IDEAS for New Business with Low investment
Summary: Watson is a remarkably flexible and complete AI development platform. To understand how you might build new services for your current employer or imagine your own Watson-based startup, look at these 30 companies that are leading the way.
In our recent reviews of historical Watson and the modern Watson of today we concluded that IBM’s Watson Group may have the first or at least the current strongest comprehensive AI platform. This is the first time that we know of that all three elements of AI have been brought together in a single user friendly platform: image processing, text and speech processing, and knowledge retrieval.
This is not so much a platform for data scientist to use to expand the capabilities of AI as it is a platform for business users (with the aid of data scientists) to exploit the capabilities of modern AI by building new products and services.
To wrap up this review of Watson, we wanted to provide some thought-starters on what new services or even new businesses you might build on Watson.
Oh, and regarding new businesses, did we mention that developers who join the Watson Ecosystem are eligible to become a Watson “partner” with a shot at the $100 Million funding IBM is making available to startups plus support and access from IBM business and technology advisors.
Defining the Opportunity in General
Deciding whether or not Watson is right for your idea is simple. The problem you define will ideally require all four of these capabilities:
- Understand: analyze and interpret all of your data, including unstructured text, images, audio and video.
- Reason: provide personalized recommendations by understanding a user's personality, tone, and emotion.
- Learn: utilize machine learning to grow the subject matter expertise in your apps and systems.
- Interact: create chat bots that can engage in dialog.
Another way to look at it is from the component standpoint.
The Knowledge Base
There must be some reasonably large body of knowledge you possess that is sufficiently complex that it’s difficult for any one person to fully grasp.
A person must need the information and be asking the question. If this was machine-to-machine there would be no need for the NLP processing and the questions would presumably be much less complex.
On the simple end, this might be all the possible rules and variations on how to set up a new account in a bank or how to order or return a product on your ecommerce site. On the complex end this may be all the possible symptoms, diagnoses, and procedures for a medical condition or potential failure and repair procedures for a complex device. On the really complex end, this could be all the known chemicals and how science allows them to interact in multiple combinations.
You will need to load and maintain the Knowledge Base, adding material as policies or possibilities expand and removing knowledge that is no longer accurate. In other words the Knowledge Base must be curated.
In a customer service application this may not be as difficult as you think since it could be loaded and largely trained directly from prior CSR logs and text-translated recordings. However, deciding what should be in the Knowledge Base and getting it there will be the most demanding part of the task.
The information contained in your Knowledge Base can have some very dynamic elements. For example, it might contain a constant social media stream (curated only to remove older material that is probably no longer relevant) allowing it to respond about trends perceived by some portion of the public.
Your Knowledge Base is not limited to text. It can also include audio clips, video, and still images. For example if the response to a query is best explained by a picture, or conversely if your user wants to input a picture and have you identify some appropriate action about that picture.
QAMs have the capability to fully interpret natural language whether written or spoken. More importantly they can also intake still images and videos as part of the query. For example, here is a picture of a rash on my arm – what should I do about it.
Outputs can also be combinations of text, speech, image, or video. Importantly, don’t forget augmented reality devices as an output. For example, in a preventive maintenance situation, the augmented reality device could display the exact repair steps needed displayed directly on the machine under repair, showing the technician exactly where to work and modifying its recommendation as each step is completed and fed back to the QAM.
Some Idea Starters
Sometimes it’s just easier to imagine how you can use a new technology if you have examples of how others have used it. So here are a number of short descriptions of new businesses or new services that have been built on Watson to get your creative juices flowing. You can see even more here.
Healthcare (Probably no area is more impacted by Watson than Healthcare)
1. Welltok built the CaféWell Health Optimization Platform which provides incentives for consumers to take care of their health. Welltok is IBM Watson’s first Ecosystem partner in consumer health and also IBM Watson’s first investment. User can ask questions in regular language, and get intelligent responses on health issues and fitness.
2. Medtronic PLC a manufacturer of medical devices will be using Watson's technology to predict diabetic attacks. The app helps patients monitor glucose levels by measuring the calories burned and food eaten.
3. Celgene Corporation and IBM Watson Health are co-developing IBM Watson for Patient Safety, a new offering that aims to enhance pharmacovigilance methods used to collect, assess, monitor, and report adverse drug reactions. Watson’s cognitive computing engine continuously learns, so it is expected that Watson for Patient Safety will increasingly be able to help identify potential drug safety signals.
4. Siemens Healthineers and IBM’s Watson Group are co-developing a platform for Population Health Management. The alliance aims to help hospitals, health systems, integrated delivery networks, and other providers deliver value-based care to patients with complex, chronic and costly conditions such as heart disease and cancer.
5. Talkspace is a global online platform that allows users to chat with a licensed therapist confidentially and anonymously. Talkspace is using IBM Watson’s Personality Insights API to better match users with therapists in their network using a self-learning system that seeks to better understand the traits of individual users.
6. LifeLearn used Watson to create Sofie, a tool to help Veterinarians diagnose and treat patients, a natural extension of Watson’s success in applications that diagnose and recommend treatments for human ailments. James Carroll, CEO of LifeLearn describes Sofie as "a treatment support application that provides veterinarians with the ability to derive evidence-based hypotheses with natural language inquiries to challenging medical situations."