Daily Archives: July 21, 2017

FILE PHOTO: A computer mouse is illuminated by a projection of a Chinese flag in this photo illustration from October 1, 2013.

REUTERS, Tim Wimborne

BEIJING -- China's government has announced a goal of becoming a global leader in artificial intelligence in just over a decade, putting political muscle behind growing investment by Chinese companies in developing self-driving cars and other advances.

Communist leaders see AI as key to making China an "economic power," said a Cabinet statement on Thursday. It calls for developing skills and research and educational resources to achieve "major breakthroughs" by 2025 and make China a world leader by 2030.

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It might not be long before machines begin thinking for themselves -- creatively, independently, and sometimes with better judgment than a human....

Artificial intelligence is one of the emerging fields along with renewable energy, robotics and electric cars where communist leaders hope to take an early lead and help transform China from a nation of factory workers and farmers into a technology pioneer.

They have issued a series of development plans over the past decade, some of which have prompted complaints Beijing improperly subsidizes its technology developers and shields them from competition in violation of its free-trade commitments.

Already, Chinese companies including Tencent Ltd., Baidu Inc. and Alibaba Group are spending heavily to develop artificial intelligence for consumer finance, e-commerce, self-driving cars and other applications.

Manufacturers also are installing robots and other automation to cope with rising labor costs and improve efficiency.

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Business leaders weigh in on the possibility of artificial intelligence replacing jobs

Thursday's statement gives no details of financial commitments or legal changes. But previous initiatives to develop Chinese capabilities in solar power and other technologies have included research grants and regulations to encourage sales and exports.

"By 2030, our country will reach a world leading level in artificial intelligence theory, technology and application and become a principal world center for artificial intelligence innovation," the statement said.

That will help to make China "in the forefront of innovative countries and an economic power," it said.

The announcement follows a sweeping plan issued in 2015, dubbed "Made in China 2025," that calls for this country to supply its own high-tech components and materials in 10 industries from information technology and aerospace to pharmaceuticals.

That prompted complaints Beijing might block access to promising industries to support its fledgling suppliers. The Chinese industry minister defended the plan in March, saying all competitors would be treated equally. He rejected complaints that foreign companies might be required to hand over technology in exchange for market access.

China has had mixed success with previous strategic plans to develop technology industries including renewable energy and electric cars.

Beijing announced plans in 2009 to become a leader in electric cars with annual sales of 5 million by 2020. With the help of generous subsidies, China passed the United States last year as the biggest market, but sales totaled just over 300,000.

2017 The Associated Press. All Rights Reserved. This material may not be published, broadcast, rewritten, or redistributed.

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China announces goal of leadership in artificial intelligence by 2030 - CBS News

We expect scary predictions about the technological future from philosophers and science fiction writers, not famous technologists.

Elon Musk, though, turns out to have an imagination just as dark as that of Arthur C. Clarke and Stanley Kubrick, who created the sentient and ultimately homicidal computer HAL 9000 in 2001: A Space Odyssey.

Musk, the founder of Tesla, SpaceX, HyperLoop, Solar City and other companies, spoke to the National Governors Association last week on a variety of technology topics. When he got to artificial intelligence, the field of programming computers to replace humans in tasks such as decision making and speech recognition, his words turned apocalyptic.

He called artificial intelligence, or AI, a fundamental risk to the existence of human civilization. For example, Musk said, an unprincipled user of AI could start a war by spoofing email accounts and creating fake news to whip up tension.

Then Musk did something unusual for a businessman who has described himself as somewhat libertarian: He urged the governors to be proactive in regulating AI. If we wait for the technology to develop and then try to rein it in, he said, we might be too late.

Are scientists that close to creating an uncontrollable, HAL-like intelligence? Sanmay Das, associate professor of computer science and engineering at Washington University, doesnt think so.

This idea of AI being some kind of super-intelligence, becoming smarter than humans, I dont think anybody would subscribe to that happening in the next 100 years, Das said.

Society does have to face some regulatory questions about AI, he added, but theyre not the sort of civilization-ending threat Musk was talking about.

The pressing issues are more like one ProPublica raised last year in its Machine Bias investigation. States are using algorithms to tell them which convicts are likely to become repeat offenders, and the software may be biased against African-Americans.

Algorithms that make credit decisions or calculate insurance risks raise similar issues. In a process called machine learning, computers figure out which pieces of information have the most predictive value. What if these calculations have a discriminatory result, or perpetuate inequalities that already exist in society?

Self-driving cars raise some questions, too. How will traffic laws and insurance companies deal with the inevitable collisions between human- and machine-steered vehicles?

Regulators are better equipped to deal with these problems than with a mandate to prevent the end of civilization. If we write sweeping laws to police AI, we risk sacrificing the benefits of the technology, including safer roads and cheaper car insurance.

Whats going to be important is to have a societal discussion about what we want and what our definitions of fairness are, and to ensure there is some kind of transparency in the way these systems get used, Das says.

Every technology, from the automobile to the internet, has both benefits and costs, and we dont always know the costs at the outset. At this stage in the development of artificial intelligence, regulations targeting super-intelligent computers would be almost impossible to write.

I dont frankly see how you put the toothpaste back in the tube at this point, said James Fisher, a professor of marketing at St. Louis University. You need to have a better sense of what you are regulating against or for.

A good starting point is to recognize that HAL is still science fiction. Instead of worrying about the distant future, Das says, We should be asking about whats on the horizon and what we can do about it.

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Despite Musk's dark warning, artificial intelligence is more benefit than threat - STLtoday.com

While much has been written about information technology companies investing in artificial intelligence, Loup Ventures managing partner Doug Clinton notes that many non-tech companies are capitalizing on AI technology as well.

Clinton has put together a portfolio of 17 publicly traded non-tech companies that are making investments in AI to improve their businesses. In a recent blog post, Clinton notes that he assembled the portfolio as a "fun exercise" and a way to draw attention to the sweeping nature of AI advancements. Loup Ventures is an early-stage venture capital firm.

Clinton selected the companies from a range of industries including health care, retail, logistics, professional services, finance, transportation, energy, construction and food/agriculture.

"In 10 years, every company will have to be an artificial intelligence company or they won't be competitive," Clinton said.

Among the companies included is IBD 50 stock Idexx Laboratories (IDXX). Idexx makes products for the animal health-care sector. On its last earnings call, the company said that its latest diagnostic products are using machine learning so the instruments always have the ability to learn and train on new data. One such product that leverages AI is its SediVue Dx analyzer, Clinton said.

The other companies on the Loup Ventures list are: Accenture (ACN), Avis Budget Group (CAR), Boeing (BA), Caterpillar (CAT), Deere (DE), Domino's Pizza (DPZ), FedEx (FDX) andGlaxoSmithKline (GSK).

There's alsoHalliburton (HAL), Interpublic Group (IPG), Macy's (M), Monsanto (MON), Nasdaq (NDAQ), Northern Trust (NTRS), Pioneer Natural Resources (PXD) and Under Armour (UA).

IBD'S TAKE:Cloud-computing leaders Amazon.com, Microsoft and Google, along with internet giants, have the inside track in monetizing artificial intelligence technology, Mizuho Securities said in a report earlier this month.

Among those venturing into the space, Clinton says:

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These Non-Tech Firms Are Making Big Bets On Artificial Intelligence ... - Investor's Business Daily

July 21, 2017 by Caleb Radford Credit: Ailytic

The Australian wine industry is turning to artificial intelligence to streamline its manufacturing.

South Australian tech firm Ailytic has developed an artificial intelligence (AI) program to significantly increase production efficiency by optimising machine use.

It uses an AI technique called 'prescriptive analytics' to account for all the variables that go into mass-producing wines such temperature, wine changeover and inventory.

The program then creates the best possible operation schedule, allowing companies to save considerable time and money.

Ailytic's list of clients includes world-renown wine companies such as Pernod Ricard, Accolade Wines and Treasury Wine Estates.

It has now included South Australian company Angove Family Winemakers as well.

Pernot Ricard Global Business Solutions Manager Pauline Paterson said AI was highly beneficial for the wine industry and helped to increase the bottom line.

"We use it mainly around production line and use it to derive the most efficient way to produce our product," she said.

"It is definitely helpful with changeover, how many bottles we need, how much wine and what order to do everything in."

Ailytic's system is able to obtain essential information from wineries using remote sensors, which are placed around machines and vineyards.

These sensors track a number of key procedures including the changeover from red to white bottling.

This includes the sub-classification of each colour such as sweet red, dry red, aromatic white and fortified wines.

Ailytic's program ensures that wine is changed quickly, without contamination, bottled using appropriate glassware, labelled and then packaged appropriately.

The sensors then transmit the data to a computer in real time using Wi-Fi.

A single pass can take anywhere between three to six hours but Ailytic's system reduces this by up to 30 per cent.

Pernod Ricard is the world's second leading wine and spirits company, with a network of grows across six countries and 8.68 billion in sales in 2015.

Its brands include Jacobs Creek, Campo Viejo, Brancott Estate, Kenwood Vineyards and Wyndham Estate.

Ailytic co-founder and CEO James Balzary said the company's AI program was perfect for the wine industry because it thrived in complex environments.

"Our algorithms work well for things like packaging, bottling, general manufacturing and sink manufacturing the wine industry is where we are seeing a lot of appetite and the most uptake," he said.

"People think of wine as a romantic artisan type of process, and it is, when you are producing small batch, but the majority of wines we drink are mass manufactured in big operations. That's where we come in the more complex the business, the bigger the benefit."

Ailytic's involvement in wine manufacturing has seen it nominated at the 2017 Wine Industry IMPACT Awards in Adelaide.

Ailytic's other clients are also based out of South Australia and include Australia's lone sink manufacturer Tasman Sinkware.

However, it does plan to expand its clientele and has already garnered international interest in their product.

"Even though the bigger wineries would find this more useful, even smaller operations will benefit from this," Balzary said.

"It's an affordable solution that used to only be accessible to bigger companies but we try to focus on bringing advanced capabilities to T2 and T3 manufacturers."

Explore further: Wine descriptions make people more emotional about wine

Research by the University of Adelaide has shown that consumers are much more influenced by wine label descriptions than previously thought.

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New supply chain research from the Martin J. Whitman School of Management at Syracuse University shows a wine distributor can significantly improve its profits by investing in wine futures, in addition to bottled wine. The ...

A US startup says it has created the world's first "smart" bottle which can keep wine as fresh as the day it was uncorked for up to a month.

To wine makers, stink bugs are more than a nuisance. These tiny pests can hitch rides on grapes going through the wine making process, releasing stress compounds that can foul the smell and taste of the finished product. ...

A French startup is looking to change the way people drink wine, one glass at a time.

US entrepreneur Elon Musk said Thursday he'd received tentative approval from the government to build a conceptual "hyperloop" system that would blast passenger pods down vacuum-sealed tubes from New York to Washington at ...

Google and the EU are gearing up for a battle that could last years, with the Silicon Valley behemoth facing a relentless challenge to its ambition to expand beyond search results.

Cheap, plastic toysno manufacturer necessary. The 2020 toy and game market is projected to be $135 billion, and 3-D printing brings those profits home.

From aerospace and defense to digital dentistry and medical devices, 3-D printed parts are used in a variety of industries. Currently, 3-D printed parts are very fragile and only used in the prototyping phase of materials ...

An underwater robot entered a badly damaged reactor at Japan's crippled Fukushima nuclear plant Wednesday, capturing images of the harsh impact of its meltdown, including key structures that were torn and knocked out of place.

Microsoft's cloud computing platform will be used outside China for collaboration by members of a self-driving car alliance formed by Chinese internet search giant Baidu, the companies announced on Tuesday.

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Artificial intelligence boosts wine's bottom line - Phys.Org

There are few things social media users love more than flooding their feeds with photos of food. Yet we seldom use these images for much more than a quick scroll on our cellphones.

Researchers from MITs Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people's eating habits. In a new paper with the Qatar Computing Research Institute (QCRI), the team trained an artificial intelligence system called Pic2Recipe to look at a photo of food and be able to predict the ingredients and suggest similar recipes.

In computer vision, food is mostly neglected because we dont have the large-scale datasets needed to make predictions, says Yusuf Aytar, an MIT postdoc who co-wrote a paper about the system with MIT Professor Antonio Torralba. But seemingly useless photos on social media can actually provide valuable insight into health habits and dietary preferences.

The paper will be presented later this month at the Computer Vision and Pattern Recognition conference in Honolulu. CSAIL graduate student Nick Hynes was lead author alongside Amaia Salvador of the Polytechnic University of Catalonia in Spain. Co-authors include CSAIL postdoc Javier Marin, as well as scientist Ferda Ofli and research director Ingmar Weber of QCRI.

How it works

The web has spurred a huge growth of research in the area of classifying food data, but the majority of it has used much smaller datasets, which often leads to major gaps in labeling foods.

In 2014 Swiss researchers created the Food-101 dataset and used it to develop an algorithm that could recognize images of food with 50 percent accuracy. Future iterations only improved accuracy to about 80 percent, suggesting that the size of the dataset may be a limiting factor.

Even the larger datasets have often been somewhat limited in how well they generalize across populations. A database from the City University in Hong Kong has over 110,000 images and 65,000 recipes, each with ingredient lists and instructions, but only contains Chinese cuisine.

The CSAIL teams project aims to build off of this work but dramatically expand in scope. Researchers combed websites like All Recipes and Food.com to develop Recipe1M, a database of over 1 million recipes that were annotated with information about the ingredients in a wide range of dishes. They then used that data to train a neural network to find patterns and make connections between the food images and the corresponding ingredients and recipes.

Given a photo of a food item, Pic2Recipe could identify ingredients like flour, eggs, and butter, and then suggest several recipes that it determined to be similar to images from the database. (The team has an online demo where people can upload their own food photos to test it out.)

You can imagine people using this to track their daily nutrition, or to photograph their meal at a restaurant and know whats needed to cook it at home later, says Christoph Trattner, an assistant professor at MODUL University Vienna in the New Media Technology Department who was not involved in the paper. The teams approach works at a similar level to human judgement, which is remarkable.

The system did particularly well with desserts like cookies or muffins, since that was a main theme in the database. However, it had difficulty determining ingredients for more ambiguous foods, like sushi rolls and smoothies.

It was also often stumped when there were similar recipes for the same dishes. For example, there are dozens of ways to make lasagna, so the team needed to make sure that system wouldnt penalize recipes that are similar when trying to separate those that are different. (One way to solve this was by seeing if the ingredients in each are generally similar before comparing the recipes themselves).

In the future, the team hopes to be able to improve the system so that it can understand food in even more detail. This could mean being able to infer how a food is prepared (i.e. stewed versus diced) or distinguish different variations of foods, like mushrooms or onions.

The researchers are also interested in potentially developing the system into a dinner aide that could figure out what to cook given a dietary preference and a list of items in the fridge.

This could potentially help people figure out whats in their food when they dont have explicit nutritional information, says Hynes. For example, if you know what ingredients went into a dish but not the amount, you can take a photo, enter the ingredients, and run the model to find a similar recipe with known quantities, and then use that information to approximate your own meal.

The project was funded, in part, by QCRI, as well as the European Regional Development Fund (ERDF) and the Spanish Ministry of Economy, Industry, and Competitiveness.

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Artificial intelligence suggests recipes based on food photos - MIT News

The Chinese government means to become a major leader in the world of artificialintelligence, via a massive investment in the sector. What The State Council, which disclosed the initiative, did not note is that it is up against U.S. based tech giants like Amazon (NASDAQ: AMZN) and Microsoft (NASDAQ: MSFT). It also has to compete with R&D by the U.S. government and Americas largest universities. The goal, based on those hurdles, is out of reach.

In an announcement, the Peoples Republic disclosed:

The State Council has issued a guideline on developing artificial intelligence (AI), setting a goal of becoming a global innovation center in this field by 2030. The total output value of artificial intelligence industries should surpass 1 trillion yuan ($147.80 billion). A mature theory and technology system should be formed. Developing AI is a complicated and systematic project according to the guideline. An open and coordinated AI innovation system should be constructed to develop not only the technology but also products and market. AI in China should be used to promote the countrys technology, economy, social welfare, maintain national security, and contribute to the world. Breakthroughs should be made in basic theories of AI, such as big data intelligence, multimedia aware computing, human-machine hybrid intelligence, swarm intelligence and automated decision-making. Advanced theories which can potentially transform AI should also be looked at, including advanced machine learning, brain-like computing, and quantum intelligent computing. Trans-boundary research should be promoted to connect AI with other subjects, such as cognitive science, psychology, mathematics, and economics.

A look at Microsofts recent earnings shows how advanced American companies are within the sector. Forits fiscal fourth quarter, which ended June 30, Microsoft posted revenue of $23.3 billion, up from $20.billion in the same quarter a year ago. Net income rose to $6.5 billion from $3.1 billion. And much of the improvement was driven by revenue from cloud initiatives.

Innovation across our cloud platforms drove strong results this quarter, said Satya Nadella, chief executive officer at Microsoft, Customers are looking to Microsoft and our thriving partner ecosystem to accelerate their own digital transformations and to unlock new opportunity in this era of intelligent cloud and intelligent edge.

Granted, even if all Microsofts revenue was from artificial intelligence and cloud operations, it would not come close to the Chinese goal. However, by most measures, Microsofts revenue in the sector is well behind Amazons, and close to sales at Alphabet (NASDAQ: GOOGL). A number of other U.S. companiesalso produce billions of dollars a year in cloud and artificial intelligencesales.

China has an ambitious goal, which does not seem even close to a real one.

By Douglas A. McIntyre

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China Wants To Become Leader In Artificial Intelligence, Somehow - 24/7 Wall St.