Amazon’s one-two punch: How traditional retailers can fight back

If you think physical retail is dead, you couldn’t be more wrong. Despite the explosion in e-commerce, we’re still buying plenty of stuff in offline stores. In 2017, U.S. retail sales totaled $3.49 trillion, of which only 13 percent (about $435 billion) were e-commerce sales. True, e-commerce is growing at a much faster annual pace. But we’re still very far from the tipping point.

Amazon, the e-commerce giant, is playing an even longer game than everyone thinks. The company already dominates online retail — Amazon accounted for almost 50 percent of all U.S. e-commerce dollars spent in 2018. But now Amazon is eyeing the much bigger prize: modernizing and dominating retail sales in physical locations, mainly through the use of sophisticated data analysis. The recent reports of Amazon launching its own chain of grocery stores in several U.S. cities — separate from its recent Whole Foods acquisition — is just one example of how this could play out.

You can think of this as the Amazon one-two punch: The company’s vast power in e-commerce is only the initial, quick jab to an opponent’s face. Data-focused innovations in offline retail will be Amazon’s second, much heavier cross. Traditional retailers too focused on the jab aren’t seeing the cross coming. But we think canny retailers can fight back — and avoid getting KO’d. Here’s how.

The e-commerce jab starts with warehousing

Physical storage of goods has long been crucial to advances in commerce. Innovations here range from Henry Ford’s conveyor belt assembly line in 1910, to IBM’s universal product code (the “barcode”) in the early 1970s, to J.C. Penney’s implementation of the first warehouse management system in 1975. Intelligrated (Honeywell), Dematic (KION), Unitronics, Siemens and others further optimized and modernized the traditional warehouse. But then came Amazon.

After expanding from books to a multi-product offering, Amazon Prime launched in 2005. Then, the company’s operational focus turned to enabling scalable two-day shipping. With hundreds of millions of product SKUs, the challenge was how to get your pocket 3-layer suture pad (to cite a super-specific product Amazon now sells) from the back of the warehouse and into the shippers’ hands as quickly as possible.

Make no mistake: Amazon’s one-two retail punch will be formidable.

Amazon met this challenge at a time when automated warehouses still had massive physical footprints and capital-intensive costs. Amazon bought Kiva Systems in 2012, which ushered in the era of Autonomous Guided Vehicles (AGVs), or robots that quickly ferried products from the warehouse’s depths to static human packers.

Since the Kiva acquisition, retailers have scrambled to adopt technology to match Amazon’s warehouse efficiencies.  These technologies range from warehouse management software (made by LogFire, acquired by Oracle; other companies here include Fishbowl and Temando) to warehouse robotics (Locus Robotics, 6 River Systems, Magazino). Some of these companies’ technologies even incorporate wearables (e.g. ProGlove, GetVu) for warehouse workers. We’ve also seen more general-purpose projects in this area, such as Google Robotics. The main adopters of these new technologies are those companies that feel Amazon’s burn most harshly, namely operators of fulfillment centers serving e-commerce.

The schematic below gives a broad picture of their operations and a partial list of warehouse/inventory management technologies they can adopt:

It’s impossible to say what optimizations Amazon will bring to warehousing beyond these, but that may be less important to predict than retailers realize.

The cross: Modernizing the physical retail environment

Amazon has made several recent forays into offline shopping. These range from Amazon Books (physical book stores), Amazon Go (fast retail where consumers skip the cashier entirely) and Amazon 4-Star (stores featuring only products ranked four-stars or higher). Amazon Live is even bringing brick-and-mortar-style shopping streaming to your phone with a home-shopping concept à la QVC. Perhaps most prominently, Amazon’s 2017 purchase of Whole Foods gave the company an entrée into grocery shopping and a nationwide chain of physical stores.

Most retail-watchers have dismissed these projects as dabbling, or — in the case of Whole Foods — focused too narrowly on a particular vertical. But we think they’re missing Bezos’ longer-term strategic aim. Watch that cross: Amazon is mastering how physical retail works today, so it can do offline what it already does incredibly well online, which is harness data to help retailers sell much more intelligently. Amazon recognizes certain products lend themselves better to offline shopping — groceries and children’s clothing are just a few examples.

How can traditional retailers fight back? Get more proactive.

Those shopping experiences are unlikely to disappear. But traditional retailers (and Amazon offline) can understand much, much more about the data points between shopping and purchase. Which path did shoppers take through the store? Which products did they touch and which did they put into a cart? Which items did they try on, and which products did they abandon? Did they ask for different sizes? How does product location within the store influence consumers’ willingness to buy? What product correlations can inform timely marketing offers — for instance, if women often buy hats and sunglasses together in springtime, can a well-timed coupon prompt an additional purchase? Amazon already knows answers to most of these questions online. They want to bring that same intelligence to offline retail.

Obviously, customer privacy will be a crucial concern in this brave new future. But customers have come to expect online data-tracking and now often welcome the more informed recommendations and the convenience this data can bring. Why couldn’t a similar mindset-shift happen in offline retail?

How can retailers fight back?

Make no mistake: Amazon’s one-two retail punch will be formidable. But remember how important the element of surprise is. Too many venture capitalists underestimate physical retail’s importance and pooh-pooh startups focused on this sector. That’s extremely short-sighted.

Does the fact that Amazon is developing computer vision for Amazon Go mean that alternative self-checkout companies (e.g. Trigo, AiFi) are at a disadvantage? I’d argue that this validation is actually an accelerant as traditional retail struggles to keep up.

How can traditional retailers fight back? Get more proactive. Don’t wait for Amazon to show you what the next best-practice in retail should be. There’s plenty of exciting technology you can adopt today to beat Jeff Bezos to the punch. Take Relex, a Finnish startup using AI and machine learning to help brick-and-mortar and e-commerce companies make better forecasts of how products will sell. Or companies like Memomi or Mirow that are creating solutions for a more immersive and interactive offline shopping experience.

Amazon’s one-two punch strategy seems to be working. Traditional retailers are largely blinded by the behemoth’s warehousing innovations, just as they are about to be hit with an in-store innovation blow. New technologies are emerging to help traditional retail rally. The only question is whether they’ll implement the solutions fast enough to stay relevant.

Let’s block ads! (Why?)

Link to original source

Industrial robotics giant Fanuc is using AI to make automation even more automated

Industrial automation is already streamlining the manufacturing process, but first those machines must be painstakingly trained by skilled engineers. Industrial robotics giant Fanuc wants to make robots easier to train, therefore making automation more accessible to a wider range of industries, including pharmaceuticals. The company announced a new artificial intelligence-based tool at TechCrunch’s Robotics/AI Sessions event today that teaches robots how to pick the right objects out of a bin with simple annotations and sensor technology, reducing the training process by hours.

Bin-picking is exactly what it sounds like: a robot arm is trained to pick items out of bins and used for tedious, time-consuming tasks like sorting bulk orders of parts. Images of example parts are taken with a camera for the robot to match with vision sensors. Then the conventional process of training bin-picking robots means teaching it many rules so it knows what parts to pick up.

“Making these rules in the past meant having to through a lot of iterations and trial and error. It took time and was very cumbersome,” said Dr. Kiyonori Inaba, the head of Fanuc Corporation’s Robot Business Division, during a conversation ahead of the event.

These rules include details like how to locate the parts on the top of the pile or which ones are the most visible. Then after that, human operators need to tell it when it makes an error in order to refine its training. In industries that are relatively new to automation, finding enough engineers and skilled human operators to train robots can be challenging.

This is where Fanuc’s new AI-based tool comes in. It simplifies the training process so the human operator just needs to look at a photo of parts jumbled in a bin on a screen and tap a few examples of what needs to be picked up, like showing a small child how to sort toys. This is significantly less training than what typical AI-based vision sensors need and can also be used to train several robots at once.

“It is really difficult for the human operator to show the robot how to move in the same way the operator moves things,” said Inaba. “But by utilizing AI technology, the operator can teach the robot more intuitively than conventional methods.” He adds that the technology is still in its early stages and it remains to be seen if it can be used during in assembly as well.

Let’s block ads! (Why?)

Link to original source

Y Combinator grad, Fuzzbuzz lands $2.7M seed round to deliver fuzzing as service

Fuzzbuzz, a graduate of the most recent Y Combinator class, got the kind of news every early-stage startup wants to hear when it landed a $2.7 million seed round to help deliver a special class of automated software testing known as fuzzing in the form of a cloud service.

Fuel Capital led the round. Homebrew and Susa Ventures also participated along with various angel investors including Docker co-founder Solomon Hykes, Mesosphere co-founder Florian Leibert and Looker co-founder Ben Porterfield.

What Fuzzbuzz does specifically is automate fuzzing at scale, says co-founder and CEO Andrei Serban. “It’s a type of automated software testing that can perform thousands of tests per second,” he explained. Fuzzbuzz, is also taking advantage of artificial intelligence and machine learning underpinnings to use feedback from the results to generate new tests automatically, so that it should get smarter as it goes along.

The goal is to cover as much of the code as possible, much faster and more efficiently than human testers ever could, and find vulnerabilities and bugs. It’s the kind of testing every company generating code would obviously want to do, but the problem is that up until now the process has been expensive and required highly specialized security engineers to undertake. Companies like Google and Facebook are able to hire these kinds of people to build fuzzing solutions, but for the most part, it’s been out of reach for your average company.

Serban says his co-founder, Everest Munro-Zeisberger, worked on the Google Chrome fuzzing team, which has surfaced more than 15,000 bugs using this technique. He wanted to put this type of testing in reach of anyone.

“Today, anyone can start fuzzing on Fuzzbuzz in less than 20 minutes. We hook directly into GitHub and your CI/CD pipeline, categorize and de-duplicate each bug found, and then notify you through tools like Slack and Jira. Using the Fuzzbuzz CLI, developers can then test and fix the bug locally before pushing their code back up to GitHub,” the company wrote in a blog post announcing the funding.

It’s still early days, and the startup is working with some initial customers. The funding should help the three founders, Serban, Munro-Zesberger and Sabera Hussain; to hire more engineers and bring a more complete solution to market. It’s an ambitious undertaking, but if it succeeds in creating a fuzzing service, it could mean delivering code with fewer bugs and that would be good for everyone.

Let’s block ads! (Why?)

Link to original source

'Child's Play' trailer shows Chucky controlling smart homes and drones


Orion Pictures

A reboot of the Child’s Play franchise will hit theaters this summer and while we already had a good idea killer toy Chucky would be more of a robot with AI capabilities this time around, the latest trailer provides further confirmation he’ll be able to control smart homes. Terrifying.

Among the items Chucky, or Buddi as the doll is known here, can take charge of is a drone — let’s hope it’s nothing like the kamikaze or shotgun-wielding ones developed in Russia. It looks like he’ll be able to tap into connected cars and thermostats too, along with perhaps a lawnmower (definitely would not want to be the guy tied up in the path of that machine).

On the flip side, people who have a Buddi app can see what Chucky is looking at, which might be good for a jump scare or two.

Both trailers so far show a lot of promise. With some talented folks involved (including Aubrey Plaza of Parks and Recreation and Legion fame, along with Mark Hamill as the voice of Chucky), this is shaping up to be a solid new starting point for the series — even if it does tap into our worst-case-scenario fears over our connected products. We’ll find out just what kind of tech-focused carnage Chucky has up his sleeves when Child’s Play arrives on June 21st.

Let’s block ads! (Why?)

Link to original source

The Exit: an AI startup’s McPivot

How Bessemer’s bet on Dynamic Yield led it through the Golden Arches

Five years ago, Dynamic Yield was courting an investment from The New York Times as it looked to shift how publishers paywalled their content. Last month, Chicago-based fast food king McDonald’s bought the Israeli company for $300 million, a source told TechCrunch, with the purpose of rethinking how people order drive-thru chicken nuggets.

The pivot from courting the grey lady to the golden arches isn’t as drastic as it sounds. In a lot of ways, it’s the result of the company learning to say “no” to certain customers. At least, that’s what Bessemer’s Adam Fisher tells us.

The Exit is a new series at TechCrunch. It’s an exit interview of sorts with a VC who was in the right place at the right time but made the right call on an investment that paid off. 

Fisher

Fisher was Dynamic Yield founder Liad Agmon’s first call when he started looking for funds from institutional investors. Bessemer bankrolled the bulk of a $1.7 million funding round which valued the startup at $5 million pre-money back in 2013. The firm ended up putting about $15 million into Dynamic Yield, which raised ~$85 million in total from backers including Marker Capital, Union Tech Ventures, Baidu and The New York Times.

Fisher and I chatted at length about the company’s challenging rise and how Israel’s tech scene is still being underestimated. Fisher has 11 years at Bessemer under his belt and 14 exits including Wix, Intucell, Ravello and Leaba.

The interview has been edited for length and clarity. 


Saying “No”

Lucas Matney: So, right off the bat, how exactly did this tool initially built for publishers end up becoming something that McDonalds wanted?

Adam Fisher: I mean, the story of Dynamic Yield is unique. Liad, the founder and CEO, he was an entrepreneur in residence in our Herzliya office back in 2011. I’d identified him earlier from his previous company, and I just said, ‘Well, that’s the kind of guy I’d love to work with.’ I didn’t like his previous company, but there was something about his charisma, his technology background, his youth, which I just felt like “Wow, he’s going to do something interesting.” And so when he sold his previous company, coincidentally to another Chicago based company called Sears, I invited him and I think he found it very flattering, so he joined us as an EIR.

Let’s block ads! (Why?)

Link to original source