AI & Machine Learning News. 10, June 2019

Edit video by editing text

A new algorithm allows video editors to modify talking head videos as if they were editing text – copying, pasting, or adding and deleting words. In television and film, actors often flub small bits of otherwise flawless performances. Other times they leave out a critical word. For editors, the only solution so far is to accept the flaws or fix them with expensive reshoots. A new algorithm makes it possible to perform text-based editing of videos of “talking heads”; that is, speakers from the shoulders up. Imagine, however, if that editor could modify video using a text transcript. Much like word processing, the editor could easily add new words, delete unwanted ones or completely rearrange the pieces by dragging and dropping them as needed to assemble a finished video that looks almost flawless to the untrained eye. A team of researchers from Stanford University, Max Planck Institute for Informatics, Princeton University and Adobe Research created such an algorithm for editing talking-head videos – videos showing speakers from the shoulders up. 2019-06-05 00:00:00 Read the full story. Interest Score: 0.8539, Positive Sentiment: 0.2174, Negative Sentiment 0.3416 CloudQuant Thoughts… We always like to start with a video… and this one continues the progression towards our future where we have no idea whether or not what we are looking at is real or not! Very impressive technology on show here.

Using the ‘What-If Tool’ to investigate Machine Learning models

The machine learning practitioner must be a detective, and this tool from teams at Google enables you to investigate and understand your models. In this era of explainable and interpretable Machine Learning, one merely cannot be content with simply training the model and obtaining predictions from it. To be able to really make an impact and obtain good results, we should also be able to probe and investigate our models. Apart from that, algorithmic fairness constraints and bias should also be clearly kept in mind before going ahead with the model. Investigating a model requires asking a lot of questions and one needs to have an acumen of a detective to probe and look for issues and inconsistencies within the models. Also, such a task is usually complex requiring to write a lot of custom code. Fortunately, the What-If Tool has been created to address this issue making it easier for a broad set of people to examine, evaluate, and debug ML systems easily and accurately. What-If Tool is an interactive visual tool that is designed to investigate the Machine Learning models. Abbreviated as WIT, it enables the understanding of a classification or regression model by enabling people to examine, evaluate, and compare machine learning models. Due to its user-friendly interface and less dependency on complex coding, everyone from a developer, a product manager, a researcher or a student can use it for their purpose. 2019-06-06 12:00:29+00:00 Read the full story. Interest Score: 2.3923, Positive Sentiment: 0.4785, Negative Sentiment 0.9569 CloudQuant Thoughts… Google are helping to plug the XAI (Explainable AI) hole that we have at the moment.  

US Senate Produces Bipartisan National AI Strategy Proposal; More Time to Comment for NIST

More than $2 billion in federal spending and several policy initiatives are the cornerstones of a new bipartisan bill that would create a government strategy for developing artificial intelligence technology. The Artificial Intelligence Initiative Act is the latest legislation to emerge from the new Senate AI Caucus, which is one of several congressional and executive branch groups focusing on the topic, as reported in fedscoop. Two founders of the caucus, Martin Heinrich, D-N.M., and Rob Portman, R-Ohio, are joined by another member, Brian Schatz, D-Hawaii, in sponsoring the bill. Filed on May 21, it aims to “organize a coordinated national strategy for developing AI” to the tune of $2.2 billion in federal investment over the next five years. The provisions include:
  • Establishing a National AI Coordination Office to coordinate federal AI efforts.
  • Asking the National Institute of Standards and Technologies to establish standards for testing AI algorithms and their effectiveness.
  • Getting the National Science Foundation to set “educational goals” for things like data bias, privacy, accountability and more.
  • Requiring the Department of Energy to build an AI research program for government and academia.
2019-06-07 14:45:49+00:00 Read the full story. Interest Score: 2.1326, Positive Sentiment: 0.2341, Negative Sentiment 0.0780 CloudQuant Thoughts… Bipartisan approach to an essential strategy if we are not to be beaten by China.  

Machine Learning Sentiment Analysis And Word Embeddings Python Keras Example

One of the primary applications of machine learning is sentiment analysis. Sentiment analysis is about judging the tone of a document. The output of a sentiment analysis is typically a score between zero and one, where one means the tone is very positive and zero means it is very negative. Sentiment analysis is frequently used for trading. For example, sentiment analysis is applied to the tweets of traders in order to estimate an overall market mood. As one might expect, sentiment analysis is a Natural language Processing (NLP) problem. NLP is a field of artificial intelligence concerned with understanding and processing language. The goal of this article will be to construct a model to derive the semantic meaning of words from documents in the corpus. At a high level, one can imagine us classifying the documents with the word good in them as positive and the word bad as negative. Unfortunately, the problem isn’t that simple since the words can be preceded by not as in not good. 2019-06-10 01:07:43.076000+00:00 Read the full story. Interest Score: 1.2247, Positive Sentiment: 0.1497, Negative Sentiment 0.3130 CloudQuant Thoughts… Reading different peoples approach to NLP and sentiment analysis is always extremely useful.

Alternative Data Quantifies How Trump Drives Markets

Indexica, a leader in the NLP alternative data space, announced that their predictive indexing intelligence engine has been able to find leading signals in news patterns related to Trump. While it’s clear that Trump’s tweets and actions move markets within seconds, what hasn’t been clear until now is whether the broader conversation stemming from him and his actions moves markets systematically. Trump tends to impact markets in four notable ways, each with identifying predictive patterns:
  • He Drives Volatility.
  • He Generally Drives Equities Higher.
  • He Polarizes the Market.
  • Nothing He Does Persists.
2019-06-06 14:19:49+00:00 Read the full story. Interest Score: 1.5524, Positive Sentiment: 0.1465, Negative Sentiment 0.2343 CloudQuant Thoughts… I told you that NLP analysis (above) would come in useful! Now go to CloudQuant and write some python code to analyse the impact of all of Trumps tweets (which you can find over at The Trump Twitter Archive). Major Acquisitions this week…
  • Google bought Looker
  • Salesfforce bough Tableau

Machine Learning Techniques that Improve Your Model

Cross Validation, Hyperparameter Tuning, and Feature Selection This is my first blog on data science. A bit of my background: I was a science student in high school, liberal arts student in college, and went on to grad school and took some practical courses (finance, quant, law, etc.) to line up a good job. I lea… 2019-06-10 01:16:34.106000+00:00 Read the full story. Interest Score: 1.5203, Positive Sentiment: 0.1931, Negative Sentiment 0.2051

Liquidnet expands AI-based trade and investment analytics with Prattle acquisition

Liquidnet has continued the expansion of its artificial intelligence (AI) investment analytics platform with the acquisition of Prattle, a provider of automated investment research solutions for portfolio managers, research analysts, and other financial professionals. Prattle has developed a proprietary Natural Language Processing (NLP) and Machine Learning (ML) system to produce analytics that measure sentiment and predict the market impact of publicly available content including central bank and corporate communications (such as company earnings calls and press releases). Asset managers can use these analytics to understand and anticipate relevant market movement, strengthen investment theses, and inform trading strategies. The announcement follows Liquidnet’s recent acquisition of RSRCHXchange, a marketplace and aggregator for asset managers to consume, discover, and purchase investment research, and the 2017 acquisition of OTAS Technologies. 2019-06-06 00:00:00 Read the full story. Interest Score: 2.5447, Positive Sentiment: 0.2407, Negative Sentiment 0.0344

Citi to digitize its trade compliance process using AI

Citi announced today a next generational project, with EY and SAS, using artificial intelligence (AI) to develop an advanced risk analytics scoring engine. EY’s risk and technology consulting experience, along with SAS Institute’s analytics platform, will help Citi’s Treasury and Trade Solutions (TTS) digitise its trade compliance processes. The next generation project is being created to streamline the time-consuming, highly manual processes associated with reviewing high volumes of global trade transactions while ensuring regulatory compliance. The AI-based risk analytics scoring engine will provide more context and usable data for aiding decision makers in reviewing trade transactions. 2019-06-05 00:00:00 Read the full story. Interest Score: 2.3941, Positive Sentiment: 0.4374, Negative Sentiment 0.1151

WWDC19 Is A Win For Developers As Apple Rolls Out Updated Core ML 3

Apple has been revolutionising personal technology for over three decades now. Apple’s obsession with cutting edge technology have made them pioneers in the most advanced fields such as machine learning. At the ongoing Apple Worldwide Developers Conference,San Jose, CA, Apple released Core ML 3 and other exciting tool upgrades for the machine learning community. Core ML forms the foundation for domain-specific frameworks and functionality. Core ML supports Vision for image analysis, NLP, and GameplayKit for evaluating learned decision trees. It is built on top of low-level primitives like Accelerate and BNNS, as well as Metal Performance Shaders and supports the acceleration of more types of advanced, real-time machine learning models. With over 100 model layers now supported with Core ML, the ML team at Apple believes that apps can now use state-of-the-art models to deliver experiences that deeply understand vision, natural language and speech like never before. And for the first time, developers can update machine learning models on-device using model personalization. This cutting-edge technique gives developers the opportunity to provide personalized features without compromising user privacy. 2019-06-07 05:26:37+00:00 Read the full story. Interest Score: 2.2412, Positive Sentiment: 0.1578, Negative Sentiment 0.0000

Top Stories May 2019 KD Nuggets

  • 3 Machine Learning Books that Helped me Level Up as a Data Scientist – May 28, 2019.
  • 7 Steps to Mastering SQL for Data Science — 2019 Edition – May 17, 2019.
  • 9 Must-have skills you need to become a Data Scientist, updated
  • A Step-by-Step Guide to Transitioning your Career to Data Science – Part 1, by Manu Jeevan- May 31, 2019.
  • AI in the Family: how to teach machine learning to your kids – May 28, 2019.
  • Animations with Matplotlib – May 30, 2019.
  • Data Scientist – Best Job of the Year in USA
  • How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls
  • How the Lottery Ticket Hypothesis is Challenging Everything we KAbout Training Neural Networks – May 30, 2019.
  • Machine Learning in Agriculture: Applications and Techniques – May 14, 2019.
  • Most Shared Past 30 Days
  • Naive Bayes: A Baseline Model for Machine Learning Classification Performance – May 07, 2019.
  • Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis, by Gregory Piatetsky
  • Step-by-step-guide-to-getting-a-job-in-data-sciencePython leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis, by Gregory Piatetsky – May 30, 2019.
  • The 3 Biggest Mistakes on Learning Data Science
  • The Data Fabric for Machine Learning – Part 1 – May 21, 2019.
  • The most desired skill in data science
  • The Third Wave Data Scientist – May 06, 2019.
  • Understanding Backpropagation as Applied to LSTM – May 30, 2019.
2019-06-03 12:50:23+00:00 Read the full story. Interest Score: 2.2388, Positive Sentiment: 0.0000, Negative Sentiment 0.2488

Google, Looker Eye Data Scaling via Multi-Cloud

Google Cloud has moved to buttress its position in the booming data analytics sector with its acquisition of data platform and visualization tool vendor Looker. Underscoring a trend among infrastructure vendors, Google Cloud said Thursday (June 6) Looker’s platform would run on multiple clouds and Looker customers would be able to access data from Google Cloud’s competitors. “We remain committed to our multi-cloud strategy and will retain and expand Looker’s capabilities to analyze data across clouds,” said Thomas Kurian, CEO of Google Cloud. 2019-06-06 00:00:00 Read the full story. Interest Score: 2.1986, Positive Sentiment: 0.0966, Negative Sentiment 0.1450

Experts Share How to Capitalize on Your Data Lake – Webinar

Data lake adoption is on the rise. Right now, 38% of DBTA subscribers have data lakes deployed to support data science, data discovery and real-time analytics initiatives, and another 20% are considering adoption. Today, most data lakes are on-premises. However, the cloud is becoming an increasingly attractive location as well. While data lakes have evolved and matured over the past few years of enterprise use, many challenges still exist. DBTA recently held a webinar with Clive Bearman, director of product marketing, Attunity and Steve Wooledge, vice president of industry solutions, Arcadia Data, who discussed how data governance, security, integration and the ability to easily access and analyze information are all critical success factors for taking the data lake to the next level. 2019-06-06 00:00:00 Read the full story. Interest Score: 2.1708, Positive Sentiment: 0.3559, Negative Sentiment 0.0712

A Guide To Machine Learning Foundations Of Task Management Software

Task management applications are changing the way we manage teams. Here are some of the primary benefits of these task management applications:
  • Task management tools improve team productivity
  • Task management tools make sure that teams operate more efficiently
  • Task management tools minimize worker stress
  • Task management tools help with monitoring trends
  • Machine learning is playing a very important role in improving the functionality of task management applications.
2019-06-07 23:51:07+00:00 Read the full story. Interest Score: 2.1144, Positive Sentiment: 0.2618, Negative Sentiment 0.0604

Register Now: Intel’s Data Science Webinar ‘Accelerating Deep Learning Workloads In The Cloud And Data Centers’

To register for the webinar, click here. The wide availability of the cloud and the impending rise of 5G puts the data ML/AI world at the cusp of disruption. Even as AI applications become more deeply integrated into the way we use the Internet, cloud and edge processing are becoming democratized and more easily accessible. Modern advancements have also made it possible to reduce latency and increase data transfer speeds, thus increasing the f… 2019-06-05 05:28:43+00:00 Read the full story. Interest Score: 2.1084, Positive Sentiment: 0.1721, Negative Sentiment 0.1291

100 Best Artificial Intelligence Books of All Time

As featured on CNN, Forbes and Inc – BookAuthority identifies and rates the best books in the world, based on public mentions, recommendations, ratings and sentiment. 2019-06-07 14:00:51+00:00 Read the full story. Interest Score: 2.0565, Positive Sentiment: 0.3683, Negative Sentiment 0.1228

Big Data Sets New Standards In Stream Processing For Emerging Markets

With today’s technology, there’s an increasing demand for stream processing. Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are. We’ll also deal with how big dat… 2019-06-07 23:47:18+00:00 Read the full story. Interest Score: 1.9533, Positive Sentiment: 0.2681, Negative Sentiment 0.0574

Duos Technologies launches next-gen automated logistics information system with AI to secure vehicle entry

Duos Technologies Group Inc ( ) said Tuesday that it is releasing its next-generation automated logistics information system with artificial intelligence to automate gatehouse processing for trucks at distribution centers. The Jacksonville, Florida-based company’s automated logistics information system, also known as the alis system, tightens security in protecting assets so distributors can “reduce risks, exposure, and loss,” said the company in a statement. 2019-06-04 00:00:00 Read the full story. Interest Score: 1.9286, Positive Sentiment: 0.2893, Negative Sentiment 0.3375

Customers and Banks Priorities Collide as AI Jolts Financial Industry

Machine learning and AI are going to have a profound effect on the way that financial actuaries issue loans, so consumers need to adapt accordingly. Big Data’s promise of value in the financial services industry is particularly differentiating. With no physical products to offer, the data, the source of the information – is without a doubt one of its most important assets. The banking and financial services business is replete with transactions, hundreds of millions of them a day, each adding a new row to the industry’s vast ocean of data. So, the question for many of the industry’s companies is how to cultivate and leverage this information to gain a competitive advantage? Investopedia says that the growing amount of data is going to be very important in the financial industry. They show statistics that 2.5 quintillion bytes of data are created every day. Over 90% of all known data has been developed in just the past few years. 2019-06-04 01:14:29+00:00 Read the full story. Interest Score: 1.9181, Positive Sentiment: 0.1451, Negative Sentiment 0.1289

Nuxeo Insight Cloud Delivers the Next Generation of Enterprise AI and Intelligent Content Services

Nuxeo, the leading cloud-native Content Services Platform (CSP), today announced the immediate availability of Nuxeo Insight Cloud, a powerful artificial intelligence (AI) offering that enables enterprises to employ machine learning models that non-technical users can use and train with their own specific data sets, which automates and delivers greater intelligence to content-driven processes. Business-specific metadata is the foundation of effective search, workflow, and other value-creation activities in content-centric business applications. The challenge has always been the manual effort and investment required to properly and accurately identify content and link it to related materials. Existing content enrichment AI services address this challenge in one of two ways. Some services are easy to deploy and provide generic metadata not based on a business’s specific content. Others allow custom model development, but require scarce data science expertise to use. 2019-06-07 00:00:00 Read the full story. Interest Score: 1.8979, Positive Sentiment: 0.3451, Negative Sentiment 0.0690

Student Resources for A.I. and Machine Learning Education

If you listen to the tech pundits (and many tech-firm CEOs), artificial intelligence (A.I.) and machine learning (ML) will define the future. And they’re certainly not wrong: virtually every industry is interested in how A.I. and ML can streamline business processes and boost profits. These are clearly areas worth any tech professional’s time and attention. But for students and new graduates, the prospect of plunging into the study of artificial intelligence is no doubt intimidating; the associated technologies (not to mention the underlying mathematics) are often hideously complicated. Nonetheless, it’s important to familiarize yourself with A.I. and ML if you want to “future proof” your career. 2019-06-06 00:00:00 Read the full story. Interest Score: 1.8939, Positive Sentiment: 0.0758, Negative Sentiment 0.0758

Random Forest vs Neural Network: Which is Better, and When?

Random Forest and Neural Network are the two widely used machine learning algorithms. What is the difference between the two approaches? When should one use Neural Network or Random Forest? Which is better: Random Forest or Neural Network? This is a common question, with a very easy answer: it depends :). I will try to show you when it is good to use Random Forest and when to use Neural Network. First of all, Random Forest (RF) and Neural Network (NN) are different types of algorithms. The RF is the ensemble of decision trees. Each decision tree, in the ensemble, process the sample and predicts the output label (in case of classification). Decision trees in the ensemble are independent. Each can predict the final response. The Neural Network is a network of connected neurons. The neurons cannot operate without other neurons – they are connected. Usually, they are grouped in layers and process data in each layer and pass forward to next layers. The last layer of neurons is making decisions. The Random Forest can only work with tabular data. (What is tabular data? It is data in a table format). On the other hand, Neural Network can work with many different data types. 2019-06-07 08:00:56+00:00 Read the full story. Interest Score: 1.8525, Positive Sentiment: 0.1748, Negative Sentiment 0.0583

Twitter Buys Artificial-Intelligence Startup to Help Fight Spam, Fake News and Other Abuse

Twitter, as part of ongoing efforts to improve the “health” of discussions on the platform, announced that it has acquired U.K.-based artificial-intelligence startup Fabula AI. Terms of the deal weren’t disclosed, according to an account in Variety. The initial focus for Fabula as part of Twitter “will be to improve the health of the conversation, with expanding applications to stop spam and abuse and other strategic priorities in the future,” according to Twitter chief technology officer Parag Agrawal, who announced the acquisition in a blog post on June 3. Fabula has developed the ability to analyze “very large and complex data sets” to detect network manipulation and can identify patterns that other machine-learning techniques can’t, according to Agrawal. The startup has created a “truth-risk scoring platform” to identify misinformation, using data from sources including Snopes and PolitiFact. 2019-06-07 14:10:47+00:00 Read the full story. Interest Score: 1.7861, Positive Sentiment: 0.1891, Negative Sentiment 0.4203

Deep Learning Vs Deep Reinforcement Learning Algorithms in Retail Industry — II

LSTM, Transfer, Federated Learning, Reinforcement and Deep Reinforcement Learning In continuation to my previous blog, which discussed on the different use-cases of machine learning algorithms in retail industry, this blog highlights some of the recent advanced technological concepts like ro… 2019-06-10 01:16:16.076000+00:00 Read the full story. Interest Score: 1.7280, Positive Sentiment: 0.2521, Negative Sentiment 0.1996

Computer Vision Gets A New Tool In The Form Of Intel’s OpenVINO™ Toolkit

Voted as one of the best developer tools, Intel’s® OpenVINO™ toolkit has become the go-to tool for vision tasks. Earlier known as Computer Vision SDK, OpenVINO™ provides developers a single, unified software layer across hardware to allow developers to build AI solutions. The end goal here is to take away the complexity of working on Computer Vision applications by providing data scientists and developers a solution to accelerate performance on a range of hardware — CPU, GPU, FPGA and VPU. Well, you read it right! The top-to-bottom optimised support is not just for Intel’s® own hardware, but for GPUs as well, enabling developers to build high-performance computer vision and deep learning based solutions. With simplicity at its core, the OpenVINO™ toolkit — a free download allows developers to deploy Computer Vision without the need to know much about neural networks. 2019-06-07 05:52:09+00:00 Read the full story. Interest Score: 1.6760, Positive Sentiment: 0.0978, Negative Sentiment 0.0559

Unsupervised Artificial Intelligence is not ready for direct customer engagement, says Pegasystems AI expert

Artificial intelligence is not safe to be let loose on customers, according to the AI lead at a global software company which uses the technology in its own platform. Pegasystems Dr Rob Walker said AI has not yet matured to a point where it can make moralistic and empathetic decisions and still risks further marginalising people. However, AI is useful for augmenting decisions of humans and automating processes at scale… 2019-06-05 13:25:32+10:00 Read the full story. Interest Score: 1.5472, Positive Sentiment: 0.1785, Negative Sentiment 0.1785

OECD Releases Guidelines for Development of Trustworthy AI, Joining the Pack

Australia is among 42 countries that in late May signed up to a new set of policy guidelines for the development of artificial intelligence (AI) systems. Yet Australia has its own draft guidelines for ethics in AI out for public consultation, and a number of other countries and industry bodies have developed their own AI guidelines, according to an account in 2019-06-04 14:00:04+00:00 Read the full story. Interest Score: 1.5118, Positive Sentiment: 0.1239, Negative Sentiment 0.4957

3 Questions with Mirella Reznic of Bitvore

FintekNews is pleased to offer our readers our “3 Questions” column, where we chat with a thought leader within a unique sector of fintech and ask them to answer just 3 questions for our audience in their vernacular. This week, we’d like to introduce you to Mirella Reznic of Bitvore. What does your firm do/offer within the fintech sector? Bitvore specializes in transforming immense unstructured data sets into predictive intelligence to help financial institutions drive surveillance, research and lead generation in the b2b space, both in the private and public sectors. Using advanced NLP and Machine Learning techniques, Bitvore extracts relevant business signals continuously from content (like the news, government filings, websites, etc.) enabling clients to quickly identify these signals or events related to companies they want to track. For example, events such as executive changes, M&A activity, upcoming changes to labor force, expansion of products or markets, legal issues and various other signals that can affect the growth and risks associated to specific companies. 2019-06-03 16:50:14+00:00 Read the full story. Interest Score: 1.4984, Positive Sentiment: 0.2366, Negative Sentiment 0.2103

Streaming Analytics: The Value is in the Action

“When we’re talking about streaming analytics, we’re talking about flipping our traditional paradigm a little bit and thinking about how we bring analytics to our data, and not necessarily data to our analytics,” said Kimberly Nevala, the Director of Business Strategies for SAS Best Practices, while discussing streaming analytics during the DATAVERSITY® Enterprise Analytics Online Conference. “Streaming analytics, as the word ‘stream’ implies, means that we’re bringing analytics to what we call ‘event streams,’” Nevala continued. Simply put, event streams are low-latency, high-throughput data-flows that generate insights by applying analytics to data while it is “in stream.” Traditionally, data is captured and stored before being analyzed, and insights that arise from that analysis are then pushed out. In streaming analytics, models or algorithms are applied to analyze the incoming data as it occurs, before the data is stored. This process provides the ability to “Interrogate the information and determine whether data has meaning and what the value is so that we know explicitly what data to store, and why, and when,” she said. 2019-06-04 07:35:38+00:00 Read the full story. Interest Score: 1.4369, Positive Sentiment: 0.1658, Negative Sentiment 0.2671

Pivotal and Cloudera Get Pummeled as Cloud Wars Heat Up

The markets have posted solid gains this week, so it might seem strange to use this section to discuss one of the biggest losers. But this is important for technology investors. Let me explain. Pivotal Software (PVTL – Get Report) crashed 41% Wednesday to $10.89. Its Friday close was slightly lower at $10.82. The money-losing enterprise software stock had a train wreck of a quarter, according to one analyst, and the outlook for fiscal 2020 is worse. A hot sector is in trouble, with more to come. Pivotal joins Nutanix (NTNX – Get Report) , Box (BOX – Get Report) , Dropbox (DBX – Get Report) and other smaller enterprise software stocks trading at new lows. On Thursday, shares of Cloudera (CLDR – Get Report) , an enterprise data analytics firm, plunged 40% and it closed down 2.11% Friday to end the week at $5.10 a share. 2019-06-09 10:19:52-04:00 Read the full story. Interest Score: 1.4176, Positive Sentiment: 0.2162, Negative Sentiment 0.2162

Google to Buy Data Analytics Company Despite New Antitrust Scrutiny

Just as government officials step up their antitrust scrutiny of the American tech giants, Google had a surprising announcement on Thursday: It is buying another company. Google said it planned to buy the data analytics company Looker for $2.6 billion in a bid to catch up to rivals in the business of cloud computing. The transaction, which is subject to government approval, will be an immediate test for regulators. “A few years ago, this deal would have been waved through without much scrutiny,” said Paul Gallant, a tech analyst with Cowen who focuses on regulatory issues. “We’re in a different world today, and there might well be some buyer’s remorse from regulators on prior tech deals like this.” 2019-06-06 00:00:00 Read the full story. Interest Score: 1.3994, Positive Sentiment: 0.1076, Negative Sentiment 0.6459

Are Businesses Ready for AI? Why the Answer Doesn’t Matter

Artificial Intelligence (AI) has been one of the most widely discussed topics in the business world for the past few years. Recently, there have been rumblings of fear and nervousness about AI’s long-term impact. Are we ready? Have we thought through the potential consequences? More and more questions pop up, which is understandable considering AI’s capacity for profound change. The biggest innovations of the modern era have been met with similar trepidation ­– the car, air travel, the internet, cell phones, smartphones. The list could go on and on. But the fact is it doesn’t really matter if we’re ready for AI or not. Before we look at why the element of fear is insignificant, let’s first consider what AI does and how it can work for all businesses as well as in specific industries. 2019-06-10 07:30:14+00:00 Read the full story. Interest Score: 1.3948, Positive Sentiment: 0.4414, Negative Sentiment 0.1766

With this AI, your voice could give away your face

From algorithms that can automatically tag you in photos, to face recognition systems embedded in city surveillance systems to voice generators that can put words in people’s mouths, AI is dismantling privacy. A new tool is peeling back the curtain a little more, with a method to figure out what your face looks like from your voice. In research published on Arxiv, a publishing site for non-peer-reviewed papers, MIT researchers created a way to reconstruct some people’s very rough likeness based on a short audio clip. The paper, “Speech2Face: Learning the Face Behind a Voice,” explains how they took a dataset made up of millions of clips from YouTube and created a neural network-based model that learns vocal attributes associated with facial features from the videos. Now, when the system hears a new sound bite, the AI can use what it’s learned to guess what the face might look like. 2019-06-06 13:15:44 Read the full story. Interest Score: 1.3944, Positive Sentiment: 0.0358, Negative Sentiment 0.2145

‘Manifesto’ Touts the Marriage of AI, Ops

Given the growing debate about whether AI qualifies as what used to be referred to as “appropriate technology,” a consensus is building around the notion that automation is ideally suited to enterprise IT, particularly since hybrid infrastructure has become central to nearly all business processes. Hence, the growing movement toward AI operations, or AIOps, led by proponents such as the industry forum AIOps Exchange. A new AIOps “manifesto” notes the centrality of IT and the need to automate more infrastructure. “This has forced developers of IT systems to switch from monolithic to modular designs, centralized to distributed architectures, static to dynamic configurations and multi-year to ephemeral life-spans at the component level,” the authors note. 2019-06-05 00:00:00 Read the full story. Interest Score: 1.3839, Positive Sentiment: 0.0301, Negative Sentiment 0.1203

Robots are not people and AI is not taking your job Inc. is secretive about sharing what happens inside the fulfillment centers that our smiling packages come from. But like how its Amazon Web Services Inc. has given glimpses into the technologies that enable its cloud services, the new re:MARS show (for machine Learning, automation, robotics and space) last week gave a peek behind the curtain of the drivers of Amazon’s technology. Jeff Wilke, chief executive of Amazon Worldwide Consumer — basically everything that isn’t under AWS CEO Andy Jassy but not including Amazon CEO Jeff Bezos’ own Blue Origin space company — highlighted that artificial intelligence and machine learning are a foundational layer for the consumer business, and much of this technology comes from AWS offerings. We also got a close look at how the latest in robotics such as Amazon’s new Prime Air drone that Wilke showed off (pictured), AI and space that’s being leveraged by hyperscale companies such as Amazon will affect enterprise organizations and their workforces. Since 2012, Amazon has deployed 200,000 robots in its fulfillment centers; during the same time, it has hired 300,000 people. Wilke said he is a fan of Erik Brynjolfsson of MIT, who wrote “Racing with the Machines” with Andy McAfee, which states that the successful companies in the future will have found ways to capitalize on machines and people working closely together. 2019-06-09 00:00:00 Read the full story. Interest Score: 1.3673, Positive Sentiment: 0.1622, Negative Sentiment 0.0927

Experts say that Google Cloud’s $2.6 billion acquisition of Looker could give it more of a competitive edge against Microsoft, Amazon, and Oracle

Google Cloud announced on Thursday its plan to acquire Looker for $2.6 billion, and experts say the deal could give it a leadership position in data analytics — giving Google an edge as it competes against Microsoft, Amazon Web Services, and legacy companies like Oracle, IBM, and SAP. Looker provides data analytics for businesses. Google Cloud has similar offerings of its own — like BigQuery, Data Studio, and Cloud ML Engine — but analysts say that Looker adds more tools to their arsenal. 2019-06-06 00:00:00 Read the full story. Interest Score: 1.3212, Positive Sentiment: 0.1554, Negative Sentiment 0.1036

Giving DevOps Teeth To Crunch Down on AI Ethics Governance

AI ethics is definitely trending. I’ve seen the phrase in my reading and heard it trip from the tongues of professional acquaintances many times in the past several months. Management fads come and go, and I wonder whether AI ethics might be one of them. In much the same way that product quality deficiencies triggered the ISO9000 fever of the 1990s and corporate malfeasance stoked the Sarbanes-Oxley mania of the 2000s, anxieties surrounding AI’s misuse are now the focus of much soul-searching in business and technical circles. Fads fade when society realizes they may have been overblown or that they proposed changes in the status quo that didn’t make sense beyond a niche subculture. As we examine the anxieties behind the ethical AI movement, we must ask whether they’ve been hyped out of proportion by mainstream culture. We must also ask whether the approaches being proposed for instilling ethics in the business AI development and operations are truly taking hold or are likely to ensure that ethically dubious AI applications never see the light of day. 2019-06-04 00:00:00 Read the full story. Interest Score: 1.3090, Positive Sentiment: 0.1151, Negative Sentiment 0.2301

AI Ethicists: Moral Grounding or Public Relations Trick?

The Wall St. Journal wrote in a March 1, 2019 article that the Need for AI Ethicists Becomes Clearer as Companies Admit Tech’s Flaws. I’m all for ethics being applied to an uncharted technological domain that could have tremendous consequences. But what’s being described sounds more like “AI business risk mitigation” than “AI ethics” to me. “The call for artificial intelligence ethics specialists is growing louder as technology leaders publicly acknowledge that their products may be flawed and harmful to employment, privacy and human rights. Software giants Microsoft Corp. and Inc. have already hired ethicists to vet data-sorting AI algorithms for racial bias, gender bias and other unintended consequences that could result in a public relations fiasco or a legal headache.” So the public call for AI ethics is growing louder since AI may be violating human rights. And the response is to uncover areas where AI can cause PR or legal problems. I sense a disconnect. 2019-06-07 09:26:47+10:00 Read the full story. Interest Score: 1.2661, Positive Sentiment: 0.2150, Negative Sentiment 0.5017

When AI Becomes an Everyday Technology

The evolution of AI has been a rich tale of exploration since its origins in the 1950’s, with the last decade providing an especially dramatic chapter of breakthrough innovations. But I believe the real story is what comes next — when the disruption stabilizes and machine learning transitions from a staple of Silicon Valley headlines to an everyday technology. It’ll be a far longer chapter — perhaps decades — in which developers all over the world use a mature set of tools to transform their industries. In 2019, we find ourselves at the start of this new chapter. AI has undergone a remarkable refinement in recent years, as barriers to entry have fallen and a wide range of products, services, resources, and best practices have emerged. As our focus shifts — finally — from AI itself to the impact that AI can have on your business, the question is no longer how this technology works, but what it can do for you. In other words, we’re entering the age of deployed AI. Deployed AI is about more than engineering — it’s about a shared vision. Engineering expertise will always play a role in AI. But in the age of deployed AI, our most important asset will be the vision that guides that expertise. 2019-06-07 12:15:40+00:00 Read the full story. Interest Score: 1.2385, Positive Sentiment: 0.3454, Negative Sentiment 0.3215

Case Study: Predictive Analytics and Data Science Keep an Eye on the Weather

…As you might expect, data and data analytics rule in generating weather forecast success. The study mentioned above was conducted by, a service of Intellovations, LLC. ForecastWatch defines itself as “the meterologists’ source” for unbiased data and analysis to improve forecast quality. The service collects weather forecasts and verifies them against actual observations for 86 countries, compiles forecasts and information from 1,350 locations, and stores 800 million historical forecasts in its proprietary database (so far). Weather companies and other businesses can use this for accurate analysis based on business parameters, or they can gain direct access to the database to create customizable data sets. 2019-06-06 07:35:33+00:00 Read the full story. Interest Score: 1.2370, Positive Sentiment: 0.2417, Negative Sentiment 0.0853

The democratization of AI: Why it’s time to make the investment

Artificial intelligence doesn’t belong to the data scientists any more. As the technology has matured, it’s become easier than ever to implement affordable, accessible AI solutions into business workflows. You don’t have to be an expert in the tech — you just need to be an expert in your own operations. And over and over, the success stories from companies that are implementing AI solutions into their workflows prove that the technology has made the leap from sci-fi fantasy to solid solutions delivering real results. The leap in AI availability and affordability comes just in time. By 2022, 93 percent of companies will have implemented AI and cognitive solutions. That means now is the time to stop waiting and start doing, because companies that don’t pilot AI solutions today are falling behind their competitors. The companies that have the best customer experience today, who are growing faster and are more profitable than their competitors, are investing faster in AI, and they’re further widening the gap from laggards, because AI is an accelerant in customer service sophistication and effectiveness. Where are companies seeing the biggest gains? Because superior customer service is the biggest differentiator today, integrating AI into customer engagement and service workflows offers the biggest leaps in customer acquisition, customer experience, customer support, and front-line employee productivity. And it’s easier than ever to integrate these technologies and stay competitive. 2019-06-10 00:00:00 Read the full story. Interest Score: 1.2126, Positive Sentiment: 0.4993, Negative Sentiment 0.1427

The war for (banking tech) talent

I had an interesting discussion about hiring technology people into banks the other day. The challenge of finding top coders is a big one, as there’s an awful lot of other firms to join out there. You could join a hot FinTech unicorn like Monzo, SoFi, Stripe, Ant Financial, Ping An or many of the others, or you could join some of the ponies (under $100 million valuation) and centaurs ($100 million to $1 billion) out there. Equally, there are many others that could attract, from technology unicorns to technology titans. So why would I join boring old bank when Amazon and Tencent are calling? A number of reasons, the banker told me. First and foremost, not everyone can join a FATBAG (my version of FANGS). Therefore, there will always be talent that doesn’t join the technology titans. You may wonder why you wouldn’t want to be there. A number of reasons, with location being a key one. If you’re joining a Netflix or Facebook, then you’re West Coast bound to Silicon Valley where the average house price is $1.4 million. Not everyone wants to be based there and many cannot afford to be there if they’re just starting out on a coding career. Second, for every unicorn a thousand ponies die. There are thousands of start-up firms out there with great ideas, but their burn rate is high and capital can often be hard to maintain operations. Even unicorns die, so you’re taking a big bet if you join a start-up. 2019-06-05 06:59:16+00:00 Read the full story. Interest Score: 1.2035, Positive Sentiment: 0.2725, Negative Sentiment 0.1362

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. 2019-06-03 05:44:37+10:00 Read the full story. Interest Score: 1.1961, Positive Sentiment: 0.2091, Negative Sentiment 0.2760

Businesses want data to predict the future, but struggle to act on the insights

Professional services firms are seeing strong demand for predictive analytics projects, but say Australian businesses still face challenges implementing or operationalising the insights gained from the statistical models. While predictive analytics is not a new capability partners from KPMG and Accenture say businesses still struggle when it comes to optimising business processes based on data. “Predictive analytics is not a new capability but the level of demand from clients is constant,” says Raphael James, Partner, KPMG Digital Delta, a newly formed business unit to assist organisations with their transformation journeys. The reality is that if you were to sit with the leadership of any organisation and you were to ask them to put on the table the list of questions that they want to answer, I think a significant portion of those would require predictive analytics to answer.” Predictive analytics helps businesses answers questions like, which of my customers is about to churn? Or from a supply chain perspective, how much product do I need to hold? Or, what will the demand for product be in the upcoming period of time? 2019-06-04 16:18:33+10:00 Read the full story. Interest Score: 1.1850, Positive Sentiment: 0.2194, Negative Sentiment 0.1756

The Backlash Against Facial Recognition Technology Continues to Grow

At one time, facial recognition technology held an enormous amount of promise as a way to improve everything from law enforcement to the way that you log into your digital devices. But now the backlash against facial recognition technology is growing. In some cases – as in the case of the city of San Francisco – politicians are calling for an outright ban on further use of the technology. And now it looks increasingly likely that the U.S. Congress might introduce bipartisan legislation to limit how facial recognition technology can be used, and by whom. Recently, for example, the Congressional House Oversight and Reform Committee hosted a hearing on the topic of facial recognition technology, in order to find out more details about how artificial intelligence that powers the technology is currently being used, and what some of the potential abuses of the technology might be. As part of the hearing that might eventually lead to a new federal law, the lawmakers heard from a wide range of experts, including legal scholars, privacy advocates, algorithmic bias researchers, and law enforcement agencies. 2019-06-07 22:00:00+00:00 Read the full story. Interest Score: 1.1545, Positive Sentiment: 0.0671, Negative Sentiment 0.4430

Predictive analytics in the travel industry: use cases

The latest technological advancements have taken the world by a storm. It’s immensely impressive to see how much better and convenient our lives have become, thanks to those advancements. One such recent development is the discovery of big data. It’s the concept to explain our advantage by making sense of the voluminous set of data sets we have been collecting. Data is a powerful word and runs all our major developments. It allows businesses to understand their shortcomings and strengths and plan accordingly. This is why businesses are investing their money in collecting meaningful data. They are making use of these data-sets to find meaningful insights for their business. The travel industry is making use of big data like a lot of other significant businesses in the market. With consistent use, they have been able to gain the right momentum in the right direction. The amount of data generated by travelers on the web is, vast. And it keeps growing by multiple folds as more and more people are making travel plans. When used diligently, travel industries can use data insights to have an edge over their competitors. 2019-06-05 05:02:00+00:00 Read the full story. Interest Score: 1.1470, Positive Sentiment: 0.3605, Negative Sentiment 0.0983

Finastra recognized as winner for 2019 Microsoft Partner of the Year Award

Finastra today announced it has won the 2019 Microsoft Alliance Global ISV Partner of the Year Award. The company was honored among a global field of top Microsoft partners for demonstrating excellence in innovation and implementation of customer solutions based on Microsoft technology. “What an immense achievement to have received this recognition less than 18 months after we announced our strategic alliance togeth… 2019-06-07 00:00:00 Read the full story. Interest Score: 1.1460, Positive Sentiment: 0.8228, Negative Sentiment 0.0588

DAM Market Set To Top $1 Billion In 2019

If you’re looking to get a handle on the explosion of content at your company, follow the lead of many organizations that have turned to digital asset management (DAM) to manage the entire content life cycle. More than 75% of global software decision makers are implementing or planning to implement DAM. How should you take advantage of this technology? DAM empowers collaboration in the upstream creative process; it provides a central repository that is a single source of truth, and it integrates into downstream technologies to deliver content to omnichannel endpoints. Forrester surveyed 33 vendors that told us they are prioritizing AI and integrations investments this year. How should you leverage artificial intelligence for your rich media? AI can help categorize large libraries of content with metadata that wouldn’t otherwise exist or that simply takes too long to enter manually. If you’re relying on file names or folders, AI can help unlock your assets for great use across the organization. Check out our recent infographic for a snapshot of DAM’s capabilities and trends and to determine whether your business and functionality requirements necessitate a DAM. 2019-06-03 14:42:06-04:00 Read the full story. Interest Score: 1.1416, Positive Sentiment: 0.3805, Negative Sentiment 0.1522

Introduction to Boosting: Implementing AdaBoost in Python

In Machine Learning context, there are typically two kinds of learners or algorithms, ones that learn well the correlations and gives out strong predictions and the ones which are lazy and gives out average predictions that are slightly better than random selection or guessing. The algorithms that fall into the former category are referred to as strong learners and the ones that fall into the latter are called weak or lazy learners. Boosting essentially is an ensemble learning method to boost the performances or efficiency of weak learners to convert them into stronger ones. Boosting simply creates a strong classifier or regressor from a number of weak classifiers or regressors by learning from the incorrect predictions of weak classifiers or regressors. From the definition, it clearly states that boosting is an ensemble method which implies that the algorithm makes use of multiple learners or models. There are different ensemble methods to improve the accuracy of predictions over a given dataset, for example, bagging or stacking. However the major difference between bagging and boosting lies in the fact that in bagging the predictions of each model is individually considered and then aggregated to produce a better result while in boosting the different algorithms work closer by learning from each other. 2019-06-10 10:22:44+00:00 Read the full story. Interest Score: 1.1345, Positive Sentiment: 0.2063, Negative Sentiment 0.0737

10 visual examples of artificial intelligence at its best

Are you wondering what artificial intelligence is and what it looks like today? Look at self-driven cars. They used to be nothing but a part of all sci-fi enthusiasts’ imagination. And now they’re on the roads of most 1st world countries. Even activities like booking appointments, troubleshooting, customer care and supply chain management can now be done by machines. There have been drones developed that can deliver orders and robots that perform shipping and manufacturing duties. But seeing is believing, right? So here are a few videos which demonstrate how far artificial intelligence has advanced. 2019-06-10 11:43:00+00:00 Read the full story. Interest Score: 1.1205, Positive Sentiment: 0.2069, Negative Sentiment 0.1724

How AI Is Becoming The Most Reliable Therapist In Mental Health

Mental health is important. Period. Around 450 million people currently suffer from mental disorders. According to a report by WHO, it is prophesied that by the year 2020, depression will be the 2nd largest disease burden for the entire world. And the rate at which news headlines of people kill themselves are coming up, it is starting to become scary. To deal with this global challenge, it is not only humans that are fighting, but technology has also formed an alliance with humans to fight mental disorder, offering hope for reversing the decline in mental wellness. Over the past few years, AI has already marked its presence in the healthcare sector. Now, as the healthcare industry is embracing artificial intelligence, AI is all set to make a difference in mental health treatment. We all know that artificial Intelligence and machine learning have become vital in health care, benefiting medical professionals to a significant extent. Talking about mental health, Clinical research psychologist, and a faculty in Psychiatry and Behavioral Sciences at Stanford School of Medicine. Dr Alison Darcy created a chatbot that resembles an instant messaging service called Woebot and it aims to replicate conversations a patient might have with his or her therapist. Dr Darcy believed that the sad truth about mental health is that more than half of the world’s population still doesn’t have access to basic health care. And that was the major driving forces behind Woebot coming to the scenario. However, no matter how good a bot is, many believe that a robot can never replace a human. But, despite this fact, there are also many people who believe that — if not completely, then at least to an extent, AI bots like Woebot is making CBT more accessible, and that itself is an achievement as a huge number of people don’t even have any idea how to go about their mental illness. 2019-06-10 05:14:24+00:00 Read the full story. Interest Score: 1.0897, Positive Sentiment: 0.1623, Negative Sentiment 0.2782

7 Online Artificial Intelligence Tools To Generate Your Own Music

The history of music is more than just creativity, it’s about technological innovation as well. From the invention of musical instruments to augmenting it with electric in the 1950s, to the advent of synthesizers and electronic music – with each innovation, the style and pallet that music offered also expanded. AI is one such big innovation coming music’s way. AI generated music, though a relatively newer tech, has gained enough prominence. Surprisingly, the music generated by computers is also getting pretty good and remember that we are in the early days of this innovation. Here are 7 online tools available for anyone to play with AI generated music. 2019-06-10 12:09:12+00:00 Read the full story. Interest Score: 1.0894, Positive Sentiment: 0.3219, Negative Sentiment 0.0000

Kernel Secrets in Machine Learning

This post is not about deep learning. But it could be might as well. This is the power of kernels. They are universally applicable in any machine learning algorithm. Why you might ask? I am going to try to answer this question in this article. Generally, in machine learning, we want to put similar things in similar places. This r… 2019-06-09 13:13:48.214000+00:00 Read the full story. Interest Score: 1.0744, Positive Sentiment: 0.1194, Negative Sentiment 0.1326

The 4 Key Questions to Ask When Thinking About Voice

Its seems that the hot topic in financial circles these days is artificial intelligence (AI), specifically voice-based apps. Some of this is driven by the fact that Google and Amazon are leading the charge in that direction in shopping, music and entertainment. But the fact is, if this nut can be cracked for banks and credit unions, it could be a game changer for the financial institutions and their customers. Given the expansion of the technology and the proliferation of talk about banking AI, it’s time to not only take a look at where AI is in relation to banking, but also see where your FI needs to be to take advantage. Also bear in mind that it isn’t the size of your FI that matters. AI APIs are now available for every budget. But like other tech gear, that doesn’t mean you should go out and buy some. Think of it like some of the other tech available. 2019-06-06 15:00:13 Read the full story. Interest Score: 1.0726, Positive Sentiment: 0.2839, Negative Sentiment 0.0946

How Advanced Analytics Is Helping to Flush Out Insurance Fraud

Advanced analytics and machine learning modeling require lots of data to be trained, and in the insurance business, there’s no better place to get data than Verisk Analytics. Here’s how the Jersey City, New Jersey-based company is using big data tools and techniques to detect fraudulent claims and connect the dots on fraud networks. Founded as a governmental entity in the early 1970s, Verisk Analytics today is a privately held clearinghouse for data and analytics services for organizations in the insurance, financial services, energy, and government businesses. Most (if not all) of the insurance companies in the United States share their anonymized claims data with Verisk, which then aggregates and enriches it and sells it back to insurance company in the form of an analytic service.   Insurance fraud (excluding medical fraud) is a $40-billion business in the United States, according to the latest data from the FBI. Large storms that get national media attention also tend to attract the attention of fraudsters. For example, the FBI estimates that fraudsters collected $6 billion of the $80 billion that the Federal Government provided for relief from Hurricane Katrina. As hurricane season approaches along the Atlantic Coast, Verisk is busy bolstering its clients defenses against the possibility of fraud. One of the ways it does this is by assessing the risk that its clients’ policies pose along possible storm routes. The company uses weather models to determine the claims exposure that insurance companies have for likely routes for hurricanes. 2019-06-05 00:00:00 Read the full story. Interest Score: 1.0269, Positive Sentiment: 0.0555, Negative Sentiment 0.4996

BMC Helps IT Operations Accelerate Innovation with New Advanced Analytics and Automation

New AIOps capabilities speed issue resolution by 50%, reduce event noise by 90%, and optimize performance, cost, and security across both cloud and data center environments. BMC, a global leader in IT solutions for the digital enterprise, today announced the latest update to its TrueSight portfolio to help IT teams more easily adopt and extend the value of Artificial Intelligence for IT Operations (AIOps) throughout their organizations – both on-premises and in the cloud. “Existing IT operations tools and processes cannot cope with the speed, data volume, and complexity of modern hybrid IT environments,” said Nayaki Nayyar, President, Digital Service and Operations Management at BMC. “We are continually innovating our TrueSight portfolio to help cloud and IT operations teams to predictively monitor, auto-remediate, as well as optimize capacity, cost, and security of business services and applications – all while ensuring high performance levels, reducing risk, and driving cost efficiencies.” 2019-06-07 07:05:30+00:00 Read the full story. Interest Score: 1.0085, Positive Sentiment: 0.3185, Negative Sentiment 0.3185

Highspot reels in $60M for AI-powered software used by Fortune 500 sales teams

Across industries, despite the tide of automation and artificial intelligence, most companies still employ humans to deal with customers for important interactions, whether that is through customer service, sales or other roles. Seattle startup Highspot is betting that a combination of these workers, empowered by technologies such as AI, is key to increasing the bottom line. The company today announced a whopping $60 million round to arm customer-facing teams with all the information they need for a smooth conversation. The Series D round brings total funding to date to $124 million and comes less than a year after Highspot landed $35 million in funding to power its rapid growth. Traditionally, the company has been focused on software for sales teams and other jobs that directly bring in money, but it is expanding to make tools to help anyone who talks to customers. Highspot’s goal is to put all the information in front of the right people, whether it is the salesperson closing a deal or a customer service rep fielding technical questions. It’s a moment that CEO Robert Wahbe describes as the “last mile” of significant purchases. 2019-06-04 12:00:25-07:00 Read the full story. Interest Score: 0.9989, Positive Sentiment: 0.2775, Negative Sentiment 0.0555

What Marketers Need to Know About Cybersecurity

Data-driven marketing has become the new marketing norm for businesses of all sizes. As Mark Flaharty, executive vice president of advertising at SundaySky says, “Arguably, the most important evolution in the history of marketing is the ability to understand what data you have, what data you can get, how to organize and, ultimately, how to activate the data.” More and more high-performing marketing teams are leveraging customer data to craft a full picture of their target consumer base. This allows them to create more focused campaigns, which naturally leads to better results. However, though customers prefer these personalized experiences (many are even willing to pay more to receive them), consumers don’t trust today’s businesses to adequately secure their personal information. A recent report by PwC indicates more than 90% of consumers believe companies must be more proactive about data protection. Without proper security strategies in place, data-driven marketing tactics could leave consumers increasingly exposed to cyber threats. 2019-06-05 11:00:00+00:00 Read the full story. Interest Score: 0.9969, Positive Sentiment: 0.1574, Negative Sentiment 0.5596

TechnologyOne reveals its new app arsenal

Enterprise resource planning software company TechnologyOne is pushing more into tech giant SAP’s territory, revealing for the first time its new suite of apps, tackling everything from employee expenses to managing meetings. The company will go live with its first 14 employee experience apps soon. While it already competes with big companies such as SAP and Oracle with its existing ERP software, the expansion into these apps will take TechnologyOne head to head with more of the tech giants’ products, such as SAP’s expense platform Concur and Oracle’s E-Business suite. 2019-06-06 00:00:00 Read the full story. Interest Score: 0.9847, Positive Sentiment: 0.1448, Negative Sentiment 0.0000

How Big Data Makes Us Rethink The Design Of Magnetic Devices

Fujitsu is currently the fourth largest IT service provider in the world. Located in Japan, the company has an unprecedented track record for innovation. The company was founded in 1935, but it has maintained a strong competitive edge by staying up-to-date with major advances in information technology. Fujitsu has recently started embracing the benefits of big data. In May 2018, Fujitsu engineers published a paper on their utilization of artificial intelligence in magnetic material design. They said it would be particularly important in finding the ideal size constraints and shapes of magnets. Artificial intelligence is going to be paramount to the research and development process for Fujitsu. They have discovered that it can play an important role in reducing energy loss. It is also helping them improve geometric magnet design. Prior to their new design specifications, these types of designs required extensive expertise. This is changing as artificial intelligence is being used to improve design outcomes. With the new AI models in place, less proficient design experts can create magnetic designs with optimal efficiency. 2019-06-07 23:43:09+00:00 Read the full story. Interest Score: 0.9593, Positive Sentiment: 0.4171, Negative Sentiment 0.1460

How big data is changing the way marketing teams strategize

e 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. Have you ever wondered how big companies find the right places to expand into? Well, they use big data to make informed decisions about economies that they want to move into. By taking advantage of public data from places like Sayari, companies can get access to live local data around the world. They can see information like the health of industries, the number of companies in the area, and the overall health of local markets. These bits of information help big companies make decisions on where they should grow. 2019-06-03 09:06:32+00:00 Read the full story. Interest Score: 0.9324, Positive Sentiment: 0.2869, Negative Sentiment 0.1614

Amazon GAs Textract, Its New Machine Learning-Based OCR Service

Companies that rely on optical character recognition (OCR) to digitize the content of printed forms may be interested in Textract, a new machine learning-based OCR service that just became available from Amazon Web Services. The OCR service can digitize simple text as well as more complex data contained in forms and tables. 2019-06-03 00:00:00 Read the full story. Interest Score: 0.9229, Positive Sentiment: 0.1538, Negative Sentiment 0.1978

WWDC 2019: What ‘Sign-In with Apple’ Means for Tech Professionals

Sign-In with Apple is a button developers can add to an app or website that acts just like any other social sign-in button (which, as we’ve noted, are hard to avoid). This allows users to sign in with a flow they’re familiar with, because of Facebook and Google’s own buttons, but without trading all their data. Sign-In with Apple does everything other sign-in options do, but keeps user data private; more critically, it alleviates developers from needing to capture and contain user data. Users can choose to share their email with developers for communication purposes, or Apple can return a bespoke email address unique to that app and user. This email goes through Apple’s exchange, so you can still communicate with users as needed; it’s just a “buffer” so users don’t give up data unwittingly. The button will allow developers to request information from users, but Apple cautions against being overzealous about that. It wants you to consider why you need that data before asking for it; and if it’s not necessary, don’t ask for it. It’s perfect for 2019 and beyond, when privacy concerns are at the forefront. 2019-06-06 00:00:00 Read the full story. Interest Score: 0.9063, Positive Sentiment: 0.1326, Negative Sentiment 0.2210

The Hitchhiker’s Guide to Feature Extraction

Good Features are the backbone of any machine learning model. And good feature creation often needs domain knowledge, creativity, and lots of time. In this post, I am going to talk about:
  • Various methods of feature creation- Both Automated and manual
  • Different Ways to handle categorical features
  • Longitude and Latitude features
  • Some Kaggle tricks
  • And some other ideas to think about feature creation.
TLDR; this post is about useful feature engineering methods and tricks that I have learned and end up using often. 2019-06-03 10:01:54+00:00 Read the full story. Interest Score: 0.9053, Positive Sentiment: 0.1321, Negative Sentiment 0.0685

Nearmap Unveils Game-Changing Streaming 3-D Online and Previews AI Technology at Navig8

Nearmap has developed new AI technology that is turning millions of aerial images, captured over a decade, multiple times a year, into valuable datasets. These datasets can be used to more accurately and efficiently measure change and quantify attributes, such as solar panels, pools, roofs or construction sites. Organizations ranging from small businesses to large companies and cities will be able to take advantage of AI-driven location intelligence. “Product innovation is in our DNA. Everything we do has the customer at the core,” said Tony Agresta, Executive Vice President of Product at Nearmap. “Our customers’ worlds are evolving every day. We need to keep innovating to continue to give our customers a competitive advantage through technology breakthroughs like the ones we are sharing today at Navig8. 2019-06-07 00:00:00 Read the full story. Interest Score: 0.8384, Positive Sentiment: 0.2795, Negative Sentiment 0.0000

Make your life smarter with these 5 AI gadgets

  1. Vortex – Robotic Toy Re-developed
  2. Tapia – The communication Robot
  3. AMBI Climate 2 AI Gadgets
  4. Chris Digital CO-DRIVER – AI Gadgets
  5. Mycroft – Open Source AI Tool
2019-06-10 09:21:54.333000+00:00 Read the full story. Interest Score: 0.7778, Positive Sentiment: 0.2722, Negative Sentiment 0.0389

A transportation investor overseeing a $200 million portfolio reveals the biggest opportunities coming to the industry

Uber and Lyft have been making headlines for the better part of a year, fueled in no small part by the two ride-hailing companies’ massive initial public offerings. But beyond the Wall Street hubbub, hundreds if not thousands of smaller startups are trying to tackle many of the same problems. After all, so much of a commute is connected. The car that drove you to work either has to park or go give more rides. That’s the thesis behind Autotech V… 2019-06-07 00:00:00 Read the full story. Interest Score: 0.7658, Positive Sentiment: 0.2088, Negative Sentiment 0.1740

Autonomous Ships of the Future: Run by AI Instead of a Crew

Efforts are underway especially by builders of cargo ships to use AI to deliver on the promise of autonomous ships. A fully autonomous ship would be considered a vessel that can operate on its own without a crew. Remote ships are those that are operated by a human from shore, and an automated ship runs software that manages its movements. As the technology matures, more types of ships will likely transition from being manned to having some autonomous capabilities, according to an account in Forbes. Autonomous ships might be used for some applications, but very likely some crew will still be onboard ships even if all hurdles to acquiring a fully autonomous fleet are crossed. 2019-06-07 14:20:28+00:00 Read the full story. Interest Score: 0.7514, Positive Sentiment: 0.1922, Negative Sentiment 0.2621

Amazon shows off new all-electric Prime Air drone that will start delivering packages ‘within months’

The drone is beefed up with a surrounding shroud that serves as the aerodynamic wing structure as well a safety guard for the rotors. It also has a proprietary computer vision system that can detect other flying objects from miles away, as well as the clotheslines in your backyard. “Wire detection is one of the hardest challenges for low-altitude flights,” Wilke explained. If the drone senses that obstructions — ranging from trees and yard furniture to homeowners and their pets — are too close to the spot where a printed delivery target has been laid down, the computer-vision system will hold off on making the delivery, Wilke said. Gur Kimchi, co-founder and vice president in charge of Amazon’s Prime Air drone development team, said computer simulations and machine learning figured prominently in the design of the drone. “We designed the system, the system designed the drone,” Kimchi said. 2019-06-05 17:25:11-07:00 Read the full story. Interest Score: 0.7229, Positive Sentiment: 0.1866, Negative Sentiment 0.0700  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. We used natural language processing (NLP) to determine an interest score, and to calculate the sentiment of the linked article using the Loughran and McDonald Sentiment Word Lists. If you would like to add your blog or website to our search crawler, please email We welcome all contributors. This news clip and any CloudQuant comment is for information and illustrative purposes only. It is not, and should not be regarded as  investment advice or as a recommendation regarding a course of action. This information is provided with the understanding that CloudQuant is not acting in a fiduciary or advisory capacity under any contract with you, or any applicable law or regulation. You are responsible to make your own independent decision with respect to any course of action based on the content of this post.