— IBM Power Systems (@IBMPowerSystems) December 5, 2017
Today, the world’s largest Fortune 500 companies and tech disruptors joined forces for a truly successful first day of The AI Summit NYC. With technical expertise dominating at Stream I talks, a huge product announcement by IBM, and a bustling expo area and demo zone throughout, it’s clear that AI is no longer hype – it’s a reality. Although by no means exhaustive, here are some of our key takeaways from some Stream A thought leaders.
Featuring contributions from Apple, IBM Watson, Google, Intel, Reddit, Nestle, TGI Friday’s, and many, many more, Day 2 promises some huge speakers. Don’t forget to keep abreast of all the latest updates as we enter Day 2 tomorrow over on Twitter using the hashtag #AISummit.
1. The tech landscape is changing fast – with big implications for businesses
The big news of the day came from IBM, who chose the AI Summit as the global launchpad for their new POWER9 chip (VentureBeat, TechCrunch, Forbes). Claiming that the dedicated AI processor will provide the juice for ‘the most powerful supercomputer in existence’, the announcement bookended a key theme highlighted by many speakers throughout the day: the need for enterprises to recognise the rapidly changing technological landscape underpinning AI. This reflects a clear shift in priorities as business and enterprise leaders increasingly move beyond asking about the relevance of AI to questioning how it can best be adopted.
“In the four or five year time window as IBM started in cognitive computing, we decided we had to completely reinvent the space. Software is what the computer does, hardware is what the computer does. For us to be able to get those radical exponential growth capabilities, we need to reinvent the computer for the cognitive era. So we have some very exciting announcements from that standpoint.”
Picciano claimed that the chip is a necessary next step in the AI revolution; symptomatic of a wider need to transform computational architecture and infrastructure. “The way you need to think about your infrastructure is not just on the aspect of how it’ll help scale business processes but how it’s going to unleash actionable insights,” he said. “What’s important to recognise is that the last forty or fifty years of computing has been based on a fairly consistent architecture. However, the math and science associated with this new insight economy is changing dramatically.”
– Bob Picciano, Sr. VP of IBM Cognitive Systems (Read the full story)
“How did this all happen? How did we get here? there’s been two parallel changes and disruptive forces happening at the same time. We all know over the last 30 years we’ve made tremendous advances with Moore’s Law – doubling CPU power. We’re actually reaching the physical limits of what you can put on a chip. The innovators realised that the GPU was the secret sauce that would result in AI being here and being in our lives on a critical day-to-day basis.”
“These are huge, huge, huge changes. NVIDIA are, if you will, the world’s AI platform, disrupting every single part of the ecosystem and any industry that you can think of. When we think of what this is going to look like in the future, the future is actually going to look very different, whether its the ways we’re accessing our cloud services on a day to day basis, interacting with our devices, to the changes we see in transportation.”
– Andrea De Souza, Global Business Development Lead, NVIDIA (Read our full interview)
”We’ve been fascinated by the concept of talking to computers for years, and today, it’s a reality. Over 10% of US households already have intelligent voice devices in the last 2.5 years – compare that with smartphones, which took five years to reach a 10% adoption rate. We’re moving incredibly quickly. The technology is there today to move to intelligent assistants. Doing the same thing slightly better or slightly faster is not going to be competitive in tomorrow’s landscape. As you look at large organisations in the enterprise, you find people having difficulty with capitalizing on all this potential. So how do we actually transform?”
– Josh Sutton, Global Head of Data and AI Practice, Publicis.Sapient (Read the full story)
“We think we are seeing an AI acceleration in the making right now, and there is going to be a real rate of change in the diversity of compute paradigms that we actually have as a result. What this means is that this acceleration will start to happen for everybody. It will change everything – from the way we live to the way we work. Traditionally, there are two systems: systems of records, and systems of engagement. Systems of intelligence integrates these two systems. So how should we go about creating them?
– Pavandeep Kalra, Director of Data Science, Artificial Intelligence and Research Group, Microsoft (Read more)
“While business executives don’t have to understand all the technical details of what is happening, they do need to be aware of what these technologies can do from a business perspective, how fast they are changing, and the potential disruption to their core business.”
– Anand Rao, Partner and Global AI Lead, PwC (Read more)
2. AI is a disruptive force today, not tomorrow – and business must adapt
One core theme of many of the keynotes was that AI is already transforming industries. Experts from GSK, Genpact, Konica Minolta and many more were very clear that AI is no longer something businesses can ignore. GSK’s Chief Data and Technology Officer, Karenann Terrell, kickstarted the discussion this morning in one of her first public speaking engagements in the role. (Wall Street Journal)
“At GSK, AI is of central importance as we think about our digital ambitions. There is so much news about what’s happening in the area, but I don’t believe this is hype. AI is actually today changing the consumer world in a way that it is starting to move into the digitisation of healthcare. Our industry will be transformed through the use of digital data and analytics. That’s obvious. Every industry is being transformed that way.”
– Karenann Terrell, Chief Data and Technology Officer, Glaxosmithkline (Read our full interview)
“There are 3 big issues that most clients we work with face. The first one is modularity. Most AI implementations aren’t done in silos that include adjacent AI and intelligent automation capabilities, and you’ve got the spectrum of digital technologies that need to come together to take them on their journey. One of the challenges that comes out of that is the need for a modular approach that allows you to insert new capabilities as your needs emerge. No company wants to end up in a scenario where they’re stuck with what they have without having that future proofing that risk mediation – so modularity is a really important part.”
“Equally, with AI, governance is really important, because you’ve got the challenges of errant bots, of biases in machine learning, challenges around picking up politically incorrect language in conversational AI and chatbots. As the workforce shifts from a human workforce to a digital workforce, you do need the control points, the checks and balances, the governance tools that we’ve all evolved with in the human workplace. So governance is a really important part. The best thing about AI is that you’ve got this whole set of technologies – particularly open source technologies that are now available – and the ability to mix and match those, but the challenge is in integrating it with the enterprise applications, because all of the data and all of the current system records already exist on other systems.”
– Sanjay Srivastava, Chief Digital Officer, Genpact (Read more)
“In the last decade, workplaces have started to evolve towards digitalisation. In the future, workplaces will be the natural environment in which the evolution of cognitive or intelligent hubs will lead to a paradigm shift in the creation of AI. In order to thrive, AI solutions need to break away from the ‘cognitive trap’ and act as AI integrators, augmenting what will be a growing commoditisation of algorithms,” Curry argues. “Taking a more holistic, longer-term view of AI services will enable enterprises to move from simply consuming information, towards managing it by augmented intelligence and improving decisionmaking processes.”
– Dennis Curry, Executive Director and Deputy CTO for Konica Minolta (read full interview)
3. AI is transforming digital content – and journalism
Many delegates will be familiar with AI in operations, travel, retail, and more. Keynote speeches from big names in media such as Buzzfeed, Associated Press, NBCUniversal and the New York Times made clear that AI is a top priority for the world’s largest global publications, transforming both the business models of the media and the way content is consumed and delivered. A key priority for AI in media highlighted was the need to get the right content to the right individuals.
“It’s very important for us to develop a framework of how to assess all of these opportunities. The tech costs are going down and there’s a lot of opportunities for tech companies to collaborate with news organisations like AP, but we need a framework. The framework we came up with asks 3 very important questions – why? Are we replacing or augmenting? – The second question is where are we applying this? are we applying this to develop smart content or to automate a specific process? Example would be computer vision to tag photos. Finally, how are we going to approach it? In that scenario, are we going to build it internally or partner with someone externally?”
– Francesco Marconi, AI Co-Lead, Associated Press (Read full interview)
The @nytimes Chief Data Scientist, Chris Wiggins, explains how the publisher created a Slack #chatbot called Blossombot that uses #machinelearning to select which stories would perform well on social media based on audience insights derived from large data sets. #AISummit pic.twitter.com/PmsGKeDu11
— IBM Watson (@IBMWatson) December 5, 2017
“It really is a truly dynamic time for journalism. Every publisher is now a startup – whether its The National, Buzzfeed, or The New York Times. We as a species are working out if there are new scalable business models that can make journalism work today.”
– Chris Wiggins, Chief Data Scientist, The New York Times
“I think of AI as a big disruptive force – and a competitive advantage. With recent advances in natural language processing, computer vision, and machine learning, AI offers powerful tools that continue to transform our industry. This will move us closer to a time when our content will be intelligent, conversant (voice enabled), interactive (responsive), proactive (it will find those who wish to consume it), and automated.”
“AI models require a lot of training – that’s how it works. To take that capability and fit to your application requires lots of customization. It’s easy to fall for the great PowerPoint and demo capabilities and think that, ‘oh, they have what we need and we can just use it’. The accuracy and confidence levels, however, vary significantly. Understanding the total cost of ownership is extremely important.”
– Sowmya Gottipati, VP Media Labs, NBCUniversal (Read full interview)