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AI & Machine Learning News. 12, November 2018

World’s first AI news anchor unveiled in China

The ‘tireless’ artificial news readers simulate the voice, facial movements, and gestures of real-life broadcasters. China’s state news agency Xinhua this week introduced the newest members of its newsroom: AI anchors who will report “tirelessly” all day every day, from anywhere in the country. Chinese viewers were greeted with a digital version of a regular Xinhua news anchor named Qiu Hao. The anchor, wearing a red tie and pin-striped suit, nods his head in emphasis, blinking and raising his eyebrows slightly.

“Not only can I accompany you 24 hours a day, 365 days a year. I can be endlessly copied and present at different scenes to bring you the news,” he says. Xinhua also presented an English-speaking AI, based on another presenter, who adds: “The development of the media industry calls for continuous innovation and deep integration with the international advanced technologies … I look forward to bringing you brand new news experiences.”
2018-11-09 00:00:00 Read the full story.

CloudQuant Thoughts… It looks a little rough right now, but we know how this plays out now, in 6-12 months it will be indistinguishable from a real News Anchor. Started off with a scary one this week!

 

Google wants to make it easier for cloud customers to find AI tools that fit their needs

Google plans to introduce a central repository for machine-learning tools Thursday, with the aim of making it easier for companies new to artificial intelligence to get up and running.

AI Hub will allow Google Cloud customers to access commonly used AI tools built by Google and share their own internal AI tools across their organization, at least in its alpha incarnation. A beta version of the service will open that hub up to tools developed by Google partners or “a broader array of public content,” according to the company.

If that sounds familiar, it’s because Seattle’s Algorithmia has been working on something similar for the last few years. Algorithmia has raised $12.9 million — including a Series A from Google’s AI investment arm — to build out what it calls the world’s largest marketplace for AI algorithms.

2018-11-08 16:00:09-08:00 Read the full story.

Google’s AI Hub Could Boost Companies’ A.I. Capabilities

Google wants to serve as a clearinghouse for artificial intelligence (A.I.) models.

The search-engine giant has announced AI Hub, which it bills as a “catalog of plug-and-play A.I. components, including end-to-end AI pipelines and out-of-the-box algorithms.” Data scientists, machine-learning experts, and companies can use the Hub to share and store A.I.-related code for utilization within their organizations.

At first glance, AI Hub seems like a specialized comp…
2018-11-11 00:00:00 Read the full story.

Google Ups its AI Game

Google Cloud is rolling out an “AI Hub” supplying machine learning content ranging from data pipelines and TensorFlow modules. It also announced a new pipeline component for the Google-backed Kubeflow open-source project, the machine learning stack built on Kubernetes that among other things packages machine learning code for reuse.

The AI marketplace and the Kubeflow pipeline are intended to accelerate development and deployment of AI applications, Google said…
2018-11-08 00:00:00 Read the full story.

CloudQuant Thoughts… No doubt what the top story is this week, Google’s AI Hub. Anything that makes AI simpler, faster, cheaper is alright by us. The more smart people who get involved with AI and ML the faster the breakthroughs will come. CloudQuant will soon be launching its own AI hub specifically for researching market trading ideas. Register with us now over at the original app.cloudquant.com and we will notify you as soon as we go live. Whilst you are there, brush up your Python skills and write a simple automated trading algo!

 

Automation May Murder 10 Percent of Jobs Next Year: Forrester

Automation will kill some 10 percent of U.S. jobs in 2019, according to a new report from analyst firm Forrester. (For those unable to access the report, VentureBeat also has a succinct breakdown.)

Analytics, chatbots, and robotics are streamlining company processes, while reducing the need for flesh-and-blood customer service agents and other kinds of employees. At least one analyst, Citi’s Mark May, is pointing to Amazon’s reduction of seasonal hiring as evidence of automation winnowing down demand for warehouse workers.
2018-11-08 00:00:00 Read the full story.

CloudQuant Thoughts… “Murder”, “Kill”, “Flesh and Blood” is this a Halloween post or did they just hire Stephen King?

 

NVIDIA Could Make a Big Move When It Reports Earnings — The Motley Fool

It’s been a roller coaster of a year for investors in NVIDIA (NASDAQ:NVDA). The stock reached all-time highs early last month, before losing more than a third of its value in the weeks that followed. The culprit appears to have been fears about a slowing in the semiconductor industry, a concern that seemed to be validated after competitor Advanced Micro Devices reported disappointing growth in its third quarter.

Investors are hoping that NVIDIA will have better news when it reports the financial results of its fiscal 2019 third quarter after the market close on Thursday, Nov. 15. Let’s look at the company’s recent quarter, and see if it provides any insight into what investors can expect when the company reports earnings.
2018-11-11 00:00:00 Read the full story.

Want to Play the Internet of Things? Jim Cramer Suggests Nvidia (Video)

Are you itching to get into semiconductors? Marc Chaikin, CEO of Chaikin Analytics, and Jim Cramer break down the “internet of things” for investors looking to add some variety to their portfolio. “If I want to be in the internet of things, I want to play [artificial intelligence], if I want to play self-driving cars, who am I going to play? It’s going to be Nvidia (NVDA – Get Report) ,” said Chaikin.
2018-11-12 06:36:00-05:00 Read the full story.

CloudQuant Thoughts… There is no doubt that Nvidia are at the forefront of a number of cutting edges but has there been a cool down in Cloud Computing? There earnings will surely point the way. Perhaps you can write a trading algorythm overr at CloudQuant.com to take advantage of the new AI super-companies?

 

AI Seen as Being the Greatest Job Engine the World Has Ever Seen

In the past few years, artificial intelligence has advanced so quickly that it now seems that hardly a month goes by without a newsworthy AI breakthrough. In areas as wide-ranging as speech translation, medical diagnosis and game play, we have seen computers outperform humans in startling ways. This has sparked a discussion about what impact AI will have on employment. Some fear that as AI improves, it will supplant workers in the job force, creating an ever-growing pool of unemployable humans who cannot economically compete with machines in any meaningful way. This concern, while understandable, is unfounded.

AI will be the greatest job engine the world has ever seen. Technology has progressed nonstop for 250 years, and in the U.S. unemployment has stayed within a narrow band of 5 to 10 percent for almost all that time, even when radical new technologies such as steam power and electricity came on the scene. AI is the most empowering of all technologies because it effectively makes anyone who uses it smarter. It increases the productivity of anyone who can apply it to their job. Once again, you hear the same refrain: “It will destroy jobs.” And sure, you can look around and find jobs that it might well eliminate, such as order taker at a fast-food restaurant. But, that is not in any way the entire story.

No, the whole story involves the other part of the equation. What will this technology enable?
2018-11-09 15:20:35+00:00 Read the full story.

CloudQuant Thoughts… a very interesting article taking the opposite to the usual point of view of AI as destroyer, nay, Murderer of jobs!

 

Internal Naysayers and AI Self-Driving Cars

…“The competitive pressure to build and market self-driving technology may lead developers to stay silent on remaining development challenges.”

It is crucial that those inside a firm consider a personal sense of duty when developing AI systems. Should you do nothing even if you believe that internal approaches are amiss? We often walk a tightrope of wanting to keep a job but at the same time wanting to speak-up when matters don’t seem right.

An associated difficulty is becoming labeled as a naysayer. Becoming an internal naysayer can be damaging to one’s ego and career. Even if you aren’t a naysayer, the odds are that during the course of your work career you will encounter one. These internal naysayers can be both a curse and a blessing (or, if you prefer the alternate sequence, I’ll say they can be both a blessing or a curse), depending upon the circumstances and the nature of the naysaying involved.
2018-11-09 15:45:21+00:00 Read the full story.
CloudQuant Thoughts… A very interesting article on speaking out when you see something going awry with your AI business!

 

Teach children the things that machines cannot learn

I often talk about teaching children to learn what machines cannot learn. Our system of education was created in the Industrial Revolution, and is based upon kids being stuffed with facts, stats and dates. They learn to parrot-fashion repeat things, and are tested to see if they can remember. It’s a very poor state of affairs. Machines can learn everything except emotions. That’s what we need to teach our kids. Emotions and the things that machines cannot learn.

I’ve seen machines that can write poetry and produce art, but it’s not real. It’s an imitation and this is where I see the rich future for humanity: emotional intelligence. This is why we need our children to learn empathy, emotion, creativity and ideas. The things that machines cannot learn. I often talk about a future where the jobs will be things that involve emotions, such as leveraged buy outs and counselling. Areas where the human heart are most in focus, and where machines lack the emotional intelligence to provide effective support. A machine can deal with facts, but can it deal with feelings?
2018-11-09 06:06:20+00:00 Read the full story.
CloudQuant Thoughts… This has been my thought process as a father for the last 16 years, what we need in the future are humans who can operate well with both lobes – logical and artistic!

 


 

Could AR help cities regulate scooters?

Over the past year, scooters have become a political minefield in some cities where the devices’ ubiquity on sidewalks are blocking access to pedestrians, baby strollers, and people with disabilities. Bad parking jobs and misuse has made these vehicles the object of rage in cities like San Francisco. A geolocation company called Fantasmo is proposing a novel solution to this particular problem: Augmented reality. The idea stems from the current problems with scooter parking. If scooter startups like Lime, Scoot, or Bird knew exactly where their users were leaving scooters on city streets, they could accurately enforce parking rules and keep sidewalks clear–for instance, by forcing a rider to move their scooter to the correct parking spot before the system ends their ride. The problem is that scooters’ built-in GPS isn’t accurate enough to pinpoint locations that precisely–so scooter companies can’t enforce parking policies effectively.

Instead of using GPS, Fantasmo is using something called “Camera Positioning Standard.” CPS, which the company is developing as an open standard that it views as the successor to GPS for far more than scooter parking, uses a digital camera and artificial intelligence to discover the world around it, akin to the way self-driving cars or augmented reality games “see.” Using this tech, Fantasmo can match the surroundings of the scooter with the company’s 3D map databases, triangulating its precise position on the street using the visual cues around it. You can see how accurate this tracking is in this demonstration video.

2018-11-07 09:25:45 Read the full story.

 

Tech C.E.O.s Are in Love With Their Principal Doomsayer

The futurist philosopher Yuval Noah Harari worries about a lot. He worries that Silicon Valley is undermining democracy and ushering in a dystopian hellscape in which voting is obsolete. He worries that by creating powerful influence machines to control billions of minds, the big tech companies are destroying the idea of a sovereign individual with free will. He worries that because the technological revolution’s work requires so few laborers, Silicon Valley is creating a tiny ruling class and a teeming, furious “useless class.” But lately, Mr. Harari is anxious about something much more personal. If this is his harrowing warning, then why do Silicon Valley C.E.O.s love him so?
2018-11-09 00:00:00 Read the full story.

 

Contemporary Data Scientists: Working Machine Learning at Scale – Anaconda

In a recent Magic Quadrant for Data Science and Machine Learning Platforms report, it was expressed that the Data Science and Machine Learning platform market will be in a state of flux over the next few years. Among the drivers of change will be providing Data Scientists with the ability to manage models and collaborate at an enterprise level as well as the availability of free and open-source options that let users begin Data Science and Machine Learning projects in an easy-to-access and low-investment way.

Anaconda debuted this year among the vendors that Gartner evaluated in the report, claiming a coveted spot in the niche category. Noted among Anaconda’s strengths was “its ability to federate and provide a central access point for a very large number of Python developers who build machine-learning capabilities continuously.” Ninety-percent of respondents to a recent Anaconda survey use Anaconda for Python, and 14 percent of respondents consider Machine Learning to be a key application for it.
2018-11-11 00:35:58-08:00 Read the full story.

 

5 ways artificial intelligence is enhancing traditional marketing

Artificial intelligence is already changing the world by making life simpler and more convenient for all of us. It blocks unwanted emails and knows exactly what we like on Netflix. It can even predict future health issues so we can take the necessary steps to prevent them.

AI is also having an effect on our careers. There are very few industries that are not currently being disrupted. From healthcare to security to the financial industry, artificial intelligence solutions are making people’s jobs easier and more efficient.

Marketing, and to an extent market research, are industries that are feeling the impact of artificial intelligence. There are a number of tools, products or services that are available to marketers now. Here are 5 ways that AI is transforming the landscape when it comes to marketing.

  • AI makes sense of all the Big Data
  • AI automates routine tasks
  • AI helps marketers connect with their audience
  • AI can assist with content curation
  • AI-powered chatbots will take customer service to an entirely new level

2018-11-09 06:02:52+00:00 Read the full story.

 

Weekly Selection — Nov 9, 2018 – Towards Data Science

 

  • Why you shouldn’t be a data science generalist
  • My secret sauce to be in top 2% of a kaggle competition
  • 5 Bite-Sized Data Science Summaries
  • Prediction Engineering: How to Set Up Your Machine Learning Problem
  • Scheduling with ease: Cost optimization tutorial for Python
  • I was looking for a house, so I built a web scraper in Python!
  • Using 3D visualizations to tune hyperparameters in ML models
  • Time Series Forecasting with RNNs

2018-11-09 16:55:26.241000+00:00 Read the full story.

 

Connected Vehicles – Are Commuters in The Privacy Driving Seat?

….To return to Tesla, that company uses a combination of telematics and sensor data to assist with its ‘machine learning and autonomous driving systems’. Tesla is aggregating this data and processing it to improve how its AutoPilot systems work for customers who have chosen to have it fitted. However, even customers who do not choose to fit the AutoPilot system still have their data collected by Tesla.
2018-11-09 00:00:00 Read the full story.

 

You Already Email Like a Robot — Why Not Automate It?

…Smart Compose and Smart Reply are, at their core, artificial-intelligence technologies: They are programmed to perform tasks, but also to adapt. To start, Smart Reply was trained on publicly available bodies of email text. (Among the most widely used for such projects is the cache of some 500,000 emails collected during the discovery phase of the Enron investigation.) “What makes machine learning different from regular programming is you look at corpuses of data to make guesses about things,” says Paul Lambert, a product manager for Gmail. “You create a model.”…
2018-11-07 00:00:00 Read the full story.

 

Fastest Analytics Using Hybrid Architectures with Machine Learning

Every year scientists and researchers gather at a conference called Super Computing, or SC, to exchange their views, solutions and problems in computational science. At SC17, there were no fewer than 22 presentations and keynotes involving Machine Learning and Deep Learning (DL). There were actually many more presentations about DL, because it is often the motivation for Hybrid Architecture (more on this later). This is remarkable if you consider that the year before, there were a grand total of two DL presentations. In other words, it appears that we are quickly moving into the era of data-driven programming.
2018-11-06 00:30:29-08:00 Read the full story.

 

AI Weekly: Tech giants need developers to help imagine the future of assistants like Alexa, Siri, and Bixby

It was a fairly big week for virtual assistants, as Facebook’s Portal video chat device went on sale and Samsung’s Bixby finally opened to third-party developers. Like the Actions on Google platform and Alexa Skills Kit, Bixby Developer Studio users will be able to create conversational apps — called “capsules” — that work with Bixby. The Bixby Marketplace will open to promote their work, and an expansion to some of the most-spoken languages on the planet will lead to opportunities beyond the United States and South Korea, which Bixby has been limited to thus far. After straggling behind Alexa and Google Assistant for over a year, Bixby could leapfrog its competitors with third-party voice apps made with more personality and humanity, said Viv Labs CEO Dag Kittlaus. He envisions a day when conversational AI can bring a device to life that knows who you are as soon as you open the box, both to create a bond and to be more helpful.

The Samsung Developer Conference was yet another instance of a tech giant expending a great deal of energy enticing business partners and developers to bring their services to its conversational platform. Google and Amazon have done the same for years.
2018-11-09 00:00:00 Read the full story.

 

Bixby lead imagines Samsung devices that talk to you when you unbox them

Viv Labs CEO Dag Kittlaus envisions a day when appliances speak to you as soon as you take them out of a box, are aware of your preferences, can talk you through a tutorial, and can build an emotional bond.

Kittlaus and Viv Labs cofounder Adam Cheyer, both co-creators of Apple’s Siri, debuted the Bixby Developer Studio for creating voice apps with Bixby, an AI assistant that will learn how to speak five new languages next year.
2018-11-09 00:00:00 Read the full story.

 

Did Samsung’s Bixby just beat out Siri, Alexa and Google?

Two years after Samsung hired the inventors of Siri to help them with Bixby, their own artificial intelligence platform, the electronics powerhouse has finally let them out of their cage. And what they have been working on looks impressive enough that it could lift Bixby out of obscurity and give Google, Amazon, Apple and Microsoft a run for their money.

At the Samsung Developer Conference here in San Francisco, Samsung showed off a new version of Bixby that doesn’t just use artificial intelligence to answer simple queries from users. It also uses artificial intelligence to write algorithms capable of performing far more complex tasks, such as booking hotel rooms or buying flowers, all from commands that users speak into their phone, their fridge, their TV or any other of the 1 billion Samsung devices that by next year will be running Bixby.
2018-11-07 00:00:00 Read the full story.

 

Dell EMC’s Matt Baker: VMware has over 600,000 customers

Dell, with more than 103,000 employees globally, is one of the largest technology companies in the world. In 2017, it was the third-largest PC vendor after Lenovo and HP, and analysts peg its market capitalization at $70 billion. The Round Rock, Texas firm sells network switches, peripherals, laptops, workstations, HDTVs, cameras, printers, servers, and MP3 players, to name a few categories. But in the years since its 2009 acquisition of IT services provider Perot Systems, it’s invested heavily in storage and networking solutions for enterprises.

Arguably the biggest push came in 2016 with the $67 billion purchase of EMC Corporation — the largest acquisition in Dell’s history. It saw the reorganization of Dell into Dell Technologies Capital, and the consolidation of its divisions into three subsidiaries: Dell Client Solutions Group, its consumer and workstation business; Dell EMC, its data management hardware and software arm; and cloud computing and virtualization services platform VMware. Today, Dell Technologies is pointed strategically at AI, data management, and the internet of things.
2018-11-09 00:00:00 Read the full story.

 

Telling Truth from Hype When Hunting for Data Science Work

There’s a lot of talk these days about “fake news”, and for good reason. But the growing uneasiness about relying on information from the web has crept beyond politics into other areas, including the search for employment. Scams and fake offers are an unfortunate reality of online job searches across industries. The data science world in particular has been swirling with skepticism, not just over whether job offers are legitimate, but about the job title itself—that is, over the tendency for some tech professionals to falsely label themselves as data scientists in the first place.

If you’d like to grab some tips for telling the scams, cons, and poppycock from real and worthwhile job opportunities in data science, read on.

  • Buzzword Soup
  • Sloppy Copy
  • Obscure Identities
  • Utopian Circumstances
  • Requests for Your Money or Confidential Information

2018-11-05 14:18:26+00:00 Read the full story.

 

Meet the Robot Who Knows How to Trade Bonds Better Than You Do

The robots have just got a step closer to managing your money. AllianceBernstein Holding LP upgraded its virtual assistant Abbie so she can now suggest the best bonds to buy and sell based on pricing, ease-of-trading and risk. Unlike any human, she can scan millions of data points to filter the universe of outstanding bonds in seconds and identify potential trades to portfolio managers using other electronic tools the firm has built. Abbie 2.0 can identify bonds that people may have missed and will be able to spot human error and communicate with chat bots like herself at other firms, according to Jeff Skoglund, chief operating officer of fixed income. The original electronic assistant AllianceBernstein introduced in January could only build orders for bonds following precise demands.
2018-11-12  Read the full story.

 

The Last Bastion Of Human Bond Trading Is Giving Up To The Algorithmic Overlords

One of the last human points of resistance to the algorithmic take-over of professional trading can be found in the fixed-income trading desk. The deft relationship business is known for having participants with Ivy League pedigrees and a lacrosse playing background, a data point that a machine learning algorithm recently used when making hiring recommendations.

With an algorithmic transition, profit margins are being squeezed as human relationships are becoming less important. Benchmarking the transition are new hiring mandates at some of the largest banks, a recent Greenwich Associates report pointed out. Relationships and fundamental market understanding are less important, the report noted, and algorithmic experience and data science skills are now in demand.
2018-11-10 17:30:12+00:00 Read the full story.

 

Asset managers are accelerating use of alternative data and advanced analytics

This inaugural study revealed that some asset management firms have reached an inflection point in generating alpha, improving business operations and increasing client acquisition and retention with alternative data and advanced analytics, according to a new survey by Element22 and UBS Asset Management. The study highlighted that the survey participants are at varying stages of a four-year journey to develop robust alternative data and advanced analytics capabilities. The latter principally includes Machine Learning (ML) and Natural Language Processing (NLP), with Smart Robotic Process Automation (SRPA) largely in trials. The study reveals that the majority of firms, 55 per cent, are still in the early stages, while 10 per cent have just started their journey. At the other end of the spectrum, only 10 per cent of firms are breaking new ground. This is when firms are generating substantial and sustainable value from their programs.
2018-11-07 00:00:00 Read the full story.

 

UOB collaborates with Intel on AML analytics project

United Overseas Bank (UOB) today announced it has collaborated with Intel to successfully test how federated advanced data analytics can enhance cross-border anti-money laundering (AML) efforts. The joint project between UOB and Intel set out to use a combination of leading technology and advanced data analytics to provide greater clarity about the extent of transactions made across countries and entities by a single client. As cross-border transaction data sit in multiple localities, maintaining data sovereignty and determining the risk of money laundering across geographies can be difficult and complex.
2018-11-12 10:42:00 Read the full story.

 

MapR Announces New Platform Update and Free Data Assessment Service

MapR Technologies, a provider of a data platform for AI and analytics, has announced a new product release and a free assessment service that provides a comprehensive understanding of a customer’s current data environment and the best practices to achieve a clear path to support AI, cloud, containers, and IoT deployments. Additionally, the company has introduced its “Clarity Program” which it says addresses questions customers may have about data lakes, how to get to the cloud, support hybrid environments, leverage containers, and extend data processing at the edge, as well as their future roadmap in light of the Cloudera-Hortonworks merger. The merger of Cloudera and Hortonworks “has put a spotlight on the fact that the shared underlying data platform is the same and there are 10 or more overlapping projects that need to be consolidated,” said Jack Norris, senior vice president, data and applications, MapR.
2018-11-08 00:00:00 Read the full story.

 

Gartner Lists Top 10 Strategic IoT Technologies, Trends Through 2023

Following is Gartner’s list of the 10 most strategic IoT technologies and trends that it expects will enable new revenue streams and business models during the next five years.

  1. Artificial Intelligence
  2. Social, Legal and Ethical IoT
  3. Infonomics and Data Brokering
  4. The Shift From Intelligent Edge to Intelligent Mesh
  5. IoT Governance
  6. Sensor Innovation
  7. Trusted Hardware and Operating System
  8. Novel IoT User Experiences
  9. Silicon Chip Innovation
  10. New Wireless Networking Technologies for IoT

2018-11-07 00:00:00 Read the full story.

 

Researchers develop AI that estimates acute kidney injury risk from clinical notes

Acute kidney injury (AKI) — a condition in which the kidneys suddenly fail to filter waste from the blood — can devastate the renal system of critically ill patients. The mortality rate can approach 89 percent if it progresses beyond stage 2 (AKI is categorized into three stages). And if it develops after major abdominal surgery, the risk of death is increased twelvefold.

Fortunately, progress has been made in developing techniques that aid in early detection. A paper published by researchers at Northwestern University and the University of Texas Health Science Center (“Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes“) describes an artificially intelligent (AI) system that can collect and extract risk factors from electronic health records (EHRs) and predict the likelihood of AKI within the first 24 hours following intensive care.
2018-11-08 00:00:00 Read the full story.

 

Become a Data Engineer with this Comprehensive List of Resources

Before a model is built, before the data is cleaned and made ready for exploration, even before the role of a data scientist begins – this is where data engineers come into the picture. Every data-driven business needs to have a framework in place for the data science pipeline, otherwise it’s a setup for failure. Most people enter the data science world with the aim of becoming a data scientist, without ever realizing what a data engineer is, or what that role entails. These data engineers are vital parts of any data science project and their demand in the industry is growing exponentially in the current data-rich environment.

There is currently no coherent or formal path available for data engineers. Most folks in this role got there by learning on the job, rather than following a detailed route. My aim for writing this article was to help anyone who wants to become a data engineer but doesn’t know where to start and where to find study resources. In this article, I have put together a list of things every aspiring data engineer needs to know. Initially we’ll see what a data engineer is and how the role differs from a data scientist. Then, we’ll move on to the core skills you should have in your skillset before being considered a good fit for the role. I have also mentioned some industry recognized certifications you should consider.
2018-11-08 23:20:37+05:30 Read the full story.

 

Mastering Deep Reinforcement Learning with OpenAI’s new ‘Spinning Up in Deep RL’ package

Reinforcement Learning is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep Reinforcement Learning refers to the combination of Reinforcement Learning with deep learning. OpenAI released their educational package for Deep Reinforcement Learning, Spinning Up in Deep RL on Nov 8 ‘ 2018. Their release statement seemed quite appealing to me, which stated:

“At OpenAI, we believe that deep learning generally — and deep reinforcement learning specifically — will play central roles in the development of powerful AI technology. While there are numerous resources available to let people quickly ramp up in deep learning, deep reinforcement learning is more challenging to break into. We’ve designed Spinning Up to help people learn to use these technologies and to develop intuitions about them. We’ve also seen that being competent in RL can help people participate in interdisciplinary research areas like AI safety, which involve a mix of reinforcement learning and other skills. We’ve had so many people ask for guidance in learning RL from scratch, that we’ve decided to formalize the informal advice we’ve been giving.”

So, I decided to quickly glance through the whole package and here’s a short tour and a bit of advice for those who wish to go through the complete package.
2018-11-11 19:18:56.104000+00:00 Read the full story.

 

Virtu to buy ITG; Nov still packed with events; A relieved VIX

Weekly news round-up including…

  • Analyzing Index Volatility Around Earnings
  • Loss-Buffering ETF that Offers Exposure to the S&P 500
  • Swedroe: Understanding Risk & Return

2018-11-07 20:57:29+00:00 Read the full story.

 

eBay’s AI algorithm proves good behaviour analysis is key to identifying credit card fraud

A report published by two eBay executives reveals that the online flea market’s new AI algorithm can identify 40% of credit card fraud transactions with high precision, a significant finding for a sector relying on tech-based detection techniques.

The approach taken by eBay turns usual ideas about automated fraud detection on its head. Rather than focusing on the changing patterns employed by bad actors to circumvent protective barriers, the proposition instead analyses instances of good behaviour.
2018-11-08 16:45:00 Read the full story.

 

We are an AI enabler, says Tealium CEO

Data platform company Tealium is positioning itself as an AI enabler on three fronts: data preparation, using machine learning to identify audiences and, activating those insights through marketers’ digital channels. “We are not an AI company, we are an AI enabler,” Tealium’s CEO Jeff Lunsford told Which-50 during a recent visit to Sydney.

Early next year Tealium is launching Tealium Think, a new product which will host machine learning models for its customers. Think will analyse data collected by Tealium to identify audience segments in real time. For example, on an ecommerce site Tealium will take the visitor-level information from CMS and run it through Tealium Think to identify which customers have a high probability of abandoning the purchase at each stage of the conversion funnel.
2018-11-12 09:54:16+11:00 Read the full story.

 

Machine Learning for RIA loyalty and customer engagement; by Morgan Stanley

Wealth management and AI is a natural combination. Standalone Fintechs, innovation labs of incumbents and of financial services IT providers, are all somehow working on this (3 types). There is another war of talent going on this area too. All three types of Financial services providers are looking for Data scientists and competing with all other industries (commerce, life sciences, and manufacturing). The market is tagging experienced conventional quants as AI experts. Public companies (mainly banks) are competing for tech branding. I realized that I have not written about Morgan Stanley as much as Goldman or JP Morgan. Of course, this is not deliberate. I am well aware of the heads on competition between which of course is accentuated from business media. Look at the headlines during this reporting season and you will undoubtedly get a sense of this short-term pressure that public markets and the quarterly cycles, inflict.

What caught my attention this time about Morgan Stanley, was the release of the new version of the so-called “Next Best Action” system to the 16,000 RIA of MS. This system has been around for several years but as a rule-based system suggesting investment options for advisors and their clients. A system that every single bank with a wealth management offering has and that we all as clients wonder which is “best” (as if that is the right question in the first place since none of these rule-based systems could be customized). Morgan Stanley’s “Next Best Action” is using Machine Learning to support advisors in increasing engagement. The success of this tool will be measured by its effectiveness to enhance the dialogue with the client whether it is through in-person meetings, phone calls or pure digital channels.
2018-11-06 00:00:00 Read the full story.

 

Accenture Forms Strategic Alliance and Invests in Data Analytics Firm Quantexa

“Accenture has invested in and formed a strategic alliance with Quantexa, a leading data analytics firm that provides technology solutions to uncover new intelligence. The minority investment made by Accenture Ventures will help Quantexa accelerate the development of its AI-powered entity resolution and network analytics technology working with Accenture Applied Intelligence. The new collaboration will help clients uncover new actionable insights across multiple industry use cases including fighting financial crime. As part of the alliance agreement, Accenture plans to build new capabilities that combine its technology and risk expertise with Quantexa’s network analytics platform. The collaboration aims to develop multiple AI-enabled solutions addressing business challenges in areas including anti-money laundering, credit risk and customer insight.”
2018-11-09 00:10:05-08:00 Read the full story.

 

Kaggle Blog : Maintained Datasets

Can you trust the data you use on Kaggle? Is it licensed? Has it been updated recently?

Those sensible questions are the reason for the new “Maintained by Kaggle” badge you may have noticed while browsing select datasets. This badge signifies that a dataset is maintained by Kaggle, though it may or may not be data that Kaggle has collected (e.g. Kaggle – Meta Kaggle vs. SF Open Data – Police Calls). Kaggle connects to datasets of other organizations using public APIs like Socrata and FRED.
2018-11-06 00:00:00 Read the full story.

 

Google Uses AI Tech To Predict Locations Of Earthquake Aftershocks

Google is working on a project that aims to make use of artificial intelligence (AI) technology in predicting the locations of earthquake aftershocks. The technology is still premature at present, but it could be a big help to many people in the future. A scientist from Google Inc. disclosed Tuesday that Google is developing a technology that utilizes machine learning to make forecasts of earthquake aftershocks. The company started the project after realizing the need to locate aftershocks so that recovery efforts could be carried out efficiently following the mainshock.

“We applied machine learning algorithms to analyze a database of earthquakes from around the world to try to predict where aftershocks might occur,” Martin Wattenberg, a senior staff research scientist at Google’s People + AI Research (PAIR) initiative, was quoted as saying by Yonhap. Wattenberg is currently working together with Harvard University researchers in developing the technology that could predict where aftershocks might take place. According to the scientist, the system they came up with so far has a precision rate of six percent, which is better from the previous three percent.
2018-11-06 08:14:30-05:00 Read the full story.

 

What’s Driving the Cloud Data Warehouse Explosion

The advent of powerful data warehouses in the cloud is changing the face of big data analytics, as companies move their workloads into the cloud. According to analysts and cloud executives, the phenomenon is accelerating, thanks largely to the potential to save large sums of money, analyze even bigger data sets, and eliminate the hassle of managing on-premise clusters. Amazon Web Services is largely credited with kicking off the cloud data warehousing (CDW) wave with Redshift. Since launching it in 2012, AWS has attracted 6,500 customers to Redshift and remains the company to beat thanks to its integration with AWS’ broad portfolio, according to a Forrester report on cloud data warehousing released last week.

But AWS Redshift has stiff competition, according to the Forrester report, which identified a total of 14 vendors in the CDW field. Those within shooting distance of AWS include Google Cloud, Snowflake, and Oracle, which Forrester identified as the other CDW leaders in its report. Snowflake, which closed a $450 million venture funding round last month, has grown quickly thanks to the ease of use, high performance, and low cost of its SQL-based offering. Google Cloud’s BigQuery, meanwhile, was cited by Forrester for its integration with AI and other data services. Oracle, meanwhile, also landed in the leader’s category of the Forrester Wave with its new Autonomous Data Warehouse (ADW). Ease of use is one of the biggest drivers of CDW, writes Forrester lead analyst Noel Yuhanna. “You can provision a cloud data warehouse in minutes without requiring any technical expertise, allowing business analysts and other nontechnical users to access, store, and process large amounts of data for insights,” he writes.
2018-11-08 00:00:00 Read the full story.

 

Here Are the Top Five Questions CEOs Ask About AI

Recently in a risk management meeting, I watched a data scientist explain to a group of executives why convolutional neural networks were the algorithm of choice to help discover fraudulent transactions. The executives—all of whom agreed that the company needed to invest in artificial intelligence—seemed baffled by the need for so much detail. “How will we know if it’s working?” asked a senior director to the visible relief of his colleagues.

Although they believe AI’s value, many executives are still wondering about its adoption. The following five questions are boardroom staples:

  1. “What’s the reporting structure for an AI team?”
  2. “Should we launch our AI effort using some sort of solution, or will coding from scratch distinguish our offering?”
  3. “Do we need a business case for AI?”
  4. “We’ve had an executive sponsor for nearly every high-profile project. What about AI?”
  5. “What practical advice do you have for teams just getting started?”

2018-11-09 15:30:37+00:00 Read the full story.

 

INVERNESS COUNSEL DEPLOYS INDATA MANAGED SERVICES OFFERING

NDATA, a leading industry provider of software, technology and services for buy-side firms, today announced that Inverness Counsel, a privately owned investment counsel firm registered with the SEC headquartered in New York City with more than $3.1 Billion in AUM, has successfully implemented INDATA’s Managed Services Offering including INDATA EOD, iPM Cloud and Epic Data API.

Inverness Counsel, one of the largest independent registered investment advisors (RIA) in the United States with a long-term track record working with high net worth individuals, families and trusts, was looking for ways to streamline its operations and technology efforts. A long-term INDATA software client, Inverness explored both in-house and third-party solutions before selecting INDATA.
2018-11-08 00:00:00 Read the full story.

 

MapR Targets Cloudera-Hortonworks Customers with ‘Clarity’ Release

MapR Technologies went on the offensive today against its Hadoop rivals Hortonworks and Cloudera with the launch of a “Clarity” release of its MapR Converged Data Platform, as well as a new offer for a free big data assessment from its professional services team. Cloudera and Hortonworks agreed to a blockbuster merger last month that will result in a single company with about 2,500 customers and $730 million in annual revenue. After the merger is complete, which is expected in the first quarter of 2019, the new company will deliver a pair of “Unity” releases to rationalize the disparate products and open source projects that comprise their respective Hadoop distributions.

It was only a matter of time before MapR Technologies, which has traditionally been viewed as the third leg of the Hadoop distribution stool, went on the offensive and attempted to capitalize on the merger of its two rivals and the impact that it will have on its offerings. That time is apparently now.
2018-11-07 00:00:00 Read the full story.

 

Maxta MxIQ Uses Analytics to Improve Storage Availability Across Clouds

Hyperconverged storage software maker Maxta, which is growing a niche clientele in a hot segment that includes Nutanix and others, has launched an analytics-insight platform to go with its frontline product. The Santa Clara, Calif.-based company claims that its new MxIQ data analytics product, released Nov. 6, gives users real-time visibility into their private cloud and multi-cloud environments to eliminate storage and data-movement issues before they occur and also obtain insights into key performance metrics.

Maxta MxIQ combines configuration metrics with visibility into capacity, performance and system health trends across data centers and clouds to provide a granular overview of customers’ IT environments. In this way, better storage-management decisions can be made—on the fly, if necessary.
2018-11-08 00:00:00 Read the full story.

 

Tech firms try to address the risks the AI race poses for research

Greg Benson has been a University of San Francisco professor teaching computer science for the last 20 years. He’s also part of a quiet effort to solve one of the field’s growing problems. During semesters, he spends one to two days a week at SnapLogic, a cloud integration company, and works full-time there during school breaks. Each year, he offers 10 of his machine learning master’s students the chance to intern at SnapLogic and work on AI research projects. If they do well, they can end up with a job. About a third of SnapLogic’s engineering team are former interns. “This has been wildly successful for us,” Benson said.

This is a useful recruiting method when even the tech giants are struggling for talent. But there’s also another innovation afoot: SnapLogic’s deal with Benson also shows how companies can support academics and make sure there are still professors to teach the next generation of AI researchers.
2018-11-08 09:50:30 Read the full story.

 

Digital transformation: Guide to become a smart company

The data revolution is gaining pace at breakneck speed, and we are finally towards the latter end of its implementation. Many inroads have been made by important stakeholders, and numerous organizations are currently trying to incorporate a data culture within their workplace. Future predictions suggest that every company will eventually be part of the data brigade and will benefit from the use of data analysis tools. How to become a data/information company – With growing hype across the market, many organizations want to know as much as they can about the intricacies involved in becoming a data/information company and what they need to do to become one. Although the questions are many, it is easy to answer them.

Being a part of the big data revolution is no different to what it was back in the day. Similar motivation is needed, and organizations need to know the importance of the process and the benefits that it would bring to them.
2018-11-07 06:20:38+00:00 Read the full story.

 

Cloudy weather ahead for IBM and Red Hat?

The world is buzzing about the software industry’s largest acquisition ever. This “game changing” IBM acquisition of Red Hat for $34 billion eclipses Microsoft’s $26.2 billion of LinkedIn, which set the previous record. And it’s the third largest tech acquisition in history behind Dell buying EMC for $64 billion in 2015 and Avago’s buyout of Broadcom for $37 billion the same year. Wall Street certainly gets nervous when it sees these lofty price tags. IBM’s stock was down 4.2 percent following the announcement, and there are probably more concerns over a broader IBM selloff around how much IBM is paying for Red Hat.

This sets the stage for massive expectations on IBM to leverage this asset as a critical turning point in its history. Given that IBM’s Watson AI poster child has failed to create sustainable growth, could this be their best opportunity to right the ship once and for all? Or is this mega merger a complicated clash of cultures and products that will make it hard to realize the full potential?
2018-11-10 00:00:00 Read the full story.

 

Why Community Engagement is Imperative for AI Success

It is clear that the commercialization of AI has begun in earnest. But as with any complex technology there are a lot of moving parts and a lot of complexity. AI is no exception since it incorporates big data and data management, advanced analytics, machine learning, and a variety of algorithms and models.

As AI tools and models mature, it will become the foundation for supporting business transformation and the ability of businesses to learn from massive amounts of data and help human and computer collaboration as never before. What is different? In the past we relied on business data to tell us where we have been and what we already know – with AI we can begin to learn from data in order to predict the future and correct problems before they impact the business. The bottom line is that AI is not a solitary approach for business To be successful, business leaders, IT professionals of all types must collaborate.

2018-11-06 15:00:53+00:00 Read the full story.

 

Police Are Using Big Data To Predict Future Crime Rates

Some police are starting to use big data to predict crime circumstances, and when and where illegal acts could happen. Here’s what to know about it.

Law enforcement has been changed drastically by technology over the past two centuries. The use of fingerprints was the beginning of the forensic revolution. DNA, ballistic analysis, CCTV and other types of technology have also played an important role. But big data may soon have a bigger impact on law enforcement than any technological development of the 21st Century. Big data has been used in law enforcement for some time. National crime databases have made it possible for law enforcement officials to check DNA, fingerprints and other forensic data across different jurisdictions across the country. Until recently, big data has mostly been used for monitoring forensic data to solve specific crimes. However, experts have started using predictive analytics algorithms to identify broader trends. This helps them in a number of ways:

  • They can make compelling cases to get emergency resources to fight recent crime waves
  • They can identify the likelihood that they are dealing with serial offenders
  • They can look for precipitating factors that cause crime epidemics and pass that information along to policymakers to take preventive measures

This could be one of the biggest breakthroughs in the quest to fight crime around the world.

2018-11-07 15:59:38+00:00 Read the full story.

 

Financial Planning in a World of Free Products and Plans

A great debate is currently being waged over the future of financial advice. On one side of the argument are the historians saying, “We’ve seen this before.” From historians’ point of view, every decade or so, new business entrants swoop in to guzzle down a bunch of the wealth management pie by providing services for free or near free.
Historians remind us of two previous “failed” attempts to eliminate the financial advice business: discount brokerages and no-load mutual funds. Schwab and e*Trade the primary villains of the first, Vanguard the unquestioned rabble-rouser of the second. To historians, the rise of fintech is of the same ilk: destined to gain a little market share, a lot of media attention, and all the while, financial advisors will continue to provide the “real” value by working with people to solve real problems of wealth accumulation and distribution. Historians are immune (and generally scoff at) the infamous phrase: “This time it’s different.” To them, it never is.
2018-11-09 00:00:00 Read the full story.

 

Clearbanc raises $70M to give startups ad money for a rev share

Selling equity to buy Facebook and Google ads is a bad deal for startups. Clearbanc offers a fundraising alternative. For fast-growing businesses reliably earning sales from their marketing spend, Clearbanc offers funding from $5,000 to $10 million in exchange for a steady revenue share of their earnings until it’s paid back plus a 6 percent fee. Clearbanc picks what merchants qualify by developing tech that scans their Stripe, Facebook ads, and other accounts to assess financial health and momentum. It’s already doled out $100 million this year. “As a business successfully scales, we continue to provide them ongoing capital” co-founder and CEO Andrew D’Souza tells me. “Our goal is the be the first and last backer of a successful business and save the entrepreneur from having to take hundreds of pitch meetings to keep their company funded.”

After largely flying under the radar since being found in 2015, now Clearbanc has some big funding news of its own. It’s now raised $70 million from a seed and new Series A round from Emergence Capital, Social Capital, CoVenture, Founders Fund, 8VC, and more with Emergence’s Santi Subotovsky joining the board. “Venture capital has shifted. Instead of funding true research and development, today 40% of venture capital goes directly to buying Google and Facebook ads” D’Souza claims (that may be true for some ecommerce startups but TechCrunch could not verify that stat for all startups). “Equity is the most expensive way to fund digital ad spend and repeatable growth. So we created something new.”
2018-11-12 00:00:00 Read the full story.

 

Facebook ‘bug’ stopped it removing terrorist content

…Facebook is using AI to spot potentially harmful posts which look like they express support for Islamic State or al-Qaeda, with an automated tool giving each post a rating to show how likely it is to contain support for terrorism. Human reviewers then prioritise the items with the highest scores, and some posts with a very high score are automatically removed if the technology indicates that there is a very high likelihood that they contain terrorist content.

Facebook said the machine learning had helped reduce the average amount of time taken to remove posts reported by users from 43 hours in the first quarter to 18 hours in the third.
2018-11-11 00:00:00 Read the full story.

 

Facebook says it’s gotten a lot better at removing material about ISIS, al-Qaeda and similar groups

Facebook took down more than 12 million pieces of terrorist content on its social network between April and September, the company disclosed on Thursday. Facebook defines terrorist content as posts that praise, endorse or represent ISIS, al-Qaeda and their affiliate groups. The removal of the terrorist content is part of an on-going effort by Facebook to rid its service of harmful content, which also includes misinformation, propaganda and spam.

Facebook said, “We measure how many pieces of content (such as posts, images, videos or comments) we took action on because they went against our standards for terrorist propaganda, specifically related to ISIS, al-Qaeda and their affiliates.” The company said it removed 9.4 million pieces of terrorist content during the second quarter and another 3 million posts during the third quarter. By comparison, the company in May announced that it removed 1.9 million posts during the first quarter of 2018.
2018-11-08 00:00:00 Read the full story.

 

UPDATE 4-Facebook referred to EU watchdog over targeting, fake ads

 

  • UK’s data watchdog refers Facebook to Irish regulator
  • Watchdog says it found broad issues at Facebook
  • Company has made changes to improve data control (Adds Acxiom statement)

Britain’s information watchdog has asked Facebook’s lead European regulator to investigate how the company targets, monitors and shows adverts to users, saying it was concerned about some practices at the world’s biggest social network. Britain’s Information Commissioner has been investigating the use of data analytics to influence politics after consultancy Cambridge Analytica obtained the personal data of 87 million Facebook users from a researcher.

The British watchdog said on Tuesday as part of that inquiry it had also found broader issues at Facebook, which it had referred to Ireland’s data regulator, the lead supervisor for the social network in the European Union.
2018-11-06 00:00:00 Read the full story.

 

European watchdog to examine Facebook’s advertising methods

UK policy makers have been urged to implement tighter rules around how digital ads can be used in elections, while Facebook is set for more scrutiny from European regulators. Those are two key takeaways from the British Information Commissioner’s investigation into the role of data analytics in elections.

Launched in May 2017, the investigation took a high profile turn in March this year when it was revealed the data of 87 million Facebook users was improperly harvested and some of it used by Cambridge Analytica to target voters during the 2016 USA Presidential campaign. The massive investigation is still ongoing (the commission says it’s working through 700 terabytes of data — the equivalent of 52 billion pages) but a 113-page report presented to UK Parliament overnight details the findings and enforceable actions undertaken so far.
2018-11-07 17:09:57+11:00 Read the full story.

 

Will GraphQL Become a Standard for the New Data Economy?

Don’t look now but a new language called GraphQL is emerging that could radically simplify how developers use APIs to get data into applications, and potentially provide a graph-like alternative to procedural REST. The company behind the open source software, Apollo, today announced the GraphQL Platform to standardize access to the new technology.

GraphQL was originally developed at Facebook to provide a more powerful way to assemble the various pieces of data that compose its social media platform. The social media giant wanted to create a higher abstraction to reduce the burden on developers to know specific details of all the various API calls for the different elements that Facebook exposes on its screen – like which users have liked a post, which have commented, and whether they’re friends with you, etc. While APIs themselves provide a good method for calling data and processes, there are some big limitations in the REST approach to API calls that the computer industry has gravitated towards, explains Geoff Schmidt, the co-founder and CEO of Apollo.
2018-11-07 00:00:00 Read the full story.

 

Get Ready for AI Transformation in the Grocery Business

Among the six digital imperatives for a successful omnichannel strategy established by FMI and Nielsen is one that involves completeness and consistency across in-store and digital shelves, cutting costs and creating a clear assortment inventory that keeps shoppers coming back. This is particularly relevant, given that grocery retail spending on technology could vastly increase shoppers’ online grocery habits. By 2022, consumers could be spending $100 billion dollars a year on online grocery. That’s equal to every U.S. household annually spending $850 online for food and beverage, according to The Digitally Engaged Food Shopper. One way that grocery retailers plan to meet this emerging demand is by considering the use of artificial intelligence (AI).

Two grocery retailers recently announced at Groceryshop how they’re tackling and optimizing the digital shelf head-on – one is implementing aisle-scanning retail inventory robots, known as Tally, and the other is automating the “picking” process for its consumers’ baskets. We also heard how AI technologies promise to solve various pain points across the grocery retail value chain, from the supply chain to merchandising and marketing.
2018-11-09 15:00:02+00:00 Read the full story.

 

This AI shows you how your face would look as a celebrity

I look like the completely forgettable leading man in any Lifetime holiday movie. Or pretty much any white male protagonist in a video game. My face is suddenly symmetrical. My beard is properly trimmed. My curly bedhead is trimmed into a soft buzz cut. And I’m smiling. Ick. That’s it–I look like Chris Pratt! And I have AI to thank.

AI Portraits is a new site and research project by Northeastern University professor Mauro Martino and researcher Luca Stornaiuolo. You upload a photo of yourself, and Martino’s AI tries to reconstruct your face with what it knows about faces.
2018-11-09 08:00:13 Read the full story.

 

3 Chip Stocks to Buy Amid Tech’s Wild Swings

Several chip stocks that have severely fallen off this year’s highs are looking well positioned to make a strong rebound. Nvidia Corp. (NVDA), Marvell Technology Group Ltd. (MRVL), and Taiwan Semiconductor Manufacturing Company Ltd. (TSM), despite all being down in double digits from earlier highs, are considered diamonds-in-the-rough, according to a few veteran market watchers. They see the semiconductor sector as a treacherous place to be right now, according to CNBC.

3 Chips that Can Rebound : Stock 5-year Performance  : Fall from 2018 Highs
Nvidia : + 1,337% : – 26.8%
Taiwan Semiconductor : + 113% : – 14.3%
Marvell Technology : + 31% : – 29.1%

2018-11-06 04:00:00-07:00 Read the full story.

 

IBM Launches Pinpoint Verify to Improve Digital Identity Trust

IBM announced its new Pinpoint Verify technology on Nov. 8, providing organizations with a model for combating online fraud with a digital identity trust approach.

Alongside the new technology release, IBM sponsored a report from Javelin, titled “Preserving Trust in Digital Services,” that provides context for why digital identity trust is needed. Among the primary findings of the 27-page report is that financial institutions reported that just 50 percent of consumers believe mobile banking is secure.

“Many popular methods, such as user name and password or knowledge-based authentication, can be both ineffective at stopping malicious users and cause customer frustration,” Jason Keenaghan, director of IAM and fraud at IBM Security, told eWEEK. “However, we were most surprised to see these organizations reporting on their actual authentication failure rates.”
2018-11-09 00:00:00 Read the full story.

 

Ever-evolving use cases for RPA

RPA or (Robotic Process Automation) is a way to automate business processes by applying technology as a solution which is governed by business logic and structured inputs. There are many tools like Blueprism available in the market to facilitate and automate basic operations.

Those who have been workingwith Excel Spreadsheets can see this as a process that builds Macros onsteroids that can do much more than just handling Excel Spreadsheets but can do many data-oriented tasks like Data Entry, Data Clean up, merging datasets, validating various web forms etc. and free up the user’s time to do more complex tasks that require their attention. Many see RPA automate mundane rules-based business processes and others see RPA as a step towards adopting machine machine learning (ML) and artificial intelligence (AI) tools in the long run.
2018-11-11 06:48:31 Read the full story.

 

A new Walmart ‘cloud factory’ will accelerate digital innovation, boost business efficiency

Walmart is expanding its technology center in Austin, Texas, to accelerate digital innovation that transforms how associates work and delivers more convenient ways for customers to shop. About 30 technologists, including engineers from both Walmart and Microsoft, will work together side by side in the cloud factory, expected to open in early 2019 as an extension to a strategic partnership announced in July. The factory will be an expansion of Walmart’s innovation hub, a vibrant workplace opened earlier this year in the center of Austin’s growing technology scene.

The Walmart-Microsoft team – known internally as “4.co” for its location at Fourth and Colorado streets – will initially focus on migrating Walmart’s thousands of internal business applications to Microsoft Azure. The team will also build new, cloud-native applications. The collaboration will be part of a multi-year journey to modernize Walmart’s enterprise application portfolio, create more efficient business processes and decrease operational costs associated with legacy architecture.
2018-11-05 15:00:08+00:00 Read the full story.

 

Hyperparameter Tuning, Regularization & Optimization

Building that first model – isn’t that what we strive for in the deep learning field? That feeling of euphoria when we see our model running successfully is unparalleled. But the buck doesn’t stop there. How can we improve the accuracy of the model? Is there any way to speed up the training process? These are critical questions to ask, whether you’re in a hackathon setting or working on a client project. And these aspects become even more prominent when you’ve built a deep neural network.

Features like hyperparameter tuning, regularization, batch normalization, etc. come to the fore during this process. This is part 2 of the deeplearning.ai course (deep learning specialization) taught by the great Andrew Ng. We saw the basics of neural networks and how to implement them in part 1, and I recommend going through that if you need a quick refresher. In this article, we will explore the inner workings of these neural networks, including looking at how we can improve their performance and reduce the overall training time. These techniques have helped data scientists climb machine learning competition leaderboards (among other things) and earn top accolades. Yes, these concepts are invaluable!
2018-11-12 12:35:07+05:30 Read the full story.

 

Predictions 2019: This Is The Year To Invest In Humans, As Backlash Against Chatbots And AI Begins

For some time, the burning question has been: Will robots replace humans? While the proliferation of robotic process automation (RPA) has reduced headcount in the back office, it’s a different story for customer service and sales. In a Forrester survey, 46% of companies said sales and marketing are leading the investment in and adoption of AI systems, followed by customer support (40%). With many companies putting wood behind the arrow of AI investments, there will be a ripple effect through sales, marketing, and customer support that impacts employees and customers.

Here are a few takeaways from our 2019 services and sales predictions:

  • Customers will lead a community-based revolt against corporate chatbots.
  • The majority of chatbot deployments will provide poor escalation paths to agents.
  • AI-embedded sales technology will cause salespeople to falsify data regularly.

2018-11-08 12:09:38-05:00 Read the full story.

 

Talend Buys Stitch for $60M

Stitch, a provider of integration services for loading cloud data warehouses, was snapped up by ETL software developer Talend today in a $60 million deal. Stitch is a relatively small firm that was spun out of RJMetrics when that firm was acquired by Magento in 2017. Just over a year later, the 33-person company racked up more than 900 customers for its cloud data warehouse integration service. According to CMO Ashley Stirrup, the Philadelphia, Pennsylvania company has been so successful because it made data integration “dirt simple.” “It’s really just a simple Web service for getting data into cloud data warehouses,” Stirrup says. “They really focused on making the whole thing a self-service process.”
2018-11-07 00:00:00 Read the full story.

 

Microsoft teams with Answer ALS, makes $1M donation to ambitious big data project

Several years ago, former football player Steve Gleason came to Microsoft with a challenge: develop technology to ease the effects of amyotrophic lateral sclerosis (ALS), a progressive neurological disease that was robbing him of his ability to move his wheelchair and play with his son. The company responded with technology that allowed him to move his wheelchair and communicate using a keyboard by moving his eyes.

Now, Answer ALS — a project that also originated from a Gleason effort — is looking beyond technology as an aid, harnessing the power of big data in the hopes of better understanding the disease and ultimately developing treatments. They’re in the midst of a five-year project to gather 6 billion data points each from 1,000 people with ALS. Thursday morning, Microsoft announced it will contribute to the groundbreaking effort with a $1 million donation in cloud computing and technical services to help researchers access that vast data.
2018-11-08 14:00:01-08:00 Read the full story.

 

Samsung Galaxy S10 Will Arrive With Dedicated Co-Processor For Improved AI

There are already a bunch of rumors about the Samsung Galaxy S10, which is expected to arrive early next year. Now, a new report claims that Samsung is planning to add a dedicated AI co-processor to the device that would be responsible for powerful artificial intelligence and machine learning tasks.

Specs for the AI co-processor are currently unavailable, but a report from the Korean website ETNews suggests that the neural processing unit (NPU) will arrive with two dedicated artificial intelligence cores. If this were true, then users should expect performance improvements when it comes to AI-related tasks. This may include image processing, image recognition and speech recognition.
2018-11-06 05:58:31-05:00 Read the full story.

 

Gap Inc. accelerates digital transformation with Microsoft Cloud

By building and centralizing its data platform on Azure, Gap Inc. can now apply advanced analytics and machine learning to gain a comprehensive understanding of customers across channels, and to deliver personalized merchandising, marketing and service for all brands in its portfolio. The company is using Microsoft Power BI to empower more employees at Gap Inc. to visualize and act on information to create the best customer experience and drive the business.
2018-11-09 00:00:00 Read the full story.

 

AI Healthcare on the NHS gets £50m shot in the arm

The UK government has announced five new “centres of excellence” for digital pathology and imaging, including radiology, using the latest advances in medical AI. The new centres will be based in Leeds, Oxford, Coventry, Glasgow and London, making intelligent image analysis available on the NHS that could potentially lead to better clinical decisions for patients and free up more staff for direct patient care.

Recent developments in machine learning have enabled companies like Kheiron to create AI systems that can detect cancer at an early stage, drastically increasing the likelihood of effective treatment. Doctors, businesses and academics will all play a role in developing and researching new products at the centres. The government says it will prioritise using genomics and image analysis to understand how other complex diseases develop. The image analysis developed by the team will use AI tools to analyse medical images such as x-rays and microscopic sections from tissue biopsies, revealed UKRI CEP Sir Mark Walport.
2018-11-06 00:00:00 Read the full story.

 

Government funds trial of artificial intelligence to help with breast cancer screenings

The UK government has given funding to a new medical trial which uses artificial intelligence technology to automate part of the screening process for breast cancer. A grant has been given to London-headquartered technology start-up Kheiron Medical, which uses a form of AI named deep learning to process millions of mammograms. The company will test its software in conjunction with the East Midlands Radiology Consortium, which works across seven NHS Trusts in the East Midlands.

Kheiron Medical’s technology helps radiologists to process large numbers of mammograms in order to identify the small proportion of people who have breast cancer. The NHS conducts “double reading” of mammograms, meaning that two different radiologists check the same images for signs of breast cancer. Kheiron Medical acts as a second reader alongside human radiologists, helping to reduce the number of experts who have to be involved in the screening process.
2018-11-11 00:00:00 Read the full story.

 

ScyllaDB Releases Scylla Open Source 3.0

ScyllaDB, the real-time big data database company, is releasing Scylla Open Source 3.0, introducing new production-ready capabilities. The company also previewed Scylla support for concurrent OLTP and OLAP, an industry first that enables simultaneous transactional and analytical processing.

Scylla Open Source 3.0 features a close-to-the-hardware design that makes optimal use of modern servers. Written from the ground-up in C++ to provide significant improvements to throughput, latency and administration, Scylla delivers scale-up performance of more than 1,000,000 IOPS per node, scales out to hundreds of nodes, and consistently achieves a 99% tail latency of less than 1 millisecond.
2018-11-09 00:00:00 Read the full story.

 

Woebot is the World’s First Mental Health Chatbot

Working 24 hours a day, 365 days a year across more than 130 countries, Woebot is undoubtedly a busy therapeutic chatbot. The good news is that Woebot recently secured $8 million to gain access to mental health care worldwide. The world’s first mental health chatbot, Woebot was founded by Dr. Alison Darcey in 2017 for young adults in college and graduate school. Designed to use natural language processing, therapeutic expertise, excellent writing, Woebot comes with “occasional dorky joke”. The therapeutic framework is said, “to create the experience of a therapeutic conversation for all of the people that use him.”

With proven results, Woebot has gained traction and now receives two million messages per week, recording a 50 percent month-over-month growth in the last quarter. A randomized controlled trial at Stanford University showed that the college students aged 18–28 years, who chatted with the therapeutic Woebot, significantly reduced the symptoms of depression in 2 weeks.
2018-11-06 15:20:20+00:00 Read the full story.

 

An Anthropologist in Silicon Valley

…Now, in 2018, we find the world abuzz with the possibilities for artificial intelligence (AI) to transform work in such fields as health care, agriculture, and education. It feels a bit like a return to the 1980s, only now with advances in AI, knowledge work is in the sights of those who are pursuing an automation agenda. The mantra now is that smart machines will be able to perform tasks that require human expertise, knowledge, and judgement.

I’ve had a chance to revisit the question of what it will take for machines to replace the things workers do as efforts are underway in my organization to design a cognitive tool ostensibly capable of performing the tasks of highly skilled workers who design IT infrastructure solutions for client organizations.
2018-11-09 00:00:00 Read the full story.

 

Cloud Computing As The Foundation For Digital Transformation

Last year, Forrester predicted that cloud computing would radically accelerate enterprise transformation everywhere. After a decade of powering small and medium business success — and giving disruptive companies the tools and technologies they needed to compete head on with the world’s largest firms — cloud was poised to drive significant enterprise change in the very firms being disrupted by innovative startups.

In 2018, cloud computing has indeed become a must-have technology for every enterprise. Cloud is no longer a place to get some cheap servers or storage. It’s not even a single place. Cloud computing is now shorthand for how companies turn amazing ideas into winning software — faster. Nearly 60% of North American enterprises now rely on public cloud platforms, five times the percentage that did just five years ago. Private clouds are growing fast, too, as companies not only move workloads to the top hyperscale public clouds but create powerful on-premises cloud platforms in their own data centers, using much of the same open source software they can find in the public clouds.
2018-11-08 12:08:23-05:00 Read the full story.

 

Big Data for Big Pharma: The Power of Predictive Analytics

The pharmaceutical industry is a billion-dollar enterprise which sits on mountains of data. It could use a tool which takes these heaps of information and neatly classifies them, highlighting the relationship between different entities like doctors, patients, prescribed drugs, and diagnoses. This industry faces countless problems related to selling, limitations dictated by privacy concerns, tighter marketing budgets and depending on the recommendation of the physician to make a sale. All these issues would be handled better if there was in place a way to anticipate future directions based on real-time data, not only historical recordings.

Predictive Analytics has the power to present elegant solutions to these by creating statistical models which can approximate the demand for certain drugs neatly, estimate the sales capacity of each doctor and follow each step of the patient journey.
2018-11-09 00:30:03-08:00 Read the full story.

 

8 unique ways to use AI for explosive business growth

Artificial Intelligence (AI) has gained momentum in every industry over the past few years. Businesses are using it to improve their productivity and performance. Many people believe that by 2030 AI will contribute $15.7 trillion to the global economy. There are lots of great benefits for those businesses who are investing in AI today – mainly in the form of having a competitive advantage. This is something that most executives seemingly understand, but it’s still important to understand its practical uses for your niche.

Make better business decisions with AI-based Analytics
Hacker Noon says the age of big data started with improvements in network and storage technology. This data is useless if you don’t properly analyze it though. In order to receive the desired output, you need to learn from the data available. However, because of its massive size this isn’t something human intelligence can do. You need to rely on machine learning and deep learning algorithms instead. Here you can find patterns, which is something that has helped Walmart understand the 245 million customers who visit their stores and websites. With this information in hand, they’ve been able to make better decisions.
2018-11-12 09:30:18+00:00 Read the full story.

 

How to Differentiate Yourself During Data Science Interviews

Landing a new data science position involves taking a series of steps to showcase your ability to work with data and whether you’ll be a good fit with the culture of a company. In this post, I’ll tackle one of the most important parts of the process (and often most dreaded): the technical interview. Most people I’ve talked with spend a lot of time practicing for coding challenges and brushing up on skills like SQL queries. While these are important aspects of preparing for an interview, they place the emphasis solely on how well you can work with a keyboard.

During my own job search, I’ve instead spent a lot of time thinking about how I can instead use the technical interview as a means to differentiate myself from the other applications. Most of us can code a function to indicate whether a number is a prime number or not (hint: modulo is your friend). What is often overlooked is how each of your answers is an opportunity to provide context to your particular form of problem solving. The optimal context will depend on the particular question you’re posed, the interviewer, and the role that you’re applying for. However, from my experience there are three main types of context that work well during the interview process.
2018-11-11 21:10:17.499000+00:00 Read the full story.

How Prague’s Avast went from Soviet-era security project to $4.5 billion IPO

…The backbone of Avast’s security is a cloud-based network that combines machine learning and artificial intelligence to detect threats and develop solutions. Any device running Avast software is constantly looking for malicious files, and anything suspicious is funneled into that network for analysis. If a problem is detected, updates are pushed out to protect users.
2018-11-12 00:00:00 Read the full story.

 

How AI, IoT, and Other Technologies Will Need to Coalesce into Comprehensive Counterdrone Defenses

Drones are the foundation of some of the most devastating weapon systems in many countries’ arsenals. They are also a growing focus of smart cities everywhere. Indeed, drone-related projects are likely to claim a significant portion of the projected $135 billion annually that public agencies worldwide will invest in smart cities by 2021, according to International Data Corporation estimates.

For all of our sakes, let’s hope that counterdrone initiatives benefit from some of that investment. Drone technology can monitor our urban environments, aid in traffic management, and accelerate disaster response. But it can just as easily be leveraged by evil people to poison our air and water, block our roads and tunnels, and detonate explosives at lightning speed and with surgical precision.
2018-11-06 00:00:00 Read the full story.

 

Impact of AI on the Security Dilemma Between the US and China

Recent breakthroughs in machine learning and artificial intelligence (A.I.) have prompted breathless speculation about their national security applications. Yet most of that work has focused narrowly on their implications for autonomous weapons systems, rather than on the broader security environment. Apart from Michael Horowitz and a handful of others, few scholars have sketched out how A.I. might affect core questions of international relations and foreign policy.

One key challenge stands out: What influence will A.I. have on security dilemmas between great powers? With the two leading producers of A.I., the United States and China, already eyeing each other warily, the question is far from an idle one. If we are to maintain a stable international order, we need to better understand how artificial intelligence may exacerbate the security dilemma—and what to do about it.
2018-11-09 15:10:50+00:00 Read the full story.

 

Inspirational, innovative groups find support and cash for causes through Social Venture Partners

Pedro Ciriano Perez doesn’t like to call his nonprofit’s approach to teaching computer science “unconventional” — but Geeking Out Kids of Color (GOKiC) definitely has a different strategy.

To open the door to technology to kids who are black, Hispanic, Muslim and other underserved races, ethnicities, religions and genders, GOKiC has a unique philosophy. “We focus around racial equality and gender first,” said Perez, “and from there we’ll teach out.”
2018-11-09 14:00:08-08:00 Read the full story.

 


Behind a paywall or registration wall…

 

Is Your Company Ready to Protect Its Reputation from Deep Fakes?

Social media platforms finally appear to be making a real effort to take on fake news. But manipulative posts may soon be the least of our problems. What looms ahead are deep fakes, realistic forgeries of people appearing to say or do things that never actually happened. Imagine, for example, an authentic-seeming video that shows your CEO promising to donate $100 million to a charitable cause — or saying something racist or sexist. Companies’ cri…
2018-11-08 15:45:41+00:00 Read the full story.

 

Why Legacy and Traditional Data is a Goldmine for AI and Analytics

Most organizations involved in advanced analytics are using big data to feed their AI projects. Many analytics teams are familiar with data in Hadoop and Spark, but are often much less fluent in legacy data sources, such as data from relational databases, enterprise data warehouses and applications running on mainframes and high-res server platforms.

Download this white paper to learn why you need to incorporate legacy data in your analytics, AI and ML initiatives and more about the steps you’ll need to take to create a data supply chain for legacy data.
2018-11-06 00:00:00 Read the full story.

 

Forrester Wave: Machine Learning Data Catalogs

Big data is growing faster than the capabilities available to manage and analyze it. Get this vendor comparison to learn how a modern master data management platform will help you to achieve better outcomes.
2018-11-09 00:00:00 Read the full story.

 

Artificial intelligence app tracks coughs and phlegm to treat lung disease

Doctors will soon be able to monitor lung disease patients remotely and tell whether they are feeling worse through technology similar to Apple’s Siri and Fitbit, IBM scientists have said. The US tech firm is trialling an artificial intelligence-powered app that can listen to patients’ coughing through their smartphone speakers, and analyse their own phlegm by uploading photos to the app.

It tracks the efficiency of the disease treatment outside of hospital to adjust it in real time, and is able to alert the doctor if it thinks the patient is getting worse. Patients with additional heart problems would be tracked by a Fitbit-style armband…
2018-11-11 00:00:00 Read the full story.

 

How an academic specialist in human memory created a chat app that’s helping companies fight harassment and discrimination

Artificial intelligence promises to reduce car accidents through autonomous driving and crime through facial recognition.

It might also help companies tackle the pervasive problems of workplace harassment and discrimination.

That’s the theory of the founders of Spot, a chatbot designed to help the victims of harassment and discrimination document their experiences. Spot uses natural language processing — and AI techno…
2018-11-11 00:00:00 Read the full story.

 

Don’t fear the rise of the robots: it is already here

With good reason too. Robots do not find themselves in many workers’ good books these days. Both blue and white collar workers fear being replaced by them, as advances in mechanical engineering and artificial intelligence software continue.

Alarm at robots’ potential impact on the workforce has led to the calls for them to be taxed, a cause that has created a rare alliance of Bill Gates, Jeremy Corbyn and the economist Robert Shiller. They argue that taxing human workers, and not robot ones, will place……
2018-11-11 00:00:00 Read the full story.

 

AI could soon be all around us — here’s how that could upend 8 different industries

Some major industries could soon be shaken up by a new development in artificial intelligence— the technology’s increasing portability.

Chip manufacturers are making processors specifically for machine learning and related AI features, noted Deloitte analysts David Schatsky, Jonathan Camhi, and Aniket Dongre in a new report. In many cases, those chips are being designed to consume minimal power, making it possible for them to be used in small, portable devices. Meanwhile, AI software developers are designing new algorithms that can be run directly on such chips without ever needing to connect to compute…
2018-11-11 00:00:00 Read the full story.


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