HOW TO BECOME ONE OF WORLD'S TOP 5 ECONOMIES: JackMaNews (10/17) DAMO Academy will change world's human 1 values of -1 data intelligence, 2 the Internet of Things, 3 fintech, 4 quantum computing : ALQ & 5 human-machine interaction-will yours be one of the first 7 DamoCity along with AliBaba's supercity Hangzhou (inaugural 40000 person comp summit, host china g20)? - will half the innovation be led by girls? correspondence isabella@unacknowledgedgiant.com rsvp chris.macrae@yahoo.co.uk (at worldclassbrands.tv project of Norman Macrae Family Foundation) if you search out a superapp story worthy of worldwide youth celebrations .. 21st c logistics netpreneurs 10T MIT

DAMO (Discovery Adventure Momentum Outlook) to attract world-class talent, build partnerships and open research laboratories in seven cities around the globe..Its research areas will cover data intelligence, the Internet of Things, fintech, quantum computing and human-machine interaction. Within those areas, it will focus on real-world applications like machine learning, network security, visual computing and Natural Language Processing. Intro to Tech Concerning AI blockchain -off site reddit:neo

Do you know top 10 ways your kids can be imagineering jobs and happy lives?: 1 friend mapping 2 additive manufacturing 3 sensors everywhere 4 type 2 blockchains =big-data-community-app'd 5 robots with more memory than university full of professors 6 everyone's a shopkkeper as well as customer 7 everyones a teacher as well as student as well as coder 8 to 10 - utellus isabella@unacknowledgedgiant.com

Friday, March 31, 2017

Data Intelligence

why DI and LoveQ matter-
 these are the most exciting times to be alive because  the investments and interactions between 3 generation- grandparents, parents and under 30s - are determining within the next 10 years whether our species is sustainable! if you didn't know of that challenge then its quite likely to be because of a war going on between big data big and big-data small; in the west global1.0 gave all the resources to big data big who now use these resources to fake news on how urgent this end game is -can we escape orwell's big brother syndrome; Jack also talks about the quotient of love- if you have a professional skill but find yourself in a market where all the rewards (including jobs) go to big data big it can take a lot of love to stand up for trusting big data small - this is especially so in education which so often seems to be designed for everyone one but the child's livelihoods- here's jack on this system tragedy  -here's an investigation of how education has turned against kids livelihoods in much of West

back to general searches on DI
Today, content is very key, but ultimately, the winning strategy has to be beyond content,” he said.
Data plays a central role here as well. Yu noted how Alibaba was able to drive box office sales in China for “A Dog’s Purpose,” a co-production of Alibaba Pictures and Steven Spielberg’s Amblin Entertainment.
Mining its massive trove of consumer data for consumers who previously purchased pet products and those who engaged with related content on Alibaba’s various media platforms, the company was able to deliver specific advertisements for the movie to its most likely audience. The end result: box office sales in China hit $88 million compared to $64 million in the U.S. “This is a good case of how we can leverage our resources and do precise marketing,” Yu said.
AI and Alibaba
Answering a question from the audience on Thursday about Alibaba’s development of artificial intelligence, Tsai noted the company is already using an AI chatbot that can handle 90 percent of customer enquiries and is spreading learning-machine technology to other areas such as logistics and product search.
“A lot of companies say they have an AI department,” Tsai said. “We don’t (say that) because AI lives in every part of our business,” he said, noting that AI “is only in the first inning of the game … We will be able to sprinkle lots of AI surprises into our core businesses to make our core businesses more valuable.”
Clear Skies Ahead for Alibaba Cloud
Investors and analysts attending the second day of Alibaba Group’s Investor Day conference were wondering if Alibaba Cloud, Alibaba’s cloud-computing subsidiary, could maintain its rapid expansion after eight consecutive quarters of triple-digit revenue growth rates.
Alibaba Cloud President Simon Hu assured attendees that, despite competition from players such as Amazon’s market-leading AWS cloud business, there are abundant blue-ocean growth opportunities globally and in China’s nascent market, which is projected to reach $20 billion by 2020, according to Bain & Co.
More than one-third of China’s top 500 companies, among them energy giant Sinopec, automaker Geely, and telecoms company China Unicom, are already Alibaba Cloud customers, as are numerous government agencies like China Customs as well as the 2022 Beijing Olympics—yet the market has barely been tapped.
“This indicates there are strong growth prospects for Alibaba Cloud going forward,” Hu said. With 15 data centers worldwide, “today our footprint is expanding across the globe, in the U.S., Japan, the Middle East and across Asia … we are truly serving a global marketplace” In the quarter ended March 2017, Alibaba Cloud reported it had 874,000 paying customers; Revenue in the quarter was $314 million, an increase of 103% compared with the same quarter of 2016.
Launched eight years ago, Alibaba Cloud is a relative latecomer to the market, but the company is already the world’s fourth-largest Internet cloud services provider in revenue and was No. 1 in China’s public cloud market last year with a market share of more than 40%, according to IDC. About 37 percent of all websites in China are hosted by Alibaba Cloud.
Hu’s positive outlook is based in part on growing demand from Chinese companies in financial services and manufacturing that are ripe for digitalization through cloud computing. China’s vast manufacturing sector wants to transition to smart manufacturing to gain greater supply chain control, yet just 1% of manufacturers have cloud capabilities today, he said.
“That’s going to go up fast,” Hu said. In addition, “many retailers want to be selling offline and online and do omni-channel marketing, this is another big opportunity for us.”
Alibaba Cloud’s innovations in big data analytics and data processing, augmented by artificial intelligence, are also expected to drive growth as the company expands its cloud services and solutions. Businesses don’t just want to store and process data in the cloud because of cost efficiencies, “businesses want to know how to use data,” Hu explained .
“What we can do in terms of technology is provide a deeper level of service. Over the course of the past year, data intelligence has become the most important strategy for Alibaba Cloud … We have 10 years of experience with (AI) algorithms and we are able to leverage that quickly.”
But will Alibaba Cloud, which is nearing profitability, continue to grow triple digits? “We believe cloud will continuously see strong growth in revenue from both more customers and increased customer spending,” said Alibaba Group CFO Maggie Wu.
“We Are A Technology Company”
Alibaba Group Chief Technology Officer Jeff Zhang wants to settle this question once and for all: is Alibaba an e-commerce company or a technology company?
“We are a technology company–we’re built on data,” Zhang said. “What all of our business units want to do with data comes down to us.” In other words, Alibaba’s massive network, data servers and computational horsepower is the fuel that powers the company’s e-commerce, not the other way around.
Not only is Alibaba a tech company, it’s one of the world’s premier tech companies, Zhang said, one that has integrated into its businesses advanced image-recognition and voice-recognition technology, artificial intelligence and “the world’s fastest cloud processing, or streaming processing, platform.”
“Our businesses are more diverse and complex than any other internet company,” he said, pointing out that Alibaba is able to drawing extensive data on shopping habits, geo-location apps, financial services and scores of other sources to help better serve customers and drive efficient merchant operations.
To cite just one example, the result of this capability can be seen in the Mobile Taobao app, which displays personalized homepages that are unique in both layout and content for millions of individual users, adding shopping recommendations from a pool of more than one billion products.
This is a bigger challenge than faced by other major internet companies, Zhang said. “Amazon and eBay are probably the biggest customers of Facebook,” he explained. “On Facebook, you see Amazon advertising and the advertising you see is different for everybody, but there are only 100,000 products listed so they are selecting one from 100,000 products to recommend to you.  So, we have a billion products; one relevant product in a billion to recommend to you requires a higher level of technology.”
While a lot of companies are investing in artificial intelligence, Alibaba has all the ingredients necessary to develop practical AI solutions and is hard at work rolling them out.
The company has massive amounts of data as fodder for learning machines, robust computational power to support real-time AI applications and process complex problems efficiently, advanced AI algorithms, and, perhaps most important, a business that is rich in opportunities to apply AI in ways that are practical and useful.
“Only if you have these things can you truly say you are an AI company,” Zhang said. “So yes, we are better at AI than other companies,” adding that “we are continuously training our systems so our platforms are becoming increasingly intelligent, and that’s our advantage.”
“At Alibaba, we are literally launching new products and new solutions each and every day,” Zhang said. Without giving details, he added that the company is investing heavily in speech-recognition technology and this summer will unveil “a whole new series” of products based on a voice-controlled intelligent platform, products for the home, entertainment, hospitality industry and education markets.

Wednesday, March 29, 2017

from goldman sacha report on ai china

Companies such as Google and Microsoft have poured vast amounts of money into research and development to expand the horizon of what AI can achieve. Machines are fed large quantities of data and taught specific tasks, allowing companies to create software that can learn and become smarter.
While the United States is generally considered to be leading the field, other countries are catching up. China, home of internet powerhouses such as BaiduAlibaba and Tencent, is one of them.
In July, China's State Council issued guidelines on developing AI inside the country and set a goal of becoming a global innovation center for it by 2030. It expects the total output value of AI industries to surpass 1 trillion yuan ($147.80 billion).
The Council encouraged the creation of open-source computing platforms and training more AI professionals and scientists. The guidelines said the government will invest in qualified AI projects and encourage private capital investment.

Key drivers to create value in China's AI space

Goldman identified four key areas where development is needed to create value in AI: talent, data, infrastructure and computing power. The bank concluded China has the talent, data and infrastructure needed to fully embrace AI.
Because AI is a relatively new technology, finding adequate number of talented individuals is a perennial problem. Experts have argued that more needs to be done to train people in new AI-related skills.
To get around talent scarcity in any particular location, U.S. tech giants are opening research labs around the world, according to Goldman. Chinese companies are also following their lead by opening Silicon Valley research labs and offering comparable salaries, Goldman said.
Earlier this year, Baidu snagged Microsoft executive Qi Lu as part of a push into AI. Meanwhile, Tencent tapped up former Microsoft scientist Yu Dong to head up its AI research facility in Seattle.
China's vast population, much of which is connected to the internet, gives the country an advantage in generating data. Moreover, China's large internet companies have comprehensive online ecosystems increasingly penetrating more of the daily lives of the country's internet users, generating volumes of data, according to Goldman.
"China understandably generates (about) 13 percent of the digital information globally. By 2020, we expect this to grow to around 20 percent to 25 percent as China's economy emerges as the world's largest," the bank said. It predicted China would generate about 9 to 10 zettabytes of data; one zettabye is about 1 trillion gigabytes.
When it comes to infrastructure, most major companies involved in AI research have adopted open-sourced platforms to attract resources and talent into their ecosystems.
Chinese companies are also following the trend, said Goldman. For example, Baidu has an open-sourced machine-learning platform called PaddlePaddle that stands for Parallel Distributed Deep Learning. Baidu also announced project Apollo, another open-sourced platform to develop autonomous driving.
AI algorithms and their performances are also limited by computing power that depends on the processing unit. Goldman noted that China had been "heavily dependent on foreign suppliers" for processing chips, but there was some "encouraging progress" in its domestic semiconductor industry.
The bank said that it expected China's dependency on foreign suppliers to decrease over time.

Companies to watch out for

Goldman said it expected the initial benefits of AI will go to China's so-called BAT: Baidu, Alibaba and Tencent. That's because these companies have substantial and unique data sets and have the right size of resources to take advantage of the the technology.
Another company to watch is Chinese on-demand services provider Meituan-Dianping. It uses big data analytics to generate the most efficient delivery route in less than 100 milliseconds, said Goldman.
China's largest ride-hailing app Didi Chuxing is also working on deep learning, human-machine interaction, computer vision and intelligent driving technologies. It processes over 4,500 terabyte of data, receives over 20 billion route requests and handles more than 20 million orders on average on a daily basis, according to Goldman.
iFLYTek is a company that focuses on speech and language recognition. The report said it has the largest market share in China's intelligent speech industry.
Hikvision is a technology company that uses AI for surveillance products, including intelligent cameras.
The report said some of the other companies to watch out for included Mobvoi, which is involved in speech and natural language and SenseTime, which focuses on computer vision and deep learning. Also included were drone maker DJI and humanoid-robot maker UBTECH.
Mobile Taobao is not just about consumption, it’s also about community and content, according to the app’s manager, Jiang Fan.
Addressing Alibaba investors in Hangzhou last week, Fan said the Alibaba mobile shopping application is “the world’s largest destination for everyday shopping, entertainment, lifestyle and community.” And it’s all driven by big data and artificial intelligence.
Just how big is that community? Some 468 million users log onto Mobile Taobao every month. And 189 million launch the app every day, with the average user doing so 7.8 times in a 24-hour period.
Mobile Taobao
Increasing usage of mobile app
They’re not doing so simply to purchase apparel, smartphones or even baby food. In fact, China’s shoppers are also taking to the mobile site for the same reasons Americans take to Facebook, YouTube or Twitter: to engage with other users and consume content.
Some of the most-popular types of content right now are live-streaming and short-form video, which allow brands to tell their stories in ways that merely placing their goods on a virtual shelf does not. Those stories are working: Users spend an average of 18 minutes a day watching live-streamed video on Mobile Taobao, Fan said, and 50 percent of watchers click through to a brand’s flagship store during a broadcast.
Live Streaming
A 24-hour online TV station
Live-streaming has also enabled the rise of “key opinion leaders,” or celebrity influencers who interact with consumers in real time and recommend products for sale. KOLs have become so central to consumption in China that Mobile Taobao has launched three types of recommendation features—Crazy About Shopping, Good Find and Wishlist—all of which driven by these celebrities.
“So, if search was the primary route to purchase in the past, today guided purchase is becoming more and more important,” Fan said.
Short-form video is also on an uptick, with 500,000 short-form videos currently on Taobao. As video-product costs come down, and with the expansion of brand-building opportunities they offer, Fan predicted that most products sold on Taobao would have a short video within five years.
“You’ll be browsing products through the short-video format, and it’s a better format to present a product or to present the story of a shop, of a merchant,” Fan said.
Also in the content space, Mobile Taobao features Weitao, a micro-blogging service for brands, the news feed Taobao Headlines and question-and-answer forum “Your Advice Please” have given consumers even more things to consume. Weitao has proved the most popular, with over 5,000 brands, media outlets and cyber celebrities using the service to reach shoppers. Fan likened these features and their popularity to other apps in the West, such as Instagram or Pinterest.
Vs Other Apps
Beating the competition
While the content and community are visible to consumers on Mobile Taobao, what they can’t see is the big data and artificial intelligence powering the platform. The most-obvious example of these tools at work, Fan said, is in customer recommendations.
The company collects data related to everything from a shopper’s purchase history to the pages they view to products they bookmark. The level of detail is so great that Mobile Taobao divides its customers into 500 different segments. Then it couples those segments with the information it has on the more than 1 billion products being sold on the site before putting artificial intelligence to work to generate the most accurate recommendations possible.
Anticipating Customer Needs
Mobile Taobao anticipates customer needs.
“We can analyze their attributes, their characteristics, their past purchase history, their purchasing behavior, [and] their perceived purchasing intention so we can make the recommendations more relevant and more targeted,” Fan said.
Merchants can be segmented, too. Mobile Taobao uses those segments, which comprise different sectors, business models and even the different needs of a merchant, to develop and deliver tools that allow them to better serve their customers. In the past, these assessments were done by human intelligence, but now AI has taken the lead, Fan said.
Intelligent Merchants
Something for every merchant
One such tool designs banner advertisements for merchants. Powered by AI, Mobile Taobao’s system can create a million different ads, each targeted to a different consumer according to his or her profile. This cuts the costs of having a human design the banner, to say nothing of AI’s ability to far outproduce what a human designer could make. Moreover, the AI can track the click-through rate of the ads to judge their effectiveness and switch out the less engaging ones in real time in favor of others that may be more engaging.
Other AI-powered tools, such as a customer-service chat botand a shopping assistant, are also being used to help both merchants and customers. Indeed, Fan notes that all of the operation models underlying consumer behavior on the platform are underpinned by AI.
“You could say that Taobao is the largest use case for artificial intelligence in the world,” he said.

Saturday, March 25, 2017

Mariya Yao (TOPBOTS) <community@topbots.com>
To:chris.macrae@yahoo.co.uk
25 Apr at 09:09

Presented by TOPBOTS // April 25, 2018 // Issue 90
Hi everyone! Last week we set up social communities and discussion forums for TOPBOTS readers to engage with each other to share content and knowledge. Join the conversation at Applied AI For Business, our Facebook group
One topic of discussion we covered this week is how business leaders should evaluate the performance of machine learning models. Often you'll see the media report that "an AI was able to achieve 95% accuracy" on some task, without any further clarification.

A common mistake made by non-technical executives is to over-focus on misleading metrics such as accuracy without understanding the importance of other evaluation metrics like precision & recall. Case in point: If 1% of the population has a disease, then a naive model that predicts everyone is healthy is 99% accurate, but the recall numbers would show you the model is worthless for your intended task of identifying patients who need treatment.

If you're not already familiar with precision and recall, here's a beginner-level article that covers the tradeoffs between accuracy, precision, and recall and also goes into details about F-Scores and ROC Curves. If you prefer to learn from video, here's a YouTube video that makes the concepts clear too. 

Got any other ideas for how we can improve TOPBOTS for you? Just shoot us a note at community@topbots.com.
~ Mariya
@thinkmariya

For those of you who are new, TOPBOTS is 
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Two Facebook & Google geniuses are combining search & AI to transform HR
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Andrew Ng's Machine Learning Yearnings: Chapters 15-19
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Notes from the AI frontier: applications and value of deep learning

An analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques.
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A simple tool to start making decisions with the help of AI
AI Canvas, a simple decision-making tool, to help incorporate a prediction machine into your decision-making process. Each space on the canvas contains one of the requirements for machine-assisted decision making, beginning with a prediction.


Beyond accuracy: precision & recall
Using the right evaluation metrics for your classification system is crucial. Otherwise, you could fall into the trap of thinking that your model performs well but in reality, it doesn’t. In this post, you will learn why it is trickier to evaluate classifiers, why a high classification accuracy is in most cases not as desirable as it sounds, what are the right evaluation metrics and when you should use them.
How StitchFix turned personal style into a data science problem
Stitch Fix provides a glimpse of how some businesses are already making use of AI-based machine learning to partner with employees for more-effective solutions. A five-year-old online clothing retailer, its success in this area reveals how AI and people can work together, with each side focused on its unique strengths.
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What human teams can learn from machine learning marketing algorithms
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