Reflections from the 2016 CB Insights Innovation Conference
I had the privilege to represent CognitiveScale at the CB Insights Innovation Conference in Santa Barbara, California last week for two days of talks and discussion on AI and its impact on industry. Attendees included investors, analysts, large corporations and entrepreneurs from leading AI startups. CB Insights announced the “AI 100,” a group of 100 startup companies using AI to redefine industries. These companies were selected as the leaders from more than 500 companies nominated. CognitiveScale was recognized as one of the AI 100 in the Core AI segment.
When I attend these conferences, I am looking for the big ideas, trends and insights that I think are key to thinking about how AI and machine learning technology will literally “change the world” over the next decade. This conference was no disappointment. Here are some of my takeaways.
Takeaway #1: Disrupt or Be Disrupted
Technology disrupts industries and that trend is accelerating. Consider the following tidbits presented at the conference:
- The average lifespan of a company in the S&P 500 has changed from 61 years as measured in 1955 to 17 years as measured in 2015. This demonstrates that technology is disrupting industry at a rapidly accelerating pace.
- A GE jet engine contains 100 sensors and captures 1 Terabyte of data on a flight from New York to Chicago. This data is being used to significantly increase efficiency and uptime while reducing maintenance costs.
- Specialized machine learning hardware such as Google’s TPU (Tensor Processing Unit) is already here and is accelerating the ability to cost-effectively use machine learning to extract data insights at high scale. This demonstrates that the technology needed to drive the AI revolution is already being put in place.
According to Anand Rao, Partner, PwC, “Artificial Intelligence is becoming a major disruptor across a number of sectors. This is evidenced by the record level of investments in AI in 2016. This is likely to continue in 2017, as AI moves from the technology sector to other traditional enterprise sectors like automotive, financial services and healthcare.“
While most of us in technology understand the phenomenon of disruption, we always see a broad range of behaviors within large companies ranging from denial to aggressive strategies to be the disruptor rather than the disrupted. As a case in point, consider this quote:
“Neither Redbox or Netflix are even on the radar screen in terms of competition.”
—James W. Keyes, CEO of Blockbuster (2008)
Takeaway #2: Alexa is Just the Tip of the Iceberg
Siri intrigued us. Now Amazon’s Alexa is becoming the “new app store for voice.” Alexa is also the top music app and has expanded our imagination about the possibility of this burgeoning new interface with exceptionally good voice recognition and intelligence.
The ability to interact with a computer even if you can’t read, write, or have a device in your hand is a new modality that will create entirely new uses of computing and machine intelligence.
Google reports that 20 percent of searches on its mobile app and on Android devices are voice-based. And ComScore predicts that by 2020, 50 percent of all searches will be voice searches. Google is the clear winner in search, but who will be the winner in voice?
Going beyond voice, consider just a few of the thirteen world-changing trends discussed by Anand Sanwal, CEO of CB Insights during his keynote:
- Personal Robot Companions that provide emotional companionship and gamified education for children
- AI Ghosts offering the ability for a robot companion to become a person, living or not
- Personalized food customized and optimized for the DNA and current vitals of an individual
- Bot Root Movement, or a group of bots that can be deployed in large numbers to influence public opinion and political outcomes
Takeaway #3: Becoming A Cognitive Business
Companies see the necessity to utilize AI and machine learning technology to enable new engagement models and new revenues while reducing costs and improving operational effectiveness. The question is, how do companies accomplish this? Here is what was discussed at the conference:
Competency – Companies need to develop a competency and a methodology for applying AI and machine learning throughout their business. A collection of point solutions is unlikely to be successful in creating a Cognitive Business.
Speed – The technology, competency and methodology must produce results in a matter of weeks, not years. For example, training a machine learning system must be fast and require minimal resources.
Business Impact – The methodology must have a constant focus on optimizing business impact and be able to measure that business impact via KPIs.
Usable & Secure Technology – The technology must be simple to use, open, have enterprise scale and security and leverage investments made to date in big data and machine learning.
The attributes above are precisely the focus of the team at CognitiveScale and why industry leading companies have engaged with us to enable them to become cognitive business leaders in their industries.
Final Thoughts: Cognitive Businesses Start with Trust
IBM CEO Ginni Rometty said something profound at the World Economic Forum last week. Despite deeply rooted fears that AI will lead to extreme levels of job loss, Rometty and others say that advances in AI will actually lead to new types of employment—not the long foretold robot takeover.
What does this mean for cognitive businesses?
Companies need to start building trust with current and future customers now. “It’s not man or machine,” Rometty said. “It’s a symbiotic relationship. Our purpose is to augment and be in service of what humans do.”
It’s time we move past our fears of AI and consider the benefits this technology can offer in areas like healthcare, education, and financial services.
But before any cognitive business can realize these benefits, they need to, as I mentioned above, optimize their business impact and create a usable and safe platform that is “in service “ of users. Man and machine working together.
Accenture estimates that artificial intelligence could double annual economic growth rates of many developed countries by 2035, transforming work, and fostering a new relationship between humans and machines.
Manoj Saxena from CogntiveScale said it best; “Augmented intelligence platforms will pair humans and machines so they can achieve something new and exponentially valuable together… providing the right advice, at the right time, with the right evidence.” We’re entering an era of “new collar jobs” that are enhanced, not replaced, by AI.