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AI & Machine Learning News. 03, June 2019

Samsung’s Creepy New AI Can Generate Talking Deepfakes From a Single Image

Our deepfake problem is about to get worse: Samsung engineers have now developed realistic talking heads that can be generated from a single image, so AI can even put words in the mouth of the Mona Lisa. The new algorithms, developed by a team from the Samsung AI Center and the Skolkovo Institute of Science and Technology, both in Moscow work best with a variety of sample images taken at different angles – but they can be quite effective with just one picture to work from, even a painting.

Not only can the new model work from a smaller initial database of pictures, it can also produce computer-generated videos in a shorter time, according to the researchers behind it. And while there are all kinds of cool applications that the technology could be used for – such as putting an ultra-realistic version of yourself in virtual reality – it’s also worrying that completely fake video footage can be produced from as little as one picture.

2019-05-26 00:00:00 Read the full story.

CloudQuant Thoughts… The possibilities for Deep Fakes are becoming more worrysome with every passing week. The ability to produce a 3d talking head from one image is spectacular.

 

Investment Data Standards Organization Releases Web Crawling Best Practices • Integrity Research

The Investment Data Standards Organization (IDSO), a non-profit consortium of alternative data industry practitioners, released draft web crawling best practice standards for industry review. Meanwhile a seminal court case that may dramatically impact web harvesting procedures is still pending. IDSO’s 17-page report, which is available to non-members, reviews risk identification, categorization, and minimization of online data collection practices known as web crawling, web harvesting or web scraping. The report focuses specifically on web crawling techniques used within the alternative data industry, which is an information economy focusing on mining investment insights from big data. “We see IDSO’s alternative data best practices as a necessary addition to the industry,” said Justin Zhen, co-founder of Thinknum, an alternative data provider which is a leading provider of web data. “The standards will help shed light on the compliance-related gray areas of leveraging powerful web harvested data such as ours to generate unique alpha.”
2019-05-29 05:15:54+00:00 Read the full story.
Interest Score: 2.1632, Positive Sentiment: 0.3196, Negative Sentiment 0.0492

CloudQuant Thoughts… Legitimate sourcing of data and paying a reasonable fee for that data is a mainstay for data research but many many machine learnings demonstrations utilize questionable data sources. Laying down best practices can only be beneficial.

 

Portland quietly launches mobile location data project with Alphabet’s controversial Sidewalk Labs

People in the Portland metro area with smartphones may not realize it, but they have digital clones. After months of preparation, the initial phase of Portland’s project employing city mobility software from Sidewalk Labs, the controversial startup owned by Google parent Alphabet, is underway.

If all goes as planned, Portland will launch a year-long pilot of the Replica software, costing nearly $500,000 in total. In exchange, Portland gets access to a massive dataset that mirrors how people actually move throughout the city and its surroundings.

The purpose is to regularly query, for example, timely insights into what worker commutes entail, what the impacts of Uber and Lyft are on traffic congestion, and how many cyclists use protected bike lanes such as those along high-trafficked areas like Governor Tom McCall Waterfront Park.
2019-05-28 13:00:29-07:00 Read the full story.
Interest Score: 1.0458, Positive Sentiment: 0.1046, Negative Sentiment 0.1917

CloudQuant Thoughts… Here in Austin a local programmer put together an incredibly useful web page that used publicly available Android phone location data to let you know traffic flow on the major arteries together with historical norms. It seems his data source was cut off and it does not surprise me to see this same data now being monetized by Google in a very similar way. The concern would be that cash strapped local councils will limit their maintenance to the more “popular” locations in their cities. It is still very impressive!

 

How NVIDIA EGX Accelerates AI at the Edge

This week at Computex 2019 in Taipei, GPU market leader NVIDIA announced its new EGX server, an engineered system that brings high performance, low latency AI to the edge. The concept of EGX is similar to NVIDIA’s DGX, which is an engineered system specifically designed for data science teams (hence DGX, where Edge = EGX). The model of the engineered system is that it’s a full turnkey solution that offers all the necessary hardware and software required to perform that specific task. It’s literally plug-and-play AI.

I’ve spoken to DGX customers who have told me that the turnkey nature of DGX enables them to speed up the process of deploying, tweaking and tuning the infrastructure required for data sciences from several weeks or even months to a single day. I expect EGX to have a similar but greater value proposition.
2019-05-29 00:00:00 Read the full story.
Interest Score: 1.5807, Positive Sentiment: 0.1383, Negative Sentiment 0.0988

CloudQuant Thoughts… I pick out Nvidia for comment on this blog probably more than any other company, which is impressive considering the amount of money invested by the major players. This “several weeks/months to a single day” comment jumped out at me from this article.

Astounding AI guesses what you look like based on your voice

A new artificial intelligence created by researchers at the Massachusetts Institute of Technology pulls off a staggering feat: by analyzing only a short audio clip of a person’s voice, it reconstructs what they might look like in real life.

The AI’s results aren’t perfect, but they’re pretty good — a remarkable and somewhat terrifying example of how a sophisticated AI can make incredible inferences from tiny snippets of data.
2019-05-28 00:00:00 Read the full story.

CloudQuant Thoughts… In the past we have had people construct how people would have looked based only on their skull,  Researchers have predicted how long extinct animals would have sounded based on their physical makeup so it should come as no surprise that AI has proven very capable at working out how someone looks from only their voice.

AI Restores Photos of ’90s Hong Kong Film Stars

Earlier this month restored images of iconic Hong Kong film stars like Bridget Lin and Joey Wong began circulating on Chinese social media. An AI-enabled touch-up process revealed distinct facial contours and features in old and fuzzy or low-res photos, revisiting the comely visages that made the public fall in love with these ’90s stars. Hashtagged AI-enhanced Lin and Wong pics spawned more than 40,000 discussion threads and 190 million page views.
2019-05-30 00:00:00 Read the full story.

CloudQuant Thoughts… Easily overshadowed by the Samsung 3d face from a single image above but this AI is potentially much more useful to us than Samsung’s. Imagine feeding it your low quality scans of family snaps and having it recreate them in super high resolution.


Decades-old discoveries are now electrifying the computing industry and will soon transform corporate America

Over the past four years, readers have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies. Most obviously, the speech-recognition functions on our smartphones work much better than they used to. When we use a voice command to call our spouses, we reach them now. We aren’t connected to Amtrak or an angry ex.

In fact, we are increasingly interacting with our computers by just talking to them, whether it’s Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, or the many voice-responsive features of Google. Chinese search giant Baidu says customers have tripled their use of its speech interfaces in the past 18 months.
2019-05-31 12:00:17+00:00 Read the full story.
Interest Score: 1.6026, Positive Sentiment: 0.2671, Negative Sentiment 0.0534

Alpha Vertex Announces the Launch of Alta, a Machine Learning Product

Alpha Vertex (www.alphavertex.ai), a financial technology company that offers analytical solutions powered by proprietary AI algorithms to financial institutions and investors, today announced the launch of Alta, its alternative data product. Created with enriched alternative datasets using big data techniques such as NLP, anomaly detection, sentiment and relation extraction,Alpha Vertex’s proprietary AI algorithms produce informational advantages and detection of new investment risk profiles for investors. Alpha Vertex takes care to control model complexity to avoid over-extrapolation and rigorously tests for the probability of false discovery. Its alternative data product and a few of its machine learning models are currently in use by a multi-billion dollar hedge fund.”
2019-05-31 07:10:25+00:00 Read the full story.
Interest Score: 3.5646, Positive Sentiment: 0.1426, Negative Sentiment 0.0951

Accelerating the Power of AI with Neural Networks

Using the Turing Test as a qualifier, Artificial Intelligence (AI) is defined as a software solution that performs a task on par with a human domain expert. When IBM’s Watson system played Jeopardy with former Jeopardy champions, much of the world saw the first real example of AI. Now, deep learning is enabling solutions that can interpret MRI images on par with doctors and operate buses on par with human drivers (e.g. Las Vegas Self Driving Shuttle).

Machine Learning (ML) is the basic foundation of AI comprised of the algorithms and data sets used to build an AI solution. In order to create a true AI system that can pass the Turing Test, the ML subset must be constantly improving with new sets of data and ongoing developments to the algorithms. While there are many different algorithms that have been in the ML toolbox for decades, it is only recently (circa. 2014) that the deep learning and neural network algorithms have taken a significant leap forward in performance due to the availability of large-labeled data sets for training and low-cost compute and storage.
2019-05-31 12:13:30+00:00 Read the full story.
Interest Score: 2.7618, Positive Sentiment: 0.3258, Negative Sentiment 0.1086

MultiVariate Time Series Analysis For Data Science Rookies

The term “univariate time series” refers to a time series that consists of single (scalar) observations recorded sequentially over equal time increments. Some examples are monthly CO2concentrations and southern oscillations to predict el nino effects.

Whereas Multivariate time series models are designed to capture the dynamic of multiple time series simultaneously and leverage dependencies across these series for more reliable predictions.
2019-05-31 11:39:29+00:00 Read the full story.
Interest Score: 2.5540, Positive Sentiment: 0.0589, Negative Sentiment 0.0589

8 Alternatives To PyBrain You Should Know To Build Neural Networks

Python-Based Reinforcement Learning, Artificial Intelligence, and Neural Network (PyBrain) offer flexible, easy-to-use and powerful algorithms for Machine Learning tasks with a variety of predefined environments to test and compare your algorithms. In this article, we list down 8 alternatives of PyBrain one must try in 2019.

  1. Azure Machine Learning
  2. DatumBox
  3. Google Cloud Machine Learning
  4. MLlib
  5. OpenCV
  6. Sci-Kit Learn
  7. Smile
  8. Weka

2019-06-03 07:27:47+00:00 Read the full story.
Interest Score: 2.4833, Positive Sentiment: 0.1910, Negative Sentiment 0.0478

Fundamentals of Self-Service Machine Learning

The recent organizational push for self-service Business Intelligence has helped the next challenge for business users become an increasing need. How to tackle the issue of having Machine Learning (ML) models embedded in all major analytics platforms? On the one hand, embedded models offer greater freedom and control over data analysis; on the other hand, confronting the native ML intelligence of these platforms is posing new risks and opportunities for ordinary users.

Without having the requisite background in Data Science or Artificial Intelligence (AI), how will these users or aspiring citizen data scientists prepare themselves for self-service Machine Learning?
2019-05-28 07:35:07+00:00 Read the full story.
Interest Score: 2.3795, Positive Sentiment: 0.1700, Negative Sentiment 0.1821

VC Funding for AI Slows, But Don’t Expect Another AI Winter Just Yet

AI firms attracted a record $9.33 billion in investments from venture capital firms in 2018, which was nearly a 10% increase from 2017. So far this year, AI funding has dipped a bit, but that doesn’t mean another AI winter is coming. AI firms attracted $2.0 billion in investments during the first quarter of 2019, according to PwC’s MoneyTree report. It was the second straight quarter of a decline in AI investment, after VCs spent $2.6 billion on AI startups in the fourth quarter of 2018 and $2.7 billion in the third quarter, which in retrospect is looking like a blockbuster quarter for deals.

Close to half of all artificial intelligence funding for the first quarter was driven by a single investment – the $940 million that the Japanese bank SoftBank Group gave to Nuro, a Mountain View, California-based robotics company, according to the report. While the value of VC investments in AI startups has declined for two straight quarters, the number of deals has stayed relatively constant. There were 112 deals in the third quarter of 2018, compared to 104 in the fourth quarter and 116 in the first quarter of 2019.
2019-05-29 00:00:00 Read the full story.
Interest Score: 2.2394, Positive Sentiment: 0.0734, Negative Sentiment 0.0734

‘Experiment Tracker’ Funded for Deep Learning

New software tools aimed at the builders of deep learning platforms and used to analyze and accelerate model training continue to advance as investors zero in on startups coming up with unique ways to track and replicate experiments while visualizing the performance of those models.

Among the tool vendors is Weights & Biases, a San Francisco-based startup that this week announced a $15 million funding round led by early stage investor Coatue Man…
2019-05-31 00:00:00 Read the full story.
Interest Score: 2.1314, Positive Sentiment: 0.0444, Negative Sentiment 0.0888

Citco integrates S3 Partners’ BLACKLIGHT Technology

The Citco Group of Companies, (Citco), a provider of asset servicing solutions to the global alternative investment industry, is partnering with S3 Partners, to integrate the data analytics firm’s BLACKLIGHT Treasury Management solution into its offering.

S3 Partners’ real-time, independent financing data prices opaque borrow and loan markets and redefines short interest, crowding and previously stale indicators for which the industry has had no centralised source. BLACKLIGHT leverages these analytics along with leading technology for better outcomes in investment process, risk man…
2019-05-31 00:00:00 Read the full story.
Interest Score: 2.1233, Positive Sentiment: 0.5179, Negative Sentiment 0.0000

How Tredence Gets It Right When It Comes To Building ML Models

Tredence, one of the leading analytics solutions providers, employs machine learning algorithms to develop analytics solutions for its customers. Their solutions range from providing prediction frameworks for online retailers in the US to cutting costs for manufacturers of thermal insulation materials. Tredence is embracing a factory approach to building AI models.

There are multiple reasons models needs to move to a factory approach. Setting up models for the first time is a highly ad hoc process which is over-dependent on the skill of the data scientist building the model. The process is also highly susceptible to human biases, and is very labour intensive. Model refreshes, on the other hand, are reactive and end up following a blind process, and remain labour intensive.
2019-05-27 06:30:43+00:00 Read the full story.
Interest Score: 1.9573, Positive Sentiment: 0.2469, Negative Sentiment 0.1058

Air Force Partners with MIT to Accelerate AI in 10 Project Areas

A new program that will strive to make “fundamental advances” in artificial intelligence is coming from the Air Force and MIT, the two organizations announced on May 20. The “MIT-Air Force AI Accelerator” will support at least 10 MIT research projects in areas like disaster relief, medical readiness, data management, maintenance and logistics, vehicle safety and cyber resiliency. Project teams will be made up of MIT faculty, staff and students, as well as members of the Air Force. The Air Force plans to invest around $15 million per year in the collaboration.

“MIT is the leading institution for AI research, education, and application, making this a huge opportunity for the Air Force as we deepen and expand our scientific and technical enterprise,” Heather Wilson, secretary of the Air Force, said in a statement. “Drawing from one of the best of American research universities is vital.”
2019-05-31 12:06:06+00:00 Read the full story.
Interest Score: 1.9186, Positive Sentiment: 0.2977, Negative Sentiment 0.5293

‘Data Workers’ Failing to Cope

More evidence is emerging that “data workers” in general and data scientists in particular are bogged down by the sheer breadth of their company’s data. Meanwhile, the skills gap between data experts and line-of-business workers continues to grow.

A vendor study attempted to gauge how much time is wasted during an average work-week fiddling with data pouring in from across multiple business processed and workflows. The IDC survey commissioned by data analytics platform vendor Alteryx (NYSE: AYX) found that data workers waste 44 percent of their time per week searching for and organizing data.
2019-05-29 00:00:00 Read the full story.
Interest Score: 1.9028, Positive Sentiment: 0.0878, Negative Sentiment 0.1464

Data Science Startup TheMathCompany Announces Series A Funding From Arihant Patni

Noted data science startup TheMathCompany announced this week that they had received funding from venture capitalist Arihant Patni in his personal capacity. According to a statement shared by the startup, the company now wants to grow its presence in the European and APAC markets.

TheMathCompany is a data science firm that helps organisations buck age-old trends and create demonstrated value with the help of robust data and analytics transformat…
2019-05-30 09:55:15+00:00 Read the full story.
Interest Score: 1.8489, Positive Sentiment: 0.1057, Negative Sentiment 0.0000

Top AI Books for Summer Reading in 2019

The recommended AI books on the list of published by MarkTechPost is selected on the basis of their reviews on Amazon, social media influence, popularity and online mentions in AI domains. This is not meant to be a ranking.
2019-05-28 14:00:52+00:00 Read the full story.
Interest Score: 1.6350, Positive Sentiment: 0.4183, Negative Sentiment 0.0380

How Data Itself Will Take IT Business to a New Level

Enterprises understand the importance of having an analytics tool that gives them a complete understanding of their customers, and the ability to communicate those insights and offer specific actions and next steps at scale empower the organization as a whole. The challenge for many brands is that the ones who touch the data, data scientists, are often siloed within a company. Those who might need be able to usethe data in meaningful ways, such as IT employees, might not have access. Businesses grapple with scarce resources against the need to analyze the incredible amount of data that is collected–never mind the need for business insights to drive efficiencies and growth.

It’s clear that the data scientist role has become increasingly important for any brand trying to stay relevant. But as more data becomes readily available and brands are able to understand that full customer journey, the focus will shift from data scientist to IT. The data science skillset is no longer important for only the employees who work within data, but also for anyone in the IT world. This is an opportunity for the IT organization to shine.
2019-05-30 00:00:00 Read the full story.
Interest Score: 1.5938, Positive Sentiment: 0.4627, Negative Sentiment 0.1371

Understanding Your Options for Stream Processing Frameworks

Real-time stream processing isn’t a new concept, but it’s experiencing renewed interest from organizations tasked with finding ways to quickly process large volumes of streaming data. Luckily for you, there are a handful of open source frameworks that could give your developers a big head start in building your own custom stream-processing application. When coupled with an underlying real-time message bus such as Apache Kafka, a stream processing framework can dramatically simplify the development of streaming applications, or what some are calling “continuous applications.” You can pick and choose from numerous pre-built functions to build a stream processing application that’s fit for purpose.

But not all frameworks are equated equal, and some are best used for certain use cases. Since the vast majority of stream processing applications are custom-built affairs, it’s important to select a framework that matches your specific needs. Here we introduce five of the most popular open source stream processing frameworks, plus NiFi.
2019-05-30 00:00:00 Read the full story.
Interest Score: 1.5901, Positive Sentiment: 0.1026, Negative Sentiment 0.0616

Robo-Advisors Started Fighting over the HNWI Market

Any robo-advisor would like to access the huge client base that banks have at their disposal. This explains why many WealthTech platforms seek partnerships with banks. However, the news is full of reports that banks, especially global ones, are investing in WealthTech platforms themselves. In 2017, MyPrivateBanking (now acquired by Cutter Associates, wealth management research and consulting firm), conducted a survey of 600 HNWIs in the U.S. and U.K. and found that more than 70% of respondents think online and automated investment tools can positively affect their wealth manager’s advice and decision-making. At the end of 2018, Morgan Stanley announced that they are speeding their collaboration with tech startups. The robo-advisory timeline clearly shows that the number of newly founded WealthTech solutions is plummeting, while banking partnerships and investments are on the rise. Why is this so?
2019-05-28 15:41:29 Read the full story.
Interest Score: 1.5860, Positive Sentiment: 0.3172, Negative Sentiment 0.0952

Data Scientist in a Business

As part of the data science journey, one will hear very valuable yet different perspectives on what it means to be a data science practitioner in the business setting, ranging anywhere from traditional data analytics and reporting to sophisticated machine learning model development and deployment, that also happens to require an advanced degree in a STEM field. Also, in pursuit of being precise in the world that isn’t, there are attempts to clearly define data analyst, statistician, data scientist, data engineer, machine learning engineer, developer, data architect or other related roles, and even to stratify into different levels within them. Then there is a discussion around the importance of data science focused educational degrees (or advanced STEM degrees in general), the number of which appears to be growing quickly. Hence, it gets confusing rather fast.

Are we trying to be precise in the world that is not?
2019-06-02 21:39:39.575000+00:00 Read the full story.
Interest Score: 1.5821, Positive Sentiment: 0.1793, Negative Sentiment 0.1371

 

Data Extraction Just Got Smarter With ML: AWS Announces Textract

Amazon Web Services, the cloud computing arm of the e-commerce giant, recently launched an ML service for automated text and data extraction. The service, known as Textract, is fully cloud-hosted and managed by AWS, and allows users to parse various forms of data easily.

The service is said to be more than just an optical character recognition algorithm, as it can parse data tables, whole pages, forms, scans, PDFs, photos and more. Moreover, it also identifies fields and tables, so as to contextualize the data and allow for the collection of cleaner datasets with deeper insights.

The company states that it can process millions of document pages “accurately” in just a few hours. All the data is exported to a JSON format, and can integrate easily with other ML-based AWS services. What sets this product apart is that there is no need to maintain any code or template, and that there is no ML experience required to operate or manage the product.
2019-05-30 09:07:24+00:00 Read the full story.
Interest Score: 1.5481, Positive Sentiment: 0.2092, Negative Sentiment 0.0000

Optimization with SciPy and application ideas to machine learning

Optimization is often the final frontier, which needs to be conquered to deliver the real value, for a large variety of business and technological processes. We show how to perform optimization with the most popular scientific analysis package in Python — SciPy and discuss unique applications in machine learning space.

Mathematical optimization is at the heart of solutions to major business problems in engineering, finance, healthcare, socioeconomic affairs. Pretty much all business problems boil down to minimization of some kind of resource cost or maximization of some kind of profit given other constraints.
2019-06-01 20:53:13.662000+00:00 Read the full story.
Interest Score: 1.5475, Positive Sentiment: 0.2261, Negative Sentiment 0.3392

OCBC launches scholarship for NUS and NTU postgraduates to pursue further studies in AI

University graduates interested to pursue further studies in the realms of artificial intelligence (AI) will be glad to know that there is now a scholarship available to give them that extra leg-up. In a statement released on Monday (June 3), OCBC Bank announced the launch of its postgraduate OCBC AI scholarship in collaboration with the National University of Singapore (NUS) and the Nanyang Technological University (NTU).

The scholarship, which OCBC said is the first of its kind to be offered by a Singapore company and bank in Asia, will be open to applicants of NUS’ Master of Computing AI and NTU’s Master of Science in Artificial Intelligence programmes. The scholarship is worth S$100,000 (US$72,900) each and covers all of the scholars’ educational and living expenses.
2019-06-03 12:56:02+00:00 Read the full story.
Interest Score: 1.5107, Positive Sentiment: 0.3316, Negative Sentiment 0.0368

Two new startups join Seattle fintech incubator run by BECU and University of Washington’s CoMotion

Two additional startups are set to join a Seattle financial technology incubator operated by BECU and based at CoMotion, the innovation arm of the University of Washington. The BECU Fintech Incubator launched last year, when it announced its initial two participating companies, Noonum and Routable (formerly Warren). Now another two startups, Attunely and Fincluziv, will round out the first cohort.

  • Attunely, based in Seattle, sells machine learning-fueled software that helps debt collection agencies improve their recovery strategies. Led by former Starbucks and aQuantive executive Scott Ferris, the company spun out of Seattle-based startup studio Pioneer Square Labs and raised a $3.7 million seed round in February.
  • Fincluziv, based in Dubai, works with banks to automate the lending process for corporate customers. The company is self-funded by its co-founders, Bruno Gremez and Samir Kasmi, who have a combined 30 years of banking industry experience. Fincluziv will relocate to Seattle to join the incubator.

2019-05-31 17:41:04-07:00 Read the full story.
Interest Score: 1.4815, Positive Sentiment: 0.1975, Negative Sentiment 0.0000

Big Data Insights Drive Surge In Digital Marketing ROI

With the help of big data, digital marketing ROI is vastly increasing. Here’s how to make the most of it, and what you need to know about it. Big data is giving savvy brands a significant edge in the market. They are able to useanalytics and other data insights to bolster customer service, reduce marginal operating costs and scale production. One of the biggest benefits of big data is in the arena of digital marketing. Dataconomy wrote a post about the value of big data in digital marketing. How does big data help with digital marketing? Here are some factors to be aware of.
2019-05-29 00:15:06+00:00 Read the full story.
Interest Score: 1.4558, Positive Sentiment: 0.2951, Negative Sentiment 0.1574

Artificial intelligence’s role in news and information needs scrutiny

AI and algorithms being used to search for content increased the risk of filter bubbles, or echo chambers, where people were exposed to only one point of view because it was what they had previously engaged with and what their friends were accessing, the Free TV submission said.

“For example, if you read an article suggesting that trade barriers should be increased, the algorithm may pigeon hole you into a group that has a trade protectionist le…
2019-05-31 00:00:00 Read the full story.
Interest Score: 1.4506, Positive Sentiment: 0.1360, Negative Sentiment 0.3626

The Importance of Data Governance in the Healthcare Industry Space

Analytics and Big Data are everywhere in the pharmaceutical industry providing insights into marketing, sales, clinical trials, claims data, patient demographics, physician engagement and much more. However, before delving into deep analytics, you must master the data, or the insights that you get will at best, be inaccurate, but at worst, cause major issues within the enterprise. Health care lags other industries when it comes to data sharing and interoperability. According to research from Stanford Medicine Health trends report in 2018, the obstacles to data sharing in health care are numerous.
2019-06-03 07:35:03+00:00 Read the full story.
Interest Score: 1.4258, Positive Sentiment: 0.1097, Negative Sentiment 0.2681

SoftBank Makes A Move Into AI Startup Funding, Plans to Invest $55M

The 800-pound gorilla in the VC space has made another move towards consolidating its position. SoftBank Group, known for its ambitious Vision Fund, is now setting up another investment fund. Reportedly, this will be dedicated to startups focusing on artificial intelligence. This is keeping in mind the vision of the founder of SoftBank, Masayoshi Son. He has long been occupied with finding companies in nascent verticals and investing in them. The company is looking to start up this fund in two to three years. It is said that the fund will raise more than $55 million towards AI companies.

In a venture to identify and invest in companies that utilize AI to redefine industries and create new ones, SoftBank is looking to snatch up companies that will change the world. To this end, the company also set up an AI-focused startup incubator known as Deepcore. Deepcore has also set up an AI fund in the past, which has since invested in 18 early-stage startups. The company is also looking to finding talent in the early stages and has found 70% of its entrepreneurs directly from the University of Tokyo.
2019-05-29 12:41:40+00:00 Read the full story.
Interest Score: 1.4253, Positive Sentiment: 0.0000, Negative Sentiment 0.0920

Seattle startup led by former VMware execs raises $4.7M for ‘machine-learning-in-a-box’ service

A Seattle startup led by former VMware execs that sells machine learning as a service has raised $4.7 million in a round led by Chris Rust of Clear Ventures. Tignis sells what it describes as “machine-learning-in-a-box” to help manufacturers, utility companies and smart buildings monitor and improve their operations.

This is the second round of financing following an initial investment last year and brings the startup’s total amount raised to $7.3 million. In addition to Rust, the company’s other investors include former VMware CEO Paul Maritz, Harel Kodesh of Silver Lake, and Ashmeet Sidana of Engineering Capital. Tignis uses the data generated by edge computing devices to help its customers improve performance, detect real-time problems and predict when issues might occur. The idea is to give companies the benefits of machine learning tools without the need to invest in their own technology.
2019-05-30 13:00:28-07:00 Read the full story.
Interest Score: 1.4014, Positive Sentiment: 0.0904, Negative Sentiment 0.0904

Alternative data as the oil industry – Cuemacro

I recently had lunch with Rob Passarella. He’s been in the alternative data industry for a number of years, with exposure to many different datasets including machine readable news, and he knows the area of alternative data extremely well. We’ve all heard of the analogy of data as being the new oil, and it’s been cited in many places including The Economist. The idea being that we can extract value from data, in the same way that those sitting on oil have done. During our discussion Rob tried to extend this notion of data being oil, into an analogy of the whole data industry (and thanks Rob for inspiring this article!). He later posted the idea as a tweet, which I’ve copied below.
2019-06-01 00:00:00 Read the full story.
Interest Score: 1.3841, Positive Sentiment: 0.1221, Negative Sentiment 0.0814

IDC: Legislation to Ban Use of Facial Recognition Could Restrict Public Sector Innovation

The City of San Francisco recently passed legislation banning the use of facial recognition by city agencies and its services (including law enforcement). Public safety agencies face an ever-increasing volume of information scaling at a rate that outpaces the human capability to analyze it. AI Trends asked Ruthbea Yesner, Vice President, Government Insights and Smart Cities and the team of analysts at IDC Government Insights, including Alison Brooks, Adelaide O’Brien, and Shawn McCarthy, to share their perspective on the potential impact that this and other in-process legislation could have on the use of intelligent automation and AI by public agencies.

Police investigations have become more complicated and onerous with the skyrocketing video and image volumes increasingly captured on smartphones and easily distributed by online. The type of video sources now that are regularly involved in police investigations include body-worn cameras, in-car police cameras, proprietary dashcams, closed-circuit television systems (resident owned, city owned, and commercial sources), mobile phones, internet videos posted on social media and, most recently, drone video. Hence there is a need to proactively, efficiently, and autonomously manage video volumes through AI of which one tool is facial recognition software. Facial recognition software has been extraordinarily useful to law enforcement agencies seeking to sift through enormous amounts of data quickly.
2019-05-28 14:20:30+00:00 Read the full story.
Interest Score: 1.3816, Positive Sentiment: 0.1354, Negative Sentiment 0.2980

5 Questions to Ask Before Implementing a Data Lake

The best analogy about data lakes and data warehouses comes from James Dixon back in 2010 when he introduced the former term. He compares a datamart with bottled water which is clean, packaged, and ready to consume, while a data lake, like its natural counterpart, can be used in various forms: to drink, to dive in, to sample it.

This difference comes from the fact that a data lake records data as it is generated, and is cleaned, filtered, and assessed only as needed. The advantage of this approach is that the same raw data can be used for multiple purposes. Although this seems like a more flexible and useful tool for the future, there is no one-size-fits-all solution in data management. Here are a few questions to ask before deciding upon data lake implementation.

  1. What kind of data do you have, and where does it come from?
  2. How do you plan to use the data?
  3. What technologies and skills do you currently have?
  4. How do you manage data?
  5. How does all this go with your company’s culture?

2019-05-28 14:10:29.822000+00:00 Read the full story.
Interest Score: 1.3475, Positive Sentiment: 0.2695, Negative Sentiment 0.1258

Machine learning and information security: impact and trends

The security industry is rife with data protection challenges. It faces catastrophic cyberattacks. And the troubles continue to mount with the rise of web-connected devices. Adding salt to the injury, is the shortage of skilled cyber talent, which fail to avert the burgeoning stress. With snowballing disruption, a prominent branch of technology development that shows promising signs to alleviate the security risks is machine learning. It has opened a new realm of data protection by leveraging the power of data and automation.

Machine learning is a branch of artificial intelligence (AI) and works on the principles of human emulation — learning from experience and patterns much like humans, but without the interference of humans. The technology has greatly grown in the past five years. The evolution can be attributed to a host of reasons. Including smart hardware, distributed computing, and the Cloud. Google, Facebook, and Amazon are already stealing ahead on the path of machine learning innovation. They enable smart search engines, dynamic news feeds, and unerring product recommendations respectively.
2019-05-29 13:44:39+00:00 Read the full story.
Interest Score: 1.3187, Positive Sentiment: 0.4297, Negative Sentiment 0.6075

The Future of Self-Service Is Customer-Led Automation: Gartner

In order to cope with the avalanche of digital information and activities, customers — like organisations — will increasingly turn to automation moving forward, according to Gartner. “There is often a lot of discussion about how enterprises continue to invest in artificial intelligence (AI) to save time and money, but we often overlook the next generation of customers being equally amenable to conducting their personal experiences the same way,” said Anthony Mullen, senior research director at Gartner.

“The reality is that customers have to engage with endless digital activities over their lifetime, which means much more data to consider. The trend of customers assigning their endless digital activities to their virtual personal assistants (VPAs), chatbots and other self-service tools will grow over the next 10 years.” Self-service is becoming the norm as customers increasingly expect an effortless experience at scale.
2019-05-31 10:01:08+10:00 Read the full story.
Interest Score: 1.2646, Positive Sentiment: 0.1621, Negative Sentiment 0.0973

3 important ways that AI is helping e-commerce stores dramatically increase conversions

What makes a successful online business? Certainly, there is no one clear answer. There are many (not-so-secret) secrets to selling online successfully – including offering great customer service, excellent products, strong marketing, and so on. However, in today’s fiercely competitive e-commerce market, features like these are give-ins. Online businesses need more support and help if they are going to capture their audience’s attention and turn them into paying customers.

When it comes to e-commerce, AI is becoming an integral part of many online businesses. It is even predicted by a study from Gartner that by next year, 85% of online customer interactions will be handled through AI technology. Most notably, AI is being used to support the most basic business goal: increase conversions. This same study also noted that when companies added AI to the mix, conversion rates grew by up to 30%.

  1. Creating a user experience founded on data
  2. Intelligent sales bots
  3. Smarter search options

2019-05-28 08:36:10+00:00 Read the full story.
Interest Score: 1.2424, Positive Sentiment: 0.2616, Negative Sentiment 0.1635

LinkedIn acquires Drawbridge to bolster its marketing and advertising offerings

LinkedIn has acquired Drawbridge, a well-funded San Francisco-area startup that uses artificial intelligence to learn more about customers and target audiences. In a blog post, the Microsoft-owned company said it would integrate Drawbridge into LinkedIn Marketing Solutions, its advertising and marketing tools division. LinkedIn’s marketing arm is growing at a 46 percent annual clip, according to the blog post, compared to 27 percent year-over-year revenue growth for LinkedIn as a whole in the most recent quarter.

Drawbridge’s technology will “accelerate” LinkedIn’s ability to help its customers reach and understand their target audiences. LinkedIn said it will “continue to maintain the strong controls our members and customers have over the data they choose to share with us.”
2019-05-28 20:33:13-07:00 Read the full story.
Interest Score: 1.2366, Positive Sentiment: 0.1124, Negative Sentiment 0.0562

5 Industries That Are Being Revolutionized By Big Data

Big data is completely transforming the way we live and the way companies conduct business. Pretty much every industry you can think of uses some form of big data technology to help optimize their business.

In this article, we reveal five industries which have been reshaped by big data technology.

  1. Retail
  2. Online Gambling
  3. Medicine
  4. Transportation
  5. Construction

2019-05-29 23:44:11+00:00 Read the full story.
Interest Score: 1.2278, Positive Sentiment: 0.3865, Negative Sentiment 0.0455

This AI tool is translating 2,000 African languages in a bid to boost local economies

A digital platform called OBTranslate that aims to translate more than 2,000 African languages to enable rural dwellers to gain easy access to global markets has been launched. According to its creator, 63 per cent of the population in Sub-Saharan Africa do not have access to global markets because of language barriers.

“Over 52 native languages in Africa have undergone language death and have no native speakers,” said Emmanuel Gabriel, founder of Germany-based OpenBinacle, the creator of OBTranslate, which was launched this month. “OBTranslate can close communication gaps on the continent.”
2019-06-01 00:00:00 Read the full story.
Interest Score: 1.2230, Positive Sentiment: 0.3540, Negative Sentiment 0.1609

Cover story: Digital Savvy Boards Drive Profitability, But Few Make the Grade

Companies with enough digitally savvy board members make more money. That’s the key finding from a recent study by MIT Sloan, which also revealed that few organisations measure up. The research found that only 24 per cent of the boards of companies listed in the US with over $1 billion in revenues were digitally savvy, and these companies outperformed the others in the research on key financial metrics. In particular, companies with a digitally savvy board had 38 per cent higher revenue growth, 34 per cent higher return on assets (ROA), and 34 per cent higher market cap growth.

“Without digitally savvy directors, a board can’t play its key role in helping guide the company to a successful future in this digital era,” the authors write. Specifically, boards need at least three members with the digital wherewithal to identify cybersecurity and privacy risks as well as business model disruptions and missed competitive opportunities.
2019-06-03 05:44:37+10:00 Read the full story.
Interest Score: 1.1961, Positive Sentiment: 0.2091, Negative Sentiment 0.2760

NextStep raising more funds to train and place healthcare workers with companies that need them

NextStep is raising more cash to build out its platform for recruiting and training healthcare workers and funneling them to employers.

Coming off a $3.3 million round last year, the Pioneer Square Labs spinout is in the process of closing out another $3 million in funding. NextStep aims to recruit people in low-wage jobs who are threatened by displacement from automation and artificial intelligence and train them for in-demand healthcare positions, including certified nursing assistant, home health aide and personal care assistant.
2019-06-01 13:00:00-07:00 Read the full story.
Interest Score: 1.1909, Positive Sentiment: 0.0384, Negative Sentiment 0.1153

How AI Came to the Rescue of Scientists Studying the Sun

In 2014, NASA lost a crucial instrument housed on the Solar Dynamics Observatory (SDO) satellite that measured extreme UV rays coming from the sun. With repair costs ranging from the millions to billions of dollars, a team from NASA Frontier Development Lab and IBM turned to artificial intelligence and historic data to see if a well-trained model could fill the data void.

I was very intrigued when I heard about this project from my good friends at NASA FDL and IBM recently. What if artificial intelligence can decipher more than images of dogs, cats, and stop signs? What could we learn from looking at images of the sun?

Could deep learning neural networks predict the missing EVE data based on analyzing terabytes of data from the past four years with hundreds of possible models and variations? “Imagine that you had listened to a symphony playing music for four years,” said Graham Mackintosh at NASA FDL, “and then one of the musicians suddenly stopped playing. Would you be able to mentally fill in the missing music from the performer who had gone silent? This is what the NASA FDL team wanted to do with the symphony of data coming from NASA’s Solar Dynamics Observatory.”
2019-05-28 14:45:35+00:00 Read the full story.
Interest Score: 1.1762, Positive Sentiment: 0.1850, Negative Sentiment 0.1586

After Funding Falls Through, MapR Seeks a Buyer to Avoid Shut Down

MapR Technologies, once one of the major distributors of Hadoop software, failed to secure additional outside funding after an extremely poor first quarter and now must take quick action – including possibly selling the company – within two week to keep its headquarters from being permanently shut down.

The once high-flying software company warned state officials two weeks ago that it may be forced to lay off all 122 employees at its Santa Clara…
2019-05-30 00:00:00 Read the full story.
Interest Score: 1.1650, Positive Sentiment: 0.0424, Negative Sentiment 0.4872

big xyt provides Liquidity Cockpit to Liquidnet for execution analysis

long with cross-checking market volumes.

big xyt is providing Liquidnet execution analysts with an interactive application to monitor market information via the Liquidity Cockpit dashboard. By using data science big xyt says its solutions capture, normalise, collate, and store trade data at a granularity that has not previously been available in the market.

Joe Fields (pictured), Execution Analyst, Global Execution & Quantitative Services at Liquidnet, says: “It is important that we are able to validate venue quality and ultimately deliver best execution to our clients. Big xyt provides support with t…
2019-06-03 00:00:00 Read the full story.
Interest Score: 1.1236, Positive Sentiment: 0.2957, Negative Sentiment 0.0000

AWS Announces General Availability of Amazon Textract

“Today, Amazon Web Services, Inc. (AWS), an Amazon.com company, announced the general availability of Amazon Textract, a fully managed service that uses machine learning to automatically extract text and data, including from tables and forms, in virtually any document without the need for manual review, custom code, or machine learning experience. Amazon Textract goes beyond simple optical character recognition (OCR) to identify the contents of fields in forms, information stored in tables, and the context in which the information is presented, such as a name or social security number from a tax form or the product SKU or quantity in a warehouse from an inventory report. The extracted text and data can be easily used to build smart searches on large archives of documents, or can be loaded into a database for use by applications, such as accounting, auditing, and compliance software.”
2019-05-31 07:15:55+00:00 Read the full story.
Interest Score: 1.0893, Positive Sentiment: 0.0436, Negative Sentiment 0.1743

Stories from the World of Municipal Analytics

The field of analytics continues to gain momentum in municipalities across the United States as local governments have begun to take Big Data seriously as a means to uncover a greater understanding of its citizens, increase the effectiveness of its projects and policies, and save money. More cities are adopting analytics practices than ever before, which yields an increased need for analytics professionals to oversee the adoption, deployment, and assessment of these new technologies at a local level. Of the successfully implemented programs, many have pushed through multiple failures and iterations to fulfill their goals related to improving governance. With sophisticated technology like machine learning and artificial intelligence comes the need to understand more complex assumptions and biases that may work against an objective that serves both comfortable and vulnerable populations.

Civic problems that could be addressed with the help of analytics may find their way to the desk of those in power from internal, funded problem sourcing efforts, but in the case of an engaged community, problems that need prioritization can often present themselves. To address a civic issue in tandem with analytics professionals, it seems there must not only exist a clear need for the application of analytics but, more crucially, buy-in from stakeholders with decision-making authority, the right resources from a talent and technology perspective, and mature, vetted data.
2019-06-02 23:39:28.143000+00:00 Read the full story.
Interest Score: 1.0711, Positive Sentiment: 0.3693, Negative Sentiment 0.4524

5 AI-Powered Tools Which Are Perfect For Conversion Rate Optimisation

Marketing is one of the most vital parts for a company, without which a business might end up struggling big time in the long run. However, marketing is not a cake walk — it is not just about spreading the word, it is a data-driven strategy to help a business grow and bring revenue. So, when we talk about revenue, for a marketer, the elephant in the room is the conversion rate, and getting that elephant is one of the most challenging tasks.

But, as artificial intelligence is evolving, it is posing a tremendous opportunity for marketers to find a solution to their conversion rate challenges. In this article, we list down 5 AI tools that would help you better your conversions.

MarketMuse, Flow XO, Convertize, Exceed.ai, Lumen5.

2019-06-01 10:56:04+00:00 Read the full story.
Interest Score: 1.0625, Positive Sentiment: 0.3139, Negative Sentiment 0.1690

Data Quality, Data Stewardship, and the Omnichannel Customer Experience

What organization—from financial services firms to retailers to healthcare providers—survives without customers? Whether they’re called consumers or patients, retaining existing or acquiring new clients is critical.

That means not taking customers for granted, but rather treating them as individuals who can enjoy personalized experiences during interaction. An estimated $62 billion is lost by U.S. businesses each year following bad customer expe…
2019-05-30 07:35:50+00:00 Read the full story.
Interest Score: 1.0351, Positive Sentiment: 0.1682, Negative Sentiment 0.2200

Big data & the internet: how ISPs are using analytics to help customers

Over the last several years, there’s been plenty of media coverage centered around all of the ways that internet service providers (ISPs) have taken advantage of big data to create new profit centers in their operations. In some cases, they’ve used it to power highly targeted online advertising platforms. And in others, they’ve used it to figure out exactly how much they could charge in particular areas before customers would start to cancel their services. The one thing that most of the coverage surrounding ISPs and big data have in common is obvious: it’s that ISPs are using big data to enrich themselves, and customers are far from pleased about it.

In reality though, ISPs around the world are also using big data in other, less controversial ways. The power of data analytics is being put to use helping broadband providers plan out capacity upgrades, proactively address network issues, and even to provide better customer service. It’s another side of the big data story that most ISPs would love the public to get interested in – but the industry hasn’t done a very good job at bringing any of it to light. To remedy that, here are two use cases that illustrate how big data is helping ISPs provide better, faster, and cheaper services to customers that you may not have heard about.
2019-05-27 09:24:25+00:00 Read the full story.
Interest Score: 1.0282, Positive Sentiment: 0.1851, Negative Sentiment 0.3085

BBVA replaces interviews with a ‘datathon’ in search for next generation of data scientists

BBVA is replacing traditional interviews with ‘datathons’ to test the ability of potential young recruits as it bids to hire a total of 2000 advanced analysts by the end of 2021, 800 of which will be data scientists.

The programme, which is aimed at science and engineering undergraduate students, as well as graduate students pursuing a master’s degree in big data and/or artificial intelligence, attracted over 1000 applications, of which 60 were shortlisted to take part in the day long ‘datathon’. The candidates were required to perform a data analysis, defining an analytical model to solve a specific problem and connect all this to a practical business use case that can be extrapolated to the bank.
2019-05-31 10:47:00 Read the full story.
Interest Score: 1.0222, Positive Sentiment: 0.1804, Negative Sentiment 0.3007

So You Want to be a Data Protection Officer?

The role of Data Protection Officer (DPO) is a security position and is a requirement per the General Data Protection Regulation (GDPR) and Brazil’s Lei Geral de Proteção de Dados (LGPD). It is reasonable to expect the United States will develop its own version of the GDPR within the next four years. Many enterprises doing internet business in Europe will need to hire a Data Protection Officer as soon as possible. These individuals will be respon…
2019-05-29 07:35:08+00:00 Read the full story.
Interest Score: 0.9891, Positive Sentiment: 0.1183, Negative Sentiment 0.2150

Grandma’s Robot: How AI Is Revolutionizing Elder Care

By 2050 almost one-in-four humans will be aged 60 years and older, double today’s share. Moreover, the number of people aged 80 years and older will quadruple. This demographic shift is opening new vistas for AI technologies in elders’ daily healthcare management, and as a useful tool for healthcare professionals and institutions treating seniors.

The AI in elder care market is expected to exceed US$5.5 billion by 2022, and will grow into one of AI’s most important support roles in societies of the future. For the elderly, taking duplicate or unnecessary medications or forgetting to take their medications altogether can greatly increase the risk of adverse reactions. To address this, New York-based AiCure provides a smartphone app that checks whether users are adhering to doctor’s prescriptions and ensures they know what to do to manage their conditions.
2019-06-01 15:01:00.853000+00:00 Read the full story.
Interest Score: 0.9869, Positive Sentiment: 0.2032, Negative Sentiment 0.3193

New Report Indicates Cyber Insurance Providers Are Too Slow to Respond to Emerging Threats, Customer Needs

Capgemini, a leading technology consulting company, and Efma, a non-profit financial industry consultant, partner each year to publish the World Insurance Report. The recently released 2019 edition highlights trends that present the greatest risks to both insurance companies and their customers, and finds that cyber insurance companies tend to lag behind both the protections that their customers are asking for and the development of emerging thre…
2019-05-31 22:00:00+00:00 Read the full story.
Interest Score: 0.9836, Positive Sentiment: 0.2900, Negative Sentiment 0.4035

Startup Using Machine Learning And Aerial Images To Reduce Risks From Wildfires

California’s hillsides are still green, thanks to a surplus of rain in the past few months, but the state is already exhorting homeowners to build 100 feet of “defensible space” around their homes, an ominous warning of the coming wildfire season. Cape Analytics, a data startup, wants to do one better, using images from the air and data analytics to identify homes most at risk from a fast-moving wildfire.

The Mountain View, California-based company said Wednesday that it is releasing a new product that makes use of its machine learning tools for aerial imagery to assess wildfire risks to people’s homes. The primary customer for the product is insurance companies, who can use the tools to assess risk and notify homeowners if that risk can be mitigated.
2019-05-28 14:10:36+00:00 Read the full story.
Interest Score: 0.9819, Positive Sentiment: 0.1227, Negative Sentiment 0.1841

US takes aim at Chinese surveillance as the trade war becomes a tech war

China continues to build its domestic surveillance capabilities, powered by artificial intelligence and lots of data. Multi-billion dollar technology firms sell their products to the government. The United States is increasingly critical not just of that tech, but of Chinese surveillance itself.

China and America’s trade war looks more and more like a tech war, and the United States appears to be widening its focus on to another category of Chinese technology: surveillance. The U.S. may put Chinese surveillance equipment company Hikvision on a blacklist that would limit its ability to acquire American components — expanding the tech rivalry between the countries and even bringing attention to the ways China monitors its own people.
2019-05-27 00:00:00 Read the full story.
Interest Score: 0.9723, Positive Sentiment: 0.1031, Negative Sentiment 0.1621

How big data is changing the way marketing teams strategize

We always hear how big data can change the face of our business. And how it’s the most important tool for growth. The question really comes down to this: what exactly is big data? Big data is a collection of information that companies can use to make actionable strategies that foster business growth. It can come in many different forms, and the uses of big data are basically unlimited.

Let’s take a look at some available big data use cases. And how implementing its potential can help your marketing team project global growth at an exponential rate. Here is how you revolutionize your marketing strategy through big data.
2019-06-03 09:06:32+00:00 Read the full story.
Interest Score: 0.9324, Positive Sentiment: 0.2869, Negative Sentiment 0.1614

This VC and his firm don’t focus on particular technologies or sectors. Instead, they look for startups with a kind of network potential. Here’s why.

Pete Flint and his partners aren’t like many of their peers.

Many venture-capital firms focus on particular technologies or industries, like artificial intelligence or healthcare. Flint and his team at NFX concentrate instead of finding businesses built to take advantage of network effects.

Network effects are what happens when a company’s service or technology becomes more useful — and potentially dominant — the more people use it. Think Facebook in social networking; the more people that are on Facebook and using it, the more likely they are to find peopl…
2019-06-01 00:00:00 Read the full story.
Interest Score: 0.9241, Positive Sentiment: 0.2556, Negative Sentiment 0.0983

How technology is changing the way businesses communicate

Keeping up with the latest trends and technology for businesses can be tricky as new advancements are being made every day. We could soon see a real shift in the way we communicate in business, both internally and externally. To better understand what the future might have in store for business communication, experts TollFreeForwarding carried out research and enlisted the help of industry experts to look into new technologies affecting the industry, and what difference tech could make in the coming years.

One of the most notable technologies to emerge in recent years is AI. We were first introduced to Siri back in 2010, and since then we have seen AI become a prominent part of business communication but is nowhere near reaching its full potential. Chatbots are a modern example of how AI is currently being effectively used in business. These are automated services that can provide human-like responses to business queries, as well as help customers navigate websites.
2019-05-31 06:00:17+00:00 Read the full story.
Interest Score: 0.9124, Positive Sentiment: 0.2477, Negative Sentiment 0.0652

Big Data Can Help You Amplify Your Sales In 2019

Big Data is taking center stage, and it is touted as one of the most groundbreaking technologies of the present time. The utilization of Big Data is not only limited to only one sector anymore. Instead,Big Data is used in various different sectors. For example, Big Data analytics are used in various agricultural fields as well to derive useful insights in order to yield better crops. Also, Big Data is used extensively in the healthcare fields to enhance the quality of care that’s being provided. However, Big Data is used extensively in the corporate world as well. Starting from the marketing teams to the customer support teams, every departments is trying to use Big Data to perform better. Lately, Big Data analytics are considered utmost important to improve the decision making of a business as well.

How is Big Data benefiting the businesses? Big Data is benefiting the businesses in several ways. Companies have started collecting large amounts of data from various sources. Starting from getting data through several online and social mediums to getting it directly from the company’s database. There are a plenty of ways of gathering useful information from different platforms. All this data is further used by the firms for several activities. For example, the insights which are derived from Big Data analytics are used by the businesses to make efficient future business strategies. The insights help the company to understand their business and their customers more deeply. This information eventually helps to plan ways to improve their business.
2019-06-01 07:30:42+00:00 Read the full story.
Interest Score: 0.8864, Positive Sentiment: 0.4073, Negative Sentiment 0.0000

Machine teaching with Dr. Patrice Simard – Podcast Episode 78, May 29, 2019 (37m)

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.

Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.
2019-05-29 15:00:31+00:00 Read the full story.
Interest Score: 0.8760, Positive Sentiment: 0.2228, Negative Sentiment 0.1727

How Real-Time Analytics Can Help Assess ROI Of Toll-Free Call Support

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.

Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.
2019-05-29 00:05:54+00:00 Read the full story.
Interest Score: 0.8600, Positive Sentiment: 0.2658, Negative Sentiment 0.1720

K Means Clustering with Dask (Image Filters for Cat Pictures)

First of all, it’s always good to remember an image is just a vector of pixels. Each pixel is a tuple of three integer values between 0 and 255 (an unsigned byte), which represent that pixel’s color’s RGB values.

We want to use K Means clustering to find the k colors that best characterize an image. That just means we could treat each pixel as a single data point (in 3-dimensional space), and cluster them.

So first, we’ll want to turn an image into a vector of pixels in Python. Here’s how we do it…
2019-06-02 19:14:19+00:00 Read the full story.
Interest Score: 0.7746, Positive Sentiment: 0.0993, Negative Sentiment 0.0596

Big Data Leads To An Impressive Array of Chatbots In Customer Service

Big data is changing the direction of customer service. Machine learning tools have led to the development of chatbots. They rely on big data to better serve customers.

According to requirements, a chatbot may assume the role of a virtual advisor or assistant. For questions where a real person has to become involved, in analyzing the received enquiries bots can not only identify what issue the given customer is addressing but also to automatically send it to the correct person or department. Machine learning tools make it easier to determine when a human advisor is needed.
2019-05-30 18:16:21+00:00 Read the full story.
Interest Score: 0.7734, Positive Sentiment: 0.2518, Negative Sentiment 0.1259

Machine Learning Helps Bloggers Secure More Traffic with Long-Tail Keywords

New bloggers often have difficulty getting traffic to their websites. The problem is that they tend to focus on competitive, high-volume keywords. This is one of the things they learn to avoid when they start learning more about blogging. The unfortunate reality is that they can be spending eons trying to get traffic this way. They would be better off focusing on a number of less competitive keywords that still provide a steady flow of traffic.

Here are two of the biggest benefits of targeting longtail keywords:

  • You can find lots of keywords that other bloggers are not targeting. As a result, you will have a much easier time getting to the top of the first page of Google for them.
  • Conversion rates for longtail keywords tend to be a lot higher because they are more specific. People searching for them have a more focused mindset and are often more committed to making a purchase. The average longtail keyword conversion rate is 36%, which is over three times as high as all keywords.

2019-06-01 14:06:24+00:00 Read the full story.
Interest Score: 0.7694, Positive Sentiment: 0.3971, Negative Sentiment 0.1737

The S&P 500 Has Formed a Rare and Ominous Triple Top

The S&P 500 has formed what certainly appears to be a rare — and dangerous — triple top. How worried should you be?

The accompanying chart paints the picture. The S&P 500 hit an initial bull market high in January 2018 at 2,873, and then turned down. It did the same thing two more times-in September of last year (reaching 2931) and then again in April of this year (at 2946).

To be sure, it would be premature to declare that the market’s behavior of the last 18 months constitutes an official triple top. There’s one more precondition: The stock market must drop from its third top below support, and we’re not there year. As this is written, the S&P 500 is some four percent below its late-April high.
2019-05-29 07:00:00-04:00 Read the full story.
Interest Score: 0.7368, Positive Sentiment: 0.0850, Negative Sentiment 0.3684

Meet Ai-Da: the robot artist giving real painters a run for their money

Auguste Rodin spent the best part of four decades working on his epic sculpture The Gates of Hell. The Mona Lisa, by contrast, took Leonardo da Vinci a mere 15 years or so, although it should be noted the Renaissance master never considered the painting finished.

So we can only imagine what those luminaries would think of an up-and-coming Oxford-based contemporary artist who can knock out complex works in under two hours. Not least because she’s a robot.
2019-06-02 00:00:00 Read the full story.
Interest Score: 0.7260, Positive Sentiment: 0.3630, Negative Sentiment 0.0000

 


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