Passage.AI Emerges for Multiple Platforms

Have always been interested in ways to make chatbot AI easier. Since our long ago successful use of the Extempo package.   Here another example emerging.

 Passage.AI aims to make building chatbots easy     By Paul Gillin in SiliconAngle

" .... The company is emerging from stealth mode today with $3 million in seed funding and the promise of technology that can help anyone create artificial intelligence-driven chatbots without writing code.

Passage.AI’s bot-building tool uses deep learning and natural language processing to enable bots to understand the context for a request, regardless of how it’s expressed, the company said. It uses “long short-term memory,” a type of neural network that is optimized for language comprehension and handwriting recognition. ... " 

See the Passage.AI site, which itself uses a chatbot to introduce itself.  Also I much like the fact that it integrates with a number of other popular assistant platforms, like Alexa, Google Home, Slack, WeChat and IOS.    Want to see how that works.

Fielding a Hundred Thousand Questions

Via O'Reilly.   We did something similar when creating our Extempo bot system, but only included a few hundred questions.  Nice to see Microsoft pushing research with this.    How many parameterized questions does a human ask in normal conversation?   How does this relate to context? To get to useful answers?  Good, largly non-technical article.  If you are at all interested in bot like interaction, worth a look.  Thinking of feeding selected elements of this through some current assistants.

100,000 questions (and answers)
Microsoft has released a set of 100,000 questions and answers that you can use to create AI systems that can read and answer questions as well as a human. The team behind the dataset hopes that releasing it will spur the kind of breakthroughs in machine reading that are already happening in image and speech recognition.  ... " 

Teaching AI Chitchat

Is it important to make AI more human?  That was part of what we attempted in our 'big' idea.  Have a piece of ad equity talk to you conversationally, and you can engage them.  Did not work then, but technology has improved. Is being clever better than being smart?   A key intelligence module of the re-emergent chatbot.   In CACM:  The power of chitchat.

Miss Piggy and Imperson Chatbots

Marketers see Chatbots as a means to engage with Virtual Assistants. Facebook's Messenger is an example mentioned here before. How does personality create engagement to deliver intelligence and services? Imperson from the Disney Accelerator is an example of how this is being done. We did this with Mr. Clean. Is this relevant beyond marketing? I think so. Miss Piggy is a sample chatbot you can explore. Link here.

Google Planning Chatbots in Messengers Leveraging Cognitive AI

I recently mentioned the linking of chatbots and messenger systems.  Recall we addressed this in early assistance systems.   See the Mr Clean tag below.

In Forbes:  Google To Launch An Artificial Intelligence Messenger Service To Rival Facebook M   .... Theo Priestley

" .... According to sources close to the Wall Street Journal, Google is looking into launching a new mobile based messenger service underpinned by artificial intelligence. “For its new service, Google, a unit of Alphabet Inc., plans to integrate chatbots, software programs that answer questions inside a messaging app,” the article claims. ...  " 

Example Use of Watson for Social Benchmarking

Always looking for good, simple examples of the use of cognitive methods, and thus also Watson. Just recently connected with Eric Santos, of Benchmark Intelligence,  and he writes how they use Watson for their social intelligence bench marking and trending. A good example of what can be done.

" ... Benchmark is a product suite that helps retail chains understand why certain locations perform better than others. Benchmark discovers the factors (customer service, product quality, cleanliness, etc) that affect unit performance. Benchmark Intelligence is a proud IBM Watson ecosystem partner. 

Currently Benchmark collects its data through various ways which includes social media listening, SMS comments, surveys and field audits. A good portion of this data is qualitative and unstructured. We needed a way to run analysis on this data and identify trends, that’s why we turned to IBM Watson. 

Benchmark is leveraging Watson’s Alchemy languages, specifically their sentiment analysis and keyword extraction technologies. We are using these cognitive technologies to analyze this unstructured data and discover the variables (customer service, cleanliness, etc.) that affect performance at each location. 

Watson looks at thousands of open-ended data points (social media reviews, SMS comments, etc.) on our platform for any given chain. For each data point Watson defines whether the statement as a whole is positive, negative or neutral. Watson also identifies the key words that make up the statement. That way as locations gather more data points, we can identify the trends that are going on at each location in the chain. 

Example use cases of this include knowing that customers complained about cockroaches at a specific location 5 times in one week and customers at another location in the same chain complained about a cashier named Bryan 4 times in one week.

Once Benchmark understand what these trends are, we can surface actionable insights that retail chains can use to improve the performance across their portfolio of locations.   .... "