In 2012, Amazon quietly acquired a robotics startup called Kiva Systems, a move that dramatically improved the efficiency of its ecommerce operations and kickstarted a wider revolution in warehouse automation. Last week, the ecommerce giant announced another deal that could prove similarly profound, agreeing to hire the founders of Covariant, a startup that has been testing ways for AI to automate more of the picking and handling of a wide range of physical objects. Covariant may have found it challenging to commercialize AI-infused industrial robots given the high costs and sharp competition involved; the deal, which will also see Amazon license Covariant's models and data, could bring about another revolution in ecommerce--one that might prove hard for any competitor to match given Amazon's vast operational scale and data trove. The deal is also an example of a Big Tech company acquiring core talent and expertise from an AI startup without actually buying the company outright. Amazon came to a similar agreement with the startup Adept in June.

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A DECADE AGO Amazon started to introduce robots into its "fulfilment centres", as online retailers call their giant distribution warehouses. Instead of having people wandering up and down rows of shelves picking goods to complete orders, the machines would lift and then carry the shelves to the pickers. That saved time and money. Amazon now has more than 350,000 robots of various sorts deployed worldwide. But it is not enough to secure its future.

Over the last couple of decades in the lending industry, financial disintermediation has occurred on a global scale. Traditionally, even for small supply of funds, banks would act as the conduit between the funds and the borrowers. It has now been possible to overcome some of the obstacles associated with such supply of funds with the advent of online platforms like Kiva, Prosper, LendingClub. Kiva for example, works with Micro Finance Institutions (MFIs) in developing countries to build Internet profiles of borrowers with a brief biography, loan requested, loan term, and purpose. Kiva, in particular, allows lenders to fund projects in different sectors through group or individual funding. Traditional research studies have investigated various factors behind lender preferences purely from the perspective of loan attributes and only until recently have some cross-country cultural preferences been investigated. In this paper, we investigate lender perceptions of economic factors of the borrower countries in relation to their preferences towards loans associated with different sectors. We find that the influence from economic factors and loan attributes can have substantially different roles to play for different sectors in achieving faster funding. We formally investigate and quantify the hidden biases prevalent in different loan sectors using recent tools from causal inference and regression models that rely on Bayesian variable selection methods. We then extend these models to incorporate fairness constraints based on our empirical analysis and find that such models can still achieve near comparable results with respect to baseline regression models.

It was just last year that we announced our investment in 6 River Systems. Today, we're celebrating the news that Shopify is acquiring them for $450M. The team at Menlo is proud to have been involved in the 6RS journey and their mission to bring automation and robotics to every company's fulfillment process. It was a pleasure working with two great founders, Jerome Dubois and Rylan Hamilton. Their deep domain experience and operational rigor quickly made 6RS the market leader!

This is where robots come in. Resembling oversize Roombas topped with Ikea shelving, these Kiva robots can carry up to 750 pounds of goods in their 40-odd cubbies. After a customer places an order, a robot carrying the desired item scoots over to a worker, who reads on a screen what item to pick and what cubby it's located in, scans a bar code and places the item in a bright-yellow bin that travels by conveyor belt to a packing station. AI suggests an appropriate box size; a worker places the item in the box, which a robot tapes shut and, after applying a shipping label, sends on its way. Humans are needed mostly for grasping and placing, tasks that robots haven't mastered yet.

Verity Studios, which took precision drone swarm technology from ETH Zurich and turned it into a spectacular live event display system, has announced a round of Series A funding totaling US $18 million from Fontinalis Partners, Airbus Ventures, Sony Innovation Fund, and Kitty Hawk. This is a lot of money for a company that most people may not know exists even if they view a Verity-powered drone show firsthand, but that's part of what makes Verity special: Everything they do is reliable, seamless, and safe, leading to experiences that have a truly mesmerizing effect. The reason we follow companies like Verity so closely, and the reason why we're happy when they get funded, is because they've managed to transition some fairly amazing robotics research into a successful business, which is a very difficult thing to do. The kinds of things that make Verity special come from over a decade of work at the Flying Machine Arena at ETH Zurich, led by Professor Raffaello D'Andrea, a lot of which we've covered in the past. For example, Verity's drones are fully redundant, able to recover from "a failed battery, a failed motor, a failed connector, a failed propeller, a failed sensor, or a failure of any other component ... through the duplication of critical components and the use of proprietary algorithms, which enable safe emergency responses to component failures."

At the Amazon Picking Challenge, 26 teams competed on their ability to pick items out of warehouse shelves. While the first year was largely focused on basic competencies, there are clear ways AI techniques can help make these systems more capable and robust. The APC follows in the footsteps of other robotics competitions, most notably RoboCup and the DARPA challenges, by posing a real-world environment in which robots must perform humanlike tasks. The APC's focus is on one core -- but extremely important -- area of robotic competency: manipulating objects in the world. The competition scenario was a Kivalike warehouse in which the robot had 20 minutes to pick items off a shelf and put them into a plastic tote.

The years of research on robotics and multiagent systems are coming together to provide just such a disruption to the material-handling industry. While autonomous guided vehicles (AGVs) have been used to move material within warehouses since the 1950s, they have been used primarily to transport very large, very heavy objects like rolls of uncut paper or engine blocks. The confluence of inexpensive wireless communications, computational power, and robotic components are making autonomous vehicles cheaper, smaller, and more capable. In recent years, we have seen an increase in the use of autonomous vehicles in the field. Examples include teleoperated military devices like iRobot's Packbot and the pilotless Predator aircraft, both of which have seen service in Iraq and Afghanistan.

Summary: For your holiday reading we present this selection of robot and AI fails. We hope this brings you hope and cheer for the coming year to know that our robot overlords are not as close as some think. For your holiday reading we present this selection of robot and AI fails. We hope this brings you hope and cheer for the coming year to know that our robot overlords are not as close as some think. Alas, it seems we've got a few more years before the robots take over.