solve all the problems and concerns around its impact on the roles of data science practitioners. However, let us recall the AI winters in the mid-’70s, and later in the ’90s, when the journey to the “promised land” did not pan out.

data-cloud

Today, we don’t see the same concerns as in the past — lack of data, data storage costs, limitations of compute power — but we still find true challenges in identifying the right use cases and applying AI in a creative fashion. At the highest of levels, it helps to understand that machine learning capability needs to translate into one of two outcomes:

  • Interaction: Understanding user needs and building better and more seamless engagement
  • Execution: Meeting customer needs in the most optimal manner with ability to self-correct and fine-tune

Stakeholder management becomes extremely important throughout the process. Framing key business problems as amenable to data-led decision-making (in lieu of traditional gut feel) to secure stakeholder buy-in is critical. Consequently, multiple groups need to be involved in identifying the right set of data sources (or best alternatives) while staying conscious of data governance and privacy considerations. Finally, stakeholders need to be fully engaged to ensure that the insights feed into business processes.

Data Scientists Become Core Change Agents

Given the hype surrounding big data analytics, data scientists need to manage responses that fall on opposite ends of the spectrum by tempering extreme optimism and handling skepticism. A combination of the following skills that go beyond platforms and technology are thus needed:

  • Framing solutions to business problems as hypotheses that will require experimentation, incorporating user input as critical feedback
  • Identifying parameters by which outcomes can be judged and being sensitive to the need for learning and iteration
  • Safeguarding against correlations being read as causal factors
  • Ensuring the right framework for data use and governance, given the potential for misuse

This requires pivoting a data scientist’s remit in a company from a pure data-analysis function into a more consultative role, engaging across business functions. Data scientists are not becoming obsolete. They are becoming bigger, more powerful, and more central to organizations, morphing from technician into change agents through the use of data.

By Guha Ramasubramanian

guha-rGuha heads Corporate Business Development at Wipro Technologies and is focused on two strategic themes at the intersection of technology and business: cybersecurity framed from a business risk perspective and how to leverage machine learning for business transformation.

Guha is currently leading the development and deployment of Apollo, an anomaly detection platform that seeks to mitigate risk and improve process velocity through smarter detection.

Big Data Comes to Bear on Healthcare

Big Data Comes to Bear on Healthcare

Big Data Healthcare

The National Institutes of Health (NIH) is examining the use of big data for infectious disease surveillance, exploring the use of information taken from social media, electronic health records, and a range of other digital sources to provide detailed and well-timed intelligence around infectious disease threats and outbreaks that traditional surveillance methods aren’t able to. On the other side of the disease spectrum, big data analytics is also helping with the management of diabetes, a disease affecting over 422 million people globally and resulting in 1.5 million deaths per year according to the World Health Organization. Today, big data and big data analytics are delivering a range of innovative health care options as well as disease and illness monitoring and prevention tools that better the wellbeing of the world’s population.

Where is All This Data Coming From?

Thanks to the digitization of records, the spreading use of sensors, and the prolific use of mobile and standard computing devices, the data that is collected and recorded today is immense. But just because all of this data exists doesn’t mean it’s necessarily useful. Consider the ‘information’ gleaned from Twitter and Facebook posts, Snapchat and text messages, and Google and Siri question and answer sessions: certainly, some of that will be relevant to someone, but the sheer volume of non-qualitative data available can sometimes be a deterrent. Fortunately, the technology that’s evolving to collect all of this data is working hand in hand with big data management and analytics tech to ensure value.

Today, big data applications can predict future actions and with the widespread use of Internet of Things tech personalized data can be collected and monitored on an individual level. Applications such as Google Trends provide practical methods for using big data, while big data analytics helps navigate and utilize unstructured data that might otherwise seem irrelevant. And thanks to tools such as Hadoop, developers are able to construct predictive models that help organizations understand user responses and better tailor applications to these results.

Solutions for Healthcare

Already big data plays a role in biomedicine, advancing methodologies and skills and creating new cultures and modes of discovery. Some experts, in fact, believe the advances in medicine suggest we’ll be facing disruption in the industry as new systems and approaches prove their worth. Precision medicine initiatives already involve above a million volunteers in the US alone, along with several NIH-funded cohorts, and it’s likely that we’ll see the sharing of lifestyle information, genomic data, and biological samples linked to electronic health records as these schemes search for superior health care solutions. The benefits of these initiatives are collaborative and cooperative science, more efficient and better-funded research enterprises, and training advances, but all of this needs to be carefully balanced with the necessary privacy and security demands of big data.

Other advantages provided by big data analysis include a better understanding of rare diseases through the precision provided by aggregated integrated data, as well as predictive modeling able to advance diagnosis of illnesses and diseases both common and rare. Though many opportunities available through big data and big data analytics require a particular cultural shift, our high-tech environment already encourages this change.

Concerns and Further Investigations

Although experts see potential in the use of big data in the healthcare field, we’re also cautioned that unconventional data streams may lack necessary demographic identifiers or provide information that underrepresents particular groups. Further, social media can’t always be relied on as a stable data source. Nevertheless, big data research continues in many unique health care areas: multiple studies are investigating social media and online health forums for drug use and the existence of adverse reactions; one European surveillance system is collecting crowdsourced data on influenza; ResistanceOpen monitors antibiotic resistance at regional levels; and many others provide unique insight into our healthcare systems. The combination of traditional and digital disease surveillance methods is promising, and says Professor Shweta Bansal of Georgetown University, “There’s a magnitude of difference between what we need and what we have, so our hope is that big data will help us fill this gap.”

By Jennifer Klostermann

Zero-Rating and Data Consumption

Zero-Rating and Data Consumption

Zero-Rating

The ordinary mobile user often feels the need to backup their personal files only after they’ve lost it. It’s almost a cliché where a grad student loses their research because a laptop was lost or the father who loses years worth of their kids photos when their phone is stolen.

To combat this, cloud services have tried to become easier to use. Everything from automatic uploads to cross platform access has been implemented.

However, only one addresses the external circumstance that is the data cap: zero-rating.

To be frank, if not for zero-rating, you could argue that not many people would use the cloud as the round-the-clock backup it was intended to be.

So what is Zero-Rating?

Zero-Rating is the practise of mobile carriers allowing users to use a data-consuming service without counting the data used against their cap. Meaning if video streaming app X is zero-rated, I can as much data as I choose through the app and it would not have an impact on my total data cap with the carrier.

cloudtweaks-pokemon-comic

For example, when Pokemon GO first launched in the US, T-Mobile offered customers a limited time offer where data used through the app had no impact on the customer’s data cap.

In short, it’s an incentive tool for mobile carrier that gives customers access to everything from content streaming to gaming on mobile.

But how does zero-rating affect cloud?

It comes back to the issue of round-the-clock protection.

Even with 3.4 billion mobile users across the world, almost 1 in 3 report data loss on mobile. While the circumstances for data loss varies, a big component of why people don’t backup constantly revolves around data caps. Simply put, no one wants to use precious MB to back up personal files because it’s conceivable that they would lose a device (or data in said device) that is with them 24/7.

Yet, mobile users are a walking contradiction when it comes to valuing their data and backing it up. One study found that while 90% of users value the data on their mobile devices. only 10% reported that they backed up their data on a daily basis. Furthermore, 72% of people polled reported that photos and videos were their most important assets on mobile – and every now and then, you hear about these users who lose chunks of precious moments stored on mobile devices.

mobile-cloud

You could argue that the decision to not back up stems more from our own psyche than any technical obstacle. Psychology Today reports that human beings are ill-prepared to deal with risk that do not pose as an immediate consequence.

In some ways, cloud adoption to prevent data loss suffers from the same branch of logic. While it takes a good personal cloud service less than 5 minutes to upload a day’s worth of photos, many of us don’t think to do it because we fail to foresee a mobile disaster. Hence, when disaster strikes, we may end up missing that pivotal group of files and photos that just so happened to remain in the queue to be uploaded.

This is where zero-rating comes into play.

In the aforementioned study, ‘ease of use’ was cited as the highest obstacle to users backing up their data. I would argue that it’s not easy to use an app intended to be automatic when you have to manually find Wi-Fi and enable the app to operate in those locations.

I mean with zero-rating cloud storage resembles car insurance except it has all the perks and nowhere near the price and headaches insurance companies cost.

So does Zero-Rating work?

Given the adoption of zero-rated service across telecoms across the world, my answer would be that zero-rating certainly has an appeal to customer. However, most of the fanfare as it relates to zero-rating revolves around content and OTT messenger services like HBO GO and WhatsApp rather than any cloud services.

From our own internal research, between cloud options that are provided with zero-service and without it, the difference is staggering. Between two mobile service providers in the same market, cloud options with zero-rating enabled have about 10x more growth in users per month than non-zero-rated clouds. A substantial endorsement for zero-rating cloud if it needed any further validation.

With the advent of services from mobile carriers – such as RCS – zero-rating is set to become even more prevalent than it is now. A trend which we have no doubt, would help reduce that total amount of data loss statistically significantly.

By Max Azarov

The Dark Side of AI Part 3 – The Brighter Side

The Dark Side of AI Part 3 – The Brighter Side

The Dark Side of AI Part 3

For the final part in this series I wanted to get away from the doom and gloom of A.I. being the end of the world. Ultimately it is this sort of fear that could lead to secrecy and a dangerous lack of transparency emerging amongst potentially condemned scientists. So to counter the problems and dangers associated with AI, I wanted to explore the most abstract and intelligent applications of Artificial Intelligence that is already having an impact on our lives.

A.I. Lawyer

Ross, the first A.I. lawyer, has been designed and built atop IBM’s cognitive computer Watson to handle the Baker & Hostetler bankruptcy practice (which is currently made up of a team of 50 lawyers). It has been built to read and understand language, suggest hypotheses when asked a question, and research case law and precedent to back up its conclusions. Ross also incorporates deep learning, allowing it gain speed and knowledge the more you interact with it.

Rather than relying on researchers and experts to find obscure precedents and case law, Ross can read through the entire history to help you get the most accurate information quicker and more efficiently. Ross can even monitor ongoing cases and new court decisions that may affect the verdict of your case! As if we didn’t already have enough lawyers…

A.I. Personal DJ

SoundHound is a music and artificial intelligence company that is attempting to merge the two into a brand new speaker – the Hurricane Speaker. The speaker combines a voice controlled personal DJ/assistant, music recognition software (that allows you to sing a tune to it for recognition), and a vast music collection from which to draw from.

The speaker will be capable of selecting music based on a your mood, creating personalised playlists with its Predictive Analysis Library (PAL) algorithm, as well as providing updates on weather, sports, setting alarms, and generally helping to organise your life.

A.I. Doctor

ResApp Health is an Australian “digital healthcare solutions” company, who have been working on an app that can diagnose respiratory conditions using the microphone on a smartphone (acting like a stethoscope). The app applies deep learning algorithms to analyse cough sounds in an attempt to identify conditions such as pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD).

But this is not an isolated use of machine learning in medicine. Enlitic is using Google’s deep learning open source tech to build an A.I. capable of diagnosing and suggesting treatment in order to help doctors solve medical issue much like a complex data problem. As a test they ran their algorithm with lung CT scans in an attempt to diagnose potentially cancerous growths, comparing it to results given by a panel of world’s top radiologists. Enlitic beat this panel comprehensively, successfully diagnosing every case of cancer when the panel missed 7%, whilst misdiagnosing 19% less cases than the human experts. Survival rates for cancer grow exponentially the earlier it is detected! For bonus points enclitic also helps doctors by showing them similar cases and helping to analyse trends that would be impossible for one doctor to see or consider.

A.I. Journalists Aid

With the associated press already using automation to cover minor league baseball games, it was only a matter of time before A.I. grew into a larger part of journalism. The next step in that growth comes via JUICE, a project funded by Google’s Digital News Initiative, and has been described as a tool to help journalists “discover and explore new creative angles on stories they write”. JUICE is being designed as an add-on to Google Docs, it uses AI systems to analyse what you have written and find creative and productive angles from which to approach the article or story. It is connected to around 470 news sites and automatically runs what they call “creative searches” to pull up relevant articles, cartoons, and multimedia that could be useful to the story. The project is aimed at improving the quality of journalism and helping writers find new ways of approaching their work. The system has had successful trials on journalism students and is expected to be more widely available at some point next year!

Although artificial intelligence can seem like an incredibly scary prospect, it is definitely a tool that has been and can continue to be used to improve many people’s lives and generally be a fantastic aid to the progression of society. However, there is a great deal of caution required in the pursuit of this technology. We cannot allow complacency of the same magnitude that we have allowed in nuclear power, climate change, and cyber security.

By Josh Hamilton

CloudTweaks Comics
Containerization: The Bold Face Of The Cloud In 2016

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Cloud Infographic – Big Data Analytics Trends

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Consequences Of Combining Off Premise Cloud Storage and Corporate Data

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Why Hybrid Cloud Delivers Better Business Agility

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Cloud Infographic: Programming Languages To Build Your Cloud

Cloud Infographic: Programming Languages To Build Your Cloud

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Cloud Infographic – The Data Scientist

Cloud Infographic – The Data Scientist

Data Scientist Report The amount of data in our world has been exploding in recent years. Managing big data has become an integral part of many businesses, generating billions of dollars of competitive innovations, productivity and job growth. Forecasting where the big data industry is going has become vital to corporate strategy. Enter the Data…

Cloud Infographic – The Future Of Big Data

Cloud Infographic – The Future Of Big Data

The Future Of Big Data Big Data is BIG business and will continue to be one of the more predominant areas of focus in the coming years from small startups to large scale corporations. We’ve already covered on CloudTweaks how Big Data can be utilized in a number of interesting ways from preventing world hunger to helping teams win…

10 Trending US Cities For Tech Jobs And Startups

10 Trending US Cities For Tech Jobs And Startups

10 Trending US Cities For Tech Jobs And Startups Traditionally actors headed for Hollywood while techies made a beeline for Silicon Valley. But times are changing, and with technological job opportunities expanding (Infographic), new hotspots are emerging that offer fantastic opportunities for tech jobs and startup companies in the industry. ZipRecruiter, an online recruitment and job…

Cloud Computing Then & Now

Cloud Computing Then & Now

The Evolving Cloud  From as early as the onset of modern computing, the possibility of resource distribution has been explored. Today’s cloud computing environment goes well beyond what most could even have imagined at the birth of modern computing and innovation in the field isn’t slowing. A Brief History Matillion’s interactive timeline of cloud begins…

Cloud-Based or On-Premise ERP Deployment? Find Out

Cloud-Based or On-Premise ERP Deployment? Find Out

ERP Deployment You know how ERP deployment can improve processes within your supply chain, and the things to keep in mind when implementing an ERP system. But do you know if cloud-based or on-premise ERP deployment is better for your company or industry? While cloud computing is becoming more and more popular, it is worth…

Three Challenges of Network Deployment in Hyperconverged Infrastructure for Private Cloud

Three Challenges of Network Deployment in Hyperconverged Infrastructure for Private Cloud

Hyperconverged Infrastructure In this article, we’ll explore three challenges that are associated with network deployment in a hyperconverged private cloud environment, and then we’ll consider several methods to overcome those challenges. The Main Challenge: Bring Your Own (Physical) Network Some of the main challenges of deploying a hyperconverged infrastructure software solution in a data center are the diverse physical…

Three Reasons Cloud Adoption Can Close The Federal Government’s Tech Gap

Three Reasons Cloud Adoption Can Close The Federal Government’s Tech Gap

Federal Government Cloud Adoption No one has ever accused the U.S. government of being technologically savvy. Aging software, systems and processes, internal politics, restricted budgets and a cultural resistance to change have set the federal sector years behind its private sector counterparts. Data and information security concerns have also been a major contributing factor inhibiting the…

Why Security Practitioners Need To Apply The 80-20 Rules To Data Security

Why Security Practitioners Need To Apply The 80-20 Rules To Data Security

The 80-20 Rule For Security Practitioners  Everyday we learn about yet another egregious data security breach, exposure of customer data or misuse of data. It begs the question why in this 21st century, as a security industry we cannot seem to secure our most valuable data assets when technology has surpassed our expectations in other regards.…

The Fully Aware, Hybrid-Cloud Approach

The Fully Aware, Hybrid-Cloud Approach

Hybrid-Cloud Approach For over 20 years, organizations have been attempting to secure their networks and protect their data. However, have any of their efforts really improved security? Today we hear journalists and industry experts talk about the erosion of the perimeter. Some say it’s squishy, others say it’s spongy, and yet another claims it crunchy.…

5 Things To Consider About Your Next Enterprise Sharing Solution

5 Things To Consider About Your Next Enterprise Sharing Solution

Enterprise File Sharing Solution Businesses have varying file sharing needs. Large, multi-regional businesses need to synchronize folders across a large number of sites, whereas small businesses may only need to support a handful of users in a single site. Construction or advertising firms require sharing and collaboration with very large (several Gigabytes) files. Financial services…

Data Breaches: Incident Response Planning – Part 1

Data Breaches: Incident Response Planning – Part 1

Incident Response Planning – Part 1 The topic of cybersecurity has become part of the boardroom agendas in the last couple of years, and not surprisingly — these days, it’s almost impossible to read news headlines without noticing yet another story about a data breach. As cybersecurity shifts from being a strictly IT issue to…

Your Biggest Data Security Threat Could Be….

Your Biggest Data Security Threat Could Be….

Paying Attention To Data Security Your biggest data security threat could be sitting next to you… Data security is a big concern for businesses. The repercussions of a data security breach ranges from embarrassment, to costly lawsuits and clean-up jobs – particularly when confidential client information is involved. But although more and more businesses are…

How To Overcome Data Insecurity In The Cloud

How To Overcome Data Insecurity In The Cloud

Data Insecurity In The Cloud Today’s escalating attacks, vulnerabilities, breaches, and losses have cut deeply across organizations and captured the attention of, regulators, investors and most importantly customers. In many cases such incidents have completely eroded customer trust in a company, its services and its employees. The challenge of ensuring data security is far more…