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Machine learning

Machine learning

 
NEWS

How to Move Machine Learning From Possibility To Practice

Marketers today might think the same thing if you tell them that machine learning can improve their email campaigns. Marketers don’t trust machines to …
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Wargaming Partners with Cloudera to Expand Online Gaming Platform usingMachine Learning

The DDRRE uses advanced machine learning algorithms to identify and predict potential player objectives and to provide players with items that will …
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Baidu’s ‘Ring Allreduce’ Library Increases Machine LearningEfficiency Across Many GPU Nodes

Baidu’s ring allreduce algorithmBaidu’s Silicon Valley AI Lab (SVAIL) announced an implementation of the ring allreduce algorithm for the deep …
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Alphabet’s internet balloons get machine learning-based navigation

Alphabet’s moonshot tech division, announced its internet balloon project, Project Loon, has new machine learning-aided navigation algorithms that …
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The Best Machine Learning Tools? Here Are 7 Everyone Should Look At

Artificial Intelligence is the hottest buzzword in computing and business at the moment, and Machine Learning is the cutting edge. If you’re looking to …
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Bloomberg Adds MachineLearning To Apache Solr Search

Bloomberg has created an open source way to use machinelearning models to weight searches, then add their values to the Solr search engine.
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Machine learning expert joins PivotalPath’s advisory board

PivotalPath, a technology-driven investment consultant, has added Josh Vogelstein, a big data and machine learning expert within the fields of …
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Redfin CTO says machine learning needs human help

Machine learning can automate the handling of huge troves of data to help companies make and save money. However, they’re not without pitfalls, …
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AI, machine learning are fueling advances in chatbot technology

With the popularity of chatbots comes a flurry of competing application frameworks. Oracle believes adhering to industry standards will prevent …
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Python libraries to lighten machine learning loads

Machine learning is exciting, but the work is complex and difficult. It typically involves a lot of manual lifting — assembling workflows and pipelines, …
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WEB

Quantum Machine Learning over Infinite Dimensions

Machine learning is a fascinating and exciting field within computer science. Recently, this excitement has been transferred to the quantum information …
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Using Google Cloud Machine Learning to predict clicks at scale

Learn how Google Cloud Machine Learning and TensorFlow make it easy to train models on very large amounts of data.
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The Rise of Machine Learning in Mobile Commerce

Machine learning is set to bloom in 2017, disrupting the ecommerce industry and ultimately becoming a foundation for future methods of …
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PhD FELLOWSHIP WITHIN MACHINE LEARNING

Stillingstittel: PhD FELLOWSHIP WITHIN MACHINE LEARNING (134581), Arbeidsgiver: NTNU – Norges teknisk-naturvitenskapelige universitet, …
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Senior C/C++ Linux Developer Machine Learning platform. EU position, Telecommute

CVEDIA provides cloud-based public or private access to any image dataset. Browsable interface allows you to visually inspect and explore. Create …
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Data Scientist – Machine Learning

Data Scientist – Machine Learning – Manchester – 15243684. Advantage Resourcing have a fantastic permanent opportunity in Manchester for a Data …
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R code with logistic regression, glm

The default family for glm is gaussian. You need to explicit state family=binomial. Your score should improve if you do this. Flag this post? Flagging …
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Machine learning in Perl

Machine learning in Perl. By Sergey Kolychev on February 21, 2017 11:58 PM. Hello everybody, this is my first post, so please go easy on me.
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Redfin CTO says machine learning needs human help

Machine learning can automate the handling of huge troves of data to help companies make and save money. However, they’re not without pitfalls, …
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Postdoctoral Research Assistant in Statistical Machine Learning

Applications are invited for a full-time ERC-funded Postdoctoral Research Assistant in Statistical Machine Learning to work on the project ‘BigBayes: …
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This Week on Singularity Hub

This Week on Singularity Hub

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China Is On its Way to Being the Next Tech Superpower

My recent trip to Beijing and Shanghai has me convinced China is the next technological superpower.

Why Neuroscience Is the Key To Innovation in AI

The future of AI lies in neuroscience.

3 Exponentials to Watch | Future of Everything With Jason Silva (Part 3)

In the third of Singularity University’s Future of Everything YouTube series with Jason Silva, Silva discusses “The Big Three” exponential technologies, which he defines as GNR: genetics, nanotechnology, and robotics.

To Design the Perfect Drone, Follow Nature’s Lead

Nature has found some elegant solutions to complicated problems and engineers have long been inspired by its designs.

The Era of Human Gene Editing Is Here—What Happens Next Is Critical

Scientists in Portland, Ore., just succeeded in creating the first genetically modified human embryo in the United States, according to Technology Review.

The World’s First Autonomous Ship Will Set Sail In 2018

What A Norwegian container ship called the Yara Birkeland will be the world’s first electric, autonomous, zero-emissions ship.

The Week’s Awesome Stories From Around the Web (Through July 29)

AUGMENTED REALITY $99 Headset Could Be Augmented Reality’s First True Chance at a Mass Market Rachel Metz | MIT Technology Review “The headset, made by Mira, is like an AR version of Samsung’s Gear VR, which gives users a virtual-reality experience when they insert one of a few Samsung smartphones.

 

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    Artificial emotional intelligence

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Artificial Intelligence Adoption

Feature: Artificial Intelligence Adoption – What it Takes for Industries to Change

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Daniel Faggella via s2.csa1.acemsc5.com 

1:07 AM (8 hours ago)

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(This week’s article is written by Dan Faggella and published on The Huffington Post)

In any industry, technology, or application area, change is often caused by a select number of trendsetters. We conducted 17 interviews with the intention of taking a closer look at the adoption of artificial intelligence in various industries and sectors.

We set out to answer questions that are critical to business leaders considering AI’s value today, namely:

  1. How AI is being adopted across industry?
  2. What’s holding adoption back?
  3. What are the timelines of adoption in different sectors?

In order to help readers find what they’re looking for, we’ve broken this article down into three major sections, each of which aims to tackle the questions above. In the article below, we lay out the main findings from our interviews, coupled with relevant quotes directly from AI executives and researchers:

“AI in Industry” Podcast: Real-Time Personalization

The big tech giants, such as Amazon, Google and Netflix, tend to set the stage in a lot of different domains and set public expectations to raise the aggregate tide of consumer experience. Our online experience is somewhat different each time we use these and other sites.

This is because many of these tech giants alter their experience user per user in a real time iterative fashion in order to create sticky experiences and to beat their competitors.

In this episode we talk to Adam Spector, the Co-Founder & Chief Business Officer at LiftIgniter, a company which provide a service which modulates website experience per users, for an array of different businesses.

Adam and I discuss what the tech giants are doing to customize their business experiences, what data they’re using to continually alter user experience and what industries and sectors might be impacted by this aggregate trend as it moves forward:

“AI for Real-Time Personalization – with LiftIgniter’s Adam Spector”

TechEmergence is Hiring:

In addition to new research initiatives, our biggest present focus at TechEmergence is building an excellent team. We’re being MORE than selective about candidates, and a good portion of be week is spent in “interview mode” as CEO.

The roles we have open now are:

  1. Content / Marketing Manager (available remote)
  2. Managing Editor, $90-100k Salary (San Francisco)
We’re certainly looking for the “right” person, and I figure that my best bet to find excellent talent is to talk to a LOT of talent, which is exactly what I’ve been doing these last 3 weeks.

If you’d like to see the details of the positions or recommend someone to apply, please see our “careers” section below:

Careers at TechEmergence

Here’s to a good week ahead,

– Daniel

 
Hey there, it’s nice to meet you.
I’m Dan, founder of TechEmergence. We serve as an objective source for business leaders looking to make productive use of AI in their industry, and I’m glad to have you with us. Find me on LinkedIn, Facebook, or contact me @danfaggella.

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Bots take over jobs of 12,000 employees

Bots take over jobs of 12,000 employees at Wipro

Co says it has achieved productivity worth 12,000 people over 140 customer engagements in 1,800 HOLMES bots in IT services.

Bots take over jobs of 12,000 employees at Wipro
Malini BhuptaMoneycontrol News

Bots are actually replacing humans at Wipro. India’s third largest IT services company, which is in the process of downsizing 10 percent of its workforce this year, kicked off Project NextGen in 2015 to improve productivity and automate processes. While the company denied plans to downsize, it said it achieved productivity worth 12,000 people over 140 customer engagements in 1,800 HOLMES bots in IT services.

Automation is, in fact, a reality now and progressively more jobs could become redundant as the pace of deployment increases.

In computer programming lingo, a bot, which is short for robot, is a program that operates as an agent for a user or another program or simulates a human activity. Wipro’s HOLMES bot uses a natural language processing (NLP)-based chat interface.

Wipro kicked off its transformative programme ‘Project NextGen’ in 2015, in consultation with McKinsey, to improve productivity of teams and automate processes. Senior managers claim teams were asked to execute the same projects with 10-15 percent less manpower, as McKinsey outlined several levers to improve productivity. Insiders claim that this was a dry run for this year’s downsizing, as teams were asked to function without 10-15 percent of the existing manpower.

The move to make do with fewer people was part of suggestions made by McKinsey to enhance productivity and help automate processes.

A very senior manager at Wipro says: “Project NextGen began very well and a few hundred senior managers were appointed as change leaders who would implement McKinsey’s recommendations. But what we did not realize was that it was a simulation of sorts to downsize later.”

From slashing coffee breaks and taking away mobile phones of employees during “Silent Hours” to real-time monitoring progress of tickets (problems raised by clients) on “White Boards” to “Huddle Meetings,” McKinsey came up with an exhaustive list of levers Wipro’s managers could use to enhance productivity of teams and cut down on waste.

But the net outcome of these initiatives was to reduce the strength of every team by 10-15 percent. Automation was supposed to be a big piece of this initiative and managers were assured that there would be no retrenchment at the end of the exercise.

In response to a questionnaire sent by Moneycontrol on gains from Project NextGen automation initiatives and consequent impact on jobs, Wipro said: “In FY17, Wipro generated productivity worth over 12,000 persons across 140+ customer engagements in over 1,800 cumulative instances of HOLMES bots in IT services, in the areas of application development, application support & maintenance and infrastructure services. Employees who are involved in such projects are then retrained and upskilled to be redeployed to handle higher value tasks.”

However, some of the change leaders that Moneycontrol spoke to said that the level of automation achieved was no more than 2-3 percent of the target, as India either lacked the requisite talent pool or that customers were not always ready for it. In many cases, privacy laws of other countries also came into play for automation.

Wipro is not looking just at automation to cut costs. It is also lowering the “Bulge Mix” –average work experience of a team. Managers have been told to lower the Bulge Mix of teams to less than 4 years. So, if a team has 40 people and the average work experience of individuals is between 0-3 years and the manager has little less than ten years, then the bulge mix will come down to less than 4 years.

Wipro, however, said: “There is no plan to change the bulge mix. We will continue to hire skilled resources at the middle and senior levels from the market.”

This also indicates that Wipro is planning to weed out more senior and experienced people who are managing the junior employees with less than 3-years experience. This is a big lever to cut costs but it also puts at risk managers with more than 10-years experience.

The existing IT services companies have so far leveraged upon the wage arbitrage that existed between the developed world and India. But the sector did little to prepare for a wave of disruptive technologies like cloud computing, which is making data centres and the support functions around it redundant.

With clients pressurizing companies to automate repetitive processes, Wipro roped in McKinsey to help it migrate from the existing model to stage where it could morph into a digital services company.

blockchain Daily update

blockchain

Daily update ⋅ May 16, 2017
 
NEWS
Blockchain Will “Change Lives” of Citizens: European Parliament Report

The European Parliament has published a dedicated report examining how Blockchain will “change lives” of EU citizens. The document, originally …
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RegTech: New Blockchain Platform Seeks To Disrupt Identity Industry

A Luxembourg-based trust services provider is teaming up with the Blockchain identity startup Cambridge Blockchain to launch a dedicated platform …
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Meet the German Baron Who Thinks Blockchain Will Beat the Middlemen

The former head of Germany’s armed forces is now helping to bring blockchain tech to some of the world’s largest financial institutions. An early …
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‘Big Four’ Irish Banks Join Blockchain Payments Pilot

Two of Ireland’s ‘Big Four’ banks are taking part in a blockchain payments trial organized by professional services firm Deloitte. According to The Irish …
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European Stability Mechanism Floats Possible Blockchain Integration

What this means: For now, it’s unlikely that the ESM leadership is considering a wholesale integration or replacement powered by blockchain. But the …
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7 interesting laws blockchain will force to change

Bitcoin’s blockchain has remained resilient to attack, and it supports a robust payment system. But this doesn’t mean the people using this technology …
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Qiwi closes purchase of InspiRussia, as blockchain tech gains ground in Russia

Russian payments services provider Qiwi PLC (NASDAQ:QIWI) has been pushing into new fintech areas like blockchain for the past couple of years.
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How to use blockchain: Following an asset through its lifecycle to learn more

Possession is nine-tenths of the law, right? But thanks to blockchain, this old adage may no longer be a viable way to settle property disputes.
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Sandbox for Public Blockchain Projects Launched in China By Wanxiang Group

On May 12, 2017, Chinese blockchain technology leader Wanxiang Group, a conglomerate with automotive, real estate and financial services …
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Blockchain A Help For SMEs

Contrary to the popular opinion, blockchain can do much more than that. Implementing this by banks, governments and small businesses would mean …
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WEB
BlockEx Partners With Winston & Strawn to Leverage Blockchain for Bond Issuance

BlockEx Partners With Winston & Strawn to Leverage Blockchain for Bond Issuance. Information contained on this page is provided by an independent …
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Blockchain delegation heads to New York

Australia’s blockchain capabilities and technologies will be showcased to global leaders and investors at Consensus 2017 in New York from 22 to 24 …
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NEMflash.com

Regular readers are probably used to the lack of clear direction as we progress through a series (and switch to a new series, and back to an old …
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New platform uses blockchain tech to assist GDPR compliance

A new platform will use blockchain technology to help businesses comply with the General Data Protection Regulation. LuxTrust and Cambridge …
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5 Things To Watch In AI And Machine Learning

Five Things To Watch In AI And Machine Learning In 2017

Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI). During the year, we saw nearly every high tech CEO claim the mantel of becoming an “AI Company”. However, only a few companies were actually able to monetize their significant investments in AI, notably Amazon AMZN +0.71%, Baidu , Facebook FB +1.75%, Google GOOGL +3.77%, IBM IBM -0.02%, Microsoft MSFT +0.29%, Tesla Motors TSLA +1.75% and NVIDIA NVDA -1.29%. But 2016 was nonetheless a year of many firsts. As a posterchild for the potential for ML, Google Deep Mind mastered the subtle and infinitely complex game of GO, soundly beating the reigning world champion. And more than a few cool products were introduced that incorporated Machine Learning, from the first autonomous vehicles to new “intelligent” household assistants such as Google Home and Amazon Echo. But will 2017 finally usher in the long-promised age of Artificial Intelligence?

NVIDIA's Saturn V supercomputer for Machine Learning is the 28th fastest computer in the world, and is the #1 in the Green 500 list of the most power efficient. (Source: NVIDIA)

NVIDIA’s Saturn V supercomputer for Machine Learning is the 28th fastest computer in the world, and is the #1 in the Green 500 list of the most power efficient. (Source: NVIDIA)

Two domains: AI and Machine Learning. These terms are not interchangeable. Machine learning, a completely different way to program a computer by training it with a massive ocean of sample data, is real and is here to stay. General Artificial Intelligence remains a distant goal and is perhaps 5-20 years away depending on the specific domain of the “intelligence” being learned. To be sure, computers trained using Machine Learning hold tremendous promise, as well as the potential for massive disruption in the workplace. But these systems remain a far cry from genuine intelligence. Just ask Apple AAPL -0.14% Siri, and you will see what I mean. The hype around AI, and confusion over what the term actually means, will inevitably lead to some disillusionment as the limitations of this technology become apparent.

With that context in mind, here’s what I expect for the coming year for Machine Learning and AI.

1. Hardware accelerators for Machine Learning will proliferate.

Today, nearly all training of deep neural networks (DNNs) is performed using NVIDIA GPUs. Conversely, DNN inference, or the actual use of a trained network can be done efficiently on CPUs, GPUs, FPGAs, or even specialized ASICs such as the Google TPU, depending on the type of data being analyzed. Both training and inference markets will be hotly contested in 2017, as Advanced Micro Devices GPUs, Intel’s newly acquired Nervana chips, NVIDIA, Xilinx and several startups all launch accelerators specifically targeting this lucrative market. If you would like a deeper dive into the various semiconductor alternatives for AI, please see my companion article on this subject here.

2. Select application domains will leverage Machine Learning to improve efficiency of mission-critical processes.

If you are trying to find the killer AI app, the increasingly pervasive nature of the technology will make it difficult to identify. However, Machine Learning has begun to deliver spectacular results in very specific niches where the pattern recognition capabilities can be exploited, and this trend will continue to expand into new markets in 2017.

    Artificial emotional intelligence

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