FINTECH

FINTECH, short for Financial Technology, describes the emerging technology applied to financial services including trading, investments, banking, and marketplaces including current exchanges and new alternative marketplaces. FINTECH covers innovations that are rapidly changing all aspects of the front office, middle office, and back office. CloudQuant is considered a FINTECH company as we are bringing crowdsourcing to algorithmic trading. Other FINTECH innovations include cryptocurrencies, machine learning, and deep learning applications.

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Alternative Data. 21, June 2018

Finding sources and uses for alternative data can be difficult. At CloudQuant we regularly read and search the internet for new sources of data that can be used in our mission to find alpha signals and build quantitative trading strategies. We recognize that we are technology and data junkies so we wrote our own crawler that specifically seeks out web pages, posts, and news articles that give us a snapshot of what is going on in the world of Alt Data. The following is a collection of articles that we think you will find interesting from the past week.

Alt Data Moves Beyond Front Office

Alternative data is commonly perceived as the grist of trading desks, where real-time information on breaking events gives a leg up to quick-profit trades. But more areas of the enterprise are leveraging Twitter and other social-media feeds that have emerged as the de facto modern-day newswire. The functions within the corporation may be different, but the underlying value proposition is the same — to benefit fr… 2018-06-13 17:32:02-04:00 Read the full story.

TRADING UP: Nasdaq Promotes Dague; Masoudi to JPM

Nasdaq has promoted Bill Dague to head of alternative data for its Global Information Services business, including responsibility for the exchange’s Analytics Hub of third-party and alternative datasets. Dague has spent four years at Nasdaq, most recently as director of data science, having also served as a senior data scientist and a software engineer since joining the exchange as a software engineer intern in 2014. Before Nasdaq, Dague was a junior pro… 2018-06-18 09:37:05-04:00 Read the full story. stock exchange evolution panel

Deutsche Bank’s analyst warns about GDPR posing risks to AI development in Europe

As the development of AI systems based on machine learning heavily relies on access to vast datasets, GDPR may restrict this access and hamper the development of AI in Europe, says Deutsche Bank’s Kevin Koerner. Less than a month after GDPR – the new data protection regulation, came into force across the European Union (EU), the effects for the business and the general public start to become clearer. The chorus of concerns about the potentially negative consequences of the implementation is gr… 2018-06-14 09:13:18+03:00 Read the full story.

BT Works With Fintech For Data Sharing Services

BT announced the availability of ipushpull’s live data sharing and collaboration services to members of the BT Radianz Cloud, one of the world’s largest, secure networked financial communities. ipushpull, a London-based fintech, provides financial markets firms with secure cloud-based data and document sharing services to help speed up decision making, boost productivity and improve efficiency. Its platform allows real-time data to be securely a… 2018-06-20 05:09:22-04:00 Read the full story.

Back Offices Migrate to ‘Data First’ Architecture

Some asset managers are finding the silver lining in the U.S. Securities and Exchange Commission’s N-PORT and N-CEN reporting regimes, according to industry insiders. “When you think of what it takes to create a filing for a regulator and what it takes to create a filing or a report for an investor, there is not that much difference between them besides form, look and feel, and output,” Todd Moyer, COO of Confluence, told Markets Media. “A lot o… 2018-06-11 16:48:55-04:00 Read the full story.    
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
stock exchange evolution panel

AI & Machine Learning News. 04, June 2018

Google Smart Compose, Machine Bias, Racist AI — Summarising One Night of Binge Reading from Blogs

After Sundar Pichai took the stage and began his Google I/O 2018’s keynote, I started to take a note of interesting things that were being announced and demoed. There were some very interesting demos and announcements, especially for those who are into Deep Learning. I was curious about Gmail’s Smart Compose and Google Duplex besides other things, both of these being use cases of Natural Language Processing. Google Duplex got a lot of attention which was not surprising since the conversation made by Google Assistant with a real human sounded seamless and also human-like. If you are into Deep Learning, you would surely want to know at least a bit about how these are done and Google’s Research blog is a good place to know more. And just in case you didn’t know, ai.googleblog.com is Google’s new research blog! 2018-06-03 05:06:39.713000+00:00 Read the full story.  

The tangled relationship between AI and human rights

It was a pleasant 21 degrees in New York when computers defeated humanity — or so many people thought. That Sunday in May 1997, Garry Kasparov, a prodigal chess grandmaster and world champion, was beaten by Deep Blue, a rather unassuming black rectangular computer developed by IBM. In the popular imagination, it seemed like humanity had crossed a threshold — a machine had defeated one of the most intelligent people on the planet at one of the most intellectually challenging games we know. The age of AI was upon us. Or perhaps not. 2018-06-01 00:00:00 Read the full story. CloudQuant Thoughts… Two interesting stories, both touching on AI and the bias that it inherits from us humans. Both well worth reading.  

Here Is IBM’s Blueprint For Winning The AI Race

One of the cornerstones of International Business Machines’ (NYSE:IBM) ongoing transformation is cognitive computing, which encompasses artificial intelligence and other related technologies. IBM is a business that serves other businesses, and its approach to artificial intelligence (AI) stays true to its purpose. IBM Watson, the company’s well-known AI system, is being used in industries like healthcare and financial services to augment the skills of professionals in those fields. The long-term potential of the technology is immense. 2018-06-03 01:21:24-04:00 Read the full story. CloudQuant Thoughts… Disregard Old Blue’s impact on AI at your peril, they have been at the forefront of all “computer” development for over 100 years and their Watson team is still at the forefront of AI development.  

What to expect at Monday’s Apple event

Apple is expected to launch an exciting new iPhone feature to address a problem it helped create: phone addiction. CEO Tim Cook will announce the company’s latest software updates and roadmap for the future on Monday at the Apple’s annual developer conference in San Jose. WWDC is a software-focused event for developers, and this year Apple isn’t expected to make any major hardware announcements.
  • Operating system updates
  • Tools for cutting down on phone use
  • More iOS updates
  • Siri could use some good news
  • iPhone apps on a Mac
  • Light privacy bragging
2018-06-03 00:00:00 Read the full story.

Headlines already from the Apple event

Apple announced Core ML 2, a new version of its suite of machine learning apps for iOS devices, at the Worldwide Developer Conference (WWDC) 2018 in San Jose, California today. Core ML 2 is 30 percent faster, Apple says, thanks to using a technique called batch prediction. Furthermore, Apple shared the toolkit will let developers shrink the size of trained machine learning models by up to 75 percent with quantization. 2018-06-04 00:00:00 Read the full story

Where Apple Could Crush the Autonomous-Driving Race

Last week, we reported on the autonomous-driving partnership between Apple Inc. (AAPL) and Volkswagen (VLKAY) . Despite being two of the largest companies in their respective industries, the current partnership is rather dismissable. As it stands, Volkswagen is producing T6 Transporter vans, which Apple is using to retrofit with its self-driving sensors and software. It’s not for commercial development or consumer use — at least not yet. It will be used to transport Apple employees between its headquarters. Even that project is unlikely to be finished this year, according to sources. While Apple and Volkswagen could build to a more meaningful partnership, it’s been slow going. 2018-05-30 14:46:54-04:00 Read the full story. CloudQuant Thoughts… Three articles on Apple, another old hand in today’s fast-moving tech industry but whilst they are rarely first to the party they are often best and their ongoing targeting of  the “cream” of each user base has delivered consistent returns.  

Google will end Project Maven military contract in 2019

Google is ending its involvement with Project Maven, the controversial Pentagon research program that sought to use AI to improve object recognition in military drones. Diane Greene, head of Google Cloud, told employees during a Friday meeting that the company will let its current contract with the Defense Department lapse in 2019 and that it will not pursue a new one, according to the New York Times and Gizmodo. The announcement comes shortly after Google said it would draft an ethics policy to guide its involvement in future military projects — one that would explicitly ban the use of artificial intelligence in weaponry. 2018-06-01 00:00:00 Read the full story at Venturebeat. Read the full story at CNN.  Read the full story at GeekWire. Read the full story at the New York Times. CloudQuant Thoughts… I have never seen such a widely reported AI story. Everyone covered this one!  

Nvidia HGX-2 Server Platform Targets HPC, AI Workloads

More than a decade ago, Nvidia executives championed general-purpose GPUs as accelerators for high-performance computing workloads. They would complement processors to enable servers to accelerate application performance while keeping a lid on power consumption. Now, at a time when modern workloads are demanding even more compute power, the company is continuing to position GPUs as the primary computing engine. At Nvidia’s GTC show in Taiwan, CEO Jensen Huang unveiled the HGX-2, a server platform designed to address the needs of both high-performance computing (HPC) and artificial intelligence (AI) workloads. The platform includes 16 of Nvidia’s Tesla V100 Tensor Core GPUs that are linked via the company’s NVSwitch interconnect fabric, which essentially enables the 16 graphics engines to work as a single GPU. The first system to leverage the HGX-2 platform was Nvidia’s upcoming DGX-2, which delivers up to 2 petaflops of performance and 512GB of HBM2 high-bandwidth memory, according to company officials. 2018-05-30 00:00:00 Read the full story. CloudQuant Thoughts… Amazing power! But Can It Run Doom?
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BlueData Introduces Turnkey Solution for AI and Machine Learning

BlueData, provider of a big-data-as-a-service (BDaaS) software platform, has launched a new solution to accelerate deployment of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in the enterprise. The BlueData AI/ML Accelerator solution includes software and professional services to deploy containerized multi-node sandbox environments for exploratory use cases with TensorFlow and other ML/DL tools. According to BlueData, AI and ML/DL have moved into the mainstream with a broad range of data-driven enterprise applications such as credit card fraud detection, stock market prediction for financial trading, credit risk modeling for insurance, genomics and precision medicine, disease detection and diagnosis, natural language processing (NLP) for customer service, autonomous driving and connected car IoT use cases, and more. 2018-05-31 00:00:00 Read the full story.  

Automating Customer Support With Human-Like Virtual Agents (Interview with Rachael Rekart of Autodesk)

Today, we sit down with Rachael Rekart, as she shares her insights on the process of developing a successful conversational agent for customer engagement. Watch the interview to learn:
  • The development process for AVA, Autodesk’s customer support assistant, and her advice for selecting a budget, software support, and design philosophy for startup teams looking to implement their own conversational agents.
  • Lessons gleaned from observing the differences in how customers behave with a human assistant versus an automated assistant.
  • Advice on the types of expertise that you’ll need when assembling a team to build and support an effective conversational agent for your company.
2018-06-01 06:35:25+00:00 Read the full story.  

Looker Boosts Data Science Capabilities in Latest Platform Release

Looker, a data platform provider, is releasing new tools and integrations to optimize data science workflows. Looker is improving its governed data workflow with an SDK for R and connections for Python, as well as streamed and merged results, Google TensorFlow integrations, and clean, visual recommendations for users. “We’re focused on preparation that happens which a lot of research will tell you takes up 70-80% of data scientists time and the operationalization piece that comes after,” said Daniel Mintz, chief data scientist at Looker. “What we’re really focused on is saving data scientists’ time and increasing their accuracy by helping them access data across their organization in a governed and version-controlled environment so what they feed into their models is correct and leverages everybody’s knowledge in the organization.” 2018-05-30 00:00:00 Read the full story.  

How To Use Data & Predictive Analytics To Design Promotions For Brick-&-Mortar Stores

Traditional brick-and-mortar (B&M) stores are under immense pressure due to the threat from Amazon and are often trying to compete by putting many products on attractive promotions. While Amazon uses sophisticated predictive analysis to personalize their marketing strategies and promotions, most brick-and-mortar stores do not have the resources to experiment and learn. In fact, 30% of promotions run by B&M stores could be toxic – making less money than the baseline situation. This happens when the margin depletion due to discounting is not adequately made up by a sales lift. 2018-06-04 10:13:34+00:00 Read the full story.  

BlueData Invites AI/ML Developers to Play in Its BDaaS Sandbox

Kids love to play in physical sandboxes. Developers love to “play” in virtual sandboxes. BlueData, which offers a new-gen big-data-as-a-service (BDaaS) software platform, has made available a new environment for AI and machine-learning developers to try out new ideas and have fun testing them. This is a new turnkey package that enables accelerated deployment of artificial intelligence, machine learning and deep learning applications in the enterprise. Turns out you can’t build these applications too quickly. They’re too much in demand from all sectors of the IT world. And once one is up and running, the next one is ready to come into action. 2018-06-01 00:00:00 Read the full story.  

6 New AI Features In Android P That Will Make Your Smartphone Even Smarter

At this years I/O Developers Conference, Google gave us the first glimpse of the new features that will come with the next version of its mobile operating system. With Android P, Google has put artificial intelligence and machine learning at the core of its operating system and focuses on digital wellbeing and simplicity. This AI-powered OS will dramatically change the way we use our smartphones. “Android P makes a smartphone smarter, helping it learn from and adapt to the user. Your apps can take advantage of the latest in machine intelligence to help you reach more users and offer new kinds of experiences,” Google said in a blog post. Let’s take a look at the brand new AI-powered features that are coming to Google’s latest mobile operating system Android P… 2018-06-01 05:07:42+00:00 Read the full story.  

Why Data Scientists Shouldn’t Rely More On P-Values In ML Experiments

Statistical concepts go hand-in-hand with machine learning, but may not always fulfill capabilities to the latter. At times, machine learning models cannot perform better if certain statistical revisions are made in them. Then again, it is open to interpretation and depends on the problem which the ML algorithms aim to solve. In this article, we consider a specific case called ‘p-values’ in statistics and discuss how it affects machine learning in general. 2018-06-01 04:54:34+00:00 Read the full story.  

Policy Gradients in a Nutshell – Towards Data Science

Reinforcement Learning (RL) refers to both the learning problem and the sub-field of machine learning which has lately been in the news for great reasons. RL based systems have now beaten world champions of Go, helped operate datacenters better and mastered a wide variety of Atari games. The research community is seeing many more promising results. With enough motivation, let us now take a look at the Reinforcement Learning problem. 2018-06-02 21:46:22.782000+00:00 Read the full story.  

Meet MIUI 10, Xiaomi’s New Artificial Intelligence-Enabled Interface

Chinese internet giant Xiaomi on Thursday launched their latest version of the MIUI interface, called the MIUI 10. They launched it along with their newest smartphone Mi 8, which runs on the MIUI 10 operating system Interestingly, artificial intelligence is one of the key components of the MIUI 10 operating system. Some of the AI features include AI Portrait which offers a software feature to allow phones to take photos with the bokeh effect without needing dual cameras. MIUI 10-powered phones will be able to use algorithms to identify the foreground and blur the background. 2018-06-01 13:13:48+00:00 Read the full story.  

June Edition: Probability, Statistics & Machine Learning – 10 must read articles

 
  • Probability concepts explained (Intro, Maximum likelihood estimation, Bayesian inference for parameter estimation).
  • The 10 Statistical Techniques Data Scientists Need to Master
  • Statistics for people in a hurry
  • Data science concepts you need to know!
  • Beyond Accuracy: Precision and Recall
  • Stranger Things: Five lessons for analyzing and communicating data
  • How To Ace Data Science Interviews: Statistics
  • On Average, You’re Using the Wrong Average
  • A One-Stop Shop for Principal Component Analysis
  • Interpreting machine learning models
2018-06-01 16:42:42.393000+00:00 Read the full story.  

How To Get Google Lens And Which Smartphones Are Compatible?

Google Lens was one of the company’s biggest announcements in 2017, and they have greatly expanded which phones have Google Lens after an initial launch exclusive to the Pixel. We detail how to get Google Lens if it works on your phone and how to start using the features. Google Lens is an AI-powered tech that combines your smartphone camera and deep machine learning to both detect an object and understand what it’s seeing. After recognizing an object, it can give you contextual actions based on what you see, and learning how to get Google Lens on your phone may help you be able to take advantage of these excellent conveniences – even if you don’t have a Pixel phone. 2018-06-01 14:50:00-04:00 Read the full story.  

Top 5 Deep Learning Research Papers You Must Read In 2018

Research work in Deep Learning (DL) has taken an innovative stance. Rather than using it to better AI and ML technologies, DL research is seeing new ideas being explored in critical areas such as healthcare and banking. We have listed down the top research papers on DL which are worth reading and have an interesting take on the subject. These papers were published in the recently concluded International Conference on Learning Representations in Vancouver, Canada, in May 2018.
  • Spherical CNNs
  • Can Recurrent Neural Networks Warp Time?
  • Learning How To Explain Neural Networks: PatternNet And PatternAttribution
  • Lifelong Learning With Dynamically Expandable Networks
  • Wasserstein Auto-Encoders
2018-05-29 11:22:26+00:00 Read the full story.  

10 ambitious predictions for how VR/AR will shape our world

Last week I will joined hundreds of commercial VR and AR experts in London to participate in VR World 2018. The two-day conference featured sessions from industry leaders pioneering immersive technology in such fields as manufacturing, automotive, entertainment, healthcare, and many others. One of the benefits of bringing together VR and AR industry leaders is to facilitate collaboration and work together on a unified vision for this new technology. 2018-06-02 00:00:00 Read the full story.  

Why hasn’t big tech cleaned up its mess?

The extraordinary backlash against big tech is rooted in three basic issues that have upset consumers:
  1. Unwittingly giving foreign hackers (and private individuals as well as companies) the tools to attack the bedrock of our democracy
  2. Turning the Internet into a giant echo chamber, reinforcing the biases of users and shielding them from other points of view
  3. Exploiting user data to become a commodity without making people aware of (or giving them the ability to understand) what is going on.
The obvious solution for big tech is to re-establish public trust by solving these problems. So why aren’t they fixed yet? Protecting user privacy — as well as preventing election interference — isn’t just a matter of accepting lower profits. Facebook, Twitter, Google, and other tech giants face huge technical challenges along with user resistance as they try to close Pandora’s box. Here, specifically, are the three main barriers to fixing the trust problem… 2018-06-03 00:00:00 Read the full story.  

3 Stocks to Buy and Hold for 50 Years

Let’s get this out of the way right up front: I don’t think there is any stock that you can buy and simply ignore for decades. The pace of technological innovation, changing consumer habits, and demographic shifts all make this virtually impossible. That said, there are companies with advantages making them likely not only to still be in your portfolio in your golden years, but also to continue to produce market-beating returns. Alphabet made its fortunes on the back of Google’s search leadership — and the company still controls an estimated 90% of the worldwide search market. This sheer dominance has made the company one of the leaders in online advertising, with an estimated 39% of the digital ad market in the U.S. last year. It also provided Alphabet with plenty of cash to invest in emerging technologies, the largest of which is artificial intelligence. One of the most visible demonstrations of Google’s AI investment is its self-driving-car spin-off Waymo. The company has driven more than 6 million miles on public roads, and more than 2.7 billion simulated miles last year alone. 2018-06-03 00:00:00 Read the full story.  

Nvidia launches Isaac robot platform with Jetson Xavier robot processor

Nvidia launched its Nvidia Isaac robot platform today to power the next generation of autonomous machines, bringing artificial intelligence capabilities to robots for manufacturing, logistics, agriculture, construction, and many other industries. Launched at Computex 2018 in Taiwan by Nvidia CEO Jensen Huang, the Nvidia Isaac platform includes new hardware, software, and a virtual-world robot simulator that makes it easy for developers to create new kinds of robots. 2018-06-04 00:00:00 Read the full story.  

Must know Information Theory concepts in Deep Learning (AI)

Information theory is an important field that has made significant contribution to deep learning and AI, and yet is unknown to many. Information theory can be seen as a sophisticated amalgamation of basic building blocks of deep learning: calculus, probability and statistics. Some examples of concepts in AI that come from Information theory or related fields:
  • Popular cross-entropy loss function
  • Building decision trees on basis of maximum information gain
  • Viterbi algorithm widely used in NLP and Speech
  • Concept of encoder-decoder popularly used in Machine Translation RNNs and various other type of models
2018-06-03 14:15:47.242000+00:00 Read the full story.  

Google and Amazon back CTRL Labs, SenseTime raises $620 million

 
  • SenseTime, the Chinese A.I. start-up, raised $620 million not even two months after closing a $600 million round.
  • Daimler led a $175 funding round for Taxify, a rival to Uber and Lyft that is operating a ride-hailing service in Europe and Africa.
  • CTRL-labs raised $28 million for wearable tech that would allow people to mentally control computers or other devices.
2018-06-01 00:00:00 Read the full story.  

3 Autonomous-Driving Chip Stocks That Look Ready to Rally

Self-driving cars can’t seem to stay out of the news these days for all the wrong reasons. But it’s becoming increasingly clear that autonomous vehicles are the future of personal transport – and that the future is coming fast. That, in turn, is driving attention to the big companies that have equally big exposure to the self-driving vehicle trend. One of the best ways to play the autonomous vehicle trend right now is with the chipmakers. The companies that make the “brains” behind self-driving cars own some of the most defensible intellectual property in the space right now. And beyond exposure to existing self-driving car programs, partnering with chipmakers provides a way for the scores of carmakers playing catch-up on their self-driving car tech to accelerate their pace. 2018-05-30 19:02:42-04:00 Read the full story.  

Skully COO Reveals the Future of Smart Technology and Motorcycles

Motorcycle riding season is getting underway — and there’s a giant cloud hanging over the industry. It’s the question everyone has been asking: ‘Will millennials start riding and (more importantly) start buying motorcycles again?” Well, the jury is still out. But, there are some interesting things happening in the industry that make me hopeful, especially when it comes to augmented reality and artificial intelligence. Meet Skully Technologies, an augmented reality, artificial intelligence, wearable tech company. Its first product is a motorcycle helmet that has augmented reality and artificial intelligence features. It’s called the Skully Fenix AR. Riders will get their hands on it later this summer at a price point of $1,899. 2018-06-03 08:20:00-04:00 Read the full story.  

Surging Demand Drives Record Q1 Revenue Growth for Server Makers: IDC

The global server market is continuing to expand, driven by a broad range of factors including demand from large cloud service providers to the rise of modern workloads such as artificial intelligence and analytics. Established server original equipment manufacturers (OEMs) such as Dell and Hewett Packard Enterprise as well are original design manufacturers (ODMs) are handling much of the demand from the largest hyperscale cloud services. 2018-05-31 00:00:00 Read the full story.  

Japan looks to launch driverless car system in Tokyo by 2020

TOKYO (Reuters) – A self-driving car service could be on Tokyo’s public roads in time for the 2020 Olympics as Japan looks to drive investment in new technology to drive economic growth, according to a government strategic review announced on Monday. 2018-06-04 08:21:54+00:00 Read the full story.  

HTC Unveils DeepQ AI Platform For Hospitals, Manufacturers

HTC has unveiled its DeepQ artificial intelligence platform that’s designed for healthcare units and manufacturers. The company has also revealed that the platform is getting AR/VR integration by next year. Digitimes reported Friday that HTC’s healthcare division, called DeepQ, has launched an AI platform of the same name. According to the Taiwanese firm, the new platform is primarily designed for hospitals and manufacturing enterprises. 2018-06-01 10:59:21-04:00 Read the full story.  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
John "Morgan" Slade

RavenPack – The State of Machine Intelligence in Capital Markets

CloudQuant CEO Morgan Slade participated in a Discussion on the State of Machine Intelligence in Capital Markets at the RavenPack Symposium in London in April 2018 – Video below. The financial sector is making a massive shift towards machine intelligence in capital markets. This panel shares their experience in using data science and domain expertise in understanding data context. With attendance exceeding 250 buy-side professionals at the London Big Data and Machine Learning Revolution in April 2018, RavenPack Research Symposium is the “must attend event” for quantitative investors and financial professionals that are serious about Big Data.  
Trevor Trinkino Quantitative Trader

Machine Learning FXCM Webinar with Trevor Trinkino of CloudQuant – Part 3/3

This morning (May 29th 2018) Trevor Trinkino presented the final part of his three-part Machine Learning webinar in co-operation with FXCM. Part one is here. Part two is here. In this series, quantitative trader Trevor Trinkino will walk you through a step-by-step introductory process for implementing machine learning and how you can turn this into a trading algorithm using Python. Plus he will show you the process of tuning your parameters for better performance of your trading system. This week we look at some of the main hyper-parameters in the Random Forest and Gradient Boosted Decision Tree algorithms and cover how to quickly tune them. Then we also spend some time briefly looking over a LSTM neural network and the applicable code in Tensorflow. Finally, we will discuss how to import the tuned machine learning model into our back-testing or live-trading environments. Files mentioned in the video are available from our Google Drive below.. Jupyter Notebook : Machine Learning Tutorial.ipynb utils.py ANN.py  
stock charts

AI & Machine Learning News. 28, May 2018

 ForwardX raises $10 million for AI-powered luggage that follows you

Autonomous luggage maker ForwardX Robotics today announced it has raised $10 million to bring its suitcase Ovis to market. At $399, the luggage can move a maximum 6.2 miles per hour and will ship to its first customers in late 2018. ForwardX was founded in 2016, but its luggage initially grabbed the world’s attention in January at the Consumer Electronics Show (CES) 2018 in Las Vegas. The 9.9 lb suitcase is made of polypropylene and carbon fiber and is able to follow you by deploying computer vision that tracks your body and face, even if you are momentarily out of sight. Though Ovis has been tested and found to be useful in environments outside airports, like city streets, its battery only lasts for four hours of use, and it must be switched to the old-fashioned manual mode on escalators since it cannot yet handle moving stairs. 2018-05-25 00:00:00 Read the full story. CloudQuant Thoughts… Been there, Done that! Seriously, have you seen the way they treat your luggage!?  

Chinese schools are testing AI that grades papers almost as well as teachers

Some schools in China have incorporated paper-grading artificial intelligence into their classrooms, according to the South China Morning Post. One in every four schools, or about 60,000 institutions, are quietly testing a machine learning-powered system that can score students’ work automatically, and even offer suggestions where appropriate. The AI, which can be accessed through various online portals, and which the report describes as similar to the system used by the Education Testing Service in the U.S., uses an evolving “knowledge base” to interpret the “general logic” and “meaning” of pupils’ essays and to highlight stylistic, structural, and thematic areas that need improvement. It can read both English and Chinese, and it’s reportedly perceptive enough to notice when paragraphs veer too far off topic. 2018-05-28 00:00:00 Read the full story. CloudQuant Thoughts… But who will you go to if you want to dispute your grade? Seriously, as long as the direction of the education is not interfered with, anything that frees up teachers time will benefit all students.  

Understanding the Trust Factor in the Analytics Era

Today, data is increasingly seen as the fuel of the business, rather than its byproduct. As a result, the old adage “garbage in, garbage out” couldn’t ring truer when it comes to maximizing the value of machine learning in the enterprise, according to Steve Zisk, senior product marketing manager of RedPoint Global, which provides a customer data platform and engagement hub. Zisk presented a session at Data Summit 2018, titled “Garbage in, Garbage Out: Why Data Quality Is the Lifeblood of Machine Learning.” Machine learning is worthless if it’s fueled by bad data, according to Zisk, who covered why simply collecting massive amounts of data isn’t enough to extract value from machine learning technology; what’s real and what’s hype when it comes to machine learning; and best practices for using machine learning to predict, identify patterns, and optimize processes for reaching customers effectively. 2018-05-24 00:00:00 Read the full story. CloudQuant Thoughts… A lot of people assume ML and AI are the panaceas for all their problems, “just throw ML at it”. But the quality of the data is paramount, as is the structure of the data. In the trading environment huge amounts of data are derived from a simple update of the Bid/Ask or a new Trade – two events of less than 50 characters of data each.    

Pillars of a Hybrid Data Management Strategy: Hybrid, Flexible and Cognitive

Chris Reuter, North America data warehousing sales leader, IBM, presented a keynote at Data Summit 2018 on the key trends in IT today and what organizations must do to advance their organizations.   Reuter focused on three main themes in the marketplace:
  • According to IDC, data will see a 30% CAGR through 2025 – that means you have think about how over the next 7 years you are going to deal with 30% CAGR on data. Cognitive systems themselves create all kinds of data and metadata so you have got to be able to store, analyize and govern that data.
  • According to McKinsey, investment growth in AI has increased 3x since 2013. Getting actual projects into production is hard but we need to infuse cognitive computing and AI into the data, he noted.
  • According to Gartner, there is value in all approaches to cloud, whether the strategy is pure cloud or not, depending on the enterprise and end goals.
2018-05-24 00:00:00 Read the full story. CloudQuant Thoughts… A 30% Cumulative Annual Growth Rate (CAGR) on data is staggering. We agree wholeheartedly with the Essential Elements and are aiming to make the first Hybrid Trading Data Management system in CloudQuant AI very soon.  

AWS’s Recently-Launched Features ‘Transcribe’ And ‘Translate’ Are Using Machine Learning In A Revolutionary Manner

Last month at AWS re:INVENT developers conference, Amazon announced two new services — Amazon Transcribe and Amazon Translate — with an aim to improve the company’s artificial intelligence and machine learning capabilities. Amazon Transcribe can analyse audio files (.wav, .mp3, .flac) stored on Amazon S3. On the other hand, Amazon Translate provides a fast translation of text-based content to create a multilingual experience on the web. It can also simply mass-translate documents on command. 2018-05-28 08:52:29+00:00 Read the full story. CloudQuant Thoughts… There are a number of similar services already available that you can try with your own Python scripts. Python (which we use in CloudQuant) is an easy to learn yet powerful language.  

The 4 Machine Learning Skills You Won’t Learn in School or MOOCs

Machine Learning (ML) has become massively popular over the last several years. And why… well simply because it works! The latest research has achieved record breaking results, even surpassing human performance on some tasks. Of course as a result many people are rushing to get into this field; and why not. It’s well funded, the technology is exciting and interesting, and there’s lots of room for growth. 2018-05-28 16:45:55.752000+00:00 Read the full story. CloudQuant Thoughts… Your model must fit the ‘business requirements’. You must ‘quickly’ select the correct ML modelling type. You MUST fit your model into the current system (no point in building a model that receives yesterday’s market data and takes three hours to crunch if you only get the data two house before the next day opens!). Strive to get the most bang for your buck. For me, all of these fit the classic 80/20 rule.  

The one essential skill that will set you apart from other developers

…and how you can hone this skill in five easy ways. According to the Global Developer Population and Demographic Study conducted by Evans Data Corporation, there are over 22 million developers worldwide and this figure is expected to raise to 26 million in 2022. So. Many. Developers. If you are one of the 20 something millions developers in the world, you might be wondering how you can set yourself apart from others and stand out from the crowd. Today, I’d like to share with you the one essential skill that is most valued for developers but not every developer possesses or understands its importance. And no, it is not public speaking skill. It took me a while to come up with an appropriate label for this skill, but I have finally come up one that I am happy with. This essential skill is the ability to “Think and act like a CEO”. 2018-05-28 07:31:01.204000+00:00 Read the full story. CloudQuant Thoughts… This is a really nice article, the final skill is often overlooked and often what kills many a young company.  

Beginner’s Guide to Jupyter Notebooks for Data Science (with Tips, Tricks!)

One of the most common questions people ask is which IDE / environment / tool to use, while working on your data science projects. As you would expect, there is a wealth of options available – from language specific IDEs like R Studio, PyCharm to editors like Sublime Text or Atom – the choice can be intimidating for a beginner. If there is one tool which every data scientist should use or must be comfortable with, it is Jupyter Notebooks. 2018-05-24 11:46:47+05:30 Read the full story. CloudQuant Thoughts… Our next product, CloudQuant.AI leverages Jupyter Notebooks into a streamlined IDE in a webpage. We will bring you more news soon.  
Below The Fold…

Enabling the Real Time Enterprise with Data Lakes, Streaming Data, and the Cloud

oduct management and marketing, Attunity, looked at what it takes to become a real time enterprise and the role of change data capture in enabling the transformation. As organizations embrace AI and machine learning versus historical views of the past, they are also moving to real time computing and away from batch processing, said Potter. Traditional approaches included business reporting, batch analysis of data at rest, and use of transactional sources, but modern approaches also incorporate data science and advanced analytics, real-time processing of data in flight, and transactional data as well as new … 2018-05-24 00:00:00 Read the full story.  

Career paths in Business Analytics and Data Science World

“Data Scientist: The Sexiest Job of the 21st Century” is one of the most popular Harvard Business Review (HBR) articles and has inspired tons of people to pursue their careers in the field of analytics. One of the main themes of this article published in HBR was the trend of growing jobs in the analytics industry. The exact same inference was predicted by IBM recently saying that the number of US data professionals will increase from 364,000 to 2.72 million by 2020! 2018-05-28 08:59:24+05:30 Read the full story.  

How Andrew Ng Perceives The AI-Powered World

Andrew Ng is a hero and a role model for everyone who is starting the machine learning journey. One of his earliest Machine Learning courses saw lakhs of students enrolling and getting a huge boost to their careers. He is now back with a course in Deep Learning specialisation supported by his company Deeplearning.ai. Andrew Ng, one of the foremost artificial intelligence experts, is working hard to train more AI experts on a larger scale who can work across a range of industries. … 2018-05-25 05:05:43+00:00 Read the full story.  

Using Machine Learning to Monitor Social Media Crises

Machine learning can be applied to sentiment analysis of unstructured data in the context of social media. As more and more people tap into social media tools to voice positive and negative opinions, it’s important to predict a social media “crisis” before one occurs. Jana Mitkovska, project manager, Raytion, and Christian Puzicha, senior solutions architect, Raytion GmbH, presented their session, “Self-Learning… 2018-05-23 00:00:00 Read the full story.  

David Weinberger Considers the Benefits and Risks of AI

Data Summit 2018 kicked off this week with a keynote by David Weinberger, senior researcher, Harvard’s Berkman Center for Internet & Society, titled “Once We Know Everything … or Suppose AI is Right?” Throughout history, it has been the goal of people to use tools to “anticipate and narrow” by taking information, and lessons learned from the past in order to control and prepare for the possibilities that may be encountered again so they can limit risk and increase the potential for success, said Weinberger. With the arrival of big data, machine learning, data interoperability, and all-to-all connections, machines are changing long-established concepts of what we know and what is able to be known. 2018-05-22 00:00:00 Read the full story.  

Anne Buff and Lynda Partner Explore What it Means to be a Data-Driven Enterprise

Two perspectives on becoming a data driven enterprise were discussed at Data Summit 2018 in presentations by Anne Buff, business solutions manager, SAS Best Practices, SAS Institute; and Lynda Partner, VP, Marketing & Analytics as a Service, Pythian. The demand to become a data-driven business with a competitive edge in the digital economy is greater now than ever. As we embrace the idea that the analytics economy will power the digital economy … 2018-05-22 00:00:00 Read the full story.  

Using Machine Learning to Report News

Machine learning is changing the way we interact with things and each other. As artificial intelligence gains steam, what we know about the world is changing. Reuters is introducing a new tool called News Tracer. It is a capability that applies AI in journalism to find events breaking on Twitter. It assigns them a newsworthiness score so people can focus on the events that are important. John Duprey, senior arc… 2018-05-22 00:00:00 Read the full story.  

This Media Startup Is Beating the Competition With a Newsroom Run by Robots

On Feb. 13 last year, the half-brother of North Korean dictator Kim Jong-Un was killed in an airport in Malaysia, in what the U.S. Department of State concluded was an assassination using a nerve agent. As North Korea and Malaysia were roiled in a diplomatic dispute, one entrepreneur in Japan and his budding news service were about to reap some attention. News of Kim Jong-Nam’s death was quickly picked up in Japan not by one of the country’s giant media conglomerates, but by a small startup. JX Press Corp., a news technology venture founded in 2008 by Katsuhiro Yoneshige while he was still a freshman in college, reported the incident more than half an hour faster than the big names, according to one observer. It did so even though it has no journalists, let alone any international bureaus. 2018-05-27 00:00:00 Read the full story.  

Qualcomm claims its on-device voice recognition is 95% accurate

At the Re-Work Deep Learning Summit in Boston, Chris Lott, an artificial intelligence researcher at Qualcomm, gave a glimpse into his team’s work on a new voice recognition program. The system, which works locally on a smartphone or other portable device, comprises two kinds of neural networks: a recurrent neural network (RNN), which uses its internal state, or memory, to process inputs, and a convolutional neural network, a neural network that … 2018-05-25 00:00:00 Read the full story.  

Using Asynchronous Method For Deep Reinforcement Learning

Machine Learning applications have propelled artificial intelligence to achieve realistic results to a great extent. This can be largely attributed to improved research and developments in areas like neural networks — particularly deep neural networks. The advancements in these networks have led to other areas of ML, like reinforcement learning (RL), to grow parallelly. 2018-05-25 10:28:46+00:00 Read the full story.  

AI marks the beginning of the Age of Thinking Machines

Every day brings considerable AI news, from breakthrough capabilities to dire warnings. A quick read of recent headlines shows both: an AI system that claims to predict dengue fever outbreaks up to three months in advance, and an opinion piece from Henry Kissinger that AI will end the Age of Enlightenment. Then there’s the father of AI who doesn’t believe there’s anything to worry about. Robert Downey, Jr. is in the midst of developing an eight-part documentary series about AI to air on Netflix. 2018-05-25 00:00:00 Read the full story.  

Microsoft is developing a tool to help engineers catch bias in algorithms

Microsoft is developing a tool that can detect bias in artificial intelligence algorithms with the goal of helping businesses use AI without running the risk of discriminating against certain people. Rich Caruana, a senior researcher on the bias-detection tool at Microsoft, described it as a “dashboard” that engineers can apply to trained AI models. “Things like transparency, intelligibility, and explanation are new enough to the field that few … 2018-05-25 00:00:00 Read the full story.  

Free Ebook Offers Insight on 16 Open Source AI Projects

Open source AI is flourishing, with companies developing and open sourcing new AI and machine learning tools at a rapid pace. To help you keep up with the changes and stay informed about the latest projects, The Linux Foundation has published a free ebook by Ibrahim Haddad examining popular open source AI projects, including Acumos AI, Apache Spark, Caffe, TensorFlow, and others. “It is increasingly common to see AI as open source projects,” Haddad said. And, “as with any technology where talent … 2018-05-22 12:33:32+00:00 Read the full story.  

Equity Market Innovation Leads to Venue Proliferation

Several startups are planning to launch either new venues or order types, and even listing standards, to solve problems in US equity trading. At last month’s SIFMA Equity Market Structure conference, executives with the following three startups and one established exchange discussed their particular market innovations and how each one fits into the existing equity market structure. Imperative Execution is on the brink of launching a dark pool t… 2018-05-25 16:25:37 Read the full story.  

Microsoft says AI is finally ready for broader use to help solve Earth’s environmental woes

REDMOND, Wash. — Lucas Joppa agrees we’re living in the Information Age. But he wishes that the present tech era wasn’t so navel gazingly focused on Homo sapiens. “I want an Information Age that encapsulates all information about life on Earth,” said Joppa, who is Microsoft’s first chief environmental scientist — and likely the first chief of this kind anywhere in the tech sector. “We’ve allowed ourselves to exist in a world where we’re completely flying blind to the rest of the life on Earth,” Joppa said. “We do that at our own peril, and it exhibits an exceptional lack of wonder about where we are and who we are and why we’re here.” 2018-05-23 22:16:19-07:00 Read the full story.  

GPU based servers can help solve Big Data energy woes

Big data keeps getting bigger, and companies may think they are reducing their carbon footprint by moving to the Cloud but this move could actually be making things worse for the environment. With each new data center created for big cloud providers, tens of thousands of new racks need to be installed, which translates into a further strain on energy resources. One way to reduce the carbon impact is … 2018-05-22 00:00:00 Read the full story.  

Strategies for Overcoming Big Data Integration Challenges at Data Summit 2018

With the rise of big data, there is the need to leverage a wider variety of data sources as quickly as possible for real-time decision making in mission-critical environments. Presentations at Data Summit 2018 showcased real-world scenarios where data integration is providing value. At Data Summit, Joseph deBuzna, VP, Field Engineering, HVR, showed how HVR helped a global financial services company that needed to architect a cloud-based trading data analytics platform. 2018-05-23 00:00:00 Read the full story.  

IBM’s head of Watson likes Elon Musk but ‘hates’ A.I. scaremongering

Warnings of artificial intelligence (AI) posing a threat to humanity are “not helpful,” a top executive at IBM has said. While critics like Tesla CEO Elon Musk have warned about the risks of developing AI, David Kenny, IBM’s senior vice president of Watson and Cloud, said the technology is already proving to be beneficial. “It’s making things safer in cybersecurity, it’s helping doctors and nurses and patients better find health … 2018-05-28 00:00:00 Read the full story.  

Pure Storage CEO says companies need to keep data ‘hot’ to work with AI

“The interest in A.I. by corporations is just off the charts,” Giancarlo said on CNBC’s “Squawk Alley.” “At Pure, we are able to…feed GPUs, high speed applications, and A.I. environments — at the speed they want that data to provide the intelligence companies want to make their businesses better.” Since A.I. is all about crunching huge amounts of data, older, tiered storage systems that rank data by age aren’t nimble enough to grant researchers quick access to even the oldest data sets, says Giancarlo. “These days, people want access to data, whether it was last week or last year or last decade. And in order to do that, the data needs to be kept hot,” Giancarlo said. “If you want to look at long term trends and data…you want to be able to mine it for more than a week or two.” 2018-05-22 00:00:00 Read the full story.  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
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AI & Machine Learning News. 21, May 2018

“AI could mean the end of human history” – Henry Kissinger (Atlantic Article – June 2018)

Three years ago, at a conference on transatlantic issues, the subject of artificial intelligence appeared on the agenda. I was on the verge of skipping that session—it lay outside my usual concerns—but the beginning of the presentation held me in my seat. The speaker described the workings of a computer program that would soon challenge international champions in the game Go. I was amazed that a computer could master Go, which is more complex than chess. In it, each player deploys 180 or 181 pieces (depending on which color he or she chooses), placed alternately on an initially empty board; victory goes to the side that, by making better strategic decisions, immobilizes his or her opponent by more effectively controlling territory. The speaker insisted that this ability could not be preprogrammed. His machine, he said, learned to master Go by training itself through practice. Given Go’s basic rules, the computer played innumerable games against itself, learning from its mistakes and refining its algorithms accordingly. In the process, it exceeded the skills of its human mentors. And indeed, in the months following the speech, an AI program named AlphaGo would decisively defeat the world’s greatest Go players. As I listened to the speaker celebrate this technical progress, my experience as a historian and occasional practicing statesman gave me pause. What would be the impact on history of self-learning machines—machines that acquired knowledge by processes particular to themselves, and applied that knowledge to ends for which there may be no category of human understanding? Would these machines learn to communicate with one another? How would choices be made among emerging options? Was it possible that human history might go the way of the Incas, faced with a Spanish culture incomprehensible and even awe-inspiring to them? Were we at the edge of a new phase of human history? 2018-05-16 11:30:41+00:00 Read the full story. CloudQuant Thoughts: AI can beat us at Chess, Go, Call of Duty. Kissinger makes some interesting points. “AlphaZero, on its own, in just a few hours of self-play, achieved a level of skill that took human beings 1,500 years to attain. Only the basic rules of the game were provided to AlphaZero. Neither human beings nor human-generated data were part of its process of self-learning.” If the process of learning involves errors, and these are an accepted part of the process, what happens when those learning errors become costly to humankind. Pot, Kettle, Henry.  

19 Data Science Tools for people who aren’t so good at programming

Programming is an integral part of data science. Among other things, it is acknowledged that a person who understands programming logic, loops and functions has a higher chance of becoming a successful data scientist. But, what about those folks who never studied programming in their school or college days? Is there no way for them to become a data scientist then? With the recent boom in data science, a lot of people are interested in getting into this domain. but don’t have the slightest idea about coding. In fact, I too was a member of your non-programming league until I joined my first job. Therefore, I understand how terrible it feels when something you have never learned haunts you at every step. The good news is that there is a way for you to become a data scientist, regardless of your programming skills! There are tools that typically obviate the programming aspect and provide user-friendly GUI (Graphical User Interface) so that anyone with minimal knowledge of algorithms can simply use them to build high quality machine learning models. 2018-05-19 00:00:00 Read the full story. CloudQuant Thoughts: Everyone has to start somewhere. I have found Microsoft Azure demos on YouTube to be a great introduction, particularly this 15 minute Titanic demo.    

Google Champions NLP by using Neural Networks to Help you Write Emails

Google debuted it’s latest NLP development – Smart Compose – at last week’s Google I/O conference. It’s a Gmail feature that uses machine learning to predict the next words you are going to write and offers sentence completion suggestions accordingly. The aim is to help users write emails faster so they can focus on their daily work, rather than be stuck in the black hole of their inbox.
  • Google has revealed the technology behind it’s Smart Compose feature for Gmail – a combination of bag of words and RNN
  • The final model was trained on billions of text examples
  • The developers used TPUs to increase the computational power and consequently increase the speed of predictions
2018-05-17 11:09:10+05:30 Read the full story. CloudQuant Thoughts: Clippy is back.. but better and stronger thanks to AI!  

This Artificial Intelligence Model Trains Itself based on it’s own Dreams

A tennis player, on the receiving end of a booming 150km/hr serve, has milliseconds to decide which way the ball is coming, how high it’ll bounce, and how he/she wants to swing the racket so as to make it go where he/she wants. The player predicts all these things subconsciously, based on the images the brain generates.
  • Researchers have developed an AI agent that dreams up scenarios and learns from them by itself (unsupervised learning)
  • The structure of the model is divided into three units: vision, memory (RNN model) and controller
  • On a selection of 100 randomly selected tracks, the average score of the model was almost three times higher than that of DeepMind’s initial Deep Q-Learning algorithm!
We have a tendency of creating a mental image of the world around us, based on events that are perceived by our limited senses. The decisions we make and the actions we take are built around these mental “models”. There is a VAST amount of information that we intake every single day; we observe something and proceed to remember an abstract version of it. Think about this for a minute – it is true for all of us. Two researchers, David Ha and Jurgen Schmidhuber, have developed an AI model that not only plays video games with awesome accuracy, but also has the ability to conjure up new scenarios (or dreams), learn from them, and then apply them on the game itself. The model can be trained in an unsupervised manner to learn the “spatial and temporal representation of the environment”. 2018-05-16 11:49:44+05:30 Read the full story. CloudQuant Thoughts: Researchers are now looking hard at how to speed up ML, from the traditional route of Hardware improvements (Google’s TPUs), to pushing the hard work out to the edges of the network onto users machines, Microsoft’s Windows ML which enables developers to use pre-trained machine learning models in their Apps and now dopamine and dream simulation.  

OpenAI : Computing power is shaping the future of AI

We’re releasing an analysis showing that since 2012, the amount of compute used in the largest AI training runs has been increasing exponentially with a 3.5 month-doubling time (by comparison, Moore’s Law had an 18-month doubling period). Since 2012, this metric has grown by more than 300,000x (an 18-month doubling period would yield only a 12x increase). Improvements in compute have been a key component of AI progress, so as long as this trend continues, it’s worth preparing for the implications of systems far outside today’s capabilities. 2018-05-18 00:00:00 Read the full story. CloudQuant Thoughts: These are staggering increases and with the parallel increases in compute power used to drive Blockchain activity one has to wonder where all the power, physical and chip, is going to come from… by 2020 bitcoin will consume more power than the world does today…. bitcoin’s effect on the price of graphics cards.   Funny or Die’s take on Google Assistant..  
Below the Fold…  

NVIDIA’s Deep Learning AI Trains Robots to Copy and Execute Human Actions

NVIDIA has developed a deep learning system that enables robots to learn and teach themselves, simply by observing human actions. In the initial demonstration, we were shown how robots detected objects (coloured boxes and a toy car in this case), picked them up and moved them.
  • Researchers at NVIDIA have developed a deep learning system that enables robots to learn from humans
  • The algorithm is powered by several neural networks that perceive objects, understand and train themselves, and then execute the actions they saw the human performing
  • These neural networks were trained on NVIDIA’s Titan X GPUs
2018-05-21 11:30:31+05:30 Read the full story.  

AEye’s iDar sensor combines camera and lidar data into a 3D point cloud

A key component of many autonomous driving systems is lidar (a portmanteau of light and radar), which bounces light — usually in form of ultraviolet, visible, or near-infrared — off of objects to map them digitally in three dimensions. But while lidar systems are great for identifying potential obstacles, they don’t always spot those obstacles quickly. At a speed of 70 miles per hour, for instance, targeting an object 60 meters away doesn’t do much good if it takes the car 100 meters to come to a stop. Post-processing introduces another delay. That is why the new sensor from startup AEye — the iDar — is built for speed first and foremost. 2018-05-21 00:00:00 Read the full story.  

Emergence Capital raises $435 million fund for enterprise AI investments

Emergence Capital today announced it has raised a $435 million fund to invest in companies helping people increase productivity through the use of machine learning. The fund will focus especially on companies that provide coaching powered by data and conversational AI to help people perform their jobs better. Emergence has previously made a number of similar investments, including in call center analysis company Chorus.ai; recruiter chatbot Mya; and Textio, which is using conversational AI to make better recruitment messages for companies that are hiring. … 2018-05-21 00:00:00 Read the full story.  

App To Use AI To ID Guests At Prince Harry & Meghan Markle’s Wedding

As millions gather to watch the Royal Wedding of Prince Harry and Meghan Markle on Saturday, May 19, Sky News – Europe’s leading entertainment company – will introduce a new interactive experience for the historic event. In addition to enjoying live coverage of the wedding, viewers around the world will be able to access the Sky News “Royal Wedding: Who’s Who” app to follow real-time updates of wedding guests as they enter St. George’s Chapel. 2018-05-16 11:30:41+00:00 Read the full story.  

Meet the first Machine Learning Algorithm that Completely Controls Facial Expressions

Artificial Intelligence is a wonderful thing, if applied correctly. It has diverse applications and it is well and truly transforming our lives in a positive way (like healthcare). But there can be certain applications, like the one you will read about below, that are a mix between genius and scary. They have the potential to be game changing, and only time will tell if it’ll be a good or bad thing. These researchers are the first to have successfully transferred the full 3 dimensional head pose, expressions, eye motions, etc. of a face, into the face of a different actor.. The results are simply mind blowing.
  • A group of researchers have developed an algorithm that takes 1 input video and reconstructs the facial expressions, head pose and eye motions on another person’s face
  • At the core of the approach is a generative neural network
  • The results are truly mind blowing. Previous efforts in this field pale in comparison to what this approach has done
2018-05-19 13:12:51+05:30 Read the full story.  

DeepMind’s Recurrent Neural Network Explores the role of Dopamine for Machine Learning

Machines have already started outperforming humans in some tasks, like classifying images, reading lips, forecasting sales, curating content, among other things. But there is a caveat attached to it – they require tons and tons of data to learn and train the model. Some of the best algorithms, like DeepMind’s AlphaGo, take a lot of data and hundreds of hours to understand the rules of a video game and master it. Humans can usually do this in one sitting. DeepMind’s latest research aims to figure out how it can get machines to learn something in a few hours, replicating human behavior. The researchers behind this study believe that it might have something to do with dopamine, the brain’s pleasure signal. Dopamine has been associated with the reward prediction error signal used in AI reinforcement learning algorithms. These systems learn to act by trial and error, guided by the reward. 2018-05-18 11:40:41+05:30 Read the full story.  

Tech Platforms and the Knowledge Problem

Jeffersonians and Hamiltonians express very different views on what an optimal economy looks like. In the long run, their visions are probably irreconcilable. In the short run, however, both sets of reformers offer important lessons for policymakers grappling with the power of massive tech, finance, and health-care firms. This essay explores these lessons, specifying where each vision has comparative advantage. Clashes amongst centralizers and decentralists can be particularly illuminating… 2018-05-20 00:02:27-04:00 Read the full story.  

Baidu COO Qi Lu steps down, AI chief now reports directly to CEO

Baidu today announced that COO Qi Lu will step down in July for personal and family reasons. Lu had been brought aboard to help the Chinese search giant become more centrally focused on AI services. “With Baidu’s strategy to transform into an AI-first company firmly in place, we are well positioned to continue the momentum that we have built in the past year,” CEO Robin Li said in a statement shared with VentureBeat. Since he joined Baidu, the company has launched a smart speaker, its Duer virtual assistant, and a $1.5 billion fund to grow its Apollo autonomous driving division. Lu will continue to serve as vice chairman of the Baidu board of directors. 2018-05-18 00:00:00 Read the full story.  

How To Convert Data Science And Machine Learning Internships Into Jobs

Can popular massive open online courses turn into job offers? This a common dilemma faced in data science forums about internships and certificate courses converting in job offers. Now that you snagged an internship, built a portfolio of work, networked with the mid and senior management team and are ready to pursue a career in data science, you are waiting for the high-paying job offer to land in your inbox. According to UC Berkeley data scientist Karsten Walker, recruiters look for specific traits such as applying scientific methodology to a business problem and look for candidates who have a demonstrated history of applying analytical concepts. 2018-05-18 11:38:31+00:00 Read the full story.  

Google Starts Beta Tests of High-Memory Cloud VMs for Demanding Apps

Enterprises now have a new option for running memory-intensive applications on Google’s cloud platform. The company this week announced beta availability of n1-ultramem, a new family of memory-optimized virtual machine (VM) instances that Google says is well suited for applications such as data analytics, enterprise resource planning and genomics. The new machine types offer more memory and computing resources than any other virtual machine type that Google currently offers and is ideal for resource-hungry High Performance Computing apps as well, according to the company. “These VMs are a cost-effective option for memory-intensive workloads, and provide you with the lowest $/GB of any Compute Engine machine type,” Google product manager Hanan Youssef, wrote in a blog May 15. 2018-05-16 00:00:00 Read the full story.  

AI decides: Is it Laurel or Yanny?

Unless you’ve been living under a rock, you’ve probably run across the Vocabulary.com audio clip that kicked off a social media “Laurel” or “Yanny” firestorm this week. Perhaps you even weighed in, offering your two cents on the elocution of the opera singer (a member of the original Broadway cast of Cats, as it turns out) in the recording. But you probably didn’t consult artificial intelligence for a second opinion. 2018-05-18 00:00:00 Read the full story.  

Finnish university’s online AI course is open to everyone

Helsinki University in Finland has launched a beginners course on artificial intelligence — one that’s completely free and open to everyone around the world. As Janina Fagerlund from the university’s project partner (tech strategy firm Reaktor) said, people who might not know that their lives are already affected by AI every day. Fagerlund mentioned the use of AI in the food industry to sort produce and other items at facilities as an example. And while you know that Facebook uses AI for facial recognition, a lot of people might not. 2018-05-20 00:00:00 Read the full story.  

Microsoft buys a start-up that wants A.I. to make conversation with humans

Microsoft has bought Semantic Machines, an artificial intelligence start-up, as it looks to boost its efforts in developing conversational AI. Berkeley, California-based Semantic’s approach to AI is using machine learning to add context to conversations with chatbots. This means taking information received by AI and applying it to future dialogue. The firm’s speech recognition team previously led automatic speech recognition development for Apple’s personal assistant Siri. 2018-05-21 00:00:00 Read the full story.  

Digital Privacy In The Era Of Artificial Intelligence – GDPR

Not a day goes by without news articles talking about artificial intelligence capabilities and its effects on our lives. The implications for the economy and the workforce are very profound. Companies use AI today for numerous tasks, such as marketers to buy their products and the financial industry to process credit applications, along with newer applications such as medical diagnosis. Use of personal data has obvious privacy implications, especially personally identifiable information (PII) can be used to identify individuals and may be sensitive. A commonplace, prevalent fear is that individuals must be careful about what personal information makes its way online because it will be there forever, or because it can’t be rectified. Since 1995, policymakers have begun to act, with the European Union spearheading such policy efforts proposing citizen digital rights. This week, the new EU General Data Protection Regulation (GDPR) is due to enter into force, strengthening the role of consent for personal data processing, adding digital rights for citizens, and focusing on how organisations should design their data privacy and protection processes. 2018-05-18 09:03:45+00:00 Read the full story.  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
Trevor Trinkino Quantitative Trader

Machine Learning FXCM Webinar with Trevor Trinkino of CloudQuant – Part 2/3

On May 15th Trevor Trinkino presented part two of a three-part Machine Learning webinar with FXCM. Part one is here.

Part 2  – Preprocess data for Random Forest. PnL and prediciton improvements…

In part two Trevor goes over how to clean and pre-process data from CloudQuant to use in a Random Forest Classifier. He then looks at the prediction and PnL improvements seen from utilizing this classifier as well as adjusting the hyper-parameters of the model. Files mentioned in the video are available from our Google Drive below.. Ipython Notebook Trades.csv FilteredClfFeatsBF100_50.csv MLClassData.csv    
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AI & Machine Learning News. 14, May 2018

Top 6 Artificial Intelligence announcements from Google I/O 2018

Google is one of the leaders in the Artificial Intelligence field and it has cemented it’s place at the top of ladder with it’s mind blowing products at the recently held annual I/O conference. New products like Google Duplex and Google Lens were showcased which left the audience gasping with awe. From updates in Google Maps to improvements for Android, Google has made every effort to make the user experience better for it’s existing line of products as well. (Read more about this particular feature at Google’s blog post – CQ)
  • Smart compose for Gmail.
  • ML Kit
  • Google Duplex
  • Suggested Actions for photos
  • Updates to Google Maps
  • Google Lens
2018-05-10 14:46:42+05:30 Read the full story. CloudQuant Thoughts: this is an amazing presentation by Google particularly the suggested actions for photos, we suggest you watch this 14 minute summary and then…

Google now says controversial AI voice calling system will identify itself to humans

Following widespread outcry over the ethical dilemmas raised by Google’s new Duplex system, which lets artificial intelligence mimic a human voice to make appointments, Google has clarified in a statement that the experimental system will have “disclosure built-in.” That seems to mean that whatever eventual shape Duplex takes as a consumer product will involve some type of verbal announcement to the person on the other end that he or she is in fact talking to an AI. 2018-05-10 00:00:00 Read the full story. CloudQuant Thoughts: To me it actually sounded like two AIs talking to each other! Which is fine!  

Qure.ai uses Machine Learning to Detect Brain Anomalies in less than 10 seconds

Qure.ai is company aiming to revolutionize healthcare with the power and assistance of deep learning. When a patient comes in with a head injury, time is of the utmost importance. A few seconds here or there can make all the difference. Qure.ai has developed their algorithms such that they can analyse CT scans of the brain in less than 10 seconds.
  • Qure.ai has developed machine learning algorithms to detect abnormalities in head CT scans
  • The researchers trained the model on a dataset of 310k images, out of which 21k images were held out for the validation set
  • The final model revealed an accuracy of 95% on the validation set
2018-05-14 12:09:48+05:30 Read the full story. CloudQuant Thoughts: Another tremendous implementation of ML.  

Move Over Photoshop – This Python Script Works like Magic on Low Light Photos (GitHub link included)

We have all taken photos from our smartphone cameras in low light – of people, places or food. And then inevitably we turn to filters in order to increase the brightness and add context to the picture. How often has it turned out the way we wanted it to? Thanks to a group of researchers from Intel and the University of Illinois Urbana-Champaign, we now have another approach to turn up the brightness in a low light photo, with stunning accuracy. As you might have guessed by now, deep learning, and more specifically computer vision and pattern recognition, is at the core of this approach.
  • This deep learning algorithm can turn low light images into incredibly professionally lit photos
  • The researchers trained the model on a curated dataset of over 10,000 images
  • At the core of of the algorithm is a convolutional neural network (CNN) and the results are truly stunning
2018-05-12 10:36:07+05:30 Read the full story. CloudQuant Thoughts: For anyone who has ever tried to recover an image, even using a powerful application like PhotoShop, this is an amazing algo!  

Boston Dynamics gears up to sell robot dogs and improves android’s running game

Cue the “Black Mirror” theme music: Boston Dynamics says it’s putting its scary SpotMini robotic dog on sale next year. The company’s founder, Marc Raibert, made the announcement on Friday at a TechCrunch robotics event at the University of California at Berkeley. “SpotMini is in pre-production now. We’ve built 10 units that’s a design that’s close to a manufacturable design. We built them in-house, but with help from contract, manufacturing-type people,” Raibert said. 2018-05-12 20:42:27-07:00 Read the full story. CloudQuant Thoughts: Officially terrified!  

Artificial Intelligence In Search of Protection — Part III

This is a series of four articles on AI and IP protection: Part I — Why patenting an AI innovation is different Part II — The advantages of patenting AI products Part III — Reasons behind not looking for patent protection Part IV — AI Patents Landscape 2018-05-10 08:19:26.323000+00:00 Read the full story. CloudQuant Thoughts: A very interesting view on Patents and AI covering a lot of ground.  

Microsoft Interns used AI to Transform the way you use Screenshots on Windows 10

Snip Insights has the capability of taking a scanned image of a document, read it, and convert it into text. Additionally, it can also recognise celebrities, other famous personalities, landmarks and places that are captured within a screenshot. Imagine you see a cool pair of sunglasses online. Instead of wondering where you buy them and searching e-commerce sites, you can take a screenshot and Snip Insights will list down places where you can buy them. How cool is that?
  • A group of Microsoft Interns have used AI to add intelligent insights to screenshots on Windows 10
  • The application is called Snip Insights and has been open sourced on GitHub
  • It can convert images to editable text, recognize faces and places in screenshots, etc.
2018-05-10 11:22:16+05:30 Read the full story. CloudQuant Thoughts: Very clever use of AI to manage the “next steps” in a common user action. Kudos to those interns!  

Mother’s Day Interview: How Nicole Finnie Became a Competitive Kaggler on Maternity Leave

As Kaggle’s moderating data scientist for the Data Science Bowl, I’m fortunate to have met first-time competitor Nicole Finnie. Her team (Unet Nuke) impressively ranked within the top 2%, earning Nicole a silver medal. More impressively, I learned that Nicole had no ML/DS experience just a year ago, and picked up these new skills through online classes during her recent maternity leave. 2018-05-10 00:00:00 Read the full story. CloudQuant Thoughts: Bringing two new intelligences into the world at once… Well done!  
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A Step by Step Guide To Creating Credit Scoring Model From Scratch

A credit scoring model is a statistical tool widely used by lenders to assess the creditworthiness of their potential and existing customers. The basic idea behind this model is that various demographic attributes and past repayment behavior of an individual can be utilized to predict hers or his probability of default. 2018-05-14 05:28:14+00:00 Read the full story.  

Your Instagram Hashtags Are Helping Facebook Build State-Of-The-Art Computer Vision Systems

Image recognition is one of the most important components in artificial intelligence systems today. Facebook has one of the most competent and brilliant AI groups in the world and has managed to attract the best in the fields to innovate further. Facebook is continuously making great progress in AI and computer vision with the latest research focussing on generating great audio captions of photos to assist visually-impaired users. But even though these machine learning models are great, they are feed on data and labels. To tackle this problem, Facebook came up with an innovative way to push the power of deep learning even further — by using hashtags put up by users on Instagram. 2018-05-14 10:10:34+00:00 Read the full story.  

Guide to Hierarchical Temporal Memory (HTM) for Unsupervised Learning

Deep learning has proved its supremacy in the world of supervised learning, where we clearly define the tasks that need to be accomplished. But, when it comes to unsupervised learning, research using deep learning has either stalled or not even gotten off the ground! There are a few areas of intelligence which our brain executes flawlessly, but we still do not understand how it does so. 2018-05-14 02:39:38+05:30 Read the full story.  

10 Must watch videos on Applications of Artificial Intelligence (AI)

5 years ago, who would have imagined AI getting this far? Self-driving cars are no longer a figment of our imagination, they are here! As Google Duplex showed recently, machines can now book appointments for us, all the while sounding completely like a human! 2018-05-10 00:00:00 Read the full story.  

Weekly Selection — May 11, 2018 – Towards Data Science

 
  • Linear Algebra for Deep Learning
  • Deep Learning Book Notes: Introduction to Probability
  • The Logistic Regression Algorithm
  • Building a Custom Mask RCNN model with Tensorflow Object Detection
  • Demystifying Generative Adversarial Networks
  • Deep Learning for Machine Empathy: Robots and Humans Interaction — Part I
  • Fast Near-Duplicate Image Search using Locality Sensitive Hashing
  • One problem to explain why AI works
2018-05-11 15:44:27.388000+00:00 Read the full story.  

How To Talk To Plants Using Machine Learning And Gesture Recognition

Botanicus Interacticus is a new interactive plant technology which does not require any new instrumentation in plants. A simple electrode placed inside the soil is able to grasp a ton of frequencies produced by the plant, converting it into a multi-touch gesture sensitive controller. Touché is a project developed at Disney Research which makes use of frequencies captured by sensing various events witnessed by the plant and simultaneously recogni… 2018-05-10 07:25:14+00:00 Read the full story.  

Clouds, catapults and life after the end of Moore’s Law with Dr. Doug Burger

Some of the world’s leading architects are people that you’ve probably never heard of, and they’ve designed and built some of the world’s most amazing structures that you’ve probably never seen. Or at least you don’t think you have. One of these architects is Dr. Doug Burger, Distinguished Engineer at Microsoft Research NExT. And, if you use a computer, or store anything in the Cloud, you’re a beneficiary of the beautiful architecture that he, and people like him, work on every day. 2018-05-09 07:58:43-07:00 Read the full story.  

3 Ways AI Could Totally Change Healthcare

Most of the time, artificial intelligence (AI) is discussed with respect to how it will make our technology devices better, how it’ll usher in driverless cars, or even how dangerous it could be for warfare. But AI capabilities could also drastically improve the efficiency and quality of healthcare. Algorithms, image recognition technology, natural-language processing, and other AI technologies could end up making our healthcare cheaper, speed up the time it takes to develop new drugs, and even help diagnose diseases in collaboration with doctors. Here’s how. 2018-05-13 00:00:00 Read the full story.  

This Neural Mesh Renderer Can Convert 2D Images Into High-Resolution 3D Objects

3D objects on a computer screen look like real life, and with the 3D glasses on, it’s almost like witnessing the event live. But is it possible to convert a two dimensional image to a 3D object and make it “come alive” with artificial intelligence? Let us dive into a research project developed in Japan. Mesh rendering gives up exceptional objects by constructing it with the help of neural networks. This process usually involves conversion of a 2D image into 3D by overlaying the image over a 3D object. It is then redefined with the backward pass of 3D rendering and then pushed through a neural network. This platform has been explored by re… 2018-05-09 06:42:50+00:00 Read the full story.  

Streaming Media Providers Lay Groundwork for More and Better Video

NEW YORK—With video traffic on pace to make up more than 80 percent of all internet traffic within two years, the tech industry is working on ways to move the bits more efficiently and increase viewer engagement in the process. At the Streaming Media East conference here this week, Facebook said it is starting to see how much its Live video, first rolled out in 2016, is increasing engagement with viewers. 2018-05-10 00:00:00 Read the full story.  

Telehealth could replace doctor visits in major cities

If you need to see a doctor, you’d better plan ahead. A 2017 survey found 24 days was the average wait time in 15 of the largest cities to schedule a physician appointment.The long waits are a result of a growing shortage of primary care physicians, along with an aging population requiring more health care. But you can jump that line — if you’re willing to go online for your medical visit.  When they jump into 98point6’s on-demand health care service (which costs $20 the first year for unlimited visits) patients immediately enter into conversation with artificial intelligence (AI). 2018-05-12 00:00:00 Read the full story.  

White House convenes AI summit and sets up advisory panel on artificial intelligence

The White House brought together scores of industry representatives for a summit focusing on artificial intelligence and its policy implications today — including representatives from Amazon, Microsoft, Google and Facebook — and set up an advisory panel of government officials to assess AI’s impact. The Select Committee on Artificial Intelligence will advise the White House on AI research and development priorities, and will help forge partnerships involving government agencies, researchers and the private sector. 2018-05-10 21:19:18-07:00 Read the full story.  

Top 10 Machine Learning Algorithms for Beginners

The study of ML algorithms has gained immense traction post the Harvand Business Review article terming a ‘Data Scientist’ as the ‘Sexiest job of the 21st century’. So, for those starting out in the field of ML, we decided to do a reboot of our immensely popular Gold blog “The 10 Algorithms Machine Learning Engineers need to know” — albeit this post is targeted towards beginners. 2018-05-09 12:00:00+00:00 Read the full story.  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
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AI & Machine Learning News. 07, May 2018

  Start your week with a little AI Fun!    

Inspired by DeepMind, Facebook Open Sources it’s own Go Beating Algorithm

The game Go has become quite the hit lately in the machine learning community ever since DeepMind unveiled it’s AlphaGo algorithm. It was the first machine led effort that beat a Go world champion. Since then, a lot of data scientists and researchers have dedicated themselves to understanding how to better DeepMind’s algorithm. The latest effort was by Facebook’s Research team.
  • Facebook has presented an open sourced ELF OpenGo, a bot that plays the popular Go game
  • ELF OpenGo won 198 of 200 games against the strongest publicly available bot; it also beat humans 14 out of 14 times!
  • The code links and other resources are included in the article
2018-05-05 10:53:30+05:30 Read the full story. CloudQuant Thoughts: Be careful, it is watching your game and working out if you also like My Little Pony.  

Welcome to the AI gold rush!

Who Is Going To Make Money In AI? Part I – Towards Data Science We are currently experiencing another gold rush, in AI. Billions are being invested in AI startups across every imaginable industry and business function. Google, Amazon, Microsoft and IBM are in a heavyweight fight investing over $20 billion in AI in 2016. Corporates are scrambling to ensure they realise the productivity benefits of AI ahead of their competitors while looking over their shoulders at the startups. China is putting its considerable weight behind AI and the European Union is talking about a $22 billion AI investment as it fears losing ground to China and the US. 2018-05-06 12:26:26.967000+00:00 Read the full story. CloudQuant Thoughts: A great article, and obviously we think the money is to be made in the Finance vertical. Try your hand at app.CloudQuant.com and soon with CloudQuant AI.  

When Even a Human is Not Good Enough as Artificial Intelligence

During a study on machine learning and applications research, I faked being an AI like the Mechanical Turk chess-playing machines of times gone by. During the post-interviews I heard the most bizarre statement from multiple attendees: “The AI made a lot of mistakes.”. This post is about people’s bias against AI’s performance and how realistic our expectations are from AI systems. 2018-05-06 12:54:40.778000+00:00 Read the full story. CloudQuant Thoughts: This is interesting, that most people’s expectations for AI is 100% accuracy, yet when a human “pretends” to be AI we judge its performance harshly. What hope is there for our algo AI?  

Facebook Adds A.I. Labs in Seattle and Pittsburgh, Pressuring Local Universities

Facebook is opening new A.I. labs in Seattle and Pittsburgh, after hiring three A.I. and robotics professors from the University of Washington and Carnegie Mellon University. The company hopes these seasoned researchers will help recruit and train other A.I. experts in the two cities, Mike Schroepfer, Facebook’s chief technology officer, said in an interview. As it builds these labs, Facebook is adding to pressure on universities and nonprofit A.I. research operations, which are already struggling to retain professors and other employees. The expansion is a blow for Carnegie Mellon, in particular. In 2015, Uber hired 40 researchers and technical engineers from the university’s robotics lab to staff a self-driving car operation in Pittsburgh. And The Wall Street Journal reported this week that JPMorgan Chase had hired Manuela Veloso, Carnegie Mellon’s head of so-called machine learning technology, to oversee its artificial intelligence operation. “It is worrisome that they are eating the seed corn,” said Dan Weld, a computer science professor at the University of Washington. “If we lose all our faculty, it will be hard to keep preparing the next generation of researchers.” 2018-05-04 00:00:00 Read the full story. 2018-05-05 17:05:57-07:00 Also on Geekwire. CloudQuant Thoughts: It is obvious that there are not many AI specialists out there if the behemoths have taken to raiding the Universities.  

$100M Startup to Take on Alexa, Google Assistant

SoundHound Inc., a The Santa Clara, California-based startup that works with customers across automotive, Internet of Things (IoT), consumer and enterprise service industries that want to create their own artificial intelligence-driven virtual assistants, announced the close of a $100 million mega-round,led by Chinese Internet giant Tencent,  to accelerate the global expansion of its platform that rivals Amazon.com Inc.’s (AMZN) Alexa and Alphabet Inc.’s (GOOGL) Google Assistant. 2018-05-07 04:00:00-06:00 Read the full story. CloudQuant Thoughts: Just when you thought Google, Amazon, and Apple had it all tied up, it turns out that car manufacturers don’t what their customers calling their cars “Alexa” or having them permanently logged into to Google, Amazon or Apple.  

How to implement four different movie recommendation approaches

“What movie should I watch this evening?” Have you ever had to answer this question at least once when you came home from work? As for me — yes, and more than once. From Netflix to Hulu, the need to build robust movie recommendation systems is extremely important given the huge demand for personalized content of modern consumers.
  1. Content-Based Filtering
  2. Memory-Based Collaborative Filtering
  3. Model-Based Collaborative Filtering
  4. Deep Learning / Neural Network
2018-05-04 13:28:53.906000+00:00 Read the full story. CloudQuant Thoughts: A nice demonstration with code…  
Below the Fold…  

Fed’s Quarles says paying ‘a lot’ of attention to spread of machine learning in finance

Federal Reserve vice chair for supervision Randal Quarles said the central bank is in the early stages of studying how the expanding use of machine learning in the financial sector may change its regulatory approach, but that so far it fits within the existing regulatory framework. “We are paying a lot of attention … within our existing framework. To the extent you have a machine learning tool that is interacting with customers we want to make sure that the traditional protections are being complied with,” Quarles said. 2018-05-06 00:00:00 Read the full story.  

SEC’s Bauguess on the role of machine readability in an AI world

This morning, I want to share with you some thoughts in this area, particularly as they relate to the role of regulatory data.
  • Myth #1: Electronic access is equivalent to machine readability.
  • Myth #2: The Commission alone develops the reporting standards incorporated in its rules.
  • Myth #3: Retail investors don’t need machine-readable data.
  • Myth #4: Requiring machine-readable reporting standards ensures high-quality data.
  • Myth #5: We don’t need the public’s views any more.
I started these remarks by acknowledging that what has fueled the machine learning revolution is data. And not just any data, but data designed to answer questions that market participants ask. Sophisticated algorithms depend on this data being of high quality and being machine readable. When applied to the emerging fields of SupTech and RegTech, there is tremendous potential for enhanced regulatory compliance. The enhancements can come at a lower cost to registrants. 2018-05-03 18:48:00 Read the full story.  

Fast Near-Duplicate Image Search using Locality Sensitive Hashing

A quick 5-part tutorial on how deep learning combined with efficient approximate nearest neighbor queries can be used to perform fast semantic similarity searches in huge collections. If you have some education in Machine Learning, the name Nearest Neighbor probably reminds you of the k-nearest neighbors algorithm. It is a very simple algorithm with seemingly no “learning” actually involved: The kNN rule simply classifies each unlabeled example by the majority label among its k-nearest neighbors in the training set. 2018-05-05 12:16:22.405000+00:00 Read the full story.  

Essentials of Deep Learning: Introduction to Unsupervised Deep Learning (with Python codes)

I am planning to write a series of articles focused on Unsupervised Deep Learning applications. This article specifically aims to give you an intuitive introduction to what the topic entails, along with an application of a real life problem. In the next few articles, I will focus more on the internal workings of the techniques involved in deep learning. Note – This article assumes a basic knowledge of Deep Learning and Machine learning concepts. 2018-05-06 22:07:12+05:30 Read the full story.  

Python or R? Hadley Wickham and Wes McKinney are Building Platform Independent Libraries!

Ursa Labs is aiming to create libraries that will work on multiple programming languages, including R and Python It has been founded by pandas creator Wes McKinney. Hadley Wickham is the technical advisor 2018-05-07 11:38:21+05:30 Read the full story.  

Inside Multimodal Neural Network Architecture That Has The Power To “Learn It All”

Multimodal machine learning is a multi-disciplinary research field that addresses some of the original goals of artificial intelligence by integrating and modelling multiple communicative modalities, including linguistic, acoustic and visual messages. It is often referred to as building models that can process information from multiple sources. 2018-05-05 06:52:30+00:00 Read the full story.  

Forget AGI (Artificial General Intelligence), let’s build really useful AI tools

The biggest opportunities in machine learning (ML) today lie not in cracking the next big nut on the path to artificial general intelligence (AGI), but in opening up existing machine learning techniques to more businesses and making them more usable. The tech giants already know this and are investing in democratizing AI to make tools and services more widely available, but the user experience (UX) of machine learning is still overlooked. 2018-05-06 00:00:00 Read the full story.  

Lobe is an Automated Deep Learning Tool for People who don’t know Programming

Lobe is a visual drag-and-drop tool that automated deep learning; no coding necessary! It lets you build custom DL models, tune them, and deploy them to your application. All the model training is done on the cloud so your machine’s performance is not impacted. 2018-05-04 10:51:30+05:30 Read the full story.  

EPAM Platform Now Uses ML to Find Data Anomalies

The addition of machine learning through neural networks significantly improves the fidelity of the information over time, allowing users to find hidden patterns, trends and anomalies, the company said. InfoNgen users are able to quickly find, analyze and share business information to speed decision-making and remain competitive. Nearly 80 percent of new data is unstructured, making it the fastest growing form of data to be stored, and companies not taking advantage of it are missing large amounts of relevant information. 2018-05-04 00:00:00 Read the full story.  

Can a computer name lipstick colors? – Towards Data Science

Based on my hunch that these lipstick names follow a certain unspoken formula, I wanted to know if a computer could learn their patterns and produce new ones. I took hundreds of lip color shades (including balms, gloss, liners and lipsticks) from the Sephora website, as well as additional shades from drugstore standbys like Revlon. I fed this dataset to a neural network, a deep learning model that learns the structure of text and can produce its own rendition of whatever material it was trained on. 2018-05-06 04:03:39.935000+00:00 Read the full story.  

How Artificial Intelligence Is Influencing Customer Experience Today

Artificial intelligence is being accepted now on a global scale. According to a report from IDC, the global investment in artificial intelligence is only increasing with time. And in the coming years too, this is going to increase. The global investment is directly proportional to the faith in this technology. And with the passing time, the increasing faith in artificial intelligence has also become possible because of the ongoing contemporary innovations in the cloud. Artificial intelligence will deliver a $1.1 trillion boost to global business revenue and create 800 thousand new jobs in the next five years. 2018-05-02 09:14:06-04:00 Read the full story.  

Web Scraping, Regular Expressions, and Data Visualization: Doing it all in Python

A Small Real-World Project for Learning 3 Invaluable Skills

As with most interesting projects, this one started with a simple question asked half-seriously: how much tuition do I pay for five minutes of my college president’s time? After a chance pleasant discussion with the president of my school (CWRU), I wondered just how much my conversation had cost me.

2018-05-04 13:28:53.906000+00:00 Read the full story.  

Barclays Upgrades Nvidia Stock on AI, Gaming Potential

Technology name Nvidia Corporation (NASDAQ:NVDA) is trading higher this morning, after getting upgraded to “overweight” from “equal weight” at Barclays, which also lifted its price target to $280 from $265. The brokerage firm said it believes the chip producer will benefit from the next wave in artificial intelligence, while also predicting strength in the company’s gaming business. At last glance, NVDA stock was up 0.7%, to trade at $227.80. 2018-05-03 00:00:00 Read the full story.  
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. 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.
Trevor Trinkino Quantitative Trader

Machine Learning FXCM Webinar with Trevor Trinkino of CloudQuant – Part 1/3

On May 1st Trevor Trinkino presented part one of a three part Machine Learning webinar with FXCM.

Discover how to prepare your computer to learn and build a strong foundation for machine learning

In this series, quantitative trader Trevor Trinkino will walk you through a step-by-step introductory process for implementing machine learning and how you can turn this into a trading algorithm using Python. Plus he will show you the process of tuning your parameters for better performance of your trading system. Presentation file is avaialble from our Google Drive.