Industry News

Industry News

ML/AI News : This is how you put the data in Data Science! Google’s new DataSet Search Engine : Real Progress Being Made in Explaining AI : 8 AI Predictions for 2020: Lessons from a Year in the Data Science Trenches

AI & Machine Learning News. 16, December 2019

AI & Machine Learning News. 16, December 2019

The Artificial Intelligence and Machine Learning Newsletter by CloudQuant

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

Holiday Movie Watching for AI and ML Fans…. A history of AI

This is how you put the data in Data Science!

One of my favorite recent additions to the Google Search family is Dataset Search. Yes, you heard that right. You can search for datasets just like you can search for images!
Google’s vertical search engines like Google Images or Google Scholar wouldn’t last long if no one used them, so their varieties tell you a little something about what people tend to look for on the internet. Images, videos, and news are hardly surprising. But datasets? There’s your hint that working with datasets isn’t just for three isolated professors in a faraway igloo. It’s big. …and it’s getting bigger.
What’s the catch? There isn’t one. This really is the same thing as searching with Google Images or Google Scholar, but for datasets. Over 20 million (!) datasets are currently indexed and available… and that index is growing quickly. Today it puts 20 million datasets at your fingertips… and there will be more tomorrow. Now that you know it exists, you can go play with it here or you can stick around for a discussion of how Dataset Search works and what it means for the data science profession and humanity in general.

2019-12-16 02:29:01.149000+00:00 Read the full story…
Weighted Interest Score: 3.9583, Raw Interest Score: 1.1367,
Positive Sentiment: 0.2038, Negative Sentiment 0.0941

CloudQuant Thoughts : Cassie Kozyrkov, Chief Decision Scientist at Google is back in our AI Blog search with a bang, GOOGLE DATASET SEARCH! 20 million Data Sets and counting. This is probably better suited to our other blog post, Alternative Data (you can subscribe to email versions of both in the panel to the right), but this is just too big a news story to wait. 20 million datasets!

Real Progress Being Made in Explaining AI

One of the biggest roadblocks that could prevent the widespread adoption of AI is explaining how it works. Deep neural networks, in particular, are extremely complex and resist clear description, which is a problem when it comes to ensuring that decisions made by AI are made fairly and free of human bias. But real progress is being made the explainable AI (XAI) problem on several fronts.
Google made headlines several weeks ago with the launch of Google Cloud Explainable AI. Explainable AI is a collection of frameworks and tools that explain to the user how each data factor contributed to the output of a machine learning model.

2019-12-09 00:00:00 Read the full story…
Weighted Interest Score: 3.9652, Raw Interest Score: 1.7273,
Positive Sentiment: 0.2293, Negative Sentiment 0.2293

CloudQuant Thoughts : Shapely Counter Factuals (what result would have been given if a value for a certain data point was different) are a very interesting concept. But we must not forget that to utilize Google’s explainable AI we must be running Google’s TensorFlow on Google’s Cloud…

8 AI Predictions for 2020: Business Leaders & Researchers Weigh In

The first industrial revolution was powered by coal, the second by oil and gas, and the third by nuclear power. The fourth — AI — is fueled by an abundance of data and breakthroughs in compute power. While this abundance has allowed us to make significant progress in recent years, there is still much to be done for AI to be the positive life-changing force that many hope it will be. We asked thought leaders at the forefront of AI and machine learning technology to contribute some insight into what they think will transpire in 2020. Their predictions center around hardware, the human impact of AI, the public’s understanding of AI, and its limitations.
2019-12-11 15:27:08+00:00 Read the full story…
Weighted Interest Score: 4.0421, Raw Interest Score: 1.6497,
Positive Sentiment: 0.2381, Negative Sentiment 0.2211

CloudQuant Thoughts :  Some very interesting thoughts and ideas from leaders in the industry including Stanley Seibert at Anacondo, with whom we have worked very closely in the past.

Lessons from a Year in the Data Science Trenches

Over the past year, I’ve gone from the simple world of writing Jupyter Notebooks to developing machine learning pipelines that deliver real-time recommendations to building engineers around the clock. While I have room for improvement (I still make plenty of coding and data science mistakes), I’ve managed to learn a few things about data science that we’ll go through in this article. Hopefully, with the lessons below, you’ll avoid many of the errors I made learning to operate on the day-to-day data science frontlines.

  1. Production data science is mostly computer science
  2. Data science is still highly subjective
  3. People and communication skills are crucial
  4. Use standard tooling and be slow to adopt new technologies
  5. Hide the internal complexity of data science with external simplicity

2019-12-09 00:00:00 Read the full story…
Weighted Interest Score: 5.8612, Raw Interest Score: 2.1270,
Positive Sentiment: 0.0000, Negative Sentiment 0.1934

CloudQuant Thoughts : A nice neat blog post which should be essential reading for anyone setting out in a Data Science role. Just some simple best behavior pointers.

Researchers report breakthrough in ‘distributed deep learning’

Online shoppers typically string together a few words to search for the product they want, but in a world with millions of products and shoppers, the task of matching those unspecific words to the right product is one of the biggest challenges in information retrieval. Using a divide-and-conquer approach that leverages the power of compressed sensing, computer scientists from Rice University and Amazon have shown they can slash the amount of time and computational resources it takes to train computers for product search and similar “extreme classification problems” like speech translation and answering general questions.
In tests on an Amazon search dataset that included some 70 million queries and more than 49 million products, Shrivastava, Medini and colleagues showed their approach of using “merged-average classifiers via hashing,” (MACH) required a fraction of the training resources of some state-of-the-art commercial systems. “Our training times are about 7-10 times faster, and our memory footprints are 2-4 times smaller than the best baseline performances of previously reported large-scale, distributed deep-learning systems,” said Shrivastava, an assistant professor of computer science at Rice.
2019-12-09 00:00:00 Read the full story…

Bootstrap Your AI Education: Here Are Some Options

Whenever I interview IT executives with AI responsibility, I like to ask them for their advice for young people or mid-career people who want to speed the learning curve on how AI can help their business and their careers.
One of my favorite responses came from Dawn Fitzgerald, Director of Digital Transformation, Data Center Operations for Schneider Electric. (She recently spoke on Digitizing the Data Center at AI World 2019 in Boston.) I had asked her how—after getting her education in electrical engineering, computer systems engineering and also earning an MBA—she learned about AI. She said, “AI is and will continue to be so pervasive that individuals in different fields need to bootstrap themselves, take as many courses as possible, do workshop with AI vendors, try self-starting efforts. Many companies will support their employees in this AI education.”

2019-12-12 22:30:13+00:00 Read the full story…
Weighted Interest Score: 4.1037, Raw Interest Score: 2.1732,
Positive Sentiment: 0.1369, Negative Sentiment 0.1027

Top Artificial Intelligence Books Released In 2019 That You Must Read

Artificial Intelligence has had many breakthroughs in 2019. In fact, we can go as far as to say that it has trickled down to every single facet of modern life. With its intervention in our daily life, it is imperative that everyone knows about how it is affecting our lives, bringing about change in it, the threats and possible solutions.
While there are some people who still think AI is only robots and chatbots, it is important that they know of the advancements in the field. There are many online courses and books on artificial intelligence that give a comprehensive understanding to the reader whether it is a professional or an AI enthusiast.
In this article, we have compiled a list of books on artificial intelligence published in 2019 that one can use to learn more about this fascinating technology:

  • Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again (Basic Books)
  • Human Compatible: AI and the Problem of Control (Allen Lane)
  • The Creativity Code: Art and Innovation in the Age of AI (Harvard University Press)
  • You Look Like a Thing, and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place (Wildfire)
  • Rebooting AI: Building Artificial Intelligence We Can Trust (Pantheon)
  • AI for People and Business: A Framework for Better Human Experiences and Business Success (Shroff/O’Reilly)

2019-12-16 13:00:00+00:00 Read the full story…
Weighted Interest Score: 3.8475, Raw Interest Score: 1.5588,
Positive Sentiment: 0.3081, Negative Sentiment 0.1813

Cindicator launches quantitative crypto hedge fund powered by hybrid intelligence

Cindicator Capital is an ecosystemic fund, based on an alpha-generating vehicle including thousands of decentralised analysts from 135 countries. The data flow of millions of forecasts from the analytical platform ( is enhanced with machine learning models and then feeds a variety of algorithmic strategies. Additionally, the fund develops strategies based on quantitative research on a variety of data sets.

Part of the fund’s revenues will be used to reward analysts for correct forecasts in proportion to their intellectual efforts and the quality of indicators based on their predictions.

Cindicator has invested USD 500,000 of the corporate treasury into the fund’s strategies. That amount will be extended gradually to USD 2.5 million in the coming months.

2019-12-16 00:00:00 Read the full story…
Weighted Interest Score: 6.6481, Raw Interest Score: 2.5163,
Positive Sentiment: 0.2330, Negative Sentiment 0.0000

5 areas of focus when adopting AI in your organization

Artificial intelligence has the potential to revolutionize financial services. According to the MIT Sloan and Boston Consulting Group’s 2019 Global Executive Study and Research Report, 90% of respondents agree that AI represents a business opportunity for their companies. Firms are investing heavily in AI capabilities, but few have a clear vision for their adoption strategy or a process for prioritizing projects, running experiments, and implementing AI on an enterprise-wide basis.
To help assist senior leaders with creating an AI strategy, five key components provide a blueprint for successful AI adoption: strategy, structure, systems, skills, and staff.
2019-12-15 00:00:00 Read the full story…
Weighted Interest Score: 5.4203, Raw Interest Score: 1.8043,
Positive Sentiment: 0.3424, Negative Sentiment 0.1976

What’s Ahead in Data for 2020—And the Coming Decade

We stand at the start of a new year and on the precipice of a new decade—the 2020s. For data managers, these will likely be the “Roaring ’20s” with data at the heart of every key business initiative, accented by a growing sophistication in technologies and methodologies focused on increasing the intelligence of the enterprise.
To provide insight on emerging trends for data-driven enterprises, DBTA reached out to industry leaders for their perspectives on not only what’s ahead in the year 2020 but also what they see developing as the next decade unfolds.
2020-12-16 00:00:00 Read the full story…
Weighted Interest Score: 5.1348, Raw Interest Score: 2.3518,
Positive Sentiment: 0.1611, Negative Sentiment 0.0644

We need laws about AI, not self-regulation

Companies and government departments using artificial intelligence technology must be accountable through laws – not merely industry codes of ethics – to allow customers to understand and potentially challenge decisions made using AI, the Australian Human Rights Commission says.
In a clarion call for the regulatory approach on AI to be reconsidered, the commission wants a new national strategy for AI, to ensure the powerful technology is governed by core democratic principles.
“Laws that apply in the real world should apply in the digital world, and we need to enforce laws more rigorously to make that happen,” said Edward Santow, the Human Rights Commissioner. “An ethics framework can help to make good choices, but is different to the law which sets baselines for proper conduct.”

People affected by decisions influenced by AI “should be able to understand the basis of the decision and be able to challenge decisions tha…

2019-12-16 00:00:00 Read the full story (PAYWALL)…
Weighted Interest Score: 4.5837, Raw Interest Score: 1.9331,
Positive Sentiment: 0.1239, Negative Sentiment 0.2726

Managing Big Data in Real-Time with AI and Machine Learning

Processing big data in real-time for artificial intelligence, machine learning, and the Internet of Things poses significant infrastructure challenges.
Whether it is for autonomous vehicles, connected devices, or scientific research, legacy NoSQL solutions often struggle at hyperscale. They’ve been built on top of existing RDBMs and tend to strain when looking to analyze and act upon data at hyperscale – petabytes and beyond.
DBTA recently held a webinar featuring Theresa Melvin, chief architect of AI-driven big data solutions, HPE, and Noel Yuhanna, principal analyst serving enterprise architecture professionals, Forrester, who discussed trends in what enterprises are doing to manage big data in real-time.

2019-12-09 00:00:00 Read the full story…
Weighted Interest Score: 4.5578, Raw Interest Score: 2.5912,
Positive Sentiment: 0.1705, Negative Sentiment 0.4773

Accenture Acquires Clarity Insights to Further Enrich AI

Accenture is acquiring Clarity Insights, a U.S.-based data consultancy with deep data science, artificial intelligence (AI), and machine learning (ML) expertise.
The acquisition will add nearly 350 employees, along with a strong portfolio of accelerators, which can help organizations more quickly realize value from their data, to Accenture’s Applied Intelligence business. These additions will further equip clients with leading capabilities to meet the growing demand for enterprise-scale AI, analytics, and automation solutions.
Founded in 2008 and headquartered in Chicago, with additional locations throughout the United States, Clarity Insights is a provider of data science and AI/ML engineering capabilities for large enterprises, and a strategic partner to clients across a range of industries, particularly healthcare, financial services and insurance.

2019-12-13 00:00:00 Read the full story…
Weighted Interest Score: 4.2837, Raw Interest Score: 2.2140,
Positive Sentiment: 0.2306, Negative Sentiment 0.1845 raises $29 million to build AI-as-medical-device at scale, a Sydney-based healthcare artificial intelligence company, announced it has completed its first capital raise of A$29 million.

Founded by brothers – Aengus Tran, a clinician and world-ranked AI engineer and Dimitry Tran, a healthcare technologist, the company has been bootstrapped since inception in 2018 and has a vision to use AI to revolutionise global healthcare.
2019-12-13 06:00:07+11:00 Read the full story…
Weighted Interest Score: 3.9531, Raw Interest Score: 1.3474,
Positive Sentiment: 0.6151, Negative Sentiment 0.0293

How 5G Will Serve AI and Vice Versa

5G is the future of the edge. Though it’s still several years away from widespread deployment, 5G is a key component in the evolution of cloud-computing ecosystems toward more distributed environments. Between now and 2025, the networking industry will invest about $1 trillion worldwide on 5G, supporting rapid global adoption of mobile, edge, and embedded devices in practically every sphere of our lives.
5G will be a prime catalyst for the trend under which more workloads are executed and data resides on edge devices. It will be a proving ground for next-generation artificial intelligence (AI), offering an environment within which data-driven algorithms will guide every cloud-centric process, device, and experience. Just as significant, AI will be a key component in ensuring that 5G networks are optimized from end to end, 24×7.

2019-12-10 00:00:00 Read the full story…
Weighted Interest Score: 3.8385, Raw Interest Score: 1.8494,
Positive Sentiment: 0.2117, Negative Sentiment 0.0334

DataRobot Snags Data Prepper Paxata

Automated machine learning softer provider DataRobot yesterday announced the acquisition of Paxata, a provider of self-service data preparation and data fabrics. And it didn’t take DataRobot long to release the first new product based on the acquisition, called AI Catalog.
Thanks to a well-regarded product and more than $430 million in venture capital backing, DataRobot has emerged as one of the leaders in the nascent machine learning operations, or MLOps, space in recent years.

2019-12-13 00:00:00 Read the full story…
Weighted Interest Score: 3.8102, Raw Interest Score: 2.0297,
Positive Sentiment: 0.1812, Negative Sentiment 0.0725

New York-Based Electronic Bond Trading Platform, Trumid, Partners with Inforalgo to Expand Client Connectivity

London, UK – December 12th, 2019 – Inforalgo, the Capital Markets data automation specialist, has announced a new partnership with fast-growing financial technology company, Trumid. The alliance will see Inforalgo provide on-demand integration to Trumid Market Center, the firm’s electronic bond trading platform, easing straight-through processing (STP).

The partnership, formed initially in response to a specific client request, will benefit a br…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 3.7523, Raw Interest Score: 1.8838,
Positive Sentiment: 0.4365, Negative Sentiment 0.0689

Open Registration for Loominus Data Science Platform

Loominus has opened up registration and is offering free accounts for a limited time. There’s a whole slew of new features including private data repos, data pipeline cloning, automated data pipelines, enhanced column type detection, UI/UX improvements, detailed information for active tasks, model stream updates and updated API documentation.
Loominus is an end-to-end platform that helps teams ingest and stage data, build advanced machine learning models with no code and deploy them into production. Loominus makes it easy for individuals and teams without experience building machine learning pipelines to take advantage of machine learning faster. Loominus is equally great for experienced data scientists that need to focus on model selection and tuning.

2019-12-15 00:00:00 Read the full story…
Weighted Interest Score: 3.5111, Raw Interest Score: 2.6212,
Positive Sentiment: 0.6553, Negative Sentiment 0.0000

Banks Are Accepting AI, But Are Struggling To Use It for Competitive Impact: Report

About 97% commercial banks are using artificial intelligence, says a new research from Genpact, a noted professional services firm focused on delivering digital transformation. However, the survey says that these institutions are unable to implement these technologies effectively for competitive advantage.

51% of the survey respondents are using AI simply for point solutions and individual tasks, with 27% testing in pilots, and only 19% leveraging it across the bank holistically. With pressures mounting from fintechs and other non-bank disruptors, these AI trials raise concerns about how effectively commercial banks can use the technology to improve customer experience and better compete.

2019-12-13 09:18:06+00:00 Read the full story…
Weighted Interest Score: 3.4035, Raw Interest Score: 1.3883,
Positive Sentiment: 0.4926, Negative Sentiment 0.2239

The AI Transparency Paradox

In recent years, academics and practitioners alike have called for greater transparency into the inner workings of artificial intelligence models, and for many good reasons. Transparency can help mitigate issues of fairness, discrimination, and trust — all of which have received increased attention. Apple’s new credit card business has been accused of sexist lending models, for example, while Amazon scrapped an AI tool for hiring after discovering it discriminated against women.
At the same time, however, it is becoming clear that disclosures about AI pose their own risks: Explanations can be hacked, releasing additional information may make AI more vulnerable to attacks, and disclosures can make companies more susceptible to lawsuits or regulatory action.
Call it AI’s “transparency paradox” — while generating more information about AI might create real benefits, it may also create new risks. To navigate this paradox, organizations will need to think carefully about how they’re managing the risks of AI, the information they’re generating about these risks, and how that information is shared and protected.
2019-12-13 13:25:54+00:00 Read the full story…
Weighted Interest Score: 3.3884, Raw Interest Score: 1.2940,
Positive Sentiment: 0.3604, Negative Sentiment 0.3440

Prime brokerage 2019: Winning tactics inside the gladiatorial arena

According to industry data provider Coalition, the world’s 12 largest investment banks produced USD18.3 billion in prime services revenue last year, up 8.3 per cent on 2017 but despite this the PB arena remains as gladiatorial as ever.

On 7 July, Deutsche Bank announced that it was selling its PB business to BNP Paribas. This has led to a period of uncertainty, during which other bank-owned primes have sought to capitalise; most notably Barclays…
2019-12-13 00:00:00 Read the full story…
Weighted Interest Score: 3.3695, Raw Interest Score: 1.6839,
Positive Sentiment: 0.1698, Negative Sentiment 0.0802

Goldman Sachs could win twice from $3b AirTrunk auction

In one corner is Australia’s Macquarie, which is bidding via funds manager Macquarie Infrastructure and Real Assets. While MIRA invests for mostly offshore funds, the fact it is domiciled in Australia could make for a cleaner exit for Goldman Sachs (the investor) and co.

In the other corner, Canadian bigwig OMERS needs no introduction in Australian auctions. This column can reveal OMERS has teamed up with one of the other leading contenders, pri…
2019-12-16 00:00:00 Read the full story…
Weighted Interest Score: 3.3473, Raw Interest Score: 1.5821,
Positive Sentiment: 0.0465, Negative Sentiment 0.0000

These fast-growing jobs for 2020 offer six-figure salaries, and they might surprise you

Looking ahead to 2020, you may be contemplating a career switch. If so, it’s probably best to consider moving into a path where growth is on the uptick and jobs are likely to be more plentiful.

LinkedIn’s latest report on emerging job trends points out those most promising positions, and there are a few surprises. Engineering jobs—particularly in AI—are perennially popular and dominate the list. However, the awareness around mental health and em…
2019-12-12 10:40:18 Read the full story…
Weighted Interest Score: 3.3470, Raw Interest Score: 2.3065,
Positive Sentiment: 0.1860, Negative Sentiment 0.0000

Handwriting Recognition using ML.NET

Referring to the ML.NET Samples repository (link) is a good starting point for new projects, because the ML.NET Samples repository provides us a ton of commonly seen machine learning problems and solutions. We can follow the code samples via copy & paste when we work on our new projects. Also, we can learn a lot of best practices from the sample solutions.

On the other hand, ML.NET offers a fantastic tool for “machine learning dummies”. Today, we will take a look at this tool and see how easy it is.

Build a Model Using ML.NET Model Builder

ML.NET Model Builder (link) is an…
2019-12-10 18:24:45.156000+00:00 Read the full story…
Weighted Interest Score: 3.2960, Raw Interest Score: 1.7785,
Positive Sentiment: 0.2541, Negative Sentiment 0.0635

Few DON’Ts for Data Scientists

Few DON’Ts for Data Scientists

Many Data Scientists focuses on algorithms and mathematics but fail to learn an important skill — communication

In this post, I present a few tips to avoid when doing Data Science. These tips are not related to coding or mathematics but are more focused on commonly underappreciated skill — communication. As a Data Scientist you need to report results of experiments on a regular basis, make propositions for further…
2019-12-16 06:17:49.756000+00:00 Read the full story…
Weighted Interest Score: 3.2166, Raw Interest Score: 1.6341,
Positive Sentiment: 0.1853, Negative Sentiment 0.2695

ASX creates the Aussie Nasdaq

The executive general manager of listings and issuer services at the ASX, Max Cunningham, said it had been working with S &P for much of the year on company classifications, as the index will be based on its GICS (Global Industry Classification Standard) criteria, which currently incorporates about 210 ASX stocks.

He said the index would give investors an increased opportunity to tap into the growth of the tech sector, even if it was outside the…
2019-12-13 00:00:00 Read the full story…
Weighted Interest Score: 3.1209, Raw Interest Score: 1.7147,
Positive Sentiment: 0.3297, Negative Sentiment 0.0659

FINRA Names Consolidated Exam Team

FINRA EVP Bari Havlik.

The Financial Industry Regulatory Authority said Thursday that it has appointed a senior leadership team to head its new examination and risk monitoring structure, a move that marks the consolidation of broker-dealer regulator’s three exam functions into a single, unified program.

The exam functions previously were divided among three programs responsible for business conduct, financial and trading compliance.

“The conso…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 3.0972, Raw Interest Score: 1.4190,
Positive Sentiment: 0.1684, Negative Sentiment 0.0481

Which Tech Employers are Hiring This Month?

As we head into the end of 2019, which tech skills are in greatest demand among employers? And which employers are hiring the most technologists?

We used Burning Glass, which collects and analyzes millions of job postings from across the U.S., to answer both of these questions. And over the past thirty days, it’s clear that employers most want technologists who can wrestle with SQL, no doubt in order to build and maintain databases.

Among progr…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 3.0832, Raw Interest Score: 1.9013,
Positive Sentiment: 0.1542, Negative Sentiment 0.1028

Charles Schwab Stock: A Top Pick for 2020

The Charles Schwab Corporation (SCHW) turned the discount brokerage industry upside down in October 2019, cutting commissions on equity and options trades to zero.(See also: Schwab Cuts Base Commissions to Zero.) The move, intended to challenge Robinhood and other rapidly growing internet innovators, was matched quickly by other competitors, setting off an industry decline that dropped shares of TD Ameritrade Holding Corporation (AMTD) and E*TRAD…
2019-12-09 13:50:10.222000+00:00 Read the full story…
Weighted Interest Score: 3.0575, Raw Interest Score: 1.5243,
Positive Sentiment: 0.3387, Negative Sentiment 0.4113

IBM’s ‘elite’ data science squad has kickstarted AI for more than 100 companies

Last year, IBM announced a Data Science Elite team whose only job is to help big enterprise companies push their first AI models into production.

Now, more than a year after the program’s launch, Rob Thomas, the IBM executive overseeing the AI SWAT team, reports that it has been a “huge success.” The team has increased from 30 data scientists to 100, and there are plans to grow significantly next year. “We hire them wherever we can, a…
2019-12-15 00:00:00 Read the full story…
Weighted Interest Score: 3.0502, Raw Interest Score: 1.4072,
Positive Sentiment: 0.2376, Negative Sentiment 0.1462

Fenergo wins A-Team Group’s Best KYC and Client On-Boarding Solution Award for Second Year Running

Data Management Insights Award marks eight award win for Fenergo this year

Fenergo, the leader in digital Client Lifecycle Management (CLM) solutions, has been awarded Best Know Your Customer (KYC) and Client On-boarding Solution at the 2019 Data Management Insight Awards. The award follows a long line of wins for Fenergo in 2019 including the Deloitte Financial Services Innovation Award, the Chartis RiskTech100 award for Best CLM and KYC Solu…
2019-12-11 00:00:00 Read the full story…
Weighted Interest Score: 3.0066, Raw Interest Score: 2.0298,
Positive Sentiment: 0.4647, Negative Sentiment 0.1956

This VC explains his bet on startups that use AI to help people get better at their jobs, without automating them away

Emergence, is ready to make a new bet on the future of cloud software.

Saper thinks the next set of cloud software companies will be what he calls “coaching networks” — basically software that uses artificial intelligence to gather information on how you perform your daily tasks and provide suggestions for improvement and efficiency.

The key is that AI will be used to augment, rather than automate, the tasks that the software is helping users do, he said.

“It’s a very different version or view of the way that AI will manifest in the enterprise than what is typically happening today,” Saper told Business Insider….
2019-12-15 00:00:00 Read the full story…
Weighted Interest Score: 2.9951, Raw Interest Score: 1.6103,
Positive Sentiment: 0.1834, Negative Sentiment 0.0204

Moula Attracts $20 Million to Fund Growth in Business Lending

Moula, an Australian non-bank business lender, has secured $20 million Series D private funding to continue fuelling expansion. The round was led by Escala Partners with ongoing support from existing shareholders Liberty Financial and Acorn Capital.

Moula has experienced strong growth over the past five years, processing over 20,000 business loan applications and growing its loan book by 124 per cent in 2019.

Moula Co-founder and CEO Aris Alleg…
2019-12-12 05:03:19+11:00 Read the full story…
Weighted Interest Score: 2.9342, Raw Interest Score: 1.4211,
Positive Sentiment: 0.5685, Negative Sentiment 0.0474

Study Something New Every Day & Participate In Hackathons, Says This General Electric Data Scientist

Focus is vital to thrive in any career, and data science is no different. Since being a proficient data scientist requires various skills, developers get perplexed and fail to concentrate on the core of the data science.

To understand effective ways for flourishing in data science landscape, we interviewed Arihant Jain for our weekly column My Journey In Data Science. Jain is a Staff Data Scientist at General Electric. He has 5+ years of experie…
2019-12-13 05:30:00+00:00 Read the full story…
Weighted Interest Score: 2.8607, Raw Interest Score: 1.6819,
Positive Sentiment: 0.3957, Negative Sentiment 0.2473

I didn’t have the cash to exercise my startup stock options. This Silicon Valley fund offered a way to do it without burying me in debt.

The Employee Stock Option, or ESO, Fund, which is based in Silicon Valley, offers a way for startup workers to exercise their stock options in exchange for a cut of the shares when the startup goes public or is acquired, plus fees and interest.

ESO Fund’s financing are non-recourse loans. In other words, the firm takes on all the risk. If your options end up not being worth much because of a disappointing IPO or if they become worthless because …
2019-12-14 00:00:00 Read the full story…
Weighted Interest Score: 2.8562, Raw Interest Score: 1.6668,
Positive Sentiment: 0.1082, Negative Sentiment 0.2381

KuppingerCole Report Leadership Compass Database and Big Data Security

This Leadership Compass from analyst firm KuppingerCole provides an overview of the market for database and big data security solutions along with guidance and recommendations for finding the sensitive data protection products that best meet client’s requirements.

The report examines a broad range of technologies, vendor product and service functionality, relative market shares, and innovative approaches to implementing consistent and comprehensive data protection across the enterprise….
2019-12-10 00:00:00 Read the full story…
Weighted Interest Score: 2.8455, Raw Interest Score: 1.6260,
Positive Sentiment: 0.6098, Negative Sentiment 0.0000

A 32-year-old investor hotshot just became partner at $550 million Dawn Capital. Here’s her view on investing in enterprise startups, Europe’s hottest market right now.

Venture capital investor Evgenia Plotnikova has been promoted to partner at Dawn Capital, a European VC firm with $550 million under management.

Plotnikova and the Dawn team invest in early-stage enterprise software startups, recently leading a $61 million round of funding into expenses management platform Soldo alongside Alphabet’s investing subsidiary CapitalG.

Plotnikova bucks Europe’s poor record of promoting women to senior roles in vent…
2019-12-16 00:00:00 Read the full story…
Weighted Interest Score: 2.8305, Raw Interest Score: 1.5889,
Positive Sentiment: 0.2787, Negative Sentiment 0.1254

2020 predictions: the new era of spending for the CFO

In the last 12 months, CFOs, particularly in the UK, have been forced to count the pennies when it comes to budgeting in an era of political and economic uncertainty. As we move into 2020 we expect, or at least hope, that we will have more clarity.

With this comes spending – CFOs will look to spend funds they have been holding back over the previous year and will look to invest in areas that will help their company thrive and grow.

CX and FS tu…
2019-12-13 13:09:39 Read the full story…
Weighted Interest Score: 2.8231, Raw Interest Score: 1.5173,
Positive Sentiment: 0.2568, Negative Sentiment 0.1167

Predictions for 2020: How the Edge, AI Workloads and Object Storage are Set to Proliferate

ge industry. As data storage balloons to the exabyte level for many enterprises, ways of managing storage are going to change drastically in 2020. Here’s how edge computing as well as managing AI and machine learning workloads, not to mention the proliferation of the private clouds, will affect organizations over the next year:

Turning the Hybrid Cloud Storage Model on its Side: Hello Edge Computing!

Hybrid cloud storage involves keeping data both on-premises and in the public cloud and having the ability to seamlessly move data across these environments. In 2020, the hybrid storage strategy will be turned …
2019-12-16 08:30:47+00:00 Read the full story…
Weighted Interest Score: 2.7725, Raw Interest Score: 1.3276,
Positive Sentiment: 0.1660, Negative Sentiment 0.1422

Facilitating Transitions of Data to the Cloud

As the urgency to compete on analytics continues to revolutionize the business world, more and more organizations are moving their data to the cloud to reduce infrastructure costs, increase efficiencies and improve time-to-value.

At the same time, there are many success factors to consider, from the strengths and weaknesses of different cloud providers, to integration hurdles, data latency challenges and governance problems.

DBTA recently had a…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 2.7655, Raw Interest Score: 1.6581,
Positive Sentiment: 0.3685, Negative Sentiment 0.1474

China on verge of becoming AI superpower as investment closes in on US

The rise of China as a leading player in artificial intelligence research has been revealed by new figures showing how quickly the country is gaining on the US.

The 2019 AI Index Report, put together by US academics and researchers, found that Chinese companies are on average receiving millions of dollars more in investment than their western counterparts.

Overall investment in Chinese companies rose to $16.6bn (£12.5bn) in the period between July 2018 and J…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 2.6950, Raw Interest Score: 1.8466,
Positive Sentiment: 0.2841, Negative Sentiment 0.0000

FINRA Completes Yearlong Consolidation of Exam Functions

The Financial Industry Regulatory Authority has completed a project it started about a year ago to consolidate its three separate examination programs—around sales practice, trading, and financial compliance and risk oversight—into a single, unified program.

Bari Havlik, executive vice president of member supervision, one of’s Ten to Watch in 2019, was tasked with the project. It was aimed at ensuring consistency, eliminatin…
2019-12-13 16:53:33+00:00 Read the full story…
Weighted Interest Score: 2.6931, Raw Interest Score: 1.2195,
Positive Sentiment: 0.0508, Negative Sentiment 0.0000

The growth of cognitive search in the enterprise, and why it matters

Enterprises typically have countless data buckets to wrangle (upwards of 93% say they’re storing data in more than one place), and some of those buckets invariably become underused or forgotten. A Forrester survey found that between 60% and 73% of all data within corporations is never analyzed for insights or larger trends, while a separate Veritas report found that 52% of all information stored by organizations is of unknown value. The opportuni…
2019-12-14 00:00:00 Read the full story…
Weighted Interest Score: 2.6775, Raw Interest Score: 1.4812,
Positive Sentiment: 0.1722, Negative Sentiment 0.0861

dotData Achieves Advanced Technology Partner Status with AWS

dotData, focused on delivering full-cycle data science automation and operationalization for the enterprise, has achieved Advanced Technology Partner status in the Amazon Web Services (AWS) Partner Network (APN). Achieving APN Advanced Technology Partner status is recognition of dotData’s ability to deliver data science automation and machine learning (ML) automation on AWS.

APN Advanced Technology Partner status is the highest tier for Technolo…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 2.6474, Raw Interest Score: 1.6867,
Positive Sentiment: 0.5221, Negative Sentiment 0.0000

Bamboolib — Learn and use Pandas without Coding

Easy Data Exploration

Bamboolib helps a great bit for Exploratory Data analysis. Now, Data exploration is an integral part of any data science pipeline. And writing the whole code for data exploration and creating all the charts is complicated and needs a lot of patience and effort to get right. I will admit sometimes I do slack off and am not able to give enough time for it.

Bamboolib makes the whole Data Exploration exercise a breeze.

For example. Here is a glimpse of your data, once you click on Visualize Dataframe.

You get to see…
2019-12-16 05:37:13.292000+00:00 Read the full story…
Weighted Interest Score: 2.6263, Raw Interest Score: 1.1616,
Positive Sentiment: 0.2020, Negative Sentiment 0.0505

Using AI In Content Is An Enterprise Imperative

Contributed Commentary by Ivan Yamshchikov, ABBYY

The goal to be a data-driven organization has been a rallying cry for enterprises for the past decade. The aspiration is to leverage content to gain powerful insights into ways businesses can better serve customers, improve operational efficiency and respond to market dynamics faster. However, these efforts have come up short and have not been attainable at the promised level—until now.

2019-12-12 22:30:30+00:00 Read the full story…
Weighted Interest Score: 2.5915, Raw Interest Score: 1.4778,
Positive Sentiment: 0.4926, Negative Sentiment 0.2189

Python: Top Programming Language of 2019?

It’s difficult to name a particular programming language as “top” or “best.” After all, different programming languages have different uses. But as we close out 2019, it’s hard to deny that Python, despite its relative age and ubiquity, has a lot of momentum behind it… with nothing to slow it down.

We base this bold statement on a number of datasets. For example, GitHub’s State of the Octoverse 2019, a comprehensive view of everything happening …
2019-12-16 00:00:00 Read the full story…
Weighted Interest Score: 2.5791, Raw Interest Score: 1.6179,
Positive Sentiment: 0.2754, Negative Sentiment 0.2065

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.