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Amazon’s inaugural re:MARS event kicked off on Tuesday, June 4 at the Aria in Las Vegas. This 4-day event is inspired by MARS, a yearly invite-only event hosted by Jeff Bezos that brings together innovative minds in Machine learning, Automation, Robotics, and Space to share new ideas across these rapidly advancing domains.

re:MARS featured a lot of announcements revealing a range of robots each engineered for a different purpose. Some of them include helicopter drones for delivery, two robot dogs by Boston Dynamics, Autonomous human-like acrobats by Walt Disney Imagineering, and much more. Amazon also revealed Alexa’s new Dialog Modeling for Natural, Cross-Skill Conversations.

Let us have a brief look at each of the announcements.

Robert Downey Jr. announces ‘The Footprint Coalition’ project to clean up the environment using Robotics

Popularly known as the “Iron Man”, Robert Downey Jr.’s visit was one of the exciting moments where he announced a new project called The Footprint Coalition to clean up the planet using advanced technologies at re:MARS.

“Between robotics and nanotechnology we could probably clean up the planet significantly, if not entirely, within a decade,” he said.

According to The Forbes, “Amazon did not immediately respond to questions about whether it was investing financially or technologically in Downey Jr.’s project.”

“At this point, the effort is severely light on details, with only a bare-bones website to accompany Downey’s public statement, but the actor said he plans to officially launch the project by April 2020,” Forbes reports.

A recent United Nations report found that humans are having an unprecedented and devastating effect on global biodiversity, and researchers have found microplastics polluting the air, ocean, and soil.

The announcement of this project has been opened to the public because the “company itself is under fire for its policies around the environment and climate change”.

Additionally, Morgan Pope and Tony Dohi of Walt Disney Imagineering, also demonstrated their work to create autonomous acrobats.

Amazon will soon deliver orders using drones

On Wednesday, Amazon unveiled a revolutionary new drone that will test deliver toothpaste and other household goods starting within months. This drone is “part helicopter and part science-fiction aircraft” with built-in AI features and sensors that will help it fly robotically without threatening traditional aircraft or people on the ground.

Gur Kimchi, vice president of Amazon Prime Air, said in an interview to Bloomberg, “We have a design that is amazing. It has performance that we think is just incredible. We think the autonomy system makes the aircraft independently safe.” However, he refused to provide details on where the delivery tests will be conducted. Also, the drones have received a year’s approval from the FAA to test the devices in limited ways that still won’t allow deliveries.

According to a Bloomberg report, “It can take years for traditional aircraft manufacturers to get U.S. Federal Aviation Administration approval for new designs and the agency is still developing regulations to allow drone flights over populated areas and to address national security concerns. The new drone presents even more challenges for regulators because there aren’t standards yet for its robotic features”.

Competitors to Amazon’s unnamed drone include Alphabet Inc.’s Wing, which became the first drone to win an FAA approval to operate as a small airline, in April. Also, United Parcel Service Inc. and drone startup Matternet Inc. began using drones to move medical samples between hospitals in Raleigh, North Carolina, in March.

Amazon’s drone is about six feet across with six propellers that lift it vertically off the ground. It is surrounded by a six-sided shroud that will protect people from the propellers, and also serves as a high-efficiency wing such that it can fly more horizontally like a plane. Once it gets off the ground, the craft tilts and flies sideways — the helicopter blades becoming more like airplane propellers.
Kimchi said, “Amazon’s business model for the device is to make deliveries within 7.5 miles (12 kilometers) from a company warehouse and to reach customers within 30 minutes. It can carry packages weighing as much as five pounds. More than 80% of packages sold by the retail behemoth are within that weight limit.”

According to the company, one of the things the drone has mastered is detecting utility wires and clotheslines. They have been notoriously difficult to identify reliably and pose a hazard for a device attempting to make deliveries in urban and suburban areas.

To know more about these high-tech drones in detail, head over to Amazon’s official blogpost.

Boston Dynamics’ first commercial robot, Spot

Boston Dynamics revealed its first commercial product, a quadrupedal robot named Spot.  Boston Dynamics’ CEO Marc Raibert told The Verge, “Spot is currently being tested in a number of “proof-of-concept” environments, including package delivery and surveying work.”

He also said that although there’s no firm launch date for the commercial version of Spot, it should be available within months, certainly before the end of the year.

“We’re just doing some final tweaks to the design. We’ve been testing them relentlessly”, Raibert said.
These Spot robots are capable of navigating environments autonomously, but only when their surroundings have been mapped in advance. They can withstand kicks and shoves and keep their balance on tricky terrain, but they don’t decide for themselves where to walk.

These robots are simple to control; using a D-pad, users can steer the robot as just like an RC car or mechanical toy. A quick tap on the video feed streamed live from the robot’s front-facing camera allows to select a destination for it to walk to, and another tap lets the user assume control of a robot arm mounted on top of the chassis.
With 3D cameras mounted atop, a Spot robot can map environments like construction sites, identifying hazards and work progress. It also has a robot arm which gives it greater flexibility and helps it open doors and manipulate objects.

The commercial version will be “much less expensive than prototypes [and] we think they’ll be less expensive than other peoples’ quadrupeds”, Raibert said.

Here’s a demo video of the Spot robot at the re:MARS event.

Alexa gets new dialog modeling for improved natural, cross-skill conversations

Amazon unveiled new features in Alexa that would help the conversational agent to answer more complex questions and carry out more complex tasks.

Rohit Prasad, Alexa vice president and head scientist, said, “We envision a world where customers will converse more naturally with Alexa: seamlessly transitioning between skills, asking questions, making choices, and speaking the same way they would with a friend, family member, or co-worker. Our objective is to shift the cognitive burden from the customer to Alexa.”

This new update to Alexa is a set of AI modules that work together to generate responses to customers’ questions and requests. With every round of dialog, the system produces a vector — a fixed-length string of numbers — that represents the context and the semantic content of the conversation.

“With this new approach, Alexa will predict a customer’s latent goal from the direction of the dialog and proactively enable the conversation flow across topics and skills,” Prasad says. “This is a big leap for conversational AI.”

At re:MARS, Prasad also announced the developer preview of Alexa Conversations, a new deep learning-based approach for skill developers to create more-natural voice experiences with less effort, fewer lines of code, and less training data than before.

The preview allows skill developers to create natural, flexible dialogs within a single skill; upcoming releases will allow developers to incorporate multiple skills into a single conversation.

With Alexa Conversations, developers provide:

(1) application programming interfaces, or APIs, that provide access to their skills’ functionality; (2) a list of entities that the APIs can take as inputs, such as restaurant names or movie times;  (3) a handful of sample dialogs annotated to identify entities and actions and mapped to API calls. Alexa Conversations’ AI technology handles the rest.

“It’s way easier to build a complex voice experience with Alexa Conversations due to its underlying deep-learning-based dialog modeling,” Prasad said.

To know more about this announcement in detail, head over to Alexa’s official blogpost.

Amazon Robotics unveiled two new robots at its fulfillment centers

Brad Porter, vice president of robotics at Amazon, announced two new robots, one is, code-named Pegasus and the other one, Xanthus.

Pegasus, which is built to sort packages, is a 3-foot-wide robot equipped with a conveyor belt on top to drop the right box in the right location.

“We sort billions of packages a year. The challenge in package sortation is, how do you do it quickly and accurately? In a world of Prime one-day [delivery], accuracy is super-important. If you drop a package off a conveyor, lose track of it for a few hours  — or worse, you mis-sort it to the wrong destination, or even worse, if you drop it and damage the package and the inventory inside — we can’t make that customer promise anymore”, Porter said.

Porter said Pegasus robots have already driven a total of 2 million miles, and have reduced the number of wrongly sorted packages by 50 percent.

Porter said the Xanthus, represents the latest incarnation of Amazon’s drive robot. Amazon uses tens of thousands of the current-generation robot, known as Hercules, in its fulfillment centers. Amazon unveiled Xanthus Sort Bot and Xanthus Tote Mover.

“The Xanthus family of drives brings innovative design, enabling engineers to develop a portfolio of operational solutions, all of the same hardware base through the addition of new functional attachments. We believe that adding robotics and new technologies to our operations network will continue to improve the associate and customer experience,” Porter says.

To know more about these new robots watch the video below:

StyleSnap: An AI-powered shopping

Amazon announced StyleSnap, a recent move to promote AI-powered shopping. StyleSnap helps users pick out clothes and accessories. All they need to do is upload a photo or screenshot of what they are looking for, when they are unable to describe what they want.

Amazon said, “You are not a poet. You struggle to find the right words to explain the shape of a neckline, or the spacing of a polka dot pattern, and when you attempt your text-based search, the results are far from the trend you were after.”

To use StyleSnap, just open the Amazon app, click the camera icon in the upper right-hand corner, select the StyleSnap option, and then upload an image of the outfit. Post this, StyleSnap provides recommendations of similar outfits on Amazon to purchase, with users able to filter across brand, pricing, and reviews.

Amazon’s AI system can identify colors and edges, and then patterns like floral and denim. Using this information, its algorithm can then accurately pick a matching style.

To know more about StyleSnap in detail, head over to Amazon’s official blog post.

Amazon Go trains cashierless store algorithms using synthetic data

Amazon at the re:MARS shared more details about Amazon Go, the company’s brand for its cashierless stores. They said Amazon Go uses synthetic data to intentionally introduce errors to its computer vision system.

Challenges that had to be addressed before opening stores to avoid queues include the need to make vision systems that account for sunlight streaming into a store, little time for latency delays, and small amounts of data for certain tasks.

Synthetic data is being used in a number of ways to power few-shot learning, improve AI systems that control robots, train AI agents to walk, or beat humans in games of Quake III.

Dilip Kumar, VP of Amazon Go, said, “As our application improved in accuracy — and we have a very highly accurate application today — we had this interesting problem that there were very few negative examples, or errors, which we could use to train our machine learning models.”

He further added, “So we created synthetic datasets for one of our challenging conditions, which allowed us to be able to boost the diversity of the data that we needed. But at the same time, we have to be careful that we weren’t introducing artifacts that were only visible in the synthetic data sets, [and] that the data translates well to real-world situations — a tricky balance.”

To know more about this news in detail, check out this video:

The Amazon re:MARS event is still ongoing and will have many more updates. To catch live updates from Vegas visit Amazon’s blog.

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Savia Lobo
A Data science fanatic. Loves to be updated with the tech happenings around the globe. Loves singing and composing songs. Believes in putting the art in smart.