Share this post:
We are witness to the most important and exciting technology shift in more than a generation – the dawn of the cognitive computing era. Cognitive systems, which are most fully realized in IBM’s Watson, can ingest and learn from a wide variety of data, reason over it, and then interact with people in ways that are more natural to us.
Cognitive technologies, including artificial intelligence (AI), augment human capabilities to help people make better decisions. What search is to simple information retrieval, cognitive computing is to advanced decision making. And unlike previous technological shifts that tended to level the playing field, these emerging AI technologies are shaping up to provide true competitive advantage to those organizations that already have intellectual advantages – in particular, robust strategies for accessing data from a variety of proprietary, third-party and public sources.
This could be the first technology shift in years that actually empowers and enhances established industry leaders–-those who refuse to let their valuable knowledge be commoditized by an intermediary.
That’s where the development community comes in and plays such a vital role. Cognitive technologies are quickly becoming an ingredient in almost every software application built today, thanks to cloud platforms that allow developers in every business to select the software components that they need to build everything from simple mobile apps to very sophisticated cognitive ecosystems.
At IBM Watson, we are focused on empowering these developers with platforms that are truly self-service and superior in three important ways: Science, Scale and Simplicity.
The tech industry is still in the early days of developing new cognitive capabilities and applying them to the world’s problems. At IBM, we already offer more than 30 Watson APIs, the components that developers use to build their applications, and our Research teams are rapidly expanding them in areas related to vision, tone, and new languages that use advances in machine learning, natural language processing and Deep Q&A.
These APIs are valuable tools for developers as they advance the ability to understand and learn an organization’s unique data, to apply reasoning to this data, and to make it accessible to decision-makers. It’s a uniquely holistic approach to provisioning computer intelligence and to addressing the emerging needs of application developers and business leaders alike.
For example, ROSS Intelligence has developed a system to help law firms search through massive databases of laws and cases and make recommendations about the best strategies for pressing a case. In the healthcare industry, Welltok’s CaféWell concierge offers insights tailored to individual’s wellness needs, learning from users with each interaction and helping to drive healthier behaviors to deliver greater value in the healthcare system.
The retail industry has also seen the transformative powers of cognitive solutions where natural language classification allows companies such as The North Face to help online shoppers find the products they need. Hilton and WayBlazer are piloting a cognitive-enabled concierge robot to transform hospitality services.
One of the most important aspects of building new cognitive applications quickly and scaling to millions of users is the cloud. To truly scale, a platform must enable developers to gain access to all the data they need with security that’s as good as — if not better than — what’s available from on-premise computing systems.
One of the advantages of the cloud is that it allows organizations to take their diverse data sets – from structured and unstructured sources – and combine with data accessed from public and third-party sources to derive new and even more powerful insights. Intelligence is the opposite of a commodity, and it becomes even more valuable when empowered, at scale, with AI.
One of the most advanced examples of this principle in action is the Watson Health Cloud, which allows developers to access the rich longitudinal health data sets that IBM has assembled – de-identified data from more than 300 million medical records and patient “lives”. A pharmaceutical company could combine that data with its own knowledge of biology, chemistry and drug effectiveness to explore more effective treatments for diseases, using Watson to help inform and accelerate research efforts.
Today’s computing environment is complex. It takes a lot of hard science to create AI technologies that work in the real world, and it requires a lot of sophisticated engineering to build the platform approach that I’ve described.
But a superior cognitive computing platform must hide this complexity to embolden developers and to empower its users. Think of it as “self-service AI.” The goal is creating development environments in which it is easy for developers to navigate, compose their apps and launch them – whether they are data scientists in a big bank, an analyst for a retailer, or a coder in a hospital system.
In turn, developers also need to remain focused on making AI simple to use. It’s one of the reasons that I believe a focus on natural human interaction is essential as this new era of computing takes hold.
At IBM Watson, we’re developing powerful services and applications capable of transforming whole industries, from healthcare, insurance, and banking, to retail, education and citizen services.
For every good idea that we have, our development community is thinking up hundreds, and thousands more. These innovators are now able to build on assets of legacy knowledge, empowered by our self-service AI.
The result is a very different type of technology disruption is taking hold, and an entirely new breed of developer is emerging at the front lines. This excites me as together we shape this new cognitive era.
To learn more about the new era of computing, read Smart Machines: IBM’s Watson and the Era of Cognitive Computing.