When you create a new solution, in a new space, people naturally have questions. They want you to define the terms you're using, explain how you compare to solutions they're more familiar with, give examples of how the solution works, and so on. We've been cheerily fielding these kinds of queries over the phone, online, and at events in our quest to spread the TDaaS word. It's very fun, but uh, not very efficient--we realized we needed to outline all these answers in one skimmable place. So here we go, answers to the most frequently asked questions of Spare5.

Just as text messaging has become a mainstream form of communication, attention is shifting to the chatbot as the next big thing for information management and customer service. Chatbots are computer programs that interpret human speech or written inquiries and decide which information is being sought. Although chatbots have been around since the 1960s, they have evolved into tools for giving out details or taking orders, such as when people search for a job or buy a movie ticket. The chatbot picks up keywords from sentences and matches them with a database to create replies. Thanks to advances in artificial intelligence and big data processing technology, the machines today can analyze and understand a wide range of speech and produce the exact services sought, said Goshi Yonekura, chief technology officer of Tokyo-based AI developer Alt Inc.

Google uses a machine-learning artificial intelligence system called "RankBrain" to help sort through its search results. Wondering how that works and fits in with Google's overall ranking system? Here's what we know about RankBrain. The information covered below comes from three original sources and has been updated over time, with notes where updates have happened. First is the Bloomberg story that broke the news about RankBrain (See also our write-up of it).

NOTE: This story has been revised from when it was originally published in October 2015 to reflect the latest information. Yesterday, news emerged that Google was using a machine-learning artificial intelligence system called "RankBrain" to help sort through its search results. Wondering how that works and fits in with Google's overall ranking system? Here's what we know about RankBrain. The information covered below comes from three original sources and has been updated over time, with notes where updates have happened.

These FAQ's oftentimes raise more questions than they answer, so that the correct answer is often not found. With Automated Chat you can anticipate in a fast and accurate way Every website visitor can communicate with a virtual assistant (chatbot). All answers are pre-entered in a knowledge management system. This system is made so every question and answer thinkable can be recognised through sentence or word recognision. With a chatbot you can provide your website visitors with information or advice in a personal way, 24 hours a day.

By regression, I mean the derivation of a continuous property of an image (e.g. the mean area of the objects shown on the image) from its pixeldata. I'd like to train the algorithm with several images with known properties, in order to use it to analyze unknown images. From my limited understanding, this should be possible. Nevertheless, I only found examples of image classification or regressions of numerical values. Therefore, I'd be very thankful for hints to examples or tutorials.

We get asked a lot of questions about how to start building with Watson, so we decided to compile our top 4 Frequently Asked Questions. You can use this as a guide to learn more about the technology, receive inspiration from use cases, get valuable resources, and ultimately begin building with the technology. Cognitive technology's strength lies in its ability to draw insights from unstructured data sets. Structured data is found in a spreadsheet, whereas unstructured data is text such as tweets, medical journals, etc. Today 80% of data is unstructured, so tools such as cognitive computing are becoming more important in helping humans understand what's inside that data.

Software engineering is about developing programs or tools to automate tasks. Instead of "doing things manually," we write programs; a program is basically just a machine-readable set of instructions that can be executed by a computer. Let's consider a classic example: e-mail spam filtering. Assuming that we have access to the source code of our e-mail client and know how to handle it, we could come up with an instinctive set of rules that may help us with our spam problem. For example: if not "sender in contacts": if "subject line contains BUY!: e-mail spam folder:" else if ... It is intuitive to say that coming up with these rules is a pretty tedious task.

Everyone has an AI in their pocket these days -- Siri, Cortana, Google Now and Amazon's Alexa have given everyone easy access to virtual assistants. But one promising startup could wind up beating them all: Viv. Viv is still in its early stages, but it has caused a lot of excitement in the tech community, and according to a profile in The Washington Post, it has drawn bids from some major players. Here's what you need to know about Viv. Viv is poised to be the next big AI assistant.

The AI can compare the user's question with others that have already been asked, thus generating a more relevant answer. Let's say she opens a bot's FAQ and asks'how can I get new password?'. Note that the user has found the bot's FAQ. So a good user interface has led her to this point already. This is thus a good example of how UI and AI work well in combination.