Daily Archives: February 9, 2017

But the idea of Lens doesn't stop at shopping. For example, that picture of a table could list to a bunch of room decor ideas. Or you can take a photo of a pomegranate, for example, and it'll spit out recipes that uses pomegranate as a main ingredient. A picture of a sweater could lead to different styles of it and how to wear it. Basically think of Lens as a way to search for something when you just don't have the words to describe what it is you're looking at.

Of course, the technology is imperfect. Not all of us take crystal clear photos on our phones, and blurry and awkward shots will probably churn out the wrong results. That's why Pinterest says Lens is still in beta, and is considered somewhat experimental technology.

Pinterest launched a couple of other visual discovery features today as well. One is called Shop The Look, which uses object recognition to automatically detect and search for items in a photo. So a picture of a living room might prompt Pinterest to bring up a list of Buyable pins for the couch, the lamp, the table and the rug. The pins won't be for that brand of furniture specifically of course, but just items that look very similar.

Pinterest says that Shop The Look will also give you styling and decor ideas too. So far, the company has partnered with folks like Curalate, Olapic, Project September, Refinery 29 and ShopStyle to curate the looks. Brands and retailers that are on board include CB2, Macy's, Target, Neiman Marcus and Wayfair.

Last but not least, Pinterest also rolled out Instant Ideas, which is represented by a tiny circle at the bottom right of a pin. Tap it and you'll see a list of related ideas. The more you tap the pins you're interested in, the more customized your recommendations will be over time.

All of these features is live on Android and iOS starting today. It's available in the US for now, with more countries to be announced at a later date.

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Pinterest uses AI and your camera to recommend pins - Engadget

In the future, service robots equipped with artificial intelligence (AI) are bound to be a common sight. These bots will help people navigate crowded airports, serve meals, or even schedule meetings.

As these AI systems become more integrated into daily life, it is vital to find an efficient way to communicate with them. It is obviously more natural for a human to speak in plain language rather than a string of code. Further, as the relationship between humans and robots grows, it will be necessary to engage in conversations, rather than just give orders.

This human-robot interaction is what Manuela M. Velosos research is all about. Veloso, a professor at Carnegie Mellon University, has focused her research on CoBots, autonomous indoor mobile service robots which transport items, guide visitors to building locations, and traverse the halls and elevators. The CoBot robots have been successfully autonomously navigating for several years now, and have traveled more than 1,000km. These accomplishments have enabled the research team to pursue a new direction, focusing now on novel human-robot interaction.

If you really want these autonomous robots to be in the presence of humans and interacting with humans, and being capable of benefiting humans, they need to be able to talk with humans Veloso says.

Velosos CoBots are capable of autonomous localization and navigation in the Gates-Hillman Center using WiFi, LIDAR, and/or a Kinect sensor (yes, the same type used for video games).

The robots navigate by detecting walls as planes, which they match to the known maps of the building. Other objects, including people, are detected as obstacles, so navigation is safe and robust. Overall, the CoBots are good navigators and are quite consistent in their motion. In fact, the team noticed the robots could wear down the carpet as they traveled the same path numerous times.

Because the robots are autonomous, and therefore capable of making their own decisions, they are out of sight for large amounts of time while they navigate the multi-floor buildings.

The research team began to wonder about this unaccounted time. How were the robots perceiving the environment and reaching their goals? How was the trip? What did they plan to do next?

In the future, I think that incrementally we may want to query these systems on why they made some choices or why they are making some recommendations, explains Veloso.

The research team is currently working on the question of why the CoBots took the route they did while autonomous. The team wanted to give the robots the ability to record their experiences and then transform the data about their routes into natural language. In this way, the bots could communicate with humans and reveal their choices and hopefully the rationale behind their decisions.

The internals underlying the functions of any autonomous robots are completely based on numerical computations, and not natural language. For example, the CoBot robots in particular compute the distance to walls, assigning velocities to their motors to enable the motion to specific map coordinates.

Asking an autonomous robot for a non-numerical explanation is complex, says Veloso. Furthermore, the answer can be provided in many potential levels of detail.

We define what we call the verbalization space in which this translation into language can happen with different levels of detail, with different levels of locality, with different levels of specificity.

For example, if a developer is asking a robot to detail their journey, they might expect a lengthy retelling, with details that include battery levels. But a random visitor might just want to know how long it takes to get from one office to another.

Therefore, the research is not just about the translation from data to language, but also the acknowledgment that the robots need to explain things with more or less detail. If a human were to ask for more detail, the request triggers CoBot to move into a more detailed point in the verbalization space.

We are trying to understand how to empower the robots to be more trustable through these explanations, as they attend to what the humans want to know, says Veloso. The ability to generate explanations, in particular at multiple levels of detail, will be especially important in the future, as the AI systems will work with more complex decisions. Humans could have a more difficult time inferring the AIs reasoning. Therefore, the bot will need to be more transparent.

For example, if you go to a doctors office and the AI there makes a recommendation about your health, you may want to know why it came to this decision, or why it recommended one medication over another.

Currently, Velosos research focuses on getting the robots to generate these explanations in plain language. The next step will be to have the robots incorporate natural language when humans provide them with feedback. [The CoBot] could say, I came from that way, and you could say, well next time, please come through the other way, explains Veloso.

These sorts of corrections could be programmed into the code, but Veloso believes that trustability in AI systems will benefit from our ability to dialogue, query, and correct their autonomy. She and her team aim at contributing to a multi-robot, multi-human symbiotic relationship, in which robots and humans coordinate and cooperate as a function of their limitations and strengths.

What were working on is to really empower people a random person who meets a robot to still be able to ask things about the robot in natural language, she says.

In the future, when we will have more and more AI systems that are able to perceive the world, make decisions, and support human decision-making, the ability to engage in these types of conversations will be essential.

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AI Systems Are Learning to Communicate With Humans - Futurism

Forbes

Five Trends Business-Oriented AI Will Inspire Forbes Until recently, artificial intelligence has looked like a new and exciting fad. Technology innovators showcased flashy ways to harness intelligence and apply it in the real world (e.g. self-driving cars, the marketing stunts of Watson, Google's AI ...

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Five Trends Business-Oriented AI Will Inspire - Forbes

The next time you go to your favorite restaurant or cocktail bar, talk with the manager about bookkeeping. Chances are that theyll tell you that they waste a ton of time collecting and recording various documents. German startup Zeitgold wants to automate this pesky process so that you can spend more time on your actual business.

The startup was founded by two of the co-founders behind SumUp Stefan Jeschonnek and Jan Deepen who left the mobile payment company in 2014. Kobi Eldar is the third co-founder. Zeitgold just raised $4.5 million from Battery Ventures and Holtzbrinck Ventures Invest (4.2 million).

So what is Zeitgold exactly? Its an all-in-one financial solution for small shop owners. The company sends you a physical box. You can put all your receipts, bills and invoices in this box. Somebody will come and pick up the box every week. The startup then scans and archives all these documents to process them Zeitgold also accepts digital documents.

This way, Zeitgold can build a structured database of all this paperwork and provide you actionable information. For instance, you can then open the Zeitgold app and accept all payment requests from your suppliers. The startup can also help you when it comes to invoice collection, payroll and everything your tax advisor will need.

You can also use the app as your one-stop shop to search for that one document youre looking for. Thanks to OCR, you can just type keywords. Zeitgold also tells you if there are missing documents.

Eventually, Zeitgold wants to automate most of it with optical character recognition, text analytics and a bunch of algorithms. Its not there yet, and a lot of work is still done by humans. But the startups team of accounting experts will train Zeitgolds algorithms over time so that it relies less on humans.

We spent the last 18 months on R&D. Now, our AI is able to create clean data sets out of unsorted physical documents, Jeschonnek told me.

The company also didnt just want to tackle one aspect of the financial paperwork. This is an interesting approach and Im curious to see if it can scale indeed.

The startup is launching in Germany first, but Zeitgold is already thinking about expanding to other countries around Germany as all shop owners face the same issues.

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SumUp co-founders are back with bookkeeping AI startup Zeitgold - TechCrunch

These 23 principles were agreed upon at the recent Beneficial AI 2017 conference at the Future of Life Institute in Boston

A list of 23 principles related to the ethics, research strategies and long-term issues arising from developing artificial intelligence technologies has been endorsed by high-profile scientists and technologists including Stephen Hawking; Elon Musk; Ray the Singularity Kurzweil; Demis Hassabis, founder and CEO of DeepMind; and Prof Yann LeCun, director of AI research at Facebook.

Curiously, actor and film-maker Joseph Gordon-Levit has also signed this list and actor-turned-science communicator Alan Alda is on the scientific advisory board.

These 23 principles were agreed upon at the recent Beneficial AI 2017 conference at the Future of Life Institute in Boston and state that the goal of AI research should be to create beneficial intelligence rather than undirected intelligence, adding that plans should be put in place in case AI systems pose catastrophic or existential risks to human life.

There was also a stipulation that strict safety and control measures are in place for self-improving and self-replicating AI systems; nobody wants swarms of determined, superintelligent nanobots deciding that planet Earths greatest threat (humans) should be eradicated.

AI-principles

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Stephen Hawking and Elon Musk endorse new AI code - Irish Times