Codify Academy Taps IBM Cloud with Watson to Design Cognitive Chatbot — from finance.yahoo.com
Chatbot “Bobbot” has driven thousands of potential leads, 10 percent increase in converting visitors to students

Excerpt:

ARMONK, N.Y., Aug. 4, 2017 /PRNewswire/ — IBM (NYSE: IBM) today announced that Codify Academy, a San Francisco-based developer education startup, tapped into IBM Cloud’s cognitive services to create an interactive cognitive chatbot, Bobbot, that is improving student experiences and increasing enrollment.

Using the IBM Watson Conversation Service, Bobbot fields questions from prospective and current students in natural language via the company’s website. Since implementing the chatbot, Codify Academy has engaged thousands of potential leads through live conversation between the bot and site visitors, leading to a 10 percent increase in converting these visitors into students.

 

 

Bobbot can answer more than 200 common questions about enrollment, course and program details, tuition, and prerequisites, in turn enabling Codify Academy staff to focus on deeper, more meaningful exchanges.

 

 

 


Also see:

Chatbots — The Beginners Guide
 — from chatbotsmagazine.com

Excerpt:

If you search for chatbots on Google, you’ll probably come across hundreds of pages starting from what is a chatbot to how to build one. This is because we’re in 2017, the year of the chatbots revolution.

I’ve been introduced to many people who are new to this space, and who are very interested and motivated in entering it, rather they’re software developers, entrepreneurs, or just tech hobbyists. Entering this space for the first time, has become overwhelming in just a few months, particularly after Facebook announced the release of the messenger API at F8 developer conference. Due to this matter, I’ve decided to simplify the basic steps of entering this fascinating world.

 


 

 

 

 

155 chatbots in this brand new landscape. Where does your bot fit? — from venturebeat.com by Carylyne Chan

Excerpt:

Since we started building bots at KeyReply more than two years ago, the industry has seen massive interest and change. This makes it hard for companies and customers to figure out what’s really happening — so we hope to throw some light on this industry by creating a landscape of chatbot-related businesses. There’s no way to put everyone into this landscape, so we have selected examples that give readers an overview of the industry, such as notable or dominant providers and tools widely used to develop bots.

To put everything into a coherent structure, we arranged companies along the axes according to the functions of their bots and how they built them.

On the horizontal axis, the “marketing” function refers to a bot’s ability to drive exposure, reach, and interaction with the brand or product for potential and current customers. The “support” function refers to a bot’s ability to assist current customers with problems and to resolve those problems for them.

On the vertical axis, “managed” refers to companies outsourcing the development of bots to external vendors, whereas “self-serve” refers to them building their bots in-house or with an off-the-shelf tool.

 

 

 

 

 

 

2017 Ed Tech Trends: The Halfway Point — from campustechnology.com by Rhea Kelly
Four higher ed IT leaders weigh in on the current state of education technology and what’s ahead.

This article includes some perspectives shared from the following 4 IT leaders:

  • Susan Aldridge, Senior Vice President for Online Learning, Drexel University (PA); President, Drexel University Online
  • Daniel Christian, Adjunct Faculty Member, Calvin College
  • Marci Powell, CEO/President, Marci Powell & Associates; Chair Emerita and Past President, United States Distance Learning Association
  • Phil Ventimiglia, Chief Innovation Officer, Georgia State University

 

 

Also see:

 

 

 

From DSC:
Reviewing the article below made me think of 2 potential additions to the Learning & Development Groups/Departments out there:

  1. Help people build their own learning ecosystems
  2. Design, develop, and implement workbots for self-service

 



 

Chatbots Poised to Revolutionize HR — from by Pratibha Nanduri

Excerpt:

Self-service is becoming an increasingly popular trend where people want to perform their tasks without needing help or input from anyone else. The increasing popularity of this trend is mainly attributed to the increasing use of computers and mobile devices to electronically manage all kinds of tasks.

As employee tolerance for downtime reduces and preferences for mobility increases, the bureaucracy which exists in managing everyday HR related tasks in the workplace will also have to be replaced. A large number of companies have still not automated even their basic HR services such as handling inquiries about holidays and leaves. Employees in such organizations still have to send their query and then wait for HR to respond.

As the number of employees goes up in an organization, the time taken by HR managers to respond to mundane admin tasks also increases. This leaves very little time for the HR manager to focus on strategic HR initiatives.

Chatbots that are powered by AI and machine learning are increasingly being used to automate mundane and repetitive tasks. They can also be leveraged in HR to simulate intelligent SMS-based conversations between employees and HR team members to automate basic HR tasks.

 



 

 

Google’s AI Guru Says That Great Artificial Intelligence Must Build on Neuroscience — from technologyreview.com by Jamie Condliffe
Inquisitiveness and imagination will be hard to create any other way.

Excerpt:

Demis Hassabis knows a thing or two about artificial intelligence: he founded the London-based AI startup DeepMind, which was purchased by Google for $650 million back in 2014. Since then, his company has wiped the floor with humans at the complex game of Go and begun making steps towards crafting more general AIs.

But now he’s come out and said that be believes the only way for artificial intelligence to realize its true potential is with a dose of inspiration from human intellect.

Currently, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. But different types of machine learning, such as speech recognition or identifying objects in an image, require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks.

Building AI that can perform general tasks, rather than niche ones, is a long-held desire in the world of machine learning. But the truth is that expanding those specialized algorithms to something more versatile remains an incredibly difficult problem, in part because human traits like inquisitiveness, imagination, and memory don’t exist or are only in their infancy in the world of AI.

 

First, they say, better understanding of how the brain works will allow us to create new structures and algorithms for electronic intelligence. 

 

From DSC:
Glory to God! I find it very interesting to see how people and organizations — via very significant costs/investments — keep trying to mimic the most amazing thing — the human mind. Turns out, that’s not so easy:

But the truth is that expanding those specialized algorithms to something more versatile remains an incredibly difficult problem…

Therefore, some scripture comes to my own mind here:

Psalm 139:14 New International Version (NIV)

14 I praise you because I am fearfully and wonderfully made;
    your works are wonderful,
    I know that full well.

Job 12:13 (NIV)

13 “To God belong wisdom and power;
    counsel and understanding are his.

Psalm 104:24 (NIV)

24 How many are your works, Lord!
    In wisdom you made them all;
    the earth is full of your creatures.

Revelation 4:11 (NIV)

11 “You are worthy, our Lord and God,
    to receive glory and honor and power,
for you created all things,
    and by your will they were created
    and have their being.”

Yes, the LORD designed the human mind by His unfathomable and deep wisdom and understanding.

Glory to God!

Thanks be to God!

 

 

 

The Business of Artificial Intelligence — from hbr.org by Erik Brynjolfsson & Andrew McAfee

Excerpts (emphasis DSC):

The most important general-purpose technology of our era is artificial intelligence, particularly machine learning (ML) — that is, the machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it’s given. Within just the past few years machine learning has become far more effective and widely available. We can now build systems that learn how to perform tasks on their own.

Why is this such a big deal? Two reasons. First, we humans know more than we can tell: We can’t explain exactly how we’re able to do a lot of things — from recognizing a face to making a smart move in the ancient Asian strategy game of Go. Prior to ML, this inability to articulate our own knowledge meant that we couldn’t automate many tasks. Now we can.

Second, ML systems are often excellent learners. They can achieve superhuman performance in a wide range of activities, including detecting fraud and diagnosing disease. Excellent digital learners are being deployed across the economy, and their impact will be profound.

In the sphere of business, AI is poised have a transformational impact, on the scale of earlier general-purpose technologies. Although it is already in use in thousands of companies around the world, most big opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning. The bottleneck now is in management, implementation, and business imagination.

The machine learns from examples, rather than being explicitly programmed for a particular outcome.

 

Let’s start by exploring what AI is already doing and how quickly it is improving. The biggest advances have been in two broad areas: perception and cognition. …For instance, Aptonomy and Sanbot, makers respectively of drones and robots, are using improved vision systems to automate much of the work of security guards. 

 

 

Machine learning is driving changes at three levels: tasks and occupations, business processes, and business models. 

 

 

You may have noticed that Facebook and other apps now recognize many of your friends’ faces in posted photos and prompt you to tag them with their names.

 

 

 

Video: 4 FAQs about Watson as tutor — from er.educause.edu by Satya Nitta

Excerpt:

How is IBM using Watson’s intelligent tutoring system? So we are attempting to mimic the best practices of human tutoring. The gold standard will always remain one on one human to human tutoring. The whole idea here is an intelligent tutoring system as a computing system that works autonomously with learners, so there is no human intervention. It’s basically pretending to be the teacher itself and it’s working with the learner. What we’re attempting to do is we’re attempting to basically put conversational systems, systems that understand human conversation and dialogue, and we’re trying to build a system that, in a very natural way, interacts with people through conversation. The system basically has the ability to ask questions, to answer questions, to know who you are and where you are in your learning journey, what you’re struggling with, what you’re strong on and it will personalize its pedagogy to you.

There’s a natural language understanding system and a machine learning system that’s trying to figure out where you are in your learning journey and what the appropriate intervention is for you. The natural language system enables this interaction that’s very rich and conversation-based, where you can basically have a human-like conversation with it and, to a large extent, it will try to understand and to retrieve the right things for you. Again the most important thing is that we will set the expectations appropriately and we have appropriate exit criteria for when the system doesn’t actually understand what you’re trying to do.

 

 

 

Chatbot lawyer, which contested £7.2M in parking tickets, now offers legal help for 1,000+ topics — from arstechnica.co.uk by Sebastian Anthony
DoNotPay has expanded to cover the UK and all 50 US states. Free legal help for everyone!

Excerpt:

In total, DoNotPay now has over 1,000 separate chatbots that generate formal-sounding documents for a range of basic legal issues, such as seeking remuneration for a delayed flight or train, reporting discrimination, or asking for maternity leave. If you divide that by 51 (US and UK) you get a rough idea of how many different topics are covered. Each bot had to be hand-crafted by the British creator Joshua Browder, with the assistance of part-time and volunteer lawyers to ensure that the the documents are actually fit for purpose.

 

 

British student’s free robot lawyer can fight speeding tickets and rogue landlords — from telegraph.co.uk by Cara McGoogan

Excerpt:

A free “robot lawyer” that has overturned thousands of parking tickets in the UK can now fight rogue landlords, speeding tickets and harassment at work.

Joshua Browder, the 20-year-old British student who created the aide, has upgraded the robot’s abilities so it can fight legal disputes in 1,000 different areas. These include fighting landlords over security deposits and house repairs, and helping people report fraud to their credit card agency.

To get robot advice, users type their problem into the DoNotPay site and it directs them to a chat bot that can solve their particular legal issue. It can draft letters and offer advice on problems from credit card fraud to airline compensation.

 

 

Free robot lawyer helps low-income people tackle more than 1,000 legal issues — from mashable.com by Katie Dupere

Excerpt:

Shady businesses, you’re on notice. This robot lawyer is coming after you if you play dirty.

Noted legal aid chatbot DoNotPay just announced a massive expansion, which will help users tackle issues in 1,000 legal areas entirely for free. The new features, which launched on Wednesday, cover consumer and workplace rights, and will be available in all 50 states and the UK.

While the bot will still help drivers contest parking tickets and refugees apply for asylum, the service will now also help those who want to report harassment in the workplace or who simply want a refund on a busted toaster.

 

 



From DSC:
Whereas this type of bot is meant for external communications/assistance, we should also watch for Work Bots within an organization — dishing up real-time answers to questions that employees have about a variety of topics. I think that’s the next generation of technical communications, technical/help desk support, as well as training and development groups (at least some of the staff in those departments will likely be building these types of bots).



 

Addendum on 7/15/17:

LawGeex: Contract Review Automation

Excerpt (emphasis DSC):

The LawGeex Contract Review Automation enables anyone in your business to easily submit and receive approvals on contracts without waiting for the legal team. Our A.I. technology reads, reviews and understands your contracts, approving those that meet your legal team’s pre-defined criteria, and escalating those that don’t. Legal can maintain control and mitigate risk while giving other departments the freedom they need to get business moving.

 

 

Winner takes all — from by Michael Moe, Luben Pampoulov, Li Jiang, Nick Franco, & Suzee Han

 

We did a lot of things that seemed crazy at the time. Many of those crazy things now have over a billion users, like Google Maps, YouTube, Chrome, and Android.

— Larry Page, CEO, Alphabet

 

 

Excerpt:

An alphabet is a collection of letters that represent language. Alphabet, accordingly, is a collection of companies that represent the many bets Larry Page is making to ensure his platform is built to not only survive, but to thrive in a future defined by accelerating digital disruption. It’s an “Alpha” bet on a diversified platform of assets.

If you look closely, the world’s top technology companies are making similar bets.

 


 

 

Technology in general and the Internet in particular is all about a disproportionate gains to the leader in a category. Accordingly, as technology leaders like Facebook, Alphabet, and Amazon survey the competitive landscape, they have increasingly aimed to develop and acquire emerging technology capabilities across a broad range of complementary categories.

 

 

 

From DSC:
After reading the item below, I wondered:

Should technical communicators, trainers, and help desk personnel get trained on how to design and develop “workbots?”


 

Forget chatbots — you should create a workbot instead — from venturebeat.com by Oren Ariel; with thanks to Thomas Frey for his tweet on this

Excerpts (emphasis DSC):

But what about employee-to-company interaction through bots? Chatbots designed for the work environment, or workbots, could become the next step function in work productivity.

Workbots could be the cure for what’s often called “app fatigue.”

They work within the corporate messenger environment (such as Jabber, Skype for Business, Slack, and others) and respond to commands and questions in natural language, whether typed or dictated. They have access to all the corporate information needed to get the job done and can perform complex tasks across multiple systems. The workbot knows what tasks are executed in which back-end system, so the user doesn’t have to know. Because bots rely on natural language processing (NLP) — the ability of humans to interact with computers using free-form language — workbots can help an employee get to the starting point quickly and without any training, in the same way a search engine would, and then help guide the user through the task in a step-by-step fashion.

Chat is no longer just about communication, it’s about bringing the user information.

 

 

 
© 2017 | Daniel Christian