AI & Machine Learning News. 09, October 2018
The Chairman of Nokia on Ensuring Every Employee Has a Basic Understanding of Machine Learning — Including Him
I’ve long been both paranoid and optimistic about the promise and potential of artificial intelligence to disrupt — well, almost everything. Last year, I was struck by how fast machine learning was developing and I was concerned that both Nokia and I had been a little slow on the uptake. What could I do to educate myself and help the company along? As chairman of Nokia, I was fortunate to be able to worm my way onto the calendars of several of the world’s top AI researchers. But I only understood bits and pieces of what they told me, and I became frustrated when some of my discussion partners seemed more intent on showing off their own advanced understanding of the topic than truly wanting me to get a handle on “how does it really work.” I spent some time complaining. Then I realized that as a long-time CEO and Chairman, I had fallen into the trap of being defined by my role: I had grown accustomed to having things explained to me. Instead of trying to figure out the nuts and bolts of a seemingly complicated technology, I had gotten used to someone else doing the heavy lifting. Why not study machine learning myself and then explain what I learned to others who were struggling with the same questions? That might help them and raise the profile of machine learning in Nokia at the same time. 2018-10-04 13:00:05+00:00 Read the full story. CloudQuant Thoughts… Nokia is one of those companies that I miss. I don’t miss that ringtone, but they were truly a technological marvel of a company. If this documentary is still available online it is well worth an hour of your time. It is great to see the current CEO, Risto Siilasmaa, continuing the Nokia tradition of excellence towards its people and its business.Babysitter screening app Predictim uses AI to sniff out bullies
If you’re a parent with young kids, you probably know how arduous it can be to screen a babysitter. According to a Care.com survey, roughly 51 percent of families opt not to hire a sitter because it’s too stressful to find someone they like. And among those who have hired one, a whopping 62 percent didn’t bother to check their references. That spurred Sal Parsa and Joel Simonoff, the cofounders of Berkeley startup Predictim, to develop a no-frills solution that taps artificial intelligence (AI) to generate personality assessments from digital footprints. The eponymous Predictim platform, which launches today, uses natural language processing (NLP) and computer vision algorithms to sift through social media posts — including tweets, Facebook posts, and Instagram photos — for warning signs. 2018-10-04 00:00:00 Read the full story. CloudQuant Thoughts… This one is for my colleague Tayloe, he wants this for everyone he deals with online!Investors Say They Were Harmed by Manipulation in Volatility Products
OCC, the world’s largest equity derivatives clearing organization, announced today that total cleared contract volume in September reached 365,152,938 contracts, up 8.7 percent compared to September 2017 volume of 335,867,813. OCC’s year-to-date average daily cleared contract volume is up 18.6 percent with 20,209,877 contracts compared to 17,038,958 contracts in 2017. 2018-10-01 19:54:10+00:00 Read the full story. CloudQuant Thoughts… Investment News aggregators like John Lothian News are ideal jumping off points for new model ideas.Machine Learning Hacks: Cheatsheets, Codes, Guides And Walkthrough
As the Data Science and Machine Learning field evolve, there is a huge demand for a number of professionals who are skilled in this domain. When one starts with learning and implementing the techniques involved in building the models with the help of necessary libraries, it can be difficult to remember all the concepts. A flowchart or a cheat sheet will definitely help one to understand and remember the footsteps to build a robust model. In this article, we shall explore a couple of cheat sheets for machine learning tasks. For a given dataset, one can make use of the cheat sheets to handle various tasks with ease. 2018-10-04 11:23:49+00:00 Read the full story. CloudQuant Thoughts… This blog post is an oversimplification of what it takes to get up and running with machine learning but cheat sheets are great to have around.Themes and Conferences per Pacoid, Episode 2
Paco Nathan‘s column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI and Economics. Welcome back to our new monthly series! September has been the busiest part of “Conference Season” with excellent new material to review. Three themes jump out recently.- Data science for accountability.
- Reinforcement learning challenges assumptions.
- AI and Economics have surprises in-store.
How Artificial Intelligence Makes Today’s Email Marketing Smarter
When it comes to new technologies in email marketing, everyone’s attention is caught byartificial intelligence (AI). The talks about marketing teams replaced by robots in the near future make people feel a mixture of jitters and excitement. The majority of email marketers can only guess what are the potential implications of AI on their work. Very few specialists know how exactly they can apply AI in their email marketing activities. At the same time, marketing automation platforms add AI features to meet the trending demand for data-driven email campaigns and added segmentation. The enthusiasts, who were among the first to implement AI-functionality, already boast about the results they get. Simply stated, today AI helps answer the eternal questions about who to send what and when. To predict the right time and content that most likely will convert an individual recipient, AI takes into account maximum available data and does this in seconds. 2018-10-02 15:30:40+00:00 Read the full story. CloudQuant Thoughts… Reminded me of the “how Target figured out a teenage girl was pregnant before her father did” story. It is an amazing tale of Data Science and Machine Learning.Fintech firm values properties based on sewer cocaine level data
An innovative proptech mortgage company backed by Savills has said it uses drug usage statistics gleaned from sewer monitoring to value homes prior to making loan offers. The extraordinary claim was made by Proportunity CEO and cofounder Vadim Toader at a Google Campus gathering in London’s Old Street tech neighbourhood this week. While explaining to a crowded room of fellow tech start-up entrepreneurs how his company values properties, he revealed that Proportunity’s data scientists use reports from official measurements of chemical compounds in sewers to determine levels of local drug use and therefore measure an area’s economic development. Attendees were shocked to hear that gentrification of a postcode can be measured by a reduction in crack cocaine residue present in local sewers. 2018-10-05 06:55:04+00:00 Read the full story. CloudQuant Thoughts… OK nothing to do with AI, ML ,BigData, Fintech etc and no idea why our algo picked it out but it is very interesting none the less!!An Australian start up is using AI to improve IVF treatment
The application of AI and deep learning can improve the results of IVF treatment by up to 50 per cent, according to Dr Michelle Perugini of Life Whisper. A critical part of IVF treatment includes analysing embryos to determine their suitability. Traditionally this step was completed by eye, with embryologists analysing images under a microscope to determine their viability – “A typically manual and imprecise process. It’s a huge accuracy uplift in picking the best embryos,It’s an area where there’s a lot of subjectivity, at the moment, in selecting the best embryos. It’s very difficult for clinicians to do that,” Perugini told Which-50. Images are scanned for complex patterns and features common in more healthy embryos, ultimately providing clinicians with information on which embryo has the best chance of success. “The AI essentially provides an extra set of eyes via the computer that can help them to make the best decision and pick the right embryos first time.” Perugini says clinicians can identify the embryos on either end of the quality spectrum with relative ease but “the 90 per cent in the middle” are difficult to assess. Adding AI and machine learning appears to have dramatically improved accuracy. Perugini cited two clinical studies which had shown adding the AI tool had improved success rates between 30 and 50 per cent. 2018-10-02 16:23:15+11:00 Read the full story. CloudQuant Thoughts… AI helping people have babies is just about the most positive use in the world. Imagine writing code that brings into the world little humans that otherwise would not have existed! Amazing!AI could “end famine” by spotting developing crises before they begin, says World Bank president.
Speaking to reporters at Stanford University, Jim Yong Kim said AI could give aid workers as much as six months’ advance warning to stabilise potential famines before they spiraled out of control. The Bank is working with Amazon, Google and Microsoft to develop a system called Artemis that would trawl through data from satellites, food prices, weather records and social media and analyse it for signs of trouble. The AI system would be linked to a funding mechanism which automatically releases relief money once certain thresholds are met, rather than waiting for a famine to be officially declared. Mr Kim said: “This could actually end famines. We are getting information well ahead of time instead of waiting until the fifth stage of famine. 2018-10-03 00:00:00 Read the full story. CloudQuant Thoughts… And if it is not helping to bring babies into the world, it is helping the poorest most desperate in the world out of horrendous situations. Oh… and Skynet!How AI and emotion tracking are helping brands avoid costly video campaign mistakes
Marketers have plenty of ways to measure video campaign success, but artificial intelligence is uncovering new methods for determining whether the dollars you’re spending are being applied optimally. That’s what video insights company YouFirst is offering, and a recent study of one of its clients, spanning 13 video campaigns over two years, is revealing. Even with the latest and greatest analytics tools at the brand’s disposal, AI and emotion tracking are opening up new insights. More importantly, AI is showing where to make changes to a campaign so it hits its exact target market — and when to pull the plug. YouFirst works by allowing a focus group of video viewers access to the content through its player, which — with permission — monitors the facial expressions of the consumer via a webcam. The AI and platform YouFirst developed can determine whether the video is eliciting an emotional response during playback, and it can understand the difference between six main emotions; anger, disgust, fear, happiness, sadness, and surprise. 2018-10-05 00:00:00 Read the full story. CloudQuant Thoughts… In 2013 prior to the launch of the Xbox One Microsoft told advertisers that its new “always on camera” could tell them how many people were in the room watching an advertisement, their ages, heart rates, muscle tension, whether or not they were smiling. So YouFirst seem a little behind the curve.. make that a lot..This week’s Triple Hitter
Cloudera, Hortonworks Merger Will Create New Data Platform
A couple of neighboring Silicon Valley data platform makers who have been competing in the Hadoop data storage and analytics market are finally joining forces–to the surprise of not many people in the enterprise IT world. In fact, some industry observers were wondering why it took so long to happen. Cloudera and Hortonworks, who both entered the business world about 10 years ago and immediately began going after the same customers, jointly announced Oct. 3 that they have agreed to become one and the same in an all-stock merger of equals worth a combined $5.2 billion. The companies, the combination of which was unanimously approved by the boards of both companies, will use their synergies to create what they describe as “the world’s leading next-generation data platform provider, spanning multi-cloud, on-premises and the edge.” 2018-10-04 00:00:00 Read the full story.Elastic IPO Expected to Raise $250M
Elastic went public today on the New York Stock Exchange in what could be one of the big data industry’s hottest IPOs of the year. Elastic started selling shares this morning under the ticker symbol ESTC at $36 per share. Oversubscribed demand led the Mountain View, California-based company to raise its price target from $26 to $29. Shares “popped” in early trading, and were up more than 90%, an indication of continued strong demand. The compan… 2018-10-05 00:00:00 Read the full story.This tech investor had a killer week thanks to two big open-source deals
Mike Volpi of Index Ventures started investing in open-source software companies when it wasn’t clear if they could make much money. This past week — more than any before it — has validated his conviction that they can. On Wednesday, Hortonworks, a big-data software company backed by Volpi, announced that it was merging with competitor Cloudera. Two days later, another one of Volpi’s companies, Elastic, started trading on the New York Stock Exchange and doubled in value in its debut. 2018-10-07 00:00:00 Read the full story. CloudQuant Thoughts… Not much to add here except that news regarding this merger, IPO and Investment took up a significant portion of this feed this week. Either they are very important or someone has a great publicist!Below the fold… Facebook Launches PyTorch 1.0 With Integrations For Google Cloud Working on their earlier vision of making development in artificial intelligence faster and more interoperable, Facebook on Tuesday announced their first-ever PyTorch Developer Conference, where they introduced updates about the growing ecosystem of software, hardware, and education partners that are deepening their investment in PyTorch. According to a report, an unspecified number of engineers are collaborating to make the open source machine learning PyTorch framework by the social media giant work with Google’s Tensor Processing Units (TPUs). This collaboration is also reportedly one of the rare instances where these tech giants are working together on a project. Rajen Sheth, director of product management at Google Cloud said in a blog post, “Today, we’re pleased to announce that engineers on Google’s TPU team are actively collaborating with core PyTorch developers to connect PyTorch to Cloud TPUs. The long-term goal is to enable everyone to enjoy the simplicity and flexibility of PyTorch while benefiting from the performance, scalability, and cost-efficiency of Cloud TPUs. 2018-10-03 06:00:51+00:00 Read the full story. 5 Amazing Machine Learning GitHub Repositories & Reddit Threads from September 2018 Welcome to the September edition of our popular GitHub repositories and Reddit discussions series! GitHub repositories continue to change the way teams code and collaborate on projects. They’re a great source of knowledge for anyone willing to tap into their infinite potential. As more and more professionals are vying to break into the machine learning field, everyone needs to keep themselves updated with the latest breakthroughs and frameworks. GitHub serves as a gateway to learn from the best in the business.
- Object Detection using Deep Learning – a one-stop shop where you can find all the top object detection algorithms designed since 2014
- Train Imagenet Models in 18 Minutes – You need to have Python 3.6 (or higher) to get started. Go ahead and dive right in.
- Pypeline – Creating Concurrent Data Pipelines – This repository contains codes, benchmarks, documentation and other resources to help you become a data pipeline expert!
- Everybody Dance Now – Pose Estimation
- Beginner Friendly AI Papers you can Implement – Quite a few links to easy-to-read AI research papers
- What Happens when an Already Accepted Research Paper is Found to have Flaws? – The original author of the paper took time out to respond to this mistake.
- Having Trouble Understanding a Research Paper? This Thread has All the Answers – That’s exactly what this thread aims to do.
- How can you Prepare for a Research Oriented Role? – this thread is an enlightening one with different takes on what the prerequisites are.
- Researchers who Claim they will Release Code Mentioned in a Paper but Never Do
- Data Detective
- Conversational Agent Designer
- Creative Catalyst\Growth Hacker
- Cyber City Analyst
- Man-Machine Teaming Manager
- Digital Targeter
- Technical Operations Officer
- Datacenter Administrators
- Help Desk Staff
- Programmers
- Data Analysts
- Don’t Fall for Buzzwords — Clarify Your Objective
- Don’t Lead with Software Selection — Team Skills Come First
- Don’t Leap to the Number Crunching — Strategically Plan the Deployment
- What AI is, and What it isn’t
- Speed of Delivery
- Power of the Technology
- Pervasiveness of Deployment
- To Cloud or Not to Cloud
- Specification
- Robustness
- Assurance
- Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning
- Iterative Initial Centroid Search via Sampling for k-Means Clustering
- Solving multiarmed bandits: A comparison of epsilon-greedy and Thompson sampling
- Why Can a Machine Beat Mario but not Pokemon?
- Neural Network Embeddings Explained
- Convolution: An Exploration of a Familiar Operator’s Deeper Roots
- Harnessing infinitely creative machine imagination
- Experimenting with twitter data using Tensorflow
Behind a Pay-Wall or Personal Data Collection Wall China’s tech giants spending more on AI than Silicon Valley China’s biggest tech companies have overtaken the giants of Silicon Valley in the race to invest in artificial intelligence and machine learning this year, according to new research for The Daily Telegraph. Out of around $14bn (£10.6bn) worth of AI investments made by the biggest eight US and Chinese tech companies this year, Chinese firms such as Baidu, Alibaba, Ant Financial and Tencent have taken a clear lead. Collectively, the four big Chinese groups have been involved in $12.8bn of the total, according to data compiled by Pitchbook, a financial data firm. 2018-10-07 00:00:00 Read the full story. Robots will take our jobs … and make more Traditional middle-class professions are about to be wiped out. Wages will fall as people compete desperately for the few jobs that remain. Unemployment will soar, and a super-rich elite will split away from the impoverished masses. There are plenty of dystopian visions out there about the likely impact of robotics and artificial intelligence on the way we all work – along with demand that capitalism be reshaped to cope. But here is something odd. Over the last 20 years, as technology has boomed and computers and smartphones have transformed the way we work and communicate, employment has been hitting record levels. 2018-10-05 00:00:00 Read the full story.
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