From Moore’s Law in 1971 to Metcalfe’s Law in 1995 to … Watson’s Law in 2018? IBM is heralding a new digital age – with a bit of chutzpah – with the name of its artificial intelligence engine.
“It’s an exponential moment, when both business and technology architectures change at the same time. It has the potential to change everything,” said IBM chairman, president and CEO Ginni Rometty at the IBM Think conference in Las Vegas last week.
IBM Watson integrates the entire spectrum of data science, artificial intelligence and machine learning to lay a foundation for open and adaptive AI. At IBM Think, the tech giant unveiled a number of new cloud technologies (private, public and on-premises), open AI opportunities for businesses, and the fully-customisable Watson Assistant that takes a new approach in the AI space by only talking to businesses.
IBM’s end goal with Watson is to build a data-driven culture for enterprises. It is asking: how can artificial intelligence (AI) be integrated into every profession or industry and industries to transform workflow? And how can one ensure that the data that is gathered will be secure and accessible, wherever it lives, and that data-driven insights can be turned into competitive advantage?
The contrast is with narrow AI, which is able to perform simple smartphone tasks like distinguishing the difference between a cat and a baby in a camera roll, using machine learning (ML). Watson has been ramped up substantially for broader, more in-depth AI, which encompasses the use of smart data patterns, and blockchain for exponential learning.
“Ultimately, we need to make data incredibly simple and accessible with no assembly required,” said Rob Thomas, general manager for IBM Analytics. “IBM Cloud Private for Data is the only platform in the enterprise with no assembly required. It’s Cloud Agile.”
IBM also unveiled two key partnerships with Apple at IBM Think: IBM Watson Services for Apple’s AI, Core ML, and IBM Cloud Developer Console for Apple.
IBM Watson Services for Core ML will allow companies to create AI-powered apps that securely connect to their enterprise data and can run offline and on cloud. The main differentiator is that the AI continuously learns, adapts and improves through each user interaction.
“All iOS developers can now build applications in devices that run Watson, even if they’re not connected,” said David Kenny, IBM’s senior vice president for IBM Watson and Cloud Platform.
“It’s about getting a better understand of what’s going on.”
The new IBM Cloud Developer Console for Apple provides key tools, like pre-configured starter kits, along with AI, data and mobile services for Apple’s coding language Swift. This enables developers to link to IBM Cloud to build easy-to-code apps that can be integrated with enterprise data and are quick to deploy.
“Watson can help you reimagine your workflows,” said Kenny. “There’s a lot of noise in the AI space, but somebody needed to help the enterprise with deep, vertical expertise. It’s about security, transparency and compliance and we wanted to make it easy for businesses to get started, so we packaged together Watson Assistant.”
Siri or Alexa? Djingo and Cortana? No matter what a company names its voice assistant, there’s a good chance it’s Watson underneath. Enter Watson Assistant: it can be embedded into anything and be used in industry-specific applications where businesses can also white-label the service. This means there is no official Watson Assistant wake-word, such as “Hey Siri”, nor plans for a Watson-branded device to be sold in the shops.
“We’re training Watson Assistant with data which really understands industries,” said Kenny. “We want to make it easier for every developer in the world who is building applications.”
Watson Assistant can be implemented across key industry sectors, from hospitality to banking data, insurance, agriculture and the automotive industry. The overarching idea is to combine AI, cloud and the Internet of Things to help businesses enhance their brand and customer experiences.
IBM Watson Assistant for Automotive, for example, is a digital assistant designed to help the automotive industry understand and interact with drivers and passengers.
In the agriculture space, IBM Watson IoT can analyse farm data like temperature, soil pH and other environmental factors to give farmers insights that can help them make better decisions – and harvest greater yields. On a global scale, Identity Guard is using IBM Watson to fight cyberbullying, using social media and smart AI monitoring tools. A collaboration between IBM Research and the University of Oxford has begun using machine intelligence to simulate and explore more effective malaria policy interventions.
As Watson Assistant develops a deeper understanding of the user, it will be able to include additional factors, such as their location and time of day. The difference between Watson Assistant and voice assistants is that learns through each interaction.
Watson, as an AI platform, can quickly build and deploy chatbots and virtual agents across a variety of channels, including mobile devices, messaging platforms, and even robots.
With Watson, IBM believes that companies won’t need to fight data, but rather use it to accelerate research and discovery, and enrich customer interactions. Adaptive AI isn’t just an advantage, was the underlying message at IBM Think, it’s essential.