If you like listening to a podcast while taking a walk, you are one of millions of people who enjoy doing this every day. Now, you can experience something totally new: interactive AI podcasting. Instead of being a passive listener, you control the flow and use of the content. You curate your own podcast experience.

What is an Interactive AI Podcast?

Interactive AI podcasts allow you to:

• Have dialogue like talking with an assistant
• Skip to the next story or next subject matter
• Ask questions/get answers about something you heard in the story
• Repeat sections of importance or pause for thinking
• Express your opinion and provide feedback simply by talking
• See images and videos accompanying the storyline

Interactive AI podcasts allow the content creator to:

• Have the AI computer voice the story automatically
• Learn where listeners skipped and disliked content
• Understand what questions were posed, and what engaged listeners
• Receive listener opinions and feedback
• Overcome the limitations of conventional podcasts as described above

Try Dr. Margo, Interactive AI Podcasting, Subject: Coronavirus

Try the BETA version of interactive podcasting (links below)! The best experience is designed for the mobile use (wearing headphones. The link to download mobile app iOS is here, and Android is here. Mobile apps have complete voice interaction – say or click on “Podcast” to start it, then say “stop podcast” to end it. The app also provides images and videos accompanying the story. Use headphones!

The link for Dr. Margo is here where you can test her using the Web browser. Make sure to click on the speaker button to hear the podcast (the button is at the bottom inside the search box.) Note that the Web browser version does not take your voice, it only takes your typing. Dr. Margo’s virtual expert will continue servicing after the podcast with questions and further information about the coronavirus.

A New Approach to Education and Corporate Training

Podcast can be an effective educational tool. Now that is enhanced by interactive AI control. Most importantly, the listener can talk to it just as talking to a teacher or a tutor.  Once dialogue is introduced, the most important element of learning starts to emerge.

The beauty of mobile phone technology is to connect us to an information source via headphones while we are busy with mundane things in life. Working out, cycling, walking, cleaning, gardening, etc. all may be accompanied by a podcast, as we multi-task and expand our potential. Interactive AI Podcasts allows the listener to pause, repeat, ask a question, or skip ahead. These are all basic functions of learning, which are further enhanced by images and videos.

Turn Your Documents into an AI Podcast

This new technology was created by exClone, which now offers its platform to you to try Interactive AI Podcasting. Click here to request a demo. The platform will be accessible by simple subscription soon.

Happy interactive podcasting!

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exClone App (iOS) Ecosystem of virtual experts (beta)

exClone App (Android) Ecosystem of virtual experts (beta)

It is finally here. You can now convert your MS Word/PDF documents into Chatbots and Virtual Experts with exClone technology. No coding involved, no data sets to mingle with, no long training cycles, no experience in AI. This is the highest level of automation in the market today where all AI functions are tucked under the hood, invisible to a chatbot builder. As a result, the path between an expert and his/her virtual version involves no other process/developer in between.

A Chatbot Learning from Documents Becomes a Virtual Expert
Siri, Cortana, Hey Google, or Alexa, lack any expertise they can chat about. If a question is asked with some complexity, they point you to search results. exClone’s process yields a virtual expert where questions are answered about the particular subject. Here is an example, Frank, who is a virtual expert on crystallography solutions using Phenix software system. Frank was built straight from MS Word documents in a single step process (we call it Instant Learning). The documents were written and curated by a real expert.

On-the-fly Learning by Conversations with Teachers After Deployment
In addition to learning from documents for deployment, exClone offers teaching virtual experts on-the-fly through conversations by designated teachers after deployment. This has a number of advantages one of which is the ability to update the system with new or modified knowledge anytime without the need for re-deployment.

Answering Questions at the Concept Level

The most powerful feature of the exClone system is its ontological answering capability where words of the question and its answer don’t match, but the concepts they refer to do match. The proprietary machine learning algorithm (Instant Learning) is able to achieve an almost human level of understanding when answering questions. This means that the system can handle hundreds of various forms of a single question, which points to the same meaning, thus can bring the same relevant answer. This is the ultimate goal in making computers understand language and learn knowledge correctly.

What does this Mean for Enterprises?
Documents in the world of enterprise are the main asset to encapsulate and preserve organizational expertise. Being able to create virtual experts out of these documents easily, with no specialized effort, means that it is now scalable and inexpensive to launch enhancements to enterprise search, help desk, call center, and training systems.

With virtual experts, the workers and customers of an enterprise can access critical information via conversational (messaging) type interface, rapidly, accurately, and efficiently. Such an efficiency directly improves bottom line.

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One of the biggest impacts chatbots are expected to make on society will be in the medical field. The newly launched DrCHAT.ai (in beta) is a prime example. DrCHAT provides patients with medical consultations prior to initial doctor’s visits, or a second opinion afterwards. Free usage and the ubiquitous availability of DrCHAT allows patients to continue consultation at every stage of treatment. This empowers women, with a number of benefits to the entire health ecosystem, and it presents unlimited potential for the use of technology such as DrChat to improve the nexus between patients and care.

The only obstacle for chatbots becoming virtual doctors is the ability to handle consultation dialogue similar to what occurs in a doctor’s office.

The dialogue obstacle is a major challenge, and solving it will determine who wins the race to claim this value service space.

Knowledge-driven Machine Learning as the Backbone
While most machine learning methods are data-driven, they all suffer the problems of data availability and reliability. However, volumes of medical knowledge are readily available that may be turned into a dialogue system. Knowledge-based machine learning accomplishes just that without the rigorous requirements of a data-driven approach. The expertise of a medical doctor, as depicted below, is converted into a conversational system through the knowledge-driven machine learning method (as indicated by the blue arrow). This process is explained in simple terms in two linkedin articles “Deep Cloning Versus Deep Learning” and “Can Machine Learning Use Knowledge …”

In the case of DrCHAT, the expertise is derived from certified Ob/Gyn physicians who have laid out over 30 different clinical flows – following American College of Obstetricians & Gynecologists guidelines for evidence-based care. Although the machine learning process continues its growth, some beta-testers have been granted early access to DrCHAT.

Compared to Flat Search Systems
One of the striking differences between flat (single-step) searches using Google, WebMD, or Wikipedia and a medical chatbot such as DrCHAT is the consultation dialogue, in which clinical work flows are utilized to allow a step-by-step conversation to diagnose illnesses and suggest treatment options. Considering the popular usage of mobile devices and messaging apps, consultation dialogue offers the richest and quickest experience compared to opening documents and sifting through large volumes of text on a narrow screen.

Single-step search engines fall short for health problems that require multi-step interaction with a patient to suggest diagnosis and treatment options.

Current Health Apps are Not Chatbots
Some current health apps, including ADA, Babylon, and YourMD, offer valuable services such as scheduling visits or video conferencing with doctors. However, their chatbot interactions are imitations of a single-step search with no genuine dialogue capability. The fact that these apps are geared toward “general medicine” to cover everything without specialization makes them less capable of delivering the requested consultation. Medicine is such a vast topic that automated consultation is best handled by specialized expertise.

Professional Version

Another important feature of DrCHAT is that it comes in two versions, one for patients and the other for professionals. Although derived from the same expertise (IP), the professional version lays out the clinical flows for decision-making which is a valuable reminder, fact-checker, and a quick guide for practitioners. The complexity of the medical terminology used during a dialogue also differs between the two versions.

Anonymity is a Big Plus for Women’s Health Chatbot

Most Ob/Gyn specialists agree that women do not always feel comfortable talking about their intimate problems, and sometimes skip mentioning critical details during face-to-face consultation. DrCHAT’s approach of anonymous dialogue, without any registration, will break down some of these barriers and further empower women during these exchanges. In return, conversation logs (without identity information) become a valuable source of information to analyze women’s behavior under a regular clinical examination.

The Future of Health Chatbots
Where we go from here will be determined by the engagement and acceptance level of health chatbots such as DrCHAT. It is clear, however, that once the concept has been validated, other specialty areas may be replicated quickly by deploying the underlying technology – which focuses on automated knowledge acquisition from experts. Cardiology, Emergency Medicine, Pediatrics, and Urology (men’s health) are some of the specialties to be launched under DrCHAT following Women’s Health. If you want to be a tester, just talk to the chatbot and ask to become a tester. Stay tuned for more on health chatbots.

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This title is the summary of what is happening in the market today, mostly encouraged by Facebook’s move for Messenger bots.

The ChatbotConf 2017 revealed this sad truth. There are 200,000 Messenger bots today, most likely none of them have a real AI backbone. A recent article summarizing the conference draws a similar conclusion.

End users of chatbots would not really care whether there is AI backbone or not if the chatbot they are using solves their problem. In a small fraction of cases, chatbots without AI can be helpful, especially in e-commerce transactions where buying and selling options are rudimentary, and the conversations can be buttonized. However, the AI issue surfaces when chatbots try to service higher complexity tasks. The way chatbots can be used in real life, this corresponds to, maybe, 90% of the cases. So, what is the AI backbone that is required?

The AI Backbone

Chatbots that represent AI must have some (if not all) of the capabilities listed below:

• NLP: Capability to understand users’ responses in their most variant form.
• Answering Questions: Ability to communicate with the user about a subject matter by absorbing knowledge and answering questions about it.
• Asking Questions: Ability to ask questions to navigate the user to solve a problem.
• Dialogue Behavior: Ability to engage users in certain behavior in concert with the chatbot’s objective (sales, transactions, advice, training, story telling, idea sharing, etc.)
• Learning from Conversations: Ability to ask users for answers and to learn from them. This should be optional since social input may not be desirable for certain objectives.
• Short-term Memory: Ability to remember the topic of conversation and interpret pronouns correctly. This requires chatbot to take into account what was said 2, 3, or 4 steps earlier.
• Long-term Memory: Remembering previous chat sessions and starting conversation from where it was left of.
• Emotions and Attitude: Ability to detect unproductive conversations, change strategy, or abort not to waste resources.
• Awareness: Ability to self-assess its performance, produce reports about its performance, and suggest bot builders the weaknesses encountered.
• Infinite Speech: Not to be restricted by a pre-defined steps of conversation.

Canning Responses Instance-by-Instance is not AI

Most chatbot platforms today are requiring instance-by-instance input from its builder to develop every step of the intended conversation in a rigid sequence. This approach is feasible for banking transactions, travel bookings, or other similar interactions where dialogue is restricted to solid options. Obviously, there is no AI backbone needed for such chatbots.

Chatbot science is at its infancy while most developers are expecting adult behavior.

Deep Learning is not a Silver Bullet

One of the latest misconceptions emerged in the market is that if there is enough data thrown at deep learning system, all the requirements listed above as AI backbone can be satisfied. Deep learning can only handle some parts of the required list, and the rest must be called the “chatbot science”. The only way to produce a chatbot development platform in the scope of AI backbone is to offer data-driven tools and/or knowledge-driven tools with certain level of built-in functions, where those functions define the secrets of the chatbot science.

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#chatbot #chatbots #AI #artificialintelligence #ConversationalAI #Virtualassistants #bots #machinelearning #NLP #DL #deeplearning

In this context, cloning is an advanced form of impersonating where the chatbot can talk about the person’s life experiences and his/her expertise as curated by the chatbot maker. Compared to impersonating a person just using his/her image and name, cloning is obviously more involved and more challenging. As an example, you can chat with Abraham Lincoln and see how it was developed via one-shot machine learning technology with no-coding requirement. This chatbot uses Wikipedia content as its main source of conversation.

As one can easily deduce, all historical characters can be cloned into chatbots for educational purposes. But cloning goes beyond that as it allows creating chatbots of teachers themselves.

Top 6 Reasons Why Cloning Chatbots are Inevitable Tools for Education

1. Control: Interactive content gives students much more control over what they want to focus on.
2. Fun: Talking/messaging/chatting is always more fun than just reading.
3. Ease: Use of small screen devices are ideal fit for chatbots which add to their educational role.
4. New Teaching Methods: Chatbots can be a great summarization tool offering students main points to remember and option to dive deeper. Various new teaching strategies can be implemented.
5. Creativity: Creation of chatbots can also be an educational experience.
6. Feedback: Conversational analytics obtainable from chatbot interactions provide valuable clues to teachers as to how students learn, or fail to learn.

Profiliration of Chatbots Require Editorial Platforms

For chatbots to take a serious role in education, their development and profiliration must be fast and effective. Here are the three most important requirements for such a progress:

1. No Coding: Chatbot creation should migrate from a coding effort to an editorial effort. This will enable students and teachers to develop education chatbots by curating content only.
2. No Corpus Training: Underlying technology should not require large corpus training, and no experience in AI. One-shot machine learning techniques must drive these platforms processing the content for chat interaction while working silently in the background.
3. Effective Communicator: Chatbots created for education must be effective, being able to answer improptu questions and offer topics of discussion. Although no chatbot today is expected to match human level dialogue, the educational effectiveness can be achieved by presenting chatbots for the specific goals they are designed for.

If you come across cloning/impersonating chatbots, please drop a note below. We may create a list of educational chatbots here.