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#431093 Video Friday: SpaceX Rocket Mishaps, ...

Your weekly selection of awesome robot videos Continue reading

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#431069 Video Friday: Agility Robotics, Pancake ...

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#431058 How to Make Your First Chatbot With the ...

You’re probably wondering what Game of Thrones has to do with chatbots and artificial intelligence. Before I explain this weird connection, I need to warn you that this article may contain some serious spoilers. Continue with your reading only if you are a passionate GoT follower, who watches new episodes immediately after they come out.
Why are chatbots so important anyway?
According to the study “When Will AI Exceed Human Performance?,” researchers believe there is a 50% chance artificial intelligence could take over all human jobs by around the year 2060. This technology has already replaced dozens of customer service and sales positions and helped businesses make substantial savings.
Apart from the obvious business advantages, chatbot creation can be fun. You can create an artificial personality with a strong attitude and a unique set of traits and flaws. It’s like creating a new character for your favorite TV show. That’s why I decided to explain the most important elements of the chatbot creation process by using the TV characters we all know and love (or hate).
Why Game of Thrones?
Game of Thrones is the most popular TV show in the world. More than 10 million viewers watched the seventh season premiere, and you have probably seen internet users fanatically discussing the series’ characters, storyline, and possible endings.
Apart from writing about chatbots, I’m also a GoT fanatic, and I will base this chatbot on one of the characters from my favorite series. But before you find out the name of my bot, you should read a few lines about incredible free tools that allow us to build chatbots without coding.
Are chatbots expensive?
Today, you can create a chatbot even if you don’t know how to code. Most chatbot building platforms offer at least one free plan that allows you to use basic functionalities, create your bot, deploy it to Facebook Messenger, and analyze its performance. Free plans usually allow your bot to talk to a limited number of users.
Why should you personalize your bot?
Every platform will ask you to write a bot’s name before you start designing conversations. You will also be able to add the bot’s photograph and bio. Personalizing your bot is the only way to ensure that you will stick to the same personality and storyline throughout the building process. Users often see chatbots as people, and by giving your bot an identity, you will make sure that it doesn’t sound like it has multiple personality disorder.
I think connecting my chatbot with a GoT character will help readers understand the process of chatbot creation.
And the name of our GoT chatbot is…
…Cersei. She is mean, pragmatic, and fearless and she would do anything to stay on the Iron Throne. Many people would rather hang out with Daenerys or Jon Snow. These characters are honest, noble and good-hearted, which means their actions are often predictable.
Cersei, on the other hand, is the queen of intrigues. As the meanest and the most vengeful character in the series, she has an evil plan for everybody who steps on her toes. While viewers can easily guess where Jon and Daenerys stand, there are dozens of questions they would like to ask Cersei. But before we start talking to our bot, we need to build her personality by using the most basic elements of chatbot interaction.
Choosing the bot’s name on Botsify.
Welcome / Greeting Message
The welcome message is the greeting Cersei says to every commoner who clicks on the ‘start conversation’ button. She is not a welcoming person (ask Sansa), except if you are a banker from Braavos. Her introductory message may sound something like this:
“Dear {{user_full_name}}, My name is Cersei of the House Lannister, the First of Her Name, Queen of the Andals and the First Men, Protector of the Seven Kingdoms. You can ask me questions, and I will answer them. If the question is not worth answering, I will redirect you to Ser Gregor Clegane, who will give you a step-by-step course on how to talk to the Queen of Westeros.”
Creating the welcome message on Chatfuel
Default Message / Answer
In the bot game, users, bots, and their creators often need to learn from failed attempts and mistakes. The default message is the text Cersei will send whenever you ask her a question she doesn’t understand. Knowing Cersei, it would sound something like this:
“Ser Gregor, please escort {{user_full_name}} to the dungeon.”
Creating default message on Botsify
To avoid calling out the Mountain every time someone asks her a question, Cersei might give you a few (safe) options to choose. The best way to do this is by using a menu function. We can classify the questions people want to ask Cersei in several different categories:

Iron Throne
Relationship with Jaime — OK, this isn’t a “safe option,” get ready to get close and personal with Sir Gregor Clegane.
War plans
Euron Greyjoy

After users choose a menu item, Cersei can give them a default response on the topic or set up a plot that will make their lives miserable. Knowing Cersei, she will probably go for the second option.
Adding chatbot menu on Botsify
Stories / Blocks
This feature allows us to build a longer Cersei-to-user interaction. The structure of stories and blocks is different on every chatbot platform, but most of them use keywords and phrases for finding out the user’s intention.

Keywords — where the bot recognizes a certain keyword within the user’s reply. Users who have chosen the ‘war plans’ option might ask Cersei how is she planning to defeat Daenerys’s dragons. We can add ‘dragon’ and ‘dragons’ as keywords, and connect them with an answer that will sound something like this:

“Dragons are not invulnerable as you may think. Maester Qyburn is developing a weapon that will bring them down for good!”
Adding keywords on Chatfuel
People may also ask her about White Walkers. Do you plan to join Daenerys and Jon Snow in a fight against White Walkers? After we add ‘White Walker’ and ‘White Walkers’ on the keyword list, Cersei will answer:
“White Walkers? Do you think the Queen of Westeros has enough free time to think about creatures from fairy tales and legends?”
Adding Keywords on Botsify

Phrases — are more complex syntaxes that the bot can be trained to recognize. Many people would like to ask Cersei if she’s going to marry Euron Greyjoy after the war ends. We can add ‘Euron’ as a keyword, but then we won’t be sure what answer the user is expecting. Instead, we can use the phrase ‘(Will you) marry Euron Greyjoy (after the war?)’. Just to be sure, we should also add a few alternative phrases like ‘(Do you plan on) marrying Euron Greyjoy (after the war),’ ‘(Will you) end up with Euron Greyjoy (after the war?)’, ‘(Will) Euron Greyjoy be the new King?’ etc. Cersei would probably answer this inquiry in her style:

“Of course not, Euron is a useful idiot. I will use his fleet and send him back to the Iron Islands, where he belongs.”
Adding phrases on Botsify
We have already asked Cersei several questions, and now she would like to ask us something. She can do so by using the form/user input feature. Most tools allow us to add a question and the criteria for checking the users’ answer. If the user provides us the answer that is compliant to the predefined form (like email address, phone number, or a ZIP code), the bot will identify and extract the answer. If the answer doesn’t fit into the predefined criteria, the bot will notify the user and ask him/her to try again.
If Cersei would ask you a question, she would probably want to know your address so she could send her guards to fill your basement with barrels of wildfire.
Creating forms on Botsify
If you have problems building your first chatbot, templates can help you create the basic conversation structure. Unfortunately, not all platforms offer this feature for free. Snatchbot currently has the most comprehensive list of free templates. There you can choose a pre-built layout. The template selection ranges from simple FAQ bots to ones created for a specific industry, like banking, airline, healthcare, or e-commerce.
Choosing templates on Snatchbot
Most tools also provide plugins that can be used for making the conversations more meaningful. These plugins allow Cersei to send images, audio and video files. She can unleash her creativity and make you suffer by sending you her favorite GoT execution videos.

With the help of integrations, Cersei can talk to you on Facebook Messenger, Telegram, WeChat, Slack, and many other communication apps. She can also sell her fan gear and ask you for donations by integrating in-bot payments from PayPal accounts. Her sales pitch will probably sound something like this:
“Gold wins wars! Would you rather invest your funds in a member of a respected family, who always pays her debts, or in the chaotic war endeavor of a crazy revolutionary, whose strength lies in three flying lizards? If your pockets are full of gold, you are already on my side. Now you can complete your checkout on PayPal.”
Chatbot building is now easier than ever, and even small businesses are starting to use the incredible benefits of artificial intelligence. If you still don’t believe that chatbots can replace customer service representatives, I suggest you try to develop a bot based on your favorite TV show, movie or book character and talk with him/her for a while. This way, you will be able to understand the concept that stands behind this amazing technology and use it to improve your business.
Now I’m off to talk to Cersei. Maybe she will feed me some Season 8 spoilers.
This article was originally published by Chatbots Magazine. Read the original post here.
Image credits for screenshots in post: Branislav Srdanovic
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#430743 Teaching Machines to Understand, and ...

We humans are swamped with text. It’s not just news and other timely information: Regular people are drowning in legal documents. The problem is so bad we mostly ignore it. Every time a person uses a store’s loyalty rewards card or connects to an online service, his or her activities are governed by the equivalent of hundreds of pages of legalese. Most people pay no attention to these massive documents, often labeled “terms of service,” “user agreement,” or “privacy policy.”
These are just part of a much wider societal problem of information overload. There is so much data stored—exabytes of it, as much stored as has ever been spoken by people in all of human history—that it’s humanly impossible to read and interpret everything. Often, we narrow down our pool of information by choosing particular topics or issues to pay attention to. But it’s important to actually know the meaning and contents of the legal documents that govern how our data is stored and who can see it.
As computer science researchers, we are working on ways artificial intelligence algorithms could digest these massive texts and extract their meaning, presenting it in terms regular people can understand.
Can computers understand text?
Computers store data as 0s and 1s—data that cannot be directly understood by humans. They interpret these data as instructions for displaying text, sound, images, or videos that are meaningful to people. But can computers actually understand the language, not only presenting the words but also their meaning?
One way to find out is to ask computers to summarize their knowledge in ways that people can understand and find useful. It would be best if AI systems could process text quickly enough to help people make decisions as they are needed—for example, when you’re signing up for a new online service and are asked to agree with the site’s privacy policy.
What if a computerized assistant could digest all that legal jargon in a few seconds and highlight key points? Perhaps a user could even tell the automated assistant to pay particular attention to certain issues, like when an email address is shared, or whether search engines can index personal posts. Companies could use this capability, too, to analyze contracts or other lengthy documents.
To do this sort of work, we need to combine a range of AI technologies, including machine learning algorithms that take in large amounts of data and independently identify connections among them; knowledge representation techniques to express and interpret facts and rules about the world; speech recognition systems to convert spoken language to text; and human language comprehension programs that process the text and its context to determine what the user is telling the system to do.
Examining privacy policies
A modern internet-enabled life today more or less requires trusting for-profit companies with private information (like physical and email addresses, credit card numbers and bank account details) and personal data (photos and videos, email messages and location information).
These companies’ cloud-based systems typically keep multiple copies of users’ data as part of backup plans to prevent service outages. That means there are more potential targets—each data center must be securely protected both physically and electronically. Of course, internet companies recognize customers’ concerns and employ security teams to protect users’ data. But the specific and detailed legal obligations they undertake to do that are found in their impenetrable privacy policies. No regular human—and perhaps even no single attorney—can truly understand them.
In our study, we ask computers to summarize the terms and conditions regular users say they agree to when they click “Accept” or “Agree” buttons for online services. We downloaded the publicly available privacy policies of various internet companies, including Amazon AWS, Facebook, Google, HP, Oracle, PayPal, Salesforce, Snapchat, Twitter, and WhatsApp.
Summarizing meaning
Our software examines the text and uses information extraction techniques to identify key information specifying the legal rights, obligations and prohibitions identified in the document. It also uses linguistic analysis to identify whether each rule applies to the service provider, the user or a third-party entity, such as advertisers and marketing companies. Then it presents that information in clear, direct, human-readable statements.
For example, our system identified one aspect of Amazon’s privacy policy as telling a user, “You can choose not to provide certain information, but then you might not be able to take advantage of many of our features.” Another aspect of that policy was described as “We may also collect technical information to help us identify your device for fraud prevention and diagnostic purposes.”

We also found, with the help of the summarizing system, that privacy policies often include rules for third parties—companies that aren’t the service provider or the user—that people might not even know are involved in data storage and retrieval.
The largest number of rules in privacy policies—43 percent—apply to the company providing the service. Just under a quarter of the rules—24 percent—create obligations for users and customers. The rest of the rules govern behavior by third-party services or corporate partners, or could not be categorized by our system.

The next time you click the “I Agree” button, be aware that you may be agreeing to share your data with other hidden companies who will be analyzing it.
We are continuing to improve our ability to succinctly and accurately summarize complex privacy policy documents in ways that people can understand and use to access the risks associated with using a service.

This article was originally published on The Conversation. Read the original article. Continue reading

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#430686 This Week’s Awesome Stories From ...

DeepMind’s AI Is Teaching Itself Parkour, and the Results Are AdorableJames Vincent | The Verge“The research explores how reinforcement learning (or RL) can be used to teach a computer to navigate unfamiliar and complex environments. It’s the sort of fundamental AI research that we’re now testing in virtual worlds, but that will one day help program robots that can navigate the stairs in your house.”
Now You Can Broadcast Facebook Live Videos From Virtual RealityDaniel Terdiman | Fast Company“The idea is fairly simple. Spaces allows up to four people—each of whom must have an Oculus Rift VR headset—to hang out together in VR. Together, they can talk, chat, draw, create new objects, watch 360-degree videos, share photos, and much more. And now, they can live-broadcast everything they do in Spaces, much the same way that any Facebook user can produce live video of real life and share it with the world.”
I Watched Two Robots Chat Together on Stage at a Tech EventJon Russell | TechCrunch“The robots in question are Sophia and Han, and they belong to Hanson Robotics, a Hong Kong-based company that is developing and deploying artificial intelligence in humanoids. The duo took to the stage at Rise in Hong Kong with Hanson Robotics’ Chief Scientist Ben Goertzel directing the banter. The conversation, which was partially scripted, wasn’t as slick as the human-to-human panels at the show, but it was certainly a sight to behold for the packed audience.”
Scientists Used CRISPR to Put a GIF Inside a Living Organism’s DNAEmily Mullin | MIT Technology Review“They delivered the GIF into the living bacteria in the form of five frames: images of a galloping horse and rider, taken by English photographer Eadweard Muybridge…The researchers were then able to retrieve the data by sequencing the bacterial DNA. They reconstructed the movie with 90 percent accuracy by reading the pixel nucleotide code.”
AI Creates Fake ObamaCharles Q. Choi | IEEE Spectrum“In the new study, the neural net learned what mouth shapes were linked to various sounds. The researchers took audio clips and dubbed them over the original sound files of a video. They next took mouth shapes that matched the new audio clips and grafted and blended them onto the video. Essentially, the researchers synthesized videos where Obama lip-synched words he said up to decades beforehand.”
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