Archives for July 2018

Here's Who Wins When Blockchain Meets the Food Chain

Margins are razor-thin in the food industry. So when a bacteria outbreak like E. coli hits, it can really wreak havoc throughout the entire supply chain.

Now, 10 leading food companies plan to build a digital tracking system that’s “the equivalent of FedEx tracking for food.”

That’s how Frank Yiannas, vice president of food safety at Walmart, described it to The Wall Street Journal.

Senior Vice President, IBM Global Industries, Platforms and Blockchain Bridget van Kralingen speaks during the forum Digitalization and the New Gilded Age at the World Bank/IMF spring meetings on Wednesday, April 18, 2018, in Washington. ( AP Photo/Jose Luis Magana)

He’s being coy. It’s a revolution. And investors should take note.

Meet the New ‘Food Trust’

Under Walmart’s leadership, Nestlé SA, Dole Food Co., Driscoll’s, Golden State Foods, Kroger Co., McCormick,  McLane Co., Tyson Foods,  and Unilever, are attempting to do something that has never been done before.

These food industry giants want to create a food trust. They want track food from the farm to the grocery aisle.

If something goes wrong, they will know exactly where it began, and why.

That type of transparency would forever change the food supply chain. It would keep suppliers on their toes.

One wrong move could kill years of goodwill. It would also give distributors and processors unprecedented control.

o make this possible, the food companies will use blockchain. The distributed digital ledger, best known for its role in keeping cryptocurrencies in check, will do the same for the food supply chain.

It will create an electronic verification network in real-time for every single food product in the trust.

Blockchain: The Missing Link in the Food Chain

Blockchain is uniquely suited for this task. That’s because its ledger system is permanent and can’t be altered.

Every time a verified event occurs, a block is created on the chain. And it is viewable by all. That makes the system inherently “trustless,” which in this context means it does not require trust.

Blockchains are popping up everywhere …

In 2017, the Financial Times reported six of the world’s largest banks — Barclays, Credit Suisse, CIBC, HSBC, MUFG and State Street — announced support for the Utility Settlement Coin (USC). That’s a blockchain created by UBS, the Swiss banking giant.

This USC system is supposed to let banks conduct transactions without waiting for traditional money transfers.

In January 2018, Maersk, the container ship conglomerate, announced a blockchain for transoceanic logistics. The Danish company hopes this open-source, digital platform will become the standard for a $4 trillion shipping industry that’s currently drowning in bureaucratic red tape and piracy.

International Business Machines is winning the public relations war. It’s behind the Maersk and food trust blockchains.

However, investors should look elsewhere for blockchain winners …

My research suggests they should focus on Microsoft.

Unlike IBM, the Redmond, Wash., software giant has the cloud computing scale to be a dominant player in blockchain. It also has a history of solving big, real world problems with the technology.

In 2015, the company shifted its business model from selling software licenses to digital subscriptions. The distinction created a flood of partners looking to sell cloud services on Azure, its cloud network.

Microsoft needed a system to quickly assess creditworthiness. The traditional process involved working with individual banks to issue standby letters of credit for the new sellers.

But the process was antiquated, and involved several levels of manual verification. So Microsoft worked with Bank of America to digitize and automate the entire process with blockchain.

Ethereum Enters the Picture

Since 2015, the company has expanded its work with blockchain …

It partnered with ConsenSys, a New York blockchain software company, to bring the Ethereum blockchain to Azure, as a Software-as-a Service layer.

Microsoft leveraged this modularity to win over R3, a consortium of 200 financial institutions. Together, they are developing Corda, a blockchain specifically built to reduce transaction friction in financial services.

In 2017, Bain & Co., a research and analytics firm, estimated $35 billion in operating and capital cost savings for a blockchain of this scale.

For Microsoft, Corda is the gateway. The prize is untold billions in sales of cloud computing services.

It is a big business for Microsoft. In the first quarter of fiscal 2018, Azure commercial cloud revenue jumped 58% to $6 billion.

As businesses move to the cloud, having a blockchain software module is a huge advantage.

The prospects are being reflected in the price. Since 2015, shares have risen an average of 31% annually. And the real growth lies ahead as more companies embrace the cloud and SaaS applications.

FedEx-like tracking for everything is coming. Buy Microsoft shares into any pullback.

China Startups Brace For 'Capital Winter' As VC Funding Slows

Workers use computers at their desks inside a co-working space for start-up companies in Beijing, China. (Photo by Tomohiro Ohsumi/Bloomberg)

After a record amount of money gushed into China’s technology sector and fueled eye-popping valuations for many private companies in recent years, venture capital is said to be drying up and startups should brace themselves for what some industry insiders describe as a “capital winter.”

That’s the view held by several China-based venture capitalists and research firms. Speaking on the sidelines of Forbes Asia’s Under 30 Summit in Hong Kong, a number of young investors and honorees from this year’s list say valuations for private companies in China will return to “more reasonable” levels in the second half of this year. They said “bubble-like” valuation levels had become prevalent in China’s private investment space, as investors poured a staggering 1.2 trillion yuan ($180 billion)— or 1.5% of the country’s gross domestic product— to fund private firms in 2017, according to Beijing-based research firm Zero2IPO.

“There is too much money in China. The not qualified startups are getting funding, and the qualified startups are getting even more funding,” says William Zhao, vice president of Bertelsmann Asia Investments, a fund with more than $1.5 billion under management. “They are good companies, but are they worth that much? I think there is a bubble in it.”

More On ForbesChina To Account For A Quarter Of World’s Top 100 Venture Investors In Five Year

But those days appear to be coming to an end. As Beijing seeks to contain financial risks in the world’s second-largest economy, venture capitalists are having a much more difficult time raising money. This is mainly because authorities are clamping down on riskier investments made by Chinese banks, announcing in April a set of far-reaching rules on their wealth-management businesses. Proceeds raised through such channels have historically accounted for a sizable part of venture capital funding in China, as they were often later used to invest in private companies for higher returns. This can also lead to significant risks as the success of early stage firms is by no means guaranteed.

According to Zero2IPO, in the first three months of this year, venture capital and private equity firms in China raised 206 billion yuan ($31 billion), a 30% decrease from the same period last year. In a recent website post, Wang Ran, chief executive of Beijing-based investment firm CEC Capital, predicted that venture capital funding in China could fall by as much as 80% by year end. For private startups, this means valuation levels would be reduced by 30%, as there would be less money to support their growth, according to the post.

“It is indeed getting very hard for a lot of funds to raise money,” says Patrick Song, chief executive of CEC Data Capital, a fund affiliated with a subsidiary of the state-run China Electronics Corp. “Now, investors are much more cautious in their investment strategy, and valuation levels for many companies are sure to come down.”

Yellow Ofo bikes sit outside of the Park-n-Ride Alameda RTD Station on April 3, 2018 in Denver, Colorado. (Photo by Helen H. Richardson/The Denver Post via Getty Images)

One area that has been singled out for criticism is the so-called sharing economy. In a recent editorial, the state-run Xinhua News Agency said there is a “bubble” in this sector, with companies rushing to launch various product-sharing schemes that don’t have a viable path to profitability. It cited the example of home-sharing startup Zhubaijia, which is similar to Airbnb, but has been suffering from mounting losses that totaled 87 million yuan ($13 million) in 2016 due to fierce competition and high operating costs. In early July, regulators de-listed Zhubaijia from China’s third stock exchange because it failed to file its 2017 annual report on time.

And some of China’s better-known sharing-economy companies are scaling down their operations. After expanding into a dozen global cities in the past two years, Beijing-based bike-sharing startup Ofo laid off the majority of its workforce in the U.S. to re-focus on China. Meanwhile, its biggest rival, Mobike, was acquired in April for $2.7 billion by China’s largest online services platform Meituan. And Guangzhou Yueqi, a smaller player that operates the Xiaoming Bike brand, went bankrupt last year amid fierce competition that has pushed prices down to less than 1 yuan ($0.16) per hour in China. The company has more than 55 million yuan ($8.2 million) in outstanding debt after deploying more than 400,000 bikes across the country since 2016, according to Xinhua.

Meanwhile, as it gets harder to raise money from private investors, a record number of Chinese tech firms are tapping public markets. So far, several dozen Chinese tech firms, including Meituan and the three-year-old e-commerce startup Pinduoduo, have opted for initial public offerings. But the hotly anticipated IPO of smartphone maker Xiaomi valued the company at only about half of its initially proposed target of $100 billion, signaling that the capital markets may not support the lofty valuations set during earlier fundraising rounds for these tech companies.

More On ForbesIPO Of Chinese E-Commerce Firm Pinduoduo Mints New Young Billionaire

But this is not to say that China’s startup boom is over. According to CB Insights, the country was home to 55 unicorns, or private companies with a valuation of $1 billion or more, as of September 2017— a number second only to the U.S. And Ant Financial, the payment affiliate of e-commerce giant Alibaba, took over ride-sharing firm Uber as the world’s highest valued private startup after completing a $14 billion mega-funding round in June.

Moreover, investors seem to be especially optimistic of blockchain technology, the digital ledgers that underpin digital coin transactions. Although Beijing banned initial coin offerings last year to curb illegal fundraising activities, this technology of secured and decentralized data storage still holds a great deal of promises in China. It can be used in industries such as finance and real estate to facilitate faster and more efficient tracking of data and contracts, thereby improving efficiency. Investors are already making early bets now, predicting that blockchain will give birth to China’s next tech behemoth.

“Blockchain will be the next disruptive technology in China,” says Li Yao, partner at China’s Tsing Ventures, a venture capital firm affiliated with the country’s prestigious Tsinghua University. “It will take some time to be ready, but it definitely has a lot of potential in many different markets.”

More On ForbesThe Next Frontier For Billionaire Investor Jim Breyer: China And Blockchain

10 Ways To Improve Cloud ERP With AI & Machine Learning

istock

</div> </div> <p>Capitalizing on new digital business models and the growth opportunities they provide are forcing companies to re-evaluate ERP’s role. Made inflexible by years of customization, legacy ERP systems aren’t delivering what digital business models need today to scale and grow. Legacy ERP systems were purpose-built to excel at production consistency first at the expense of flexibility and responsiveness to customers’ changing requirements. By taking a business case-based approach to integrating Artificial Intelligence (AI) and machine learning into their platforms, Cloud ERP providers can fill the gap legacy ERP systems can’t.</p> <p><strong>Closing</strong><strong> Legacy ERP Gaps With Greater Intelligence And Insight </strong></p> <p>Companies need to be able to respond quickly to unexpected, unfamiliar and unforeseen dilemmas with smart decisions fast for new digital business models to succeed. That’s not possible today with legacy ERP systems. Legacy IT technology stacks and the ERP systems they are built on aren’t designed to deliver the data needed most.</p> <p>That’s all changing fast. A clear, compelling business model and successful execution of its related strategies are what all successful Cloud ERP implementations share. Cloud ERP platforms and apps provide organizations the flexibility they need to prioritize growth plans over IT constraints. And many have taken an Application Programming Interface (API) approach to integrate with legacy ERP systems to gain the incremental data these systems provide. In today’s era of Cloud ERP, rip-and-replace isn’t as commonplace as reorganizing entire IT architectures for greater speed, scale, and customer transparency using cloud-first platforms.</p> <p> </p> <p>New business models thrive when an ERP system is constantly learning. That’s one of the greatest gaps between what Cloud ERP platforms’ potential and where their legacy counterparts are today. Cloud platforms provide greater integration options and more flexibility to customize applications and improve usability which is one of the biggest drawbacks of legacy ERP systems. Designed to deliver results by providing AI- and machine learning insights, Cloud ERP platforms, and apps can rejuvenate ERP systems and their contributions to business growth.</p> <p>The following are the 10 ways to improve Cloud ERP with AI and machine learning, bridging the information gap with legacy ERP systems:</p> <ol> <li><strong>Cloud ERP platforms need to create and strengthen a self-learning knowledge system that orchestrates AI and machine learning from the shop floor to the top floor and across supplier networks.</strong> Having a cloud-based infrastructure that integrates core ERP Web Services, apps, and real-time monitoring to deliver a steady stream of data to AI and machine learning algorithms accelerates how quickly the entire system learns. The Cloud ERP platform integration roadmap needs to include APIs and Web Services to connect with the many suppliers and buyer systems outside the walls of a manufacturer while integrating with legacy ERP systems to aggregate and analyze the decades of data they have generated.</li>

</ol>

Boston Consulting Group, AI in The Factory of the Future, April 2018

</div> </div> <ol start="2"> <li><strong>Virtual agents have the potential to redefine many areas of manufacturing operations, from pick-by-voice systems to advanced diagnostics.</strong> Apple’s Siri, Amazon’s Alexa, Google Voice, and Microsoft Cortana have the potential to be modified to streamline operations tasks and processes, bringing contextual guidance and direction to complex tasks. An example of one task virtual agents are being used for today is guiding production workers to select from the correct product bin as required by the Bill of Materials. Machinery manufacturers are piloting voice agents that can provide detailed work instructions that streamline configure-to-order and engineer-to-order production. Amazon has successfully partnered with automotive manufacturers and has the most design wins as of today. They could easily replicate this success with machinery manufacturers.</li> </ol>

Company websites

</div> </div> <ol start="3"> <li><strong>Design in the Internet of Things (IoT) support at the data structure level to realize quick wins as data collection pilots go live and scale.</strong> Cloud ERP platforms have the potential to capitalize on the massive data stream IoT devices are generating today by designing in support at the data structure level first. Providing IoT-based data to AI and machine learning apps continually will bridge the intelligence gap many companies face today as they pursue new business models. Capgemini has provided an analysis of IoT use cases shown below, highlighting how production asset maintenance and asset tracking are quick wins waiting to happen. Cloud ERP platforms can accelerate them by designing in IoT support.</li> </ol>

Source: Capgemini Internet of Things (IoT) study, Unlocking the business value of IoT in operations

</div> </div> <ol start="4"> <li><strong>AI and machine learning can provide insights into how Overall Equipment Effectiveness (OEE) can be improved that aren’t apparent today.</strong> Manufacturers will welcome the opportunity to have greater insights into how they can stabilize then normalize OEE performance across their shop floors. When a Cloud ERP platform serves as an always-learning knowledge system, real-time monitoring data from machinery and production assets provide much-needed insights into areas for improvement and what’s going well on the shop floor.</li> </ol>

Industry Analysis

</div> </div> <ol start="5"> <li><strong>Designing machine learning algorithms into track-and-traceability to predict which lots from which suppliers are most likely to be of the highest or lowest quality.</strong> Machine learning algorithms excel at finding patterns in diverse data sets by continually applying constraint-based algorithms. Suppliers vary widely in their quality and delivery schedule performance levels. Using machine learning, it’s possible to create a track-and-trace application that could indicate which lot from which supplier is the riskiest and those that are of exceptional quality as well.</li> <li><strong>Cloud ERP providers need to pay attention to how they can help close the configuration gap that exists between PLM, CAD, ERP and CRM systems by using AI and machine learning.</strong> The most successful product configuration strategies rely on a single, lifecycle-based view of product configurations. They’re able to alleviate the conflicts between how engineering designs a product with CAD and PLM, how sales &amp; marketing sell it with CRM, and how manufacturing builds it with an ERP system. AI and machine learning can enable configuration lifecycle management and avert lost time and sales, streamlining CPQ and product configuration strategies in the process.</li> <li><strong>Improving demand forecasting accuracy and enabling better collaboration with suppliers based on insights from machine learning-based predictive models is attainable with higher quality data.</strong> By creating a self-learning knowledge system, Cloud ERP providers can vastly improve data latency rates that lead to higher forecast accuracy. Factoring in sales, marketing, and promotional programs further fine-tunes forecast accuracy.</li> <li><strong>Reducing equipment breakdowns and increasing asset utilization by analyzing machine-level data to determine when a given part needs to be replaced.</strong> It’s possible to capture a steady stream of data on each machine’s health level using sensors equipped with an IP address. Cloud ERP providers have a great opportunity to capture machine-level data and use machine learning techniques to find patterns in production performance by using a production floor’s entire data set. This is especially important in process industries where machinery breakdowns lead to lost sales. Oil refineries are using machine learning models comprise more than 1,000 variables related to material input, output and process perimeters including weather conditions to estimate equipment failures.</li> <li><strong>Implementing self-learning algorithms that use production incident reports to predict production problems on assembly lines needs to happen in Cloud ERP platforms.</strong> A local aircraft manufacturer is doing this today by using predictive modeling and machine learning to compare past incident reports. With legacy ERP systems these problems would have gone undetected and turned into production slowdowns or worse, the line having to stop.</li> <li><strong>Improving product quality by having machine learning algorithms aggregate, analyze and continually learn from supplier inspection, quality control, Return Material Authorization (RMA) and product failure data.</strong> Cloud ERP platforms are in a unique position of being able to scale across the entire lifecycle of a product and capture quality data from the supplier to the customer. With legacy ERP systems manufacturers most often rely on an analysis of scrap materials by type or caused followed by RMAs. It’s time to get to the truth about why products fail, and machine learning can deliver the insights to get there.</li> </ol> <p>&nbsp;</p>” readability=”40″>

Capitalizing on new digital business models and the growth opportunities they provide are forcing companies to re-evaluate ERP’s role. Made inflexible by years of customization, legacy ERP systems aren’t delivering what digital business models need today to scale and grow. Legacy ERP systems were purpose-built to excel at production consistency first at the expense of flexibility and responsiveness to customers’ changing requirements. By taking a business case-based approach to integrating Artificial Intelligence (AI) and machine learning into their platforms, Cloud ERP providers can fill the gap legacy ERP systems can’t.

Closing Legacy ERP Gaps With Greater Intelligence And Insight

Companies need to be able to respond quickly to unexpected, unfamiliar and unforeseen dilemmas with smart decisions fast for new digital business models to succeed. That’s not possible today with legacy ERP systems. Legacy IT technology stacks and the ERP systems they are built on aren’t designed to deliver the data needed most.

That’s all changing fast. A clear, compelling business model and successful execution of its related strategies are what all successful Cloud ERP implementations share. Cloud ERP platforms and apps provide organizations the flexibility they need to prioritize growth plans over IT constraints. And many have taken an Application Programming Interface (API) approach to integrate with legacy ERP systems to gain the incremental data these systems provide. In today’s era of Cloud ERP, rip-and-replace isn’t as commonplace as reorganizing entire IT architectures for greater speed, scale, and customer transparency using cloud-first platforms.

New business models thrive when an ERP system is constantly learning. That’s one of the greatest gaps between what Cloud ERP platforms’ potential and where their legacy counterparts are today. Cloud platforms provide greater integration options and more flexibility to customize applications and improve usability which is one of the biggest drawbacks of legacy ERP systems. Designed to deliver results by providing AI- and machine learning insights, Cloud ERP platforms, and apps can rejuvenate ERP systems and their contributions to business growth.

The following are the 10 ways to improve Cloud ERP with AI and machine learning, bridging the information gap with legacy ERP systems:

  1. Cloud ERP platforms need to create and strengthen a self-learning knowledge system that orchestrates AI and machine learning from the shop floor to the top floor and across supplier networks. Having a cloud-based infrastructure that integrates core ERP Web Services, apps, and real-time monitoring to deliver a steady stream of data to AI and machine learning algorithms accelerates how quickly the entire system learns. The Cloud ERP platform integration roadmap needs to include APIs and Web Services to connect with the many suppliers and buyer systems outside the walls of a manufacturer while integrating with legacy ERP systems to aggregate and analyze the decades of data they have generated.

Boston Consulting Group, AI in The Factory of the Future, April 2018

  1. Virtual agents have the potential to redefine many areas of manufacturing operations, from pick-by-voice systems to advanced diagnostics. Apple’s Siri, Amazon’s Alexa, Google Voice, and Microsoft Cortana have the potential to be modified to streamline operations tasks and processes, bringing contextual guidance and direction to complex tasks. An example of one task virtual agents are being used for today is guiding production workers to select from the correct product bin as required by the Bill of Materials. Machinery manufacturers are piloting voice agents that can provide detailed work instructions that streamline configure-to-order and engineer-to-order production. Amazon has successfully partnered with automotive manufacturers and has the most design wins as of today. They could easily replicate this success with machinery manufacturers.

Company websites

  1. Design in the Internet of Things (IoT) support at the data structure level to realize quick wins as data collection pilots go live and scale. Cloud ERP platforms have the potential to capitalize on the massive data stream IoT devices are generating today by designing in support at the data structure level first. Providing IoT-based data to AI and machine learning apps continually will bridge the intelligence gap many companies face today as they pursue new business models. Capgemini has provided an analysis of IoT use cases shown below, highlighting how production asset maintenance and asset tracking are quick wins waiting to happen. Cloud ERP platforms can accelerate them by designing in IoT support.

Source: Capgemini Internet of Things (IoT) study, Unlocking the business value of IoT in operations

  1. AI and machine learning can provide insights into how Overall Equipment Effectiveness (OEE) can be improved that aren’t apparent today. Manufacturers will welcome the opportunity to have greater insights into how they can stabilize then normalize OEE performance across their shop floors. When a Cloud ERP platform serves as an always-learning knowledge system, real-time monitoring data from machinery and production assets provide much-needed insights into areas for improvement and what’s going well on the shop floor.

Industry Analysis

  1. Designing machine learning algorithms into track-and-traceability to predict which lots from which suppliers are most likely to be of the highest or lowest quality. Machine learning algorithms excel at finding patterns in diverse data sets by continually applying constraint-based algorithms. Suppliers vary widely in their quality and delivery schedule performance levels. Using machine learning, it’s possible to create a track-and-trace application that could indicate which lot from which supplier is the riskiest and those that are of exceptional quality as well.
  2. Cloud ERP providers need to pay attention to how they can help close the configuration gap that exists between PLM, CAD, ERP and CRM systems by using AI and machine learning. The most successful product configuration strategies rely on a single, lifecycle-based view of product configurations. They’re able to alleviate the conflicts between how engineering designs a product with CAD and PLM, how sales & marketing sell it with CRM, and how manufacturing builds it with an ERP system. AI and machine learning can enable configuration lifecycle management and avert lost time and sales, streamlining CPQ and product configuration strategies in the process.
  3. Improving demand forecasting accuracy and enabling better collaboration with suppliers based on insights from machine learning-based predictive models is attainable with higher quality data. By creating a self-learning knowledge system, Cloud ERP providers can vastly improve data latency rates that lead to higher forecast accuracy. Factoring in sales, marketing, and promotional programs further fine-tunes forecast accuracy.
  4. Reducing equipment breakdowns and increasing asset utilization by analyzing machine-level data to determine when a given part needs to be replaced. It’s possible to capture a steady stream of data on each machine’s health level using sensors equipped with an IP address. Cloud ERP providers have a great opportunity to capture machine-level data and use machine learning techniques to find patterns in production performance by using a production floor’s entire data set. This is especially important in process industries where machinery breakdowns lead to lost sales. Oil refineries are using machine learning models comprise more than 1,000 variables related to material input, output and process perimeters including weather conditions to estimate equipment failures.
  5. Implementing self-learning algorithms that use production incident reports to predict production problems on assembly lines needs to happen in Cloud ERP platforms. A local aircraft manufacturer is doing this today by using predictive modeling and machine learning to compare past incident reports. With legacy ERP systems these problems would have gone undetected and turned into production slowdowns or worse, the line having to stop.
  6. Improving product quality by having machine learning algorithms aggregate, analyze and continually learn from supplier inspection, quality control, Return Material Authorization (RMA) and product failure data. Cloud ERP platforms are in a unique position of being able to scale across the entire lifecycle of a product and capture quality data from the supplier to the customer. With legacy ERP systems manufacturers most often rely on an analysis of scrap materials by type or caused followed by RMAs. It’s time to get to the truth about why products fail, and machine learning can deliver the insights to get there.

Louis Columbus is an enterprise software strategist with expertise in analytics, cloud computing, CPQ, Customer Relationship Management (CRM), e-commerce and Enterprise Resource Planning (ERP).

I am currently serving as Principal, IQMS. Previous positions include product management at Ingram Cloud, product marketing at iBASEt, Plex Systems, senior analyst at AMR Research (now Gartner), marketing and business development at Cincom Systems, Ingram Micro, a SaaS start…

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Google's Grand Plan To Make AI Accessible To Developers And Businesses

Artificial intelligence took center stage at Google’s annual user conference, Cloud Next 2018. The company made several announcements that make machine learning and artificial intelligence accessible to both developers and businesses.

Fei-Fei Li, Chief Scientist, Google AISource: Google

One of the first announcements came in the form of Cloud AutoML, a managed service that lets developers build machine learning models without requiring any specialized knowledge in machine learning or coding. AutoML Vision, along with other automated ML services became publicly available. According to Google, it is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs, by leveraging Google’s state-of-the-art transfer learning, and Neural Architecture Search technology.

With AutoML, developers use a simple graphical user interface (GUI) to train, evaluate, improve, and deploy models based on their own data. Apart from computer vision, AutoML also offers translation and natural language models. AutoML Natural Language helps customers to predict custom text categories specific to domains automatically. With AutoML Translation, they can upload translated language pairs to train custom translation models.

Google has also enhanced its cognitive computing APIs. Cloud Vision API now recognizes handwriting, supports additional file types (PDF and TIFF) and product search, and can identify where an object is located within an image. The improvements to Cloud Text-to-Speech include multilingual access to voices generated by DeepMind WaveNet technology and the ability to optimize for the type of speaker from which the speech is intended to play. Cloud Speech-to-Text added the ability to identify what language is spoken as well as different speakers in a conversation, word-level confidence scores, and multi-channel recognition. With this enhancement, customers can record each participant separately in multi-participant recordings.

Dialogflow, the platform to build bots, can now be used to build AI-powered virtual agents for the contact center, including phone-based conversational agents known as interactive voice response (IVR). Google Cloud Contact Center, an AI solution based on Dialogflow, includes new features alongside other tools to assist live agents and to perform analytics.

With Dialogflow Phone Gateway, customers can assign a working phone number to the virtual agent and begin taking calls. The dynamic platform can scale based on the utilization patterns. Behind the scenes, all of the telephony infrastructure, speech recognition, speech synthesis, natural language understanding and orchestration are managed automatically.

Another component of Dialogflow Enterprise, the Dialogflow Knowledge Connector understands unstructured documents like FAQs or knowledge base articles to automatically build intents with automated responses sourced from internal document collections, enriching the conversational experience with little extra effort. The added information extracted from the knowledge base is integrated with the Dialogflow agent to deliver conversational user experience.

Apart from the above enhancements, Dialogflow now includes automatic spelling correction, sentiment analysis and text-to-speech capabilities.

Google is integrating its cloud-based machine learning assets with Dialogflow to build an intelligent contact center. The platform includes an agent assist system to provide the call center agents with relevant information through suggested articles and shortcuts for fulfilling relevant tasks in real time. Another feature called the Conversational Topic Modeler uses Google AI to analyze historical audio and chat logs to uncover insights about topics and trends in customer interactions.

Google is working with several industry players to integrate Cloud Contact Center AI with mainstream contact center platforms.

From automated ML to AI-based contact center, Google wants AI to become accessible to both developers and enterprises.

Southwest Airlines Says It Won't Do This Incredibly Annoying Thing That Other Airlines Always Do (And Passengers Rejoice)

Case in point: There’s a lot of stuff to get annoyed about with air travel. But my #1 pet peeve is when flight attendants insist that you listen to them while they try to sell you on an airline-sponsored credit card.

Mental muscle memory

Of course, there are times when it’s crucial that you pay attention to the cabin crew. Even if you’ve flown 100 times this year, it’s still useful to hear the safety instructions–if only for mental muscle memory in the event of an actual emergency.

And if you’ve memorized it all, at least you can understand the benefit of being quiet so that other not-so-frequent fliers can absorb the information.

But a lot of airlines go beyond that. They turn off the in-flight entertainment and insist that passengers sit still and quiet while the flight attendants pitch you on a credit card.

It’s doubly annoying when you already have the credit card that they’re pitching you.

Flight attendants on both United and American get paid commissions for each credit card they sell: between $50 and $100 depending on the circumstances.

Not even optional?

On United Airlines it’s not even optional: As my colleague Chris Matyszczyk recently wrote, flight attendants are actually being required to try to make sales on every flight. (The flight attendants say they don’t like the policy anymore than the passengers do.)

People worried recently, when Southwest Airlines announced that it was going to launch a branded credit card of its own.

Would it mean that we’d start hearing credit card pitches on LUV? Would singing flight attendants be replaced with hawking salespeople?

My friends, we needn’t have worried. 

‘No plans for an onboard sales program’

Writing in the Chicago Business Journal, the utterly indefatigable Lewis Lazare reports that Southwest says it has “no plans for an onboard sales program for the new Priority card.”

That means no brochures for busy flight attendants to hand out, no “lean[ing] heavily on passengers to consider signing up for the new card,” and no annoying on-board announcements trying to hawk the new credit card.

By the way, as Lazare aptly summarizes, Southwest’s new credit card comes with:

  • a $149 annual fee 
  • 7,500 anniversary Rapid Rewards points each year 
  • a $75 annual Southwest travel credit, 
  • 20 percent back on inflight purchases, and 
  • up to four upgraded boardings per year when available

Is that a good deal, then? Should you apply for a Southwest Airlines-branded Chase Rapid Rewards Priority? 

I have no skin in the game either way. And maybe neither should your flight attendant.
 

Facebook’s Biggest Problem? A Crisis of Words.

“The [executive] either has a meaning and cannot express it, or he inadvertently says something else, or he is almost indifferent as to whether his words mean anything or not.”

The quote is from Politics and the English Language and while George Orwell never made Facebook CEO Mark Zuckerberg his object of scorn—the original reads “writer” in place of “executive”—he would have been right to do so. More than any other company today, Facebook has a freakish inability to use words.

Facebook’s penchant for verbal nonsense is neither new nor particularly unique in a corporate world that loves self-interested spin. But today, that habit is driving a crisis of trust engulfing the Silicon Valley company. The failure of its executives, particularly co-founder Zuckerberg, to speak in plain, candid language during earnings calls and other appearances is a big reason that Facebook can’t escape the moral quagmire that led to an overnight plunge in its lofty stock price.

Want an example of Facebook’s failure with words? Begin with Zuckerberg’s bizarre insistence that he doesn’t run a media company. Facebook has long operated a global broadcast channel with more viewers than any television station on the planet, and has gobbled much of the advertising revenue once enjoyed by traditional media outlets. Yet in testifying before Congress in April, Zuckerberg again would not concede the obvious proposition that Facebook is a media company.

“I consider us to be a technology company,” he told lawmakers on Capitol Hill. Many observers interpreted the response as an attempt to shirk responsibility for Facebook’s role as a purveyor of news, video, and other media in the wake of Russian interference in U.S. elections.

Such prevarications are akin to the CEO of a large energy company declaring, when confronted with a massive spill: “We’re not an oil company.” In Facebook’s case, the company pumps its own pollution in the form of fake news, troll armies, and conspiracy theories. At Facebook’s scale, it amounts to a massive sludge of toxic media. If Zuckerberg truly hopes to clean it up, he can start by admitting he’s in the media business.

Another example of what Orwell called “debased language” is Facebook’s invocation of “the community” to justify behavior that is abhorrent and wrong. Most recently, executives muttered about “community standards” in a limp defense of why Facebook allows Holocaust deniers or the noxious conspiracy site InfoWars to flourish on its platform.

Zuckerberg himself has invoked “the community” over and over to explain Facebook’s foot-dragging. But as sociologist Zeynep Tufekci pointed out, Zuckerberg has failed to explain how the 2 billion people who use Facebook can possibly be defined as a community.

I called Facebook to learn more about what “community” means to the company, to little avail. A spokesperson said Facebook develops guidelines “with the community in mind” and on the basis of “safety, equity, and voice.” I asked the spokesperson to explain how a billion people can be “a community” and she simply referred me back to the guidelines.

The exchange underscored why New York Times columnist Farhad Manjoo has concluded that Facebook’s stated policies make no sense. “All of this fails a basic test: It’s not even coherent. It is a hodgepodge of declarations and exceptions and exceptions to the exceptions,” Manjoo wrote while describing Zuckerberg’s verbal contortions about Holocaust deniers using the service.

The incoherence is frustrating but, worse, it’s disempowering. When Zuckerberg defends Facebook’s latest outrage in the name of the community, it puts all of us in that community—you and me and the trolls and the hate-mongers and yes, the Holocaust deniers. No decent person wants to be part of such a community. Most see a community as a group of people who share similar values and with whom they choose to identify. To Zuckerberg, the word apparently means something else.

“Platforms like Facebook, which exist for the express purpose of ‘creating community,’ turn out to be in the business of exploiting the communities they’ve created for the benefit of those outside (the business community, the strategic communications community, the Moldovan hacker community),” explains writer Carina Chocanoa. “They invite members to ‘participate,’ but not, in the end, to make decisions together; the largest rewards, and the greatest powers, stay private.”

If Zuckerberg wants to cling to the word “community,” he will have to make some hard decisions about who is part of that community and who is not. Such a decision should be informed by law and ethics and philosophy—not a slapdash jumble of words compiled by his public relations team.

In a remarkable farewell letter this month, a longtime Facebook executive, Alex Stamos, made this very point. Using blunt and very understandable language, Stamos attributed the company’s current predicament to thousands of small decisions and called for a change. “We need to be willing to pick sides when there are clear moral or humanitarian issues,” Stamos wrote in the letter, first published by BuzzFeed. (Stamos served as chief information security officer at Facebook.)

That clarity—of words and thoughts and deeds—is what’s needed from Zuckerberg if he wants to lift his company out of the moral muck. One way to start would be for him to jettison what Orwell called “lump[s] of verbal refuse” and speak to Facebook users in clear English.

Qualcomm's $44 billion NXP offer deadline passes, no word from China

SAN FRANCISCO/BEIJING (Reuters) – The deadline for Qualcomm Inc (QCOM.O) to buy NXP Semiconductors (NXPI.O) passed at midnight U.S. eastern time without any word on Chinese regulatory approval, likely shutting the door on a deal embroiled in a bitter U.S.-China spat.

Qualcomm had said earlier in the day that it would drop its $44 billion bid for NXP – the world’s biggest semiconductor takeover – unless it received a last minute reprieve. If the deal is terminated, Qualcomm will pay a $2 billion deal breakup fee to NXP no later than 09:00 ET on July 26.

There was no word from China’s State Administration for Market Regulation or Qualcomm after the time for the deal to expire passed. Qualcomm did not immediately respond to a request for comment.

Investors expressed relief at Qualcomm’s comments earlier in the day and the company’s shares rose nearly 7 percent in after market trading. The San Diego chipmaker delivered surprisingly strong third-quarter results and a rosy outlook for so-called 5G technology, the next generation of wireless data networks.

The company also said earlier on Wednesday that it will buy back $30 billion in shares if the deal ultimately failed, making good on a promise to reassure investors about its prospects.

Qualcomm still faces challenges, including expectations that its chips will not be in the next round of Apple’s iPhones and the need to find new markets beyond mobile phones without NXP’s help. But it cited progress on one of two major patent royalty conflicts, thought to be with Chinese phonemaker Huawei Technologies Co Ltd [HWT.UL], in the form of a $700 million interim agreement.

The collapse of the deal may discourage other U.S. firms hoping to buy into China’s huge developing markets and companies, although technology deals seemed the main concern.

“We obviously got caught up in something that was above us,” Qualcomm Chief Executive Steve Mollenkopf said in an interview after the announcement earlier in the day.

“We think moving on, reducing the amount of uncertainty in the business and increasing the focus is the right thing to do with the company.”

Qualcomm needed approval from China, the last of nine global regulators to be consulted, because the country accounted for nearly two-thirds of its revenue last year.

FILE PHOTO: A sign on the Qualcomm campus is seen in San Diego, California, U.S. November 6, 2017. REUTERS/Mike Blake

Barring a last-minute reprieve, the chipmaker said in its results release it would make good on a pledge with NXP to call off the merger if it had not won Chinese regulatory approval by 23:59 Eastern U.S. time on Wednesday.

NXP Semiconductors shares fell almost 4 percent to $94.50.

TRUMP’S ROLE

Moves by the Trump administration have played an outsized role in Qualcomm’s fate, and there had been expectations that the lifting of a ban on U.S. chipmakers doing business with China’s ZTE Corp (000063.SZ) would clear the way for the NXP deal.

Dealmakers advising on mergers and acquisitions hoped the fallout would be limited to the technology sector in which China is racing for primacy against the United States.

United Technologies Corp (UTX.N) chief Gregory Hayes said earlier this week that the industrial conglomerate was on track with regulatory approvals to close its $23 billion acquisition of U.S. airplane-parts maker Rockwell Collins Inc (COL.N), seeking to quell fears that China could delay its review.

No other major semiconductor deal is pending. Broadcom, whose $117 billion hostile bid for Qualcomm was blocked by the United States in March on national security grounds, says its $19 billion purchase of U.S. software company CA Technologies (CA.O) does not require China’s blessing.

For Qualcomm, the deal’s demise means it will have to focus on expanding beyond making mobile chips.

Qualcomm predicted on Wednesday that Apple would drop the company’s chips from its next-generation iPhones in favor of modems from Intel Corp (INTC.O), the latest sign of fallout from their acrimonious battle over pricing and licensing costs. Qualcomm’s revenue projections had already assumed it would gain no new revenue from Apple.

Intel and Apple both declined to comment.

Qualcomm sold $3 billion of chips last year for non-phone use, up 75 percent from two years ago. It has a $5 billion “backlog” of chip sales to the automotive industry, in which NXP is also a dominant player, it said.

Reporting by Michael Martina in Beijing and Greg Roumeliotis in New York; Additional reporting by Adam Jourdan and Ben Blanchard in Beijing; Writing by Patrick Graham and Sayantani Ghosh; Editing by Meredith Mazzilli, Richard Chang and Muralikumar Anantharaman

Retailers set sights on Facebook, Google ad revenue

BERLIN/CHICAGO (Reuters) – People with hay fever hate dust. That was the premise of a marketing drive launched by British vacuum cleaner maker Dyson with U.S. retailer Target Corp.

FILE PHOTO: Facebook, Amazon, Alibaba and Google logos are seen in this combination photo from Reuters files. REUTERS/File Photos

Using data about its customers’ shopping habits, Target homed in on shoppers who likely had allergies and showed them ads for Dyson’s cordless V6 vacuum on social media and Target’s website. The result: sales for the vacuums doubled among shoppers who regularly purchase anti-allergy treatments and products such as Claritin or humidifiers on Target.com and in stores.

Data about real people and real behaviors “actually get a much stronger result because the fidelity of that data is so much richer,” said Kristi Argyilan, Target’s senior vice president of media and guest engagement.

Retailers ranging from Target and Walmart Inc to grocers such as Tesco Plc are working aggressively to attract big advertisers to their websites in a bid to drive sales, according to interviews with retailers, packaged goods makers, consumer data firms and marketing consultants.

Specifically, they are selling more ad space, pop-up banners and search-bar keywords to consumer goods companies such as Kraft Heinz Co and Procter & Gamble Co. These makers of everything from soup to shampoo are investing more to advertise on retailers’ websites where people who already have an intent to buy are guided to specific products using their individual shopping habits.

This online ad revenue offers significantly higher margins for retailers than selling goods in stores.

By carving out a space for themselves in the booming digital ad market, they are taking on Alphabet Inc’s Google and Facebook Inc and the $114 billion they received last year in global online ad revenue. According to research company eMarketer, Google and Facebook’s revenue accounted for nearly half of the global market in 2017.

For a Graphic, click tmsnrt.rs/2K04vpc

Supermarkets have long charged brands to place products in the busiest parts of their stores, such as near the checkout counter.

As more shopping shifts online, e-commerce giants Amazon.com Inc and Alibaba Group Holding Ltd pioneered replicating that strategy on their websites by mining data to target advertising at selected customers or groups. Amazon ad revenue alone could jump to $6.6 billion by 2019 from $2.8 billion last year, according to JPMorgan.

While retailers have a long way to go before they come close to Google and Facebook digital advertising prowess, their instant access to data on what is selling puts stores in a strong position, said Joe Zawadzki, chief executive of MediaMath, which helps brands manage ad campaigns.

“To the extent that the retailer can help the manufacturer, it becomes a new revenue opportunity and a way forward for them,” he said. “We’re very much at the start of this.”

Alphabet and Facebook declined to comment. To be sure, retailers and brands for the foreseeable future will still be drawn to advertise with Facebook and Google given the internet giants’ massive customer base in order to drive traffic to their websites. And the Silicon Valley companies likely will make overtures to long-time clients of theirs to avoid losing business.

BANNERS, POP-UPS AND MONEY BACK

Retailers are offering a range of marketing options online, including banner ads, pop-ups and money-off deals. As with Google, suppliers can pay for keywords to get their products listed at the top of any search.

Some industry observers expect voice aides like Amazon’s Alexa may one day let brands pay to be the first product recommended when a shopper asks to purchase an item such as ketchup, a feature known as “Amazon’s Choice.” Amazon told Reuters it has no plans to let companies pay for the distinction, “nor do we have plans to advertise on Alexa broadly.”  

“We’re making sure that when consumers are typing in ‘ketchup’, our product is really above, that it comes up into that first screen,” Nina Barton, Kraft Heinz president of global online and digital growth, told Reuters in an interview.

Barton said Kraft Heinz, the owner of the Philadelphia cream cheese and Planters peanuts brands, was on track to spend four times more on e-commerce marketing in 2018 than it did last year, including advertising on social media, search engines and retailer’s websites.

Consumer companies bid against one another for thousands of keywords such as “ketchup” or “chocolate,” often even snatching up keywords that are important to rival brands to undercut them, said Nii Ahene, co-founder CPC Strategy, a digital marketing agency that advises several major consumer packaged goods companies, including Unilever.

Retailers are paid anything from 25 cents to $2 each time a shopper clicks on a sponsored search item, depending on the product being sold,  he said. Ads for supplements, for instance, cost a premium as people are more likely to buy the same vitamins repeatedly and that means more sales for the consumer company, according to Ahene.

“Companies like Kraft Heinz and Nestle have always paid for a premium placement, whether it’s at the front of the store, in an end-cap or premium placement on a shelf. This is simply the evolution of existing processes to a digital storefront,” he said.

SALES IMPACT

The push by retailers comes as some major brands question the value of some online ads.

Procter & Gamble, the world’s biggest advertiser, pressured Facebook and Alphabet’s YouTube and other media companies to reveal how many people see their ads and how ad agencies spend advertising dollars.

The average view time for an ad on a mobile news feed is just 1.7 seconds, Marc Pritchard, P&G’s chief brand officer, told the Association of National Advertisers’ media conference in March.

“Even Facebook and Google can’t tell P&G properly whether their ads have worked, whereas if you’re buying retail media we can measure whether there has been a statistically significant uplift from running that media campaign,” said Guillaume Bacuvier, a former Google advertising executive who is now chief executive of customer data company Dunnhumby, which is owned by British supermarket Tesco.

The average time that an ad is viewable on retailer sites is about 16 seconds, according to Dunnhumby, which defines “viewable” as when at least half of the ad is on the screen.

In one case, Tesco ran banner adverts on its website for a leading brand of dishwasher tablets. Dunnhumby said almost 100,000 pounds ($132,000) of sales came from customers exposed to the ad, with 6 percent of the sales happening in a store.

That translated into a return on advertising spending of $11.34 for every $1 invested, according to Dunnhumby, noting that more than 2,200 new customers had added the brand to their online favorites list as a result of the campaign. That is far more than an average return on ad spend of $2.62 for every $1 invested across all media types, according to a 2016 Nielsen report.

It is those kinds of numbers that are helping win over marketing experts including Andrew Clarke at Mars Inc, another major advertiser and the maker of M&M’s candy and Wrigley’s gum.

“The advantage potentially of these players is they can help really demonstrate the impact of our marketing dollars on a transaction, both online and potentially offline as well,” Clarke told Reuters. ($1 = 0.7577 pounds)

Additional reporting by Kate Holton, Dominique Vidalon, Lisa Baertlein, Martinne Geller and Jeffrey Dastin; editing by Vanessa O’Connell and Edward Tobin

Can We Trust The Health Claims For Hyped Foods? A New Research Review Tests The Evidence

(Photo by Ben Pruchnie/Getty Images)

We’re awash in hyped claims made about the health-impacts of countless foods and supplements. Determining which claims are backed by credible evidence isn’t always easy – contradiction is more common than clarity. A new review of “controversial and hyped” foods conducted by a team of researchers from the American College of Cardiology (the second in a series) attempts to inject some clarity by evaluating health claims against an array of research, with particular focus on heart health.

The review divides foods into three categories: Evidence of harm; Lacking in evidence of harm or benefit; and Evidence of benefit. For each food, the team evaluated the research and concluded with “bottom line” recommendations guided by the evidence.

In the “Evidence of harm” category, added sugars are unsurprisingly at the top of the list. “Added sugars promote atherogenesis [a disorder in which plaques form in artery walls] and increase cardiovascular disease (CVD) risk,” the review reports.

The evidence particularly points to the dangers of high fructose corn syrup (HFCS), which, despite claims by sugar industry lobbyists, does not affect the body in exactly the same way as other forms of sugar. Quoting from the paper: “Although sucrose and HFCS are now believed to be metabolically equivalent, their fructose and glucose moieties [chemical reactions] are not. Fructose uptake by the liver is unregulated and induces greater hepatic lipogenesis [process involved in storing energy as fat] than does glucose.”

The researchers recommend strictly limiting consumption of added sugars, especially sugary sodas, fruit drinks and sports drinks that account for half of our added-sugar intake: “Individuals should limit added sugar to less than 10% of calories, and preferably less than 100 calories daily for women and less than 150 calories daily for men.”

Energy drinks also rank high on the evidence-of-harm list for a slew of health badness, including “increased blood pressure, platelet aggregation, and arrhythmia risk.”

Dairy products sit prominently in the “Lacking in evidence of harm or benefit” category. While they’re often high in saturated fat, they’re also high in vitamins, minerals and high-quality protein. “It appears that there is no clear consensus in the published data or among experts on the effects of dairy products on CVD,” the review notes.

Fermented foods, including yogurt and kimchi, also appear in the lacking-evidence category, with research starting to show potential health benefits of these gut-bacteria boosting foods. In general, however, the science is still too murky to support recommending them for heart health, although there’s also no evidence of harm.

The “Evidence of benefit” category is the biggest, featuring legumes, coffee, tea, omega-3 fatty acids, mushrooms and moderate alcohol consumption.

Coffee, the recent star of several studies showing health benefits, gets ample coverage here as well, with the conclusion that drinking a little each day is a great idea as long as it’s not loaded with sugar. “Moderate, habitual coffee consumption reduces risk for stroke, diabetes, premature death and digestive diseases,” the review confirms.

Tea also earns high marks, with strong evidence that it “improves artery health, reverses blood vessel dysfunction and reduces cholesterol.”

Omega-3 fatty acids from both plant and marine sources receive a favorable nod for “reducing CVD risk and improving lipid profiles,” but omega-3s from fish seem to provide the clearest benefits (with the caveat that eating fish lower on the food chain is recommended to avoid ingesting too much mercury).

Mushrooms and legumes are both recommended as diet additions for being high in antioxidants and heart-healthy fiber. Although research to-date hasn’t found strong heart health benefits from eating mushrooms, they “may be associated with improvement in inflammatory and antioxidative pathways and may have beneficial effects on known CVD comorbid risk factors.”

Alcohol is the most controversial item in the review. The researchers say that while credible research shows real upsides of moderate consumption (“vasodilatory, antiplatelet and anti-inflammatory properties”), the negatives may overshadow the benefits. “It is not recommended that individuals initiate alcohol consumption for health benefit, and for those already drinking, consumption should be limited to recommended amounts and preferably consumed with meals,” the researchers add in a cautionary footnote.

The research review, part 2 in a series, was published in the Journal of the American College of Cardiology

You can find David DiSalvo on Twitter, FacebookGoogle Plus, and at his website, daviddisalvo.org.

How Southeast Asia's EdTech Startups Could Reinvent Education

(Photo by Taylor Weidman/Getty Images)

The cliché is true: education is highly valued in fast-growing Asian countries. The issue is how to provide quality education for the millions who now demand it, in settings from big cities like Bangkok and Hanoi to remote rural areas. While various nations push to improve their school systems, new waves of education technology (EdTech) firms are entering the scene as well—and they’re starting to offer solutions that could transform how learning is done.

EdTech is an emergent growth sector throughout this region. Many companies have products and services that seem, at first glance, to be fairly standard stuff. There are mobile apps children can use to learn basic skills via digital games and quizzes; there are platforms to link students of all ages with online tutors.

But a closer look often reveals new twists which have broader potential. How about a mobile app with videos and practice tests in a variety of subjects—plus a chat function for access to a standby tutor, in case you get stuck, and referrals to longer-term help (either online or in person) if needed? That’s Ruangguru, a “one-stop learning” company founded by two young Indonesians who last year made the Forbes 30 Under 30 list in the Asia/Consumer Tech category.

Tech-enabled eduactionhttp://compasslist.com/insights/10_and-the-winner-is-ruangguru

Startups in other EdTech niches are doing notable work, too. Let’s meet some, after a quick overview of the social and market forces that are bringing them forth.

The shift from catch-up to leapfrog 

Multiple factors are driving demand for better education of all kinds, at all levels, across Southeast Asia. Growing economies need skilled workers. Parents want bright futures for their children. Post-secondary education, ideally at a university, has become the goal of many. And nearly everybody wants or needs to learn English, which makes English instruction a booming field in itself.

Now for the challenges. Public budgets in most ASEAN countries aren’t lavish. Most have made great strides in providing universal access to schooling, but still wrestle with raising the quality. Bringing the whole picture up to world-class standards the traditional way is a tough proposition, as it would require training vastly more top-notch teachers and sending them everywhere, accompanied by massive upgrades to curricula and resources.

This opens the door to non-traditional approaches. The growth of mobile and internet penetration opens it wider. Information technology can’t solve every education problem, nor can it substitute for person-to-person learning. It can, however, facilitate interaction and multiply the impact of each person.

Stanley Han is the founder and CEO of KooBits, a company with an app for helping teach the Singapore math curriculum. In an email to me, he wrote:

“Engaging students to learn has always been the job of a teacher. However, the latest EdTech development in Asia has seen platforms that are able to successfully engage learners at scale. As a result, these students’ learning is becoming self-directed and collaborative in nature. Teachers benefit from such platforms because their time is freed up to do more important coaching and mentoring.”

Han is clear on his long-term vision for Asean countries. “I believe a learner-centric platform, facilitated by technology, will help democratize access to quality content and teaching, and will scale easily across the region.”

Such a vision is a paradigm shift in two senses. It shifts the frame of reference from teachers (who are scarce) to learners (who are many), and it aims to leapfrog existing best practices, not catch up to them. Here are more paradigm-shifting examples.

Developing digital tools and platforms to help children learn betterhttp://mushings.com/2014/08/13/koobits-math/

One-stop shopping and ‘blended’ platforms

XSeed, based in Singapore and branching to other countries, is a B2B firm, selling the educational equivalent of enterprise software to schools. But XSeed offers more than Western firms like U.S.-based Blackboard. The Blackboard software is essentially a digital infrastructure that teachers can use for posting assignments, fielding questions from students, and so forth. XSeed includes content, embodied in digital materials such as learning apps for students and lesson plans for teachers. This is a “one-stop solution” of a different kind than Ruangguru’s, allowing schools to buy infrastructure plus state-of-the-art curricula in a unified, relatively cost-effective package.

For parents and older students in Southeast Asia, online guides to educational resources are popular. One of the most informative is the Malaysian website EduAdvisor. The site has thoughtfully written intros to careers in a wide range of fields, from computer science to culinary arts. Then come comparison tables listing universities and schools that teach the subjects, from Malaysia to Australia. Like similar sites, EduAdvisor is free for users, getting revenue from referral fees and ads. Unlike some, it appears to be genuinely useful and includes a growing menu of related services.

Finally, there are multitudes of companies teaching English. They’ve taken off as rising incomes combined with rising aspirations have led more people to pay for lessons. A big fish in this pond is China-based online tutoring firm ABC360, which rode a $15 million round of series B financing, while expanding into the Philippines and Thailand. Another interesting one is a company in Vietnam called Yola.

Yola uses an O2O (online-to-offline) model. Some basic English skills are taught or reinforced through an app, but the key element is bringing students to in-person programs at Yola’s training centers in the Hanoi and Ho Chi Minh City areas.

Tu Ngo, cofounder and VP of Yola, says a “blended” approach of this type may be the template for future education in all subjects.

Vietnam’s YOLA, changing lives through educationhttps://edu2review.com/danh-gia/trung-tam-ngoai-ngu-thong-minh-yola

Ngo thinks a time is close when “startups will design a full high-quality blended online and offline learning journey.” This, she says, will “ultimately transform the way students learn for the 21st century. Instead of EdTech serving as supplementary tools to existing schools or teachers, or supplementing for lower quality public education, I can see many experimental, innovative schools working with technology to redefine the ‘school experience’ altogether.”

“If they can crack this model not only for the premium/elite market, but also for the mass affordability market, that would have huge impacts,” says Ngo. She sees a number of ways it could be possible, both in Southeast Asia and worldwide.

The biggest opportunity for EdTech in Southeast Asia, is that it is less tied to legacy institutions and systems than most places are—which opens up the possibilities for major EdTech advances to happen here first.