Shout Future

Did you know there’s a bit of artificial intelligence (AI) magic behind the scenes helping to make your holiday dreams come true? Santa’s little helpers have gone high-tech this year. From finding the perfect gift to AI-enabled toys and even composing a holiday song—that truthfully will take a bit more refinement before it becomes a holiday classic—AI has infiltrated our holidays from start to finish.

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AI drives online shopping experiences

Those of you who are adept behind the keyboard might be surprised that this hasn’t been true for years, but the scales have tipped in favor of online shopping with 51% of the Deloitte 2017 Holiday Retail Surveyrespondents saying they would be making the bulk of their purchases online this holiday season. In the past, shoppers would research and compare prices online, but the majority still went to stores to make their purchases.

Artificial intelligence algorithms help make online shopping experiences more personal. AI gets to know your preferences and behaviors to provide personal recommendations and save you the time of culling through thousands of product results to find just what you’re looking for. This AI tech is getting so good that it knows what you want—and can suggest complementary products—even better than you do.

The fashion retailer Stitch Fix is the perfect implementation of this technology. Customers fill out a style profile and personal stylists, heavily guided by algorithms, pick out items the customer will most likely enjoy. The algorithms keep getting smarter based on the ongoing feedback of the customer when they return an item because they don’t like it. These algorithms can help streamline our shopping experience to reduce the amount of choices we have. Increasingly, shoppers are preferring to use voice-search enabled assistants to shop and ComScore predicts that by 2020, 50 percent of all searches will be voice activated. Yep, you guessed it. AI at work again.

AI enhances customer service for retailers

Another way AI supports our online holiday shopping experience is through the use of chat bots. We likely won’t be able to determine if we are chatting with a human or a chatbot in the future as they step in to guide our purchases and handle questions about orders that have historically required retailers to hire a bunch of seasonal staff for the holidays. The North Face currently offers direct interaction with its IBM’s Watson-supported system and customers to help determine what item is the best for the customers’ needs. Chat bots are also used to answer queries or FAQs that can bog down human customer service personnel and have the capability to funnel customers that require human intervention to a human.

AI is being used by some stores to provide customers with a customized and personal experience in the store similar to what they get when shopping online. The Mall of America launched E.L.F., short for Experiential List Formulator, to help shoppers plan a personalized shopping experience by using the brains of an IBM Watson-enabled platform. The entire system is driven by AI and can understand through voice recognition technology queries and sentiments of customers and can output a personalized plan for each customer based on their answers to a series of questions.

AI impacts retailer’s operations

In addition to the customer-facing impacts of AI to the holiday shopping experience, there’s a tremendous amount of AI tech being utilized behind the scenes as well. From insights to manage inventory and to optimize supply chains and delivery routes, AI helps make retail more efficient.

A modern “Silent Night”

And perhaps the most entertaining use of AI for the holidays is experiments to have AI compose new holiday songs. Although more fine tuning is needed before these holiday melodies become classics, this early work provides interesting insight into the possibilities for AI and human collaboration for music composition. A team of computer scientists at the University of Toronto first fed the machine hours of pop songs so the algorithm could understand the elements of what makes a good song. Then they had it write a story about a picture of a Christmas tree with presents underneath it. The outcome of this effort is a tune that shows some promise but still needs quite a bit of work, but it also supports the idea that AI might be a “great band member” in the future and that humans and AI will continue to collaborate to make music that we all can enjoy. Thomas Holm, a Norwegian “The Voice” contestant, is the musician that collaborated with Microsoft to refine the lyrics and finalize a song created by artificial intelligence called “Joyful Time in the City,” and this experiment gives us a good look at how music composition might happen in the future with the support of AI.

AI has infiltrated this holiday season like never before. In most cases, the efficiencies and conveniences AI enabled retail provides us are welcome by all.

Bernard Marr is a best-selling author & keynote speaker on business, technology and big data. His new book is Data Strategy. To read his future posts simply join his network here.

Credit: Forbes

December 23, 2017 No comments

May 18, 2017 1 comments

AI, Artificial intelligence, AI Artificial Intelligence, AI Lab,

China's first national laboratory for brain-like artificial intelligence (AI) technology was inaugurated Saturday to pool the country's top research talent and boost the technology. China’s rapid rise up the ranks of AI research has the world's scientific community taking notice. In October, the Obama White House released a “strategic plan” for AI research, which noted that the U.S. no longer leads the world in journal articles on “deep learning,” a particularly hot subset of AI research right now. The country that had overtaken the U.S.? China, of course.
“I have a hard time thinking of an industry we cannot transform with AI,” says Andrew Ng, chief scientist at Baidu. Ng previously cofounded Coursera and Google Brain, the company’s deep learning project. Now he directs Baidu’s AI research out of Sunnyvale, California, right in Silicon Valley.

“China has a fairly deep awareness of what’s happening in the English-speaking world, but the opposite is not true,” says Ng. He points out that Baidu has rolled out neural network-based machine translation and achieved speech recognition accuracy that surpassed humans—but when Google and Microsoft, respectively, did so, the American companies got a lot more publicity. “The velocity of work is much faster in China than in most of Silicon Valley,” says Ng Approved by the National Development and Reform Commission in January, the lab, based in China University of Science and Technology (USTC), aims to develop a brain-like computing paradigm and applications.

The university, known for its leading role in developing quantum communication technology, hosts the national lab in collaboration with a number of the country's top research bodies such as Fudan University, Shenyang Institute of Automation of the Chinese Academy of Sciences as well as Baidu, operator of China's biggest online search engine.

Wan Lijun, president of USTC and chairman of the national lab, said the ability to mimic the human brain's ability in sorting out information will help build a complete AI technology development paradigm. The lab will carry out research to guide machine learning such as recognizing messages and using visual neural networks to solve problems. It will also focus on developing new applications with technological achievements.

May 15, 2017 3 comments

Microsoft is undertaking several projects dedicated to sustainability

Microsoft has been making significant contributions in Tech for Good and has taken significant steps towards environment conservation. The company’s going green mantra is underscored by the $1.1 million in 2016, fundraising and 5,949 number of volunteering hours put in by its employees.

But it doesn’t stop there. Microsoft’s ecosystem allows the firm, its employees, and the business partners to leverage new technologies for improving sustainability of their companies and communities. The Redmond giant recently tied up with The Nature Conservancy, a nonprofit to extend support for nonprofits globally.

greening the planet

Microsoft’s commitment towards nature is deeply rooted in the technologies it utilizes. Microsoft announced a $1 billion commitment to bring cloud computing resources to nonprofit organizations around the world. The firm donates near $2 million every day in products and services to nonprofits as a part of the commitment.

Microsoft has extended its support to organizations like World Wildlife Fund, Rocky Mountain Institute,Carbon Disclosure Project, Wildlife Conservation Society, and the U.N. Framework Convention on Climate Change’s (UNFCCC) Climate Neutral Now initiative.

Here are a slew of use cases

How Prashant Gupta’s initiative is helping farmers in Andhra Pradesh increase revenue? Prashant Gupta works as a Cloud + Enterprise Principal Director at Microsoft. Gupta is undertaking significant developments for environment. Earlier, Gupta had facilitated a partnership for Microsoft with a United Nations agency, the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), and the Andhra Pradesh government. The project involved helping ground nut farmers cope with the drought.

Gupta and his team leveraged advanced analytics and machine learning to launch a pilot program with a Personalized Village Advisory Dashboard for 4,000 farmers in 106 villages in Andhra Pradesh. It also included a Sowing App with 175farmers in one district.

Based on weather conditions, soil, and other indicators; the Sowing App advises farmers on the best time to sow. The Personalized Village Advisory Dashboard provides insights about soil health, fertilizer recommendations, and seven-day weather forecasts.

Microsoft’s Azure cloud platform for Nature Conservancy’s Coastal Resilience program: The Coastal Resilience is a public-private partnership led by The Nature Conservancy to help coastal communities address the devastating effects of climate change and natural disasters. The program has trained and helped over 100 communities globally about the uses and applications of the Microsoft’s Natural Solutions Toolkit.

The toolkit contains a suite of geospatial tools and web apps for climate adaptation and resilience planning across land and sea environments. This has helped in strategizing for risk reduction, restoration, and resilience to safeguard local habitats, communities, and economies.

Puget Sound: Puget Sound’s lowland river valleys is a treasure house, delivering valuable assets, a wealth of natural, agricultural, industrial, recreational, and health benefits to the four million people who live in the region. However, the communities are at increasing risk of flooding issues from rising sea levels, more extreme coastal storms, and more frequent river flooding.

The Conservancy’s Washington chapter is building a mapping tool as part of the Coastal Resilience toolkit to reduce the flow of polluted storm water into Puget Sound. Emily Howe, an aquatic ecologist is in charge of the project, which revolves around developing the new Storm water Infrastructure mapping tool. This tool will be eventually integrated into the Puget Sound Coastal Resilience tool set, that will be hosted on Azure.

Furthermore, it will include a high-level heat map of storm water pollution for the region, combining an overlay of pollution data with human and ecological data for prioritizing areas of concern.

Data helps in Watershed Management: Today, around 1.7 billion people living in the world’s largest cities depend on water flowing from watersheds. However, estimates suggest that those sources of watershed will be tapped by up to two-thirds of the global population, by 2050.

Kari Vigerstol, The Nature Conservancy’s Global Water Funds Director of Conservation had overseen development of a tool to provide them with better data. The project entailed assisting cities and protecting their local water sources. 4,000 cities were analyzed by “Beyond the Source”. The results stated that natural solutions can improve water quality for four out of five cities.

Furthermore, The Natural Solutions Toolkit is being leveraged globally to better understand and protect water resources around the world. Through the water security toolkit, cities will be furnished with a more powerful set of tools. Users can also explore data, and access proven solutions and funding models utilizing the beta version of Protecting Water Atlas. This tool will help in improving water quality and supply for the future.

Microsoft is illuminating these places with its innovative array of big data and analytics offerings

In Finland, Microsoft partnered with CGI to develop a smarter transit system for the city of Helsinki. This data-driven initiative saw Microsoft utilize the city’s existing warehouse systems to create a cloud-based solution that could collate and analyse travel data. Helsinki’s bus team noticed a significant reduction in fuel costs and consumption, besides realizing increased travel safety, and improved driver performance.
Microsoft Research Lab Asia designed a mapping tool, called Urban Air for the markets in China. The tool allows users to see, and even predict, air quality levels across 72 cities in China. The tool furnishes real-time, detailed air quality information, making use of big data and machine learning. Additionally, the tool combines a mobile app, which is used about three million times per day.
Microsoft is implementing environmental strategies worldwide. The firm is assisting the city of Chicago in designing new ways to gather data. Additionally, the firm is also helping the city utilize predictive analytics in order to better address water, infrastructure, energy, and transportation challenges.
Boston serves as another great instance where Microsoft is working to spread information about the variety of urban farming programs in Boston. Microsoft is also counting on the potential of AI and other technology to increase the impact for the city.
Microsoft has also partnered with Athena Intelligence for developing the hill city of San Francisco. As a part of this partnership, Microsoft is leveraging Athena’s data processing and visualization platform to gather valuable data about land, food, water, and energy. This will help in improving local decision-making.

Outlook

Data is not all that matters. At the end, it’s essentially about how cities can be empowered to take action based on that data. Microsoft has comprehensively supported the expansion of The Nature Conservancy’s innovative Natural Solutions Toolkit. The solution suite is already powering on-the-ground and in-the-water projects around the world, besides benefiting coastal communities, residents of the Puget Sound, and others globally.

Microsoft is doing an excellent job, delivering on its promise to empower people and organizations globally to thrive in a resource-constrained world. The organization is empowering researchers, scientists and policy specialists at nonprofits by providing them with technology that addresses sustainability.

May 11, 2017 4 comments

TAPPING A NEURAL NETWORK TO TRANSLATE TEXT IN CHUNKS

Facebook.com, facebook AI, artificial intelligence, language translation

Facebook.com artificial intelligence

Facebook's research arm is coming up with better ways to translate text using AI.

Facebook

Facebook’s billion-plus users speak a plethora of languages, and right now, the social network supports translation of over 45 different tongues. That means that if you’re an English speaker confronted with German, or a French speaker seeing Spanish, you’ll see a link that says “See Translation.”

But Tuesday, Facebook announced that its machine learning experts have created a neural network that translates language up to nine times faster and more accurately than other current systems that use a standard method to translate text.

The scientists who developed the new system work at the social network’s FAIR group, which stands for Facebook A.I. Research.

“Neural networks are modeled after the human brain,” says Michael Auli, of FAIR, and a researcher behind the new system. One of the problems that a neural network can help solve is translating a sentence from one language to another, like French into English. This network could also be used to do tasks like summarize text, according to a blog item posted on Facebook about the research.

But there are multiple types of neural networks. The standard approach so far has been to use recurrent neural networks to translate text, which look at one word at a time and then predict what the output word in the new language should be. It learns the sentence as it reads it. But the Facebook researchers tapped a different technique, called a convolutional neural network, or CNN, which looks at words in groups instead of one at a time.

“It doesn’t go left to right,” Auli says, of their translator. “[It can] look at the data all at the same time.” For example, a convolutional neural network translator can look at the first five words of a sentence, while at the same time considering the second through sixth words, meaning the system works in parallel with itself.

Graham Neubig, an assistant professor at Carnegie Mellon University’s Language Technologies Institute, researches natural language processing and machine translation. He says that this isn’t the first time this kind of neural network has been used to translate text, but that this seems to be the best he’s ever seen it executed with a convolutional neural network.

“What this Facebook paper has basically showed— it’s revisiting convolutional neural networks, but this time they’ve actually made it really work very well,” he says.

Facebook isn’t yet saying how it plans to integrate the new technology with its consumer-facing product yet; that’s more the purview of a department there call the applied machine learning group. But in the meantime, they’ve released the tech publicly as open-source, so other coders can benefit from it

That’s a point that pleases Neubig. “If it’s fast and accurate,” he says, “it’ll be a great additional contribution to the field.”

May 09, 2017 No comments

How to learn Machine learning? Learning machine learning is not a big deal but if you want to be an expert in any field you need someone as a mentor. So try to follow some professional machine learning blogs like Shout Future, Kdnuggets, Analytics Vidhya etc., and if you have any doubts, clarify it through forums or directly ask in comments.

Machine Learning

I realised the growth and development of machine learning in future will be incredible, so started to learn Machine learning back in 2013. I started from scratch and I confused a lot. Because I don't know what to do and where to start.
I think you are also like me! Here I mentioned step by step learning process to become a professional machine learning engineer yourself.

1.Getting Started:

Find out what is machine learning.
Skills to become machine learning engineer.
Attend conferences and workshops.
Interact with experienced people directly or through social media.

2. Learn Basics of Mathematics and statistics:

Start to learn Descriptive and Inferential statistics by Udacity course.
Linear algebra course by Khan Academy and MITopenCourseware
Learn Multivariate Calculus by Calculus One
Learn Probability by edX course.

3. Choose your tool: Learn R or Python:

Learn R:

R is very easy to learn compare than python.
Interactive intro to R programming language by Data Camp.
Exploratory data analysis by Coursera.
Start to follow R-Bloggers.

Learn Python:

Start your programming with Google's Python Class.
Intro to data analysis by Udacity.

4. Basic and Advanced machine learning tools:

Machine Learning Course by Coursera.
Machine Learning classification by Coursera.
Intro to Machine Learning by Udacity.
Blogs and Guides like Shout Future, machine Learning mastery, etc.
Algorithms: Design and Analysis 1
Algorithms: Design and Analysis 2

5. Build your Profile:

Start your Github profile.
Start to practice in Kaggle competitions.

That's it. With these skills you can enter into the sexiest job in the world now called "Data Scientist". Plan well and follow this steps very well.

You have to travel very long to become an expert in this field. So start your journey from today onwards and separate yourself from the crowd.

Please Comment your ideas and opinions.

May 09, 2017 13 comments

greening the planet

Here are a slew of use cases

Microsoft is illuminating these places with its innovative array of big data and analytics offerings

Outlook

TAPPING A NEURAL NETWORK TO TRANSLATE TEXT IN CHUNKS

2. Learn Basics of Mathematics and statistics:

3. Choose your tool: Learn R or Python:

4. Basic and Advanced machine learning tools:

5. Build your Profile:

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It's A "Holly Jolly" Artificial Intelligence Enabled Special Christmas

greening the planet

Here are a slew of use cases

Microsoft is illuminating these places with its innovative array of big data and analytics offerings

Outlook

TAPPING A NEURAL NETWORK TO TRANSLATE TEXT IN CHUNKS

2. Learn Basics of Mathematics and statistics:

3. Choose your tool: Learn R or Python:

4. Basic and Advanced machine learning tools:

5. Build your Profile:

About me

Follow Us

Labels

recent posts

Blog Archive

Follow Us

Report Abuse

About Me