Customization & Conversation Meet Your Clients Where They Are

Customization & Conversation Meet Your Clients Where They Are


Therefore, 79% of firms think their clients desire SMS assistance. If you desire high reaction prices from pleased clients, these data show that text-messaging is the method to go.

Given that messaging applications surpassed social networking applications in appeal in 2014, there’s been a great deal of bandwagon-jumping stress for services to swiftly release customer-facing chatbots right into Facebook Carrier, WhatsApp, as well as various other messaging networks.

Unless business currently started the discussion using your favored messaging application, there’s no evident location to begin. Just how would certainly business recognize which is your recommended messaging application, anyways? There are numerous options currently, similar to social media sites, as well as none is best for everybody. Suppose business went all-in on WhatsApp, as well as you just utilize Carrier? Prior to you have actually ever before spoken to the business for consumer assistance, you’re upset.

Envision momentarily: Where would certainly you go initially when you have an issue with a service? Allow’s claim you should make an adjustment to your airline company trip plan, or return a malfunctioning item that you purchased online. Are you mosting likely to open up Facebook Carrier? Just how would certainly you also launch that discussion?

While I locate these usage situations intriguing, I have actually been hesitant of this fad given that it started in 2014. Are messaging applications actually the very best location to give client service? As well as are chatbots– also innovative ones– properly to reply to the expanding need for text-based client assistance?

The future of chatbots for companies is not in messaging applications, yet in TEXT.
SMS is chosen by lots of for text-based assistance.
It holds true that messaging applications have actually surpassed social networks, however that does not indicate that’s the very best area for customer care from your service. These metrics confirm just the applications’ appeal, not their energy or their capability to offer your clients’ demands ideal.

However are messaging applications truly the most effective location to supply client service? Or is the most effective tool one that your clients currently utilize day-to-day – SMS messaging?

Prior to your company gets on the messaging train, take a go back as well as evaluate the landscape. As opposed to aiming to make use of all the messaging applications you believe your consumers may be utilizing in the future, or attempting to “go where the millennials are,” why rule out a trustworthy, steady innovation that additionally has the merit of being a tool your customers currently make use of and also enjoy, and also where there’s a tried and tested reaction price and also need?

SMS reaction prices vanquish various other kinds of text-based interaction
Many people have e-mail also, you might say, so why not utilize e-mail? Isn’t really that a tried and tested network of consumer interaction? While that holds true, inning accordance with the Bench Proving ground, temporary reaction prices for sms message are continually more than e-mail. Text for advertising have a 98% open price, while e-mail open prices just balance concerning 20%. Typically, text read within 5 secs. Furthermore, 97% of smart device customers make use of message messaging frequently, making it one of the most widely-used smart device function.

As an organisation, you could eliminate the concern which messaging application to sustain by developing your text-based assistance networks by means of SMS rather. Everybody that has a mobile phone with among the messaging applications additionally has a contact number and also an integrated texting application. Also individuals that do not have mobile phones (though they could be progressively less in specific Western nations) could obtain a fantastic consumer assistance experience with a text string. Rather than fretting about where your consumers could be, depend on SMS to discover them where they currently are.

Meet Your Consumers Where They Currently Are with SMS Chatbots
Brand names are under a great deal of stress to produce consumer-facing chatbots for Facebook Carrier, WhatsApp as well as their very own applications.

Ideal techniques for SMS chatbots for consumer interaction
SMS isn’t really going anywhere, in spite of exactly what the Chief executive officers of messaging business could like you think. When it concerns client service, take into consideration releasing an SMS chatbot over a messaging application one, to far better offer your consumer’s demands. If you have actually made a decision the moment is ideal for your firm to release an SMS chatbot, take into consideration these ideal techniques initially, to guarantee you’re offering optimum worth for your customers:

This suggests that crawlers improved TEXT will certainly quickly have an abundant user interface as the criterion, which will certainly equip much better, extra constant interaction throughout tools– without needing customers to download and install an application or close friend any person. Watch on information concerning RCS, as it’s something you’ll likely be reading about in the coming quarters.
When it pertains to chatbots, just what not to touch with a ten-foot stick
Lastly, there’s a lengthy checklist of “Do n’ts” for chatbots. Right here’s a list of points you ought to not made with SMS chatbots:
Do not send out cruel spam or overuse SMS messages (as an example, to share info the individual currently saw online or in your application).

( It do without claiming that you must exercise great health with essentials like customer opt-in and also conformity with the Telephone Customer Security Act as well as various other appropriate laws).

If you’re seeking motivation, below are some modern-day crawlers that give genuine worth:
Reply Yes offers an ecommerce solution over mobile messaging. The client enters their contact number, and afterwards the solution messages them item pictures as well as summaries. The consumer could react LIKE, DISAPPROVAL, or OWN to individualize future choices. Or, as the name suggests, respond YES to buy the item.
Number assists individuals conserve loan with little financial institution transfers and also smart evaluation of their savings account equilibriums as well as purchases. While it has applications for iphone as well as Android, its TEXT user interface is extensive as well as individuals do not have to download and install the application to obtain one of the most from it.

Your consumers will certainly thanks.

Do not be newfangled– or individuals will not involve with you for long.
Just what makes a robot actually wonderful? Inning accordance with Robert Hoffer, that worked with among the initial effective chatbots on the web, “the majority of developers concur crawlers should have something looking like a human character.” Although his production, AOL Split second Carrier’s SmarterChild, had not been all that advanced, it had a dampness that we do not usually see in contemporary robots. At its optimal, SmarterChild talked with 250,000 individuals a day.

Resources One has its very own crawler for financial clients called Eno. Consumers could utilize it to quickly figure out even more concerning their loan.
StaffJoy informs your group regarding organizing updates, making sure that adjustments to a complicated timetable never ever obtain missed out on. This could be made use of making assistance groups, storehouses, shipment business, or dining establishments extra efficient.

If a human is anticipated, do not make it difficult to obtain to a human on the line (like lots of voice-based client service lines presently do).
Actually, if you’re a smaller sized organisation, or currently have a customer support personnel, think about sliding the crawler completely, and also making TEXT a network to get to genuine individuals.
On the other hand, if a crawler could address a concern as well as handling an individual is unneeded, do not make the consumer speak with an individual to obtain a response.

Do not auto-message clients with aggressive or intrusive sales pitches.
Do not make use of robots as a replacement genuine individuals when an individual touch is required.
Do not produce a chatbot just since you believe its character is enjoyable. Clients do not desire enjoyment– they desire aid!

The lower line is: do not utilize a chatbot since it’s brand-new and also glossy. Just include one right into your interaction process if it truly enhances the consumer experience. And also do not be sidetracked by the appeal of brand-new messaging applications. Rather, fulfill your clients where they currently are with text-based interaction via TEXT– as well as, when proper, with chatbots because high-touch network.

Do not disregard consumers with legit issues or make use of a “we’ll solve back to you” autoresponder, afterwhich no person ever before subsequents.

Do not release chatbots that state the exact same point over as well as over once more, or have no individuality.

Locate methods making it clear just what the limits of the robot’s capacities are, as well as to interact to the individual what it could as well as (unconditionally, a minimum of) can not do.
Fail beautifully by constantly carrying out pleasant, helpful rejections and also mistake messages, like “I’m sorry, I’m not comprehending the concern– I’ll attach you to my human associate.” Those outs will certainly aid you stay clear of producing the message interaction matching of roadway craze.

If your firm wants leveraging an existing All-natural Language Handling or AI system to construct a crawler, as well as DeepPIXEL both offer expert system, consisting of all-natural language handling (NLP), to improve as well as equip client service as well as sales groups. A 3rd alternative, Conversable, “powers the crossway of AI with messaging as well as voice.”
Ultimately, for an enjoyable instance, Botline Bling allows any person imitate a texting partnership with the musician Drake.
A lot more great information: SMS disadvantage
tinues to advance. Take the introduction of the RCS (” Rich Communications Solution”) requirement, a campaign sustained by an enhancing variety of service providers around the globe. While big providers are still assembling around exactly how the industry will certainly function, RCS (occasionally called “Advanced Messaging”) makes it possible for abundant customer communications, vibrant components, and also analytics, right in the messaging inbox.

How we determine who’s to blame

How do people assign a cause to events they witness? Some philosophers have suggested that people determine responsibility for a particular outcome by imagining what would have happened if a suspected cause had not intervened.

This kind of reasoning, known as counterfactual simulation, is believed to occur in many situations. For example, soccer referees deciding whether a player should be credited with an “own goal” — a goal accidentally scored for the opposing team — must try to determine what would have happened had the player not touched the ball.

This process can be conscious, as in the soccer example, or unconscious, so that we are not even aware we are doing it. Using technology that tracks eye movements, cognitive scientists at MIT have now obtained the first direct evidence that people unconsciously use counterfactual simulation to imagine how a situation could have played out differently.

“This is the first time that we or anybody have been able to see those simulations happening online, to count how many a person is making, and show the correlation between those simulations and their judgments,” says Josh Tenenbaum, a professor in MIT’s Department of Brain and Cognitive Sciences, a member of MIT’s Computer Science and Artificial Intelligence Laboratory, and the senior author of the new study.

Tobias Gerstenberg, a postdoc at MIT who will be joining Stanford’s Psychology Department as an assistant professor next year, is the lead author of the paper, which appears in the Oct. 17 issue of Psychological Science. Other authors of the paper are MIT postdoc Matthew Peterson, Stanford University Associate Professor Noah Goodman, and University College London Professor David Lagnado.

Follow the ball

Until now, studies of counterfactual simulation could only use reports from people describing how they made judgments about responsibility, which offered only indirect evidence of how their minds were working.

Gerstenberg, Tenenbaum, and their colleagues set out to find more direct evidence by tracking people’s eye movements as they watched two billiard balls collide. The researchers created 18 videos showing different possible outcomes of the collisions. In some cases, the collision knocked one of the balls through a gate; in others, it prevented the ball from doing so.

Before watching the videos, some participants were told that they would be asked to rate how strongly they agreed with statements related to ball A’s effect on ball B, such as, “Ball A caused ball B to go through the gate.” Other participants were asked simply what the outcome of the collision was. 

As the subjects watched the videos, the researchers were able to track their eye movements using an infrared light that reflects off the pupil and reveals where the eye is looking. This allowed the researchers, for the first time, to gain a window into how the mind imagines possible outcomes that did not occur.

“What’s really cool about eye tracking is it lets you see things that you’re not consciously aware of,” Tenenbaum says. “When psychologists and philosophers have proposed the idea of counterfactual simulation, they haven’t necessarily meant that you do this consciously. It’s something going on behind the surface, and eye tracking is able to reveal that.”

The researchers found that when participants were asked questions about ball A’s effect on the path of ball B, their eyes followed the course that ball B would have taken had ball A not interfered. Furthermore, the more uncertainty there was as to whether ball A had an effect on the outcome, the more often participants looked toward ball B’s imaginary trajectory.

“It’s in the close cases where you see the most counterfactual looks. They’re using those looks to resolve the uncertainty,” Tenenbaum says.

Participants who were asked only what the actual outcome had been did not perform the same eye movements along ball B’s alternative pathway.

“The idea that causality is based on counterfactual thinking is an idea that has been around for a long time, but direct evidence is largely lacking,” says Phillip Wolff, an associate professor of psychology at Emory University, who was not involved in the research. “This study offers more direct evidence for that view.”

In this video, two participants’ eye-movements are tracked while they watch a video clip. The blue dot indicates where each participant is looking on the screen. The participant on the left was asked to judge whether they thought that ball B went through the middle of the gate. Participants asked this question mostly looked at the balls and tried to predict where ball B would go. The participant on the right was asked to judge whether ball A caused ball B to go through the gate. Participants asked this question tried to simulate where ball B would have gone if ball A hadn’t been present in the scene. (Image: Tobias Gerstenberg)

How people think

The researchers are now using this approach to study more complex situations in which people use counterfactual simulation to make judgments of causality.

“We think this process of counterfactual simulation is really pervasive,” Gerstenberg says. “In many cases it may not be supported by eye movements, because there are many kinds of abstract counterfactual thinking that we just do in our mind. But the billiard-ball collisions lead to a particular kind of counterfactual simulation where we can see it.”

One example the researchers are studying is the following: Imagine ball C is headed for the gate, while balls A and B each head toward C. Either one could knock C off course, but A gets there first. Is B off the hook, or should it still bear some responsibility for the outcome?

“Part of what we are trying to do with this work is get a little bit more clarity on how people deal with these complex cases. In an ideal world, the work we’re doing can inform the notions of causality that are used in the law,” Gerstenberg says. “There is quite a bit of interaction between computer science, psychology, and legal science. We’re all in the same game of trying to understand how people think about causation.”

The research was funded by the National Science Foundation through MIT’s Center for Brains, Minds and Machines, and by the Office of Naval Research.


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Cable Cleats Market Regulations, Size, Share and Competitive Landscape Outlook to 2025

According to a new market research report published by Credence Research “Cable Cleats Market (By Material: Metallic and Non-metallic; By Number of Cores: Single Core and Multicore) – Growth, Future Prospects, and Competitive Landscape, 2017-2025”, cable cleats market was valued at US$ 559.6 Mn in 2016 and is estimated to grow at a CAGR of 5.9% from 2017 to 2025.

Market Insights

Cable cleat is a cable management product used to support and hold cables installed on trays/ladders or without conduit systems. These are useful in ensuring long life of cables as they reduce damage caused to the cables due to their own weight. Cable cleats have been useful in applications having heavy cables, power lines and transportation infrastructure.

The complete report is available at

The market for cable cleats worldwide has received the necessary impetus from revival of the construction industry post economic recession. Additionally, the market has been witnessing impressive growth since the introduction of cable cleats of standard EN 50368 in 2003. Another major factor driving market growth is the advantages offered by cable cleats for effective cable management. Holding and maintaining the cable position even in the most critical conditions such as short circuits are easily handled by cable cleats. With the consistently growing efforts in innovating cleat designs, the market growth is estimated to remain strong throughout the forecast period.

The cable cleat providers across the world focus majorly on providing cable management solutions specific to different applications. This has significantly impacted the cable cleats industry in a positive manner. Manufacturers are now inclined towards designing cable cleats that can be used for specific applications such as high power cables, railway power cables, commercial buildings and several others. Cable cleat manufacturer emphasizes on expanding their product portfolio that can cater to varying requirements. These may include physical strength, various levels of short circuits, area of installation and several others. The trend is primarily governed by the consistently increasing competition in the overall cable management systems market worldwide.

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Competitive Insights:

The market for cable cleats is fairly unorganized and is characterized by a large number of local as well as international cable cleat manufacturers. Big players face tough competition from local players in terms of price and availability. Companies have been engaged in coming up with new and improved product designs and aim towards expanding their sales and distribution network. The use of more stable materials is one of the prime focus of cable cleats manufacturers. Major players in the market include Ellis Patents Ltd., Remora Electrical Limited, BICON, Eland Cables Limited, CMP Products Limited, Oglaend System Group, Nantong Naco Fluid Equipment Co. Ltd., IPD Group Limited, TransDelta International Industries L.L.C and Novoflex Marketing Pvt. Ltd.

Key Trends:

– Providing application specific solutions for cable management

– Distribution network expansion and acquisitions

– Consistently growing demand for cable cleats from the energy sector

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Celebrating the life of doctoral student and alumnus Michael B. Cohen

Michael B. Cohen ’14, SM ’16 had a deep love for mathematics and the theoretical foundations of computing — a love that was infectious, brilliant, and always shared with others. Cohen, a doctoral student in the Department of Electrical Engineering and Computer Science (EECS), died suddenly from natural causes in September. He was 25 years of age.

At the time of his passing, Cohen was visiting the University of California at Berkeley, where he had gone to meet with colleagues at the Simons Institute for the Theory of Computing. A member of the Theory of Computing group at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, he had roots in the Washington area.

Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director CSAIL, said, “We are all still stunned by the news of the passing of Michael Cohen. Michael was a beloved student at CSAIL, a brilliant colleague in the theory group, and a joyful presence everywhere he went. This is a huge and collective loss for the entire CSAIL community.”

Cohen first came to MIT as an undergraduate student, and he lived in East Campus. He earned his bachelor’s in mathematics in 2014, having skipped his second year at MIT to work at Facebook. He then stayed on at MIT to pursue a graduate degree in computer science.

Scott Aaronson, a professor of computer science at the University of Texas at Austin who taught at MIT from 2007 to 2016, recalled Cohen as a particularly motivated first year student, ready to solve open problems, or basically tackle anything.

Writing on his blog, Aaronson noted that when he met Cohen he realized at once that he “was a freshman who I could — must — talk to like an advanced grad student or professor.” In his class on quantum complexity theory, Cohen had the habit of sitting in the front row and carrying on dialogues with Aaronson, often catching any errors or “unjustified claims.” At the same time, Aaronson was impressed by Cohen’s intellectual humility, as his focus was on understanding and clarifying tough concepts for everyone in the class, not showing off. Such openness led to Cohen “having a huge circle of friends.”

His fellow MIT students described him as “energetic, fun, and supportive,” and admired his irrepressible spirit of “exuberance and generosity.” Cameron Musco, a doctoral student in the same lab as Cohen and a frequent co-author, wrote, “It was impossible to ignore his energy, wonder, and excitement for research, current events, and everything in between.” Cohen was a notable presence on the 5th and 6th floors of the Stata Center at MIT, Musco also recalled, “always … surrounded by a group of friends happy to banter or simply to listen. He was a natural teacher — truly kind, humble, welcoming, positive, and always willing to slow his thoughts for a moment to share his brilliance.”

Cohen was an intellectual tour-de-force beyond the campus as well. He spent a summer at Microsoft Research, where he quickly cemented a reputation for “his larger-than-life personality” and academic brilliance. A statement by the team he worked with at Microsoft read: “Michael was a brilliant mathematician and a rising star in his field. … [H]e made sweeping progress in online learning and online algorithms, two fields he had just recently become acquainted with. In addition to solving five open problems in these areas, he continued his substantial progress on the k-server problem, one of the most celebrated and notoriously difficult challenges in the space of adaptive algorithms.”

Sebastien Bubeck, a researcher in the Theory Group at Microsoft Research who worked alongside Cohen, shared what he called a “typical Michael story,” about when they first met in October 2016 at MIT: “We were about to start lunch with a small group of graduate students and Michael entered the room, he (gently) interrupted the conversation and his first sentence to me was a question about mirror descent that I was not able to answer. (We now know the answer, and as it turns out his question was pretty deep and the answer highly non-trivial.)”

Bubeck, like many others, was also struck by Cohen’s remarkable way of doing mathematics, primarily never writing anything on paper. James R. Lee, a professor of computer science at University of Washington, said, “His mind was always going at 100 mph, so it was remarkable that he didn’t miss a beat in calibrating (i.e., slowing down) for an audience (or for those who did not know him).”

Luca Trevisan, a professor of electrical engineering and computer science at Berkeley, noted that “in a few short years, Michael left his mark on a number of problems.” At the time of his death, Cohen was credited as a co-author on papers with more than 30 distinct collaborators. Tom Cohen, Michael’s father, remarked that his son, “more than anything, wished to become part of that community and to engage in a meaningful way on relevant research in the field.” Cleary, he achieved that and much more, becoming a leading light in the theoretical computer science community.

As Lee wrote, “one got the sense that this was all a warmup for Michael. It’s really disheartening that we won’t get to see what comes next.” He and others have committed to ensuring that Cohen’s work is more than just remembered, but spread far and wide and used to tackle the kinds of open problems that he adored.

Those wishing to making contributions in Cohen’s name should consider, a charity he admired that provides money to poor people in Africa.


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Point of Sale Terminals Market (POS Market) forecast by 2022 published by leading research firm

Emerging technologies increases the demand for the POS (Point of sale) Terminal Market; convenience and flexibility of POS terminals minimized customers waiting time, improved billing process, maintained customer records safely as per security concerns, data back up and pertaining personal information of customer confidential, may inhibit the global POS terminal market.

Digital payment anticipated the POS terminal market growth valued at approximately US$45.97 Bn in 2016 and expected to reach approximately US$98.27 Bn by 2022. Increasing demand for wireless technologies expected to witness growth at 20% of CAGR in between 2017 and 2022.

Click Here To Brows Report on Point of sale (POS) Terminals Market :

POS terminals transmit encrypted tokens during the payment process; its advanced feature includes inventory management, CRM financials and the proliferation of NFC and EMV-enabled devices may drive the industrial market in the next years.

The geographical distribution of the global POS terminals market considered the regional markets of North America, Europe, Asia Pacific, Latin America and rest of the world.

In regional segmentation North America accounted the largest market share of POS terminal followed with Europe and Asia-Pacific respectively. The North America dominated the POS terminal market with the rising adoption of wireless technology across the hospitality applications, restaurants, automotive shops and grocery stores. However the region of Asia-Pacific surprisingly anticipated the POS terminal market with the growing CAGR of 13% in upcoming future. Rapid advancements in the card acceptance and use of debit cards are expected to serve high growth over the forecast period in Asia-Pacific region; especially in India and China; where supermarkets are owing to grow in the upcoming years. It will drive the global revenue of the POS terminals market.

Increasing governmental support in order to improve the digital transaction with advanced technologies boosted the global market of the POS terminals especially in developed economies like Asia-Pacific region. The growing usage of POS terminals with NFC devices in the industrial and retail sector will expected to drive CAGR of 10% over the forecast period. A sustainable governmental effort to promote the computerized payment instead of traditional transaction with cash register will encourage the POS terminal market in this region.

The competitive market for the POS terminals includes New POS technology, NCR Corporation, NFC Corporation, PAX technology, Veri fone Systems, Ingenico SA, Panasonic Corporation, Toshiba Corporation, Cisco Systems and others.

Click Here To Download Full Report Sample on Point of sale (POS) Terminals Market :

Application segment of the POS terminals include healthcare, retail, hospitality, entertainment, warehouses, automotive shops, grocery stores and e-commerce sites. The growing usage of POS terminals in these segments witnessed a significant turnaround over the forecast period.

On the basis of component segment POS terminal market segmented into hardware and software, it simplifies the accounting process and promotes the digital payment platform. Card acceptance increases the merchants to enroll the digital transaction will exhibit remarkable opportunities and growth in the POS terminal market.

An advanced and appropriate POS terminal can simplifies the transaction process and save time and money with efficient customer services, it is highly adopted by retailers and e-Commerce companies as per security concerns and confidential financial information of the customers.

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Automotive Lightweight Materials Market is expected to reach US$ 180.9 Bn by 2025, expanding at a CAGR of 13.1% from 2017 to 2025.

According to a new market research report published by Credence Research, Inc. “Automotive Lightweight Materials Market – Growth, Future Prospects and Competitive Analysis, 2017 – 2025,” automotive lightweight material market was valued at US$ 59.7 Bn in 2016, and is expected to reach US$ 180.9 Bn by 2025, expanding at a CAGR of 13.1% from 2017 to 2025.

Market Insights

Lightweight materials help to decrease the weight of the vehicle and reduce energy consumption. Technological advancement, worldwide increase in vehicle production and rise in disposable income are the major factors driving the growth of automotive lightweight material market. Government regulation on environmental and standard enforced to cut down CO2 emission and technological evolution are driving the global automotive lightweight materials market. High cost associated with lightweight materials may restrain the growth of automotive lightweight materials market.

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Chassis and suspension comprise more than 30% of the overall weight of the vehicle, which creates the huge market for the lightweight materials. The lightweight materials which is used in chassis and suspension are AHSS and aluminum. The plastic materials segment is likely to grow at the fastest rate in the forecast period due to increased usage of plastic in automobile interiors, such as seats, dashboard, instrument panel, and interior roofs. Electric vehicles uses large amount of lightweight materials, as these are mainly driven by battery, wherein lightweight materials help to improve their performance.

North America and Europe were the largest regional markets for automotive lightweight materials. Advanced fuel economy, growing demand for low CO2 emission and stringent government regulations are supporting the lightweight materials market in the region. Government raised the norms such as CAFÉ fuel standards and EPA Tier-3 norms for light duty vehicles, to ensure that a vehicles produced from now on would be much lighter in weight. North America has the largest market for light trucks. In North America highest demand for automotive lightweight material is majorly driven by U.S. Asia Pacific will be the fastest growing region in the forecast period due to an increase in the production of automobiles followed by rise in the demand for fuel efficient vehicles. In Asia Pacific demand is manly comes from countries like India, China, and Japan.

Some of the major companies operating in the market include Alcoa, Inc., BASF SE, Thyssenkrupp AG, Covestro AG, Arcelormittal S.A., Lyondellbasell Industries N.V., Novelis, Inc., Toray Industries, Inc., PPG Industries, Inc., and Owens Corning.

Browse the full Automotive Lightweight Materials Market – Growth, Future Prospects and Competitive Analysis, 2017 – 2025 report at

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Bug-repair system learns from example

Anyone who’s downloaded an update to a computer program or phone app knows that most commercial software has bugs and security holes that require regular “patching.”

Often, those bugs are simple oversights. For example, the program tries to read data that have already been deleted. The patches, too, are often simple — such as a single line of code that verifies that a data object still exists.

That simplicity has encouraged computer scientists to explore the possibility of automatic patch generation. Several research groups, including that of Martin Rinard, an MIT professor of electrical engineering and computer science, have developed templates that indicate the general forms that patches tend to take. Algorithms can then use the templates to generate and evaluate a host of candidate patches.

Recently, at the Association for Computing Machinery’s Symposium on the Foundations of Software Engineering, Rinard, his student Fan Long, and Peter Amidon of the University of California at San Diego presented a new system that learns its own templates by analyzing successful patches to real software.

Where a hand-coded patch-generation system might feature five or 10 templates, the new system created 85, which makes it more diverse but also more precise. Its templates are more narrowly tailored to specific types of real-world patches, so it doesn’t generate as many useless candidates. In tests, the new system, dubbed Genesis, repaired nearly twice as many bugs as the best-performing hand-coded template system.

Thinning the herd

“You are navigating a tradeoff,” says Long, an MIT graduate student in electrical engineering and computer science and first author on the paper. “On one hand, you want to generate enough candidates that the set you’re looking through actually contains useful patches. On the other hand, you don’t want the set to include so many candidates that you can’t search through it.”

Every item in the data set on which Genesis was trained includes two blocks of code: the original, buggy code and the patch that repaired it. Genesis begins by constructing pairs of training examples, such that every item in the data set is paired off with every other item.

Genesis then analyzes each pair and creates a generic representation — a draft template — that will enable it to synthesize both patches from both originals. It may synthesize other, useless candidates, too. But the representation has to be general enough that among the candidates are the successful patches.

Next, Genesis tests each of its draft templates on all the examples in the training set. Each of the templates is based on only two examples, but it might work for several others. Each template is scored on two criteria: the number of errors that it can correct and the number of useless candidates it generates. For instance, a template that generates 10 candidates, four of which patch errors in the training data, might score higher than one that generates 1,000 candidates and five correct patches.

On the basis of those scores, Genesis selects the 500 most promising templates. For each of them, it augments the initial two-example training set with each of the other examples in turn, creating a huge set of three-example training sets. For each of those, it then varies the draft template, to produce a still more general template. Then it performs the same evaluation procedure, extracting the 500 most promising templates.

Covering the bases

After four rounds of this process, each of the 500 top-ranking templates has been trained on five examples. The final winnowing uses slightly different evaluation criteria, ensuring that every error in the training set that can be corrected will be. That is, there may be a template among the final 500 that patches only one bug, earning a comparatively low score in the preceding round of evaluation. But if it’s the only template that patches that bug, it will make the final cut.

In the researchers’ experiments, the final winnowing reduced the number of templates from 500 to 85. Genesis works with programs written in the Java programming language, and the MIT researchers compared its performance with that of the best-performing hand-coded Java patch generator. Genesis correctly patched defects in 21 of 49 test cases drawn from 41 open-source programming projects, while the previous system patched 11.

It’s possible that more training data and more computational power — to evaluate more candidate templates — could yield still better results. But a system that allows programmers to spend only half as much time trying to repair bugs in their code would be useful nonetheless.


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