AI & Machine Learning News. 06, January 2020

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?

Just about squeeze this one in for 12th night!

Top 10 Investment Themes For 2020

As you may recall, my overall theme for 2019 was “slowing but growing” and while this will likely become “slower but still growing” in the new year, I believe that 2020 will be “The Year of the 3 Big E’s” – earnings, the economy and the election, given the interconnected nature of these three factors. In this regard, below are my top ten investment themes for 2020.

1. Positioning For A Year With Two Distinct Halves
2. Demand For Tax-Free Income Remains High
3. Biotech M&A Activity Likely To Continue
4. Preferreds Continue To Become A Preferred Source Of Income
5. ESG-Based Strategies Gain More Prominence
6. Finding Value In Dividends
7. International Equities Attract Investment Flows
8. Strong Consumer Fuels Further Growth In E-Commerce
9. AI Implementations Increase Across Multiple Industries
10. Counterbalancing Consensus With Contrarians

2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 4.1091, Raw Interest Score: 1.8887,
Positive Sentiment: 0.3209, Negative Sentiment 0.1605

CloudQuant Thoughts : Number 9 is no surprise to anyone reading this blog and Enviromental Social and Governance has been a hot topic for us in 2019, culminating in our white paper confirming the value of ESG alternative data from G&SQ, head over to our data catalog for more info.

How Renaissance beat the markets with Machine Learning

The Man Who Solved The Market illustrates how Jim Simons and his motley crew of scientists and mathematicians built Renaissance Technology, the most profitable quant fund in history. Truth be told, I wish there were more juicy details on what their edge in markets is, but it’s wishful thinking given the secrecy of the field in general and Renaissance in particular.

Instead of my usual articles where I implement machine learning models, I decided to pen my learning points from the book, so whoever wants to skip the Mercer-funding-Trump drama and the side effects of ultra-rich employees can still learn the precious nuggets of how the Medallion fund achieved 66.1% average annual returns since 1988.

  1. Financial knowledge is optional
  2. Rationalising the model’s predictions is not top priority
  3. Research papers are likely wrong
  4. Have a single trading model
  5. Industrial grade coding is crucial
  6. Trade your edges to its capacity
  7. Garbage in, garbage out
  8. Don’t trust your models 100%
  9. Quants are human too
  10. Longer term anomalies are harder to profit from
  11. Beating the markets with machine learning is tough

2020-01-03 23:41:00.998000+00:00 Read the full story…
Weighted Interest Score: 4.0086, Raw Interest Score: 1.9471,
Positive Sentiment: 0.3088, Negative Sentiment 0.2551

CloudQuant Thoughts : The author of the book, Gregory Zuckerman, was a key speaker at the recent Battle of the Quants in London. John ‘Morgan’ Slade of CloudQuant was also a panelist on a discussion around Environmental, Social and Governance Data.

US restricts exports of AI for analyzing satellite images

U.S. technology companies that build artificial intelligence software for analyzing satellite imagery will face new restrictions on exporting their products to China and elsewhere.

The Commerce Department said new export rules take effect Monday that target emerging technology that could give the U.S. a significant military or intelligence advantage. A special license would be required to sell software outside the U.S. that can automatically scan aerial images to identify objects of interest, such as vehicles or houses.

The rules could affect a growing sector of the tech industry using algorithms to analyze satellite images of crops, trade patterns and other changes affecting the economy or environment.

2020-01-05 00:00:00 Read the full story…
Weighted Interest Score: 2.6405, Raw Interest Score: 1.3640,
Positive Sentiment: 0.0853, Negative Sentiment 0.0000

CloudQuant Thoughts : It should come as no surprise that the US would begin attempting to ring fence its AI technological advances from the Chinese. However, with US college educated Chinese AI specialists creating huge numbers of extremely advanced start-ups in China, they may be closing the gate after the horse has bolted (see what I did there? Ring Fenced, Bolt, Gate, Horse… pfft AI).

Vision-Based AI Model Solves Sudoku In A Swift

Artificial intelligence is now being used to solve the grid-based number puzzle — Soduko. The puzzle, Sudoku, is no match for today’s artificial; intelligence (AI) systems, however, a novel approach to the challenge is trending on GitHub due to its practical integration of computer vision technologies. Users can now use GUI Smart Sudoku Solver to find the solution of the Sudoku puzzle, by simply snapping a photo of the puzzle printed on the newspaper or playbook and the AI model will automatically transfer the image to a computer-friendly language to find the answer.

Approximately a decade ago, Swedish developer Hans Andersson has built an amusing Sudoku solver based on a LEGO mobile robot, which used to navigate over the puzzle and detected numbers on Sudoku printouts using a light sensor, then used to solve the puzzles using a recursive backtracking algorithm. This new vision-based AI Sudoku Solver looks like an upgraded version of the LEGO robot, with way faster processing time, improved portability, and definitely fewer restrictions.
2020-01-02 09:22:36+00:00 Read the full story…
Weighted Interest Score: 2.6970, Raw Interest Score: 1.3491,
Positive Sentiment: 0.2951, Negative Sentiment 0.0843

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.
2020-01-06 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

Specialized AI Chip Market Seen Expanding Rapidly

The fragmenting and increasingly specialized AI chip market will cause developers of AI applications to have to make platform choices for upcoming projects, choices with potentially long-term implications.

AI chip specialization arguably began with graphics processing units, originally developed for gaming then deployed for applications such as deep learning. When NVIDIA released its CUDA toolkit for making GPUs programmable in 2007, it opened the market up to a wider range of developers, noted a recent account in IEEE Spectrum written by Evan Sparks, CEO of Determined AI.

GPU processing power has advanced rapidly. Chips originally designed to render images are now the workhorses powering AI R&D. Many of the linear algebra routines necessary to make Fortnite run at 120 frames per second, are now powering the neural networks at the heart of advanced applications in computer vision, automated speech recognition and natural language processing, Evans notes.

2020-01-02 22:30:08+00:00 Read the full story…
Weighted Interest Score: 4.7240, Raw Interest Score: 2.3247,
Positive Sentiment: 0.1134, Negative Sentiment 0.0567

ProBeat: AI startups raised fewer funding rounds in 2019

2019 is over, and while we’re already looking forward to AI in 2020, there’s still plenty to say about the past year. While funding news isn’t as critical to our coverage here at VentureBeat as it once was, we do still follow the money for transformative tech. Nowadays, that includes AI. In 2019, AI startups raised more money than in 2018, and in fewer rounds, according to data from Crunchbase. According to Pitchbook, though, both deal size and the number of deals decreased from 2018 to 2019.

Here’s a breakdown of the past five years per Crunchbase’s AI category:

  • 2015: $6.2 billion raised over 1,600 rounds
  • 2016: $7.5 billion raised over 2,200 rounds
  • 2017: $14.3 billion raised over 2,900 rounds
  • 2018: $21.5 billion raised over 3,200 rounds
  • 2019: $24.7 billion raised over 2,500 rounds

Startups tagged within Crunchbase’s AI category raised 15% more money in 2019 compared to 2018, and in 28% fewer rounds. Zooming out a bit, it appears that money is increasingly flowing into AI startups, but investors are being more selective.
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 4.3278, Raw Interest Score: 2.1502,
Positive Sentiment: 0.0000, Negative Sentiment 0.1762

Ambarella Enables AI on Connected Cameras Using Amazon SageMaker Neo

A new press release reports, “Ambarella, Inc., an artificial intelligence (AI) vision silicon company, today announced that Ambarella and Amazon Web Services, Inc. (AWS) customers can now use Amazon SageMaker Neo to train machine learning (ML) models once and run them on any device equipped with an Ambarella CVflow®-powered AI vision system on chip (SoC). Until now, developers had to manually optimize ML models for devices based on Ambarella AI vision SoCs. This step c…
2020-01-03 08:05:43+00:00 Read the full story…
Weighted Interest Score: 3.8579, Raw Interest Score: 2.1352,
Positive Sentiment: 0.1017, Negative Sentiment 0.1017

Receipt Bank raises $73m in Series C funding

Source: Receipt Bank

Receipt Bank, the world’s leading digital bookkeeping platform, has raised $73 million (£55 million) in equity and debt in a successful Series C funding round.

The round was led by Insight Partners, joined by Augmentum Fintech with participation from existing investors Kennet Partners and Canadian Imperial Bank of Commerce (CIBC). Receipt Bank and its shareholders were advised by Harris Williams.

The funds will be used t…
2020-01-03 08:49:00 Read the full story…
Weighted Interest Score: 3.8295, Raw Interest Score: 2.3348,
Positive Sentiment: 0.3957, Negative Sentiment 0.0791

Top 11 Tools For Distributed Machine Learning

The advantages of using distributed ML models are plenty, here we list the popular toolkits and techniques that enable distributed machine learning:

  1. MapReduce and Hadoop
  2. Apache Spark
  3. Baidu AllReduce
  4. Horovod
  5. Caffe2
  6. Microsoft Cognitive Toolkit
  7. DistBelief
  8. Tensorflow
  9. DIANNE (Distributed Artificial Neural Networks)
  10. MXNet
  11. Petuum

2019-12-30 06:36:00+00:00 Read the full story…
Weighted Interest Score: 3.8079, Raw Interest Score: 2.0913,
Positive Sentiment: 0.2302, Negative Sentiment 0.1919

Natural Language Processing with Spark

This is an introductory tutorial on developing predictive machine learning models using PySpark. I am going to demonstrate the basics of Natural Language Processing (NLP) while utilizing the power of Spark. We will use PySpark; which is a Python API for Spark. The dataset for this tutorial is fetched from the ‘NLP with Disaster Tweets’ Kaggle competition. The full code is available on GitHub.

The data consists of tweets and our task is to predict which tweets are related to a disaster. This may improve the response time for several interested parties, such as Police Force, Fire Brigade or News Agencies, etc. We will be performing text classification, by building predictive machine learning models, which is a category of NLP. The following algorithms can help you get instigated in your Text Analytics or NLP endeavor and has numerous applications.
2020-01-06 05:04:27.431000+00:00 Read the full story…
Weighted Interest Score: 3.4986, Raw Interest Score: 1.9133,
Positive Sentiment: 0.0294, Negative Sentiment 0.1079

Why Machine Learning Services Are Disrupting Every Industry Across the Globe

Machine learning is having a major impact on the global marketplace. It will have a profound effect on companies of all sizes over the next few years. Artificial Intelligence is surrounding us everywhere. We cannot go with our day without approaching a solution involving AI. Machine learning is a field of Artificial Intelligence which specializes in setting machine using algorithms to learn certain things by itself.

Machine learning has a vast number of applications. We can approach machine learning systems by going out shopping, using our banking account or even in public transport. How much is machine learning changing things up? What is the demand for this new technology? One estimate pegged the global market for machine learning at $2.5 billion in 2017 and estimated that it would reach $12.3 billion less than a decade later. These estimates have been raised even higher by a newer study by Deloitte. This is proof that it is in high demand and is making a huge splash on the global marketplace.

2020-01-03 11:30:23+00:00 Read the full story…
Weighted Interest Score: 3.3008, Raw Interest Score: 1.8566,
Positive Sentiment: 0.3290, Negative Sentiment 0.0470

20 AI Predictions for 2020

It doesn’t take a soothsayer to know that artificial intelligence will have a bomber 2020. But getting the details right is important, which is why we turned to industry experts to give us their predictions on exactly how AI will evolve next year.

2019-12-30 00:00:00 Read the full story…
Weighted Interest Score: 3.2726, Raw Interest Score: 1.3809,
Positive Sentiment: 0.3077, Negative Sentiment 0.2290

2020 AI Trends for the Enterprise

In looking back at how far we’ve come in the last decade, from BI to predictive analytics to AI, one thing is for sure: 2020 will undoubtedly hold even more rapid development in the field of data science and machine learning. Aside from generally preparing AI strategies for near constant change (i.e., introducing flexibility and sustainability across technology,processes, and even people), what can enterprises expect in this new decade?

  • A Change in the Data Scientist Role Itself
  • The Essential Management of Cloud Costs
  • The Move Toward Initiative-Driven Teams

2020-01-02 00:00:00 Read the full story…
Weighted Interest Score: 3.1793, Raw Interest Score: 1.4147,
Positive Sentiment: 0.2063, Negative Sentiment 0.0884

Aurora Mobile Launches Mini Program Version of iAPP

rovides mobile internet companies and investors with real-time data and deeper insights into market trends to help them make better business decisions. The mini program version of iAPP offers various big data and analytical functions including tracking and detailed real-time data on emerging trends and dynamics of other mini programs.”

The release goes on, “Clients can easily log in and view mobile app and mini programs DAU data in real-time and sort by industry, DAU, monthly DAU growth and many other operational indicators. Leveraging Aurora Mobile’s cutting edge data analytics capabilities, clients…
2020-01-03 08:10:23+00:00 Read the full story…
Weighted Interest Score: 3.1500, Raw Interest Score: 1.6533,
Positive Sentiment: 0.6933, Negative Sentiment 0.0000

AI To Combat Sexual Harassment With Chatbots, Apps & Trained Algorithms

With artificial intelligence penetrating most industries to make communication and innovation easier, using it to fight sexual harassment could be its best move yet. According to statistics, 56% of women believe that sexual harassment at the workplace has increased over the years, and 53% of women have been subject to sexual comments, gestures, jokes at the workplace. The same study also states that close to 80% of women are…
2020-01-06 12:30:00+00:00 Read the full story…
Weighted Interest Score: 3.0846, Raw Interest Score: 1.0841,
Positive Sentiment: 0.2502, Negative Sentiment 0.8061

ML Ops: Machine Learning as an Engineering Discipline

As ML matures from research to applied business solutions, so do we need to improve the maturity of its operation processes

So, your company decided to invest in machine learning. You have a talented team of Data Scientists churning out models to solve important problems that were out of reach just a few years ago. All performance metrics are looking great, the demos cause jaws to drop and executives to ask how soon you can have a model in production.

It should be pretty quick, you think. After all, you already solved all the advanced scienc-y, math-y problems, so all that’s left is routine IT work. How hard can it be?

Pretty hard, it turns out. reports that “only 22 percent of companies using machine learning have successfully deployed a model”. What makes it so hard? And what do we need to do to improve the situation? Let’s start by looking at the root causes.
2020-01-03 21:25:45.522000+00:00 Read the full story…
Weighted Interest Score: 3.0463, Raw Interest Score: 1.7596,
Positive Sentiment: 0.1480, Negative Sentiment 0.1809

Why explainable AI is a critical business strategy (VB Live)

Not only do customers care whether AI results are explainable, but internally, white-box AI is less risky. But what does it mean in practice? And how can businesses move away from black-box systems to more explainable AI?

“It’s pretty obvious that when you don’t understand how a decision or process is made, you run the risk of making a bad decision,” says Triveni Gandhi, data scientist at Dataiku. “You can’t just expect a model to be magical and be correct every time. You need to make sure that the decisions it’s making are aligned with your stated goals, both in an ethical way and as far as underlying business value.”

2020-01-06 00:00:00 Read the full story…
Weighted Interest Score: 2.9102, Raw Interest Score: 1.0737,
Positive Sentiment: 0.2065, Negative Sentiment 0.2891

Essential Optimisation Algorithm Techniques for Deep Learning

With so many sectors making use of deep learning, the driving force — algorithms have to be efficient for the neural networks to learn faster and achieve better results. Optimisation techniques become the centrepiece of deep learning algorithms when one expects better and faster results from the neural networks, and the choice between these optimisation algorithms techniques can make a huge difference between waiting for hours or days for excellent accuracy.

With limitless applications and a wide variety of researched topics on optimisation algorithms, here we highlight a few essential points taken from a well-written paper.
2020-01-02 09:30:00+00:00 Read the full story…
Weighted Interest Score: 2.7371, Raw Interest Score: 1.3907,
Positive Sentiment: 0.2608, Negative Sentiment 0.2318

These 10 Chicago Tech Companies Raised over $700m in 2019

Chicago tech companies made some big gains this year — especially these 10, which collectively raised over $700M. Tempus topped the list with an impressive $200M, and enterprise software company Vistex took the second slot with its $105M round.

2020-01-02 00:00:00 Read the full story…
Weighted Interest Score: 2.7188, Raw Interest Score: 1.6573,
Positive Sentiment: 0.1563, Negative Sentiment 0.0313

Goldman Sachs vs. Google: Which Offers Better Pay?

Over the past several quarters, Goldman Sachs has been competing hard against Google, Facebook, and other tech giants for the best technology talent. For example, Google ramped up its recruitment for cloud architects in New York City just as Goldman Sachs began pursuing those same candidates for its Marcus retail bank and software engineering platform.

That sort of rivalry is great news for technologists with the right skills who want to work fo…
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 2.6982, Raw Interest Score: 1.8339,
Positive Sentiment: 0.1000, Negative Sentiment 0.0333

Expanding Your Data Science and Machine Learning Capabilities

Expanding Your Data Science

and Machine Learning Capabilities


Surviving and thriving with data science and machine learning means not only having the right platforms, tools and skills, but identifying use cases and implementing processes that can deliver repeatable, scalable business value. The challenges are numerous, from selecting data sets and data platfo…
2020-06-25 00:00:00 Read the full story…
Weighted Interest Score: 2.5744, Raw Interest Score: 1.7004,
Positive Sentiment: 0.2429, Negative Sentiment 0.0810

AI Weekly: Celeste Kidd on how to close the AI research gender gap

This week, VentureBeat published a collection of predictions about where machine learning is heading in 2020 from industry leaders like PyTorch creator Soumith Chintala, IBM Research director Dario Gil, Nvidia machine learning research director Anima Anandkumar, and Google AI chief Jeff Dean.

Each expert shared insights about subfields they think will make strides in the year ahead, like multitask learning and semi-supervised learning, and everyone seemed to agree that Transformer in…
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 2.5526, Raw Interest Score: 1.1873,
Positive Sentiment: 0.1696, Negative Sentiment 0.4900

Top 12 Datanami Stories of 2019

2019 was an eventful year in the big data space, with enough intersecting story lines to keep a big data watcher enmeshed for hours – if not days — on end. We did our best to trace the story lines out for you, dear reader, to help you better understand what new technology is emerging, who’s using it for what, and why.

One useful editorial exercise to do at the beginning of the year – when the news flow is rather slow — is to determine what stori…
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 2.5470, Raw Interest Score: 1.4615,
Positive Sentiment: 0.2725, Negative Sentiment 0.2477

Modern Data Warehousing: Enterprise Must-Haves

Modern Data Warehousing:

Enterprise Must-Haves


To fit into modern analytics ecosystems, legacy data warehouses must evolve – both architecturally and technologically – to deliver the agility, scalability and flexibility that business need to thrive in today’s data-driven economy. Alongside new architectural approaches, a variety of technologies have emerge…
2020-11-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5448, Raw Interest Score: 1.6053,
Positive Sentiment: 0.0944, Negative Sentiment 0.0000

Data Lake Modernization for Speed, Scale and Agility


Data lake adoption has more than doubled over the past three years. Currently in use by 45% of DBTA subscribers to support data science, data discovery and real-time analytics initiatives, data lakes are still underpinned by Hadoop in many cases, although cloud-native approaches are on the rise. The technologies and best practices surrounding data lakes continue to evolve, as well as the challenges, from data governance and security, to integration and architecture. Join us for a special roundtable webinar on March 19th to learn …
2020-03-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5355, Raw Interest Score: 1.6227,
Positive Sentiment: 0.2028, Negative Sentiment 0.1014

Unlocking the Power of DataOps

DBTA ROUNDTABLE WEBINAR THURSDAY, MAY 7, 2020 – 11:00 am PT / 2:00 pm ET

A new methodology is on the rise at insights-hungry enterprises looking to bring improved quality and reduced cycle times to data analytics. Borrowing from Agile Development, DevOps and statistical process control, DataOps is poised to revolutionize data analytics with its eye on the entire data lifecycle, from data preparation, to reporting. However, improving the flow of data between managers and consumers within an organization through greater communication, integration and automation is no simple task, and it requires cultural ch…
2020-05-07 00:00:00 Read the full story…
Weighted Interest Score: 2.5234, Raw Interest Score: 1.4953,
Positive Sentiment: 0.6542, Negative Sentiment 0.0000

Cars Careening Out-of-Control In Crash Mode: The Case Of AI Autonomous Cars

By Lance Eliot, the AI Trends Insider


While innocently sitting at a red light, a car rammed into the rear of my car. I was not expecting it.

Things began to happen so quickly that I barely remember what actually did happen once the crash began.

Within just a few brisk seconds, my car was pushed into a car ahead of me, ripping the back and left-side of my car. The gas tank ruptured and gasoline leaked onto the ground, my airbag deployed, …
2020-01-02 22:30:24+00:00 Read the full story…
Weighted Interest Score: 2.4513, Raw Interest Score: 0.7466,
Positive Sentiment: 0.1109, Negative Sentiment 0.3584

3 Recent IPOs to Watch in 2020

Investing in small new companies is always a gut-wrenching endeavor requiring discipline and patience — 2019 was proof of that. In a tale of two markets, IPOs could seemingly do no wrong through the first half of the year as investors greeted them with open arms and asked few questions. The resulting inflated valuations on many of these stocks reversed course starting in the autumn, though, with many recent IPOs now back near or under their publ…
2020-01-05 00:00:00 Read the full story…
Weighted Interest Score: 2.4211, Raw Interest Score: 1.4194,
Positive Sentiment: 0.1607, Negative Sentiment 0.1071

Data Management Best Practices for Machine Learning

Data Management Best Practices

for Machine Learning


Machine learning is on the rise at businesses hungry for greater automation and intelligence with use cases spreading across industries. A recent study fielded amongst the subscribers of Database Trends and Applications found that 48% currently have machine learning initiatives underway with another 20% cons…
2020-01-23 00:00:00 Read the full story…
Weighted Interest Score: 2.3850, Raw Interest Score: 1.8900,
Positive Sentiment: 0.4296, Negative Sentiment 0.0000

Ethical Hurdles of Combating Racially Biased Police Algorithms

Ethical Hurdles of Combating Racially Biased Police Algorithms

Adjusting the weight of variables for algorithms used in criminal justice could be promising, or problematic.

Cincinnati City Councilman Jeff Pastor (Photo: Kareem Elgazzar/The Enquirer, originally featured on

At the conclusion of the 2019 calendar year, Jeff Pastor, Councilman for the City of Cincinnati, Ohio, called for a sweeping review of the city’s racial dispa…
2020-01-06 08:23:42.836000+00:00 Read the full story…
Weighted Interest Score: 2.3502, Raw Interest Score: 1.0889,
Positive Sentiment: 0.0863, Negative Sentiment 0.5391

Investor predictions for 2020: Venture capitalists on what to watch for and how startups should prepare

2019 was an extraordinary year for the Seattle tech ecosystem and broader global innovation economy. But with the growth of Amazon and Microsoft, a bubbling startup scene across the Pacific Northwest, and a pivotal election upcoming, 2020 could be even crazier.

As per GeekWire annual tradition, we caught up with five venture capitalists to get their predictions for the coming year. The investors are closely watching tech trends, as they all plan…
2020-01-02 18:31:53+00:00 Read the full story…
Weighted Interest Score: 2.1902, Raw Interest Score: 1.1530,
Positive Sentiment: 0.1779, Negative Sentiment 0.1318

Construction tech is looking to disrupt an industry that’s been notoriously slow to embrace change — insiders say these are the 10 contech startups to watch in 2020

uction labor costs continue to increase and construction productivity has been flat for decades. These forces have created demand for cheaper construction, leading to the application of new tech like machine learning, robotics, 3D-imaging, and drones.

While the sector hasn’t seen nearly as much attention as fintech or its cousin, proptech, it has received $27 billion in funding since 2008, according to McKinsey partner Jose Luis Blanco. There are two contech unicorns — Procore and Katerra.

We’ve polled construction tech experts, VCs, and analysts to create a list of 10 of the hottest contech startups to wat…
2020-01-04 00:00:00 Read the full story…
Weighted Interest Score: 2.1531, Raw Interest Score: 1.3578,
Positive Sentiment: 0.1997, Negative Sentiment 0.0399

How CEOs Can Navigate the Muddying Waters of Data Privacy Regulation

This has been a banner year for cybersecurity crime, with hackers targeting consumers, government agencies, and private corporations alike. According to the Ponemon Institute, the average total cost of a data breach is $3.86 million, and 80% of U.S. businesses expect that they will have had a critical breach this year. These numbers are not only sizable; they’re alarming.

Top executives have reason to be concerned. New data privacy mandates such…
2019-12-30 00:00:00 Read the full story…
Weighted Interest Score: 2.1369, Raw Interest Score: 1.2417,
Positive Sentiment: 0.1155, Negative Sentiment 0.4909

Create Your Own Data Science Curriculum

fied under the data science umbrella. Each of these roles will differ in terms of the skill sets needed and in particular the depth of knowledge required for certain skills.

For example, the role of machine learning engineer will require a deep knowledge of programming and data engineering so the focus for your curriculum for this type of role will lie closer to the software engineering skillset. Whereas a research data scientist working on new algorithms and techniques will require more extensive knowledge of mathematics and statistical concepts.

It is therefore vital to determine upfront the area of data …
2020-01-05 18:42:25.516000+00:00 Read the full story…
Weighted Interest Score: 2.1367, Raw Interest Score: 1.2916,
Positive Sentiment: 0.3176, Negative Sentiment 0.0635

Here’s exactly how to check if your company’s AI is as advanced as you think it is, from the engineer pushing GM’s driverless-car unit Cruise

Artificial intelligence has the potential to completely change how companies like Walmart and McDonald’s operate, but one challenge can be figuring out how well early-stage projects are advancing.

Hussein Mehanna, the head of artificial intelligence and machine learning at Cruise, says a key metric is how many models an organization is testing in a given month.

While he declined to say how many the self-driving-car co…
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 2.1167, Raw Interest Score: 1.3956,
Positive Sentiment: 0.0607, Negative Sentiment 0.2124

Tech’s extraordinary decade: What mattered most in the past 10 years of innovation

the challenges created by technology over the past 10 years, it struck me that it would be worth sharing my list here, to add context and a different perspective.

Here’s my list.

Machine learning, artificial intelligence.

Breakthroughs in speech recognition and computer vision.

Ascendance of Big Tech’s new guard: Facebook, Google, Snapchat, Twitter, etc.

Amazon 3.0: Everything Store becomes Everything Company.

Microsoft’s surprising renaissance.

U.S. vs. China, new innovation race.

Recognition of diversity, equity and inclusion in shaping next generation of technology.

Security reckoning, real-world conseq…
2020-01-01 17:25:48+00:00 Read the full story…
Weighted Interest Score: 2.1095, Raw Interest Score: 1.3722,
Positive Sentiment: 0.1715, Negative Sentiment 0.1715

The Inextricable Link Between Data Security and End-of-Life IT Equipment

The accelerated development of data privacy regulations such as Europe’s GDPR (General Data Protection Regulation of 2018) and the CCPA (California Consumer Privacy Act), which took effect Jan. 1, along with the increase in widely reported data breaches and the resulting fines means that data privacy and security and regulatory compliance are high-profile issues for enterprises across the globe.

Growing concerns pushed organizations to invest 10…
2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 2.1064, Raw Interest Score: 1.2175,
Positive Sentiment: 0.1642, Negative Sentiment 0.5335

Database Management Today: New Strategies and Technologies

Database Management Today:

New Strategies and Technologies


From machine learning and automation, to hybrid and multicloud environments, technology trends continue to reshape the practice of database management. As a result, database professionals face new challenges and opportunities. Today, the average database team is tasked with managing more databases, bigger databases and a greater variety of databases – on-premises and in the cloud. At the same time, businesses are hung…
2020-04-09 00:00:00 Read the full story…
Weighted Interest Score: 2.0886, Raw Interest Score: 1.5063,
Positive Sentiment: 0.3347, Negative Sentiment 0.0837

Samsung’s ‘artificial human’ looks stunningly real; To mesmerize crowds at CES 2020 on Jan 7

A Samsung subsidiary named STAR Labs has been developing what is called ‘Neon,’ which is an artificial human project. As per the reports, the South Korean company is working on a realistic human avatar that will have a multipurpose use.

Recently a tweet which included some leaked videos which almost verified that the company is working on this mysterious project which is expected to be unveiled at CES 2020 this week.

Samsung’s Neon project

As …
2020-01-07 00:00:00 Read the full story…
Weighted Interest Score: 2.0847, Raw Interest Score: 1.1100,
Positive Sentiment: 0.0336, Negative Sentiment 0.1345

What Are Plug and Play Language Models

“Recycling is good for the world. NO! YOU COULD NOT BE MORE WRONG!!” When OpenAI’s GPT model was prompted with the above sentence, it completed with the following:

“Recycling is good for the world. NO! YOU COULD NOT BE MORE WRONG!!” Let me explain why. Recycling takes time, money and energy, and it doesn’t really solve the problem, and that’s because recycling is all about selling to customers who cannot afford to recycle. If you don’t have an…
2020-01-02 13:30:00+00:00 Read the full story…
Weighted Interest Score: 1.9897, Raw Interest Score: 1.2440,
Positive Sentiment: 0.3649, Negative Sentiment 0.2156

Google’s DeepMind A.I. beats doctors in breast cancer screening trial

Artificial Intelligence (AI) powered by Google’s DeepMind algorithm may be more accurate at spotting breast cancer than real life doctors.

The findings, published in on Wednesday, come after researchers from Imperial College London and Google Health “trained” a computer to spot abnormalities on X-ray images of nearly 29,000 women.

Separate studies used imagery from U.K. and U.S. women and concluded that in …
2020-01-02 00:00:00 Read the full story…
Weighted Interest Score: 1.9812, Raw Interest Score: 1.0955,
Positive Sentiment: 0.3130, Negative Sentiment 0.4695

How Spotify’s Algorithm Manages To Find Your Inner Groove

Have you ever wondered how Spotify manages to recommend you that perfect song, playlist or even that ‘daily mix’?

The answer is simple — data.

Spotify’s algorithm is always finding new ways to understand the kind of music one listens to — from the songs that are always on repeat to the favourite genre that one can’t let go.

Not only is the algorithm monitoring the music history but also analyses the reason behind a person listening to a pa…
2020-01-06 11:30:00+00:00 Read the full story…
Weighted Interest Score: 1.9543, Raw Interest Score: 0.7311,
Positive Sentiment: 0.1791, Negative Sentiment 0.1641

Ambarella unveils new AI chips for automotive cameras and driver assistance

Chip designer Ambarella has announced two new chips for automotive cameras and advanced driver assistance systems (ADAS) based on its CVflow architecture for artificial intelligence processing. The Santa Clara, California-based company unveiled the CV22FS and CV2FS automotive camera system-on-chips (SoCs) with CVflow AI processing and ASIL-B compliance to enable safety-critical applications.

Ambarella will also demo applications with its existing chips — as well as a robotics platform and Amazon SageMaker Neo technology for training machine-learning models — at CES 2020, th…
2020-01-06 00:00:00 Read the full story…
Weighted Interest Score: 1.9413, Raw Interest Score: 1.2665,
Positive Sentiment: 0.0507, Negative Sentiment 0.0844

Google AI system beats doctors in detection tests for breast cancer

New York | Google Health has developed a system that can identify breast cancer more accurately than radiologists, in the latest sign that artificial intelligence could improve early detection of disease in images.

In a paper published in the scientific journal Nature, experts from Google Health, Alphabet’s DeepMind unit, and UK and US universities showed the AI model reduced both false positives, in which patients are wrongly told they have cancer, as well as false negatives, where the disease is present but not diagnosed.

Screening mammograms is known …
2020-01-02 00:00:00 Read the full story…
Weighted Interest Score: 1.8686, Raw Interest Score: 1.2070,
Positive Sentiment: 0.3018, Negative Sentiment 0.2414

AI inventor rejected by British and European patent authorities in landmark case

The world’s first “AI inventor” has been denied recognition by patent authorities in the UK and Europe.

A nine-strong squad of international legal experts is battling for designs conceived by artificial intelligence to be recognised in law, and has filed patent applications on its behalf around the world.

The UK Intellectual Property Office said it was “right [that changes to the law around AI-designed patents] be debated more widely”.

The landmark case has highlighted growing anxieties among lawmakers about the role of machines in the creative process internationally.

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2020-01-03 00:00:00 Read the full story…
Weighted Interest Score: 1.8373, Raw Interest Score: 1.1159,
Positive Sentiment: 0.4923, Negative Sentiment 0.3610

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