IBM Watson general manager David Kenny recently interviewed the technology new media The InformaTIon about IBM Watson's direction and unique advantages in developing artificial intelligence compared to other technology giants.
At this time 6 years ago, Watson was on the TV quiz show Jeopardy! It was unveiled, and at the beginning of this month it was on the Super Bowl. Interestingly, although IBM Watson is well known, it is primarily focused on business applications, and there are no artificial intelligence products that focus on the consumer market like other technology giants like Amazon, Apple and Google. IBM focuses on promoting Watson's many capabilities to industries such as healthcare, retail, and finance because it has accumulated a wealth of expertise in these industries. Many IBM customers are using the virtual assistants supported by Watson to handle customer support business. IBM has ambitious goals. Watson general manager David Kenny said that they are currently considering whether they can verify the news to determine the authenticity of the content.
Interview essence
David Kenny, General Manager of IBM Watson, explains how they compete with technology companies like Google for AI talent and how they can promote their services to businesses.
Kenny joined IBM more than a year ago. Prior to this, he worked in the advertising industry, served as president of Akamai, an Internet backbone services company, and later operated The Weather Company. At the end of 2015, IBM acquired most of The Weather Company's business. Kenny also joined the Big Blue. The Weather Company is able to collect massive weather data from sensors around the world and analyze it to provide 26 million weather forecasts per day. It is this ability that has attracted IBM. IBM sees this as part of the Internet of Things and has invested $3 billion in expansion in this area.
A former Kenny colleague said that Kenny's initial mission was to run Watson. Because of the previous contacts with many large corporate customers, it was in line with IBM's goal of winning more Watson corporate customers. Since last November, he has been the head of IBM's public cloud service and two data teams, one of which focuses on IoT products.
In an interview with The InformaTIon, he talked about how IBM competes with other large technology companies in the field of artificial intelligence, talks about IBM's internal debate about whether to focus on the consumer market or the enterprise market, and talks about why IBM is not like other companies. The same reason for the ambitious acquisition in the field of artificial intelligence.
The following is a sorted interview.
McLaughlin: When it comes to Watson, some people think of Jeopardy! But Watson's ability today is far beyond the quiz. Six years ago, Watson was just a research project at the IBM data center. What has it been included in the development to the present?
Kenny: At the heart of Watson is a Watson platform associated with the cloud platform. Artificial intelligence requires a lot of bandwidth to get the data, and it requires considerable computing power to "reason" or predict. At present, hundreds of outstanding applications have been built by IBM inside and outside based on Watson.
From a consumer perspective, or from a search and business perspective, what makes Watson unique compared to other artificial intelligence companies is that the data we are designing is not on the Internet. Because of this, we are committed to developing medical health and financial services, studying tax laws and architectural drawings, and applying data to the publishing field.
We build use cases for each vertical domain. The first is to communicate with the robot. We have a deeper knowledge base in specific areas. The second is to discover, for example, how to search for gene sequences or clinical trials, or to study tax laws. Then, learn the rules, which are critical to compliance, auditing, and anti-money laundering. Watson is learning this knowledge and applying it to a range of applications, some from IBM and some from third-party applications. Why is Watson growing? Because these areas are growing.
McLaughlin: IBM launched a Watson ad that allowed Watson to have a short conversation with celebrities like humans. If you want to promote Watson to your business, why do you put such an advertisement?
Kenny: Our argument is different from the other three artificial intelligence companies. There is a lot of debate in this area: - Should we shape Watson's brand image in a consumer-oriented way? The benefit of this is that you can create a set of standards. If you think that artificial intelligence will move in the direction of an artificial intelligence operating system, you can work in this direction. But we don't think so.
In most interactions with Watson, end users don't see Watson. They only think they are talking to a bank, insurance company, lawyer or doctor. Watson is primarily responsible for extending the personality of corporate users, so it's more like a "white label." The reason why we explore enhancing intelligence, not artificial intelligence, is because much of our work is to enhance the effectiveness of various corporate measures.
McLaughlin: In the field of artificial intelligence, IBM is the most senior company. But why is Google becoming the first choice for artificial intelligence talent?
Kenny: At the end of the day, we use search to find information and tend to use artificial intelligence to provide guidance for decision making. I don't think all the talents are flocking to Google. They certainly attracted many people, especially those at Stanford University. This is really admirable. But if you have expertise in a particular field, I think IBM Watson is a better choice because we are experts in the vertical field. The most valuable people are often experts in a certain field. You will not seek real estate advice from your oncologist or seek advice on buying a car from a real estate agent. Therefore, we are building professional vertical artificial intelligence, which is very beneficial for those who are concerned about the professional field.
Consumers want to talk to Google Home or Amazon Echo, which is very helpful, and the search function helps consumers find a lot of information. Many people today pay attention to these horizontal areas. But what I want to say is that there are still many people around the world who are concerned with vertical fields and expertise, and this is the long-term advantage of IBM. We have also designed our artificial intelligence in this way. These are two different design ideas, but they are all important.
McLaughlin: How does IBM create an attractive corporate culture to attract artificial intelligence talent in colleges and universities?
Kenny: Obviously, IBM Research has deeper roots than Alphabet. We have been working on the IBM Research Labs in Almaden, New York, Zurich and Tokyo for a long time. But many young people join IBM because they want to influence the world. Although IBM is a large company, you can also change the way banks, accounting, construction, retail, healthcare, or the environment have a huge impact on how a particular area works. I believe that we offer people an opportunity to make a significant impact on important areas of the world.
McLaughlin: How important is it that some artificial intelligence technologies are processed faster than other artificial intelligence technologies?
Kenny: Obviously, IBM Research has deeper roots than Alphabet. We have been working on the IBM Research Labs in Almaden, New York, Zurich and Tokyo for a long time. But many young people join IBM because they want to influence the world. Although IBM is a large company, you can also change the way banks, accounting, construction, retail, healthcare, or the environment have a huge impact on how a particular area works. I believe that we offer people an opportunity to make a significant impact on important areas of the world.
McLaughlin: How important is it that some artificial intelligence technologies are processed faster than other artificial intelligence technologies?
Kenny: The key is not only speed, but also the accuracy and practicality of the decision. There are always trade-offs between speed and accuracy, and you must be sure that the final outcome will work. Ultimately, we use search to find information and tend to use artificial intelligence to provide guidance for decision making. Do you understand the decisions I have to make? Does the system provide useful advice? Watson can help when you focus on major decisions such as clinical trials, or what is the value of my balance sheet, or what is my best way to file tax returns. All in all, helping customers make smarter decisions is how we increase our market share.
The search function advances the “commoditization†process of many businesses, such as newspapers, because their value lies in the distribution channels. But I think that the value of artificial intelligence in the distribution channel can't compare its value in intelligence. So we decided to help companies improve their intelligence. Because of this, our focus is on the quality of intelligence and decision making, not just speed.
Currently, we are looking for a way to verify facts with artificial intelligence. Is a certain news true, has it been verified, or can it be verified? For this reason, I believe that the distribution channel has reached the limit in the economy. Because what really matters is the content that is disseminated through distribution channels. Therefore, Watson adds value through data rather than interfaces. We hope that when others judge us, we will not only value the speed distribution indicator, but also the accuracy and the subtle complexity and quality of decision-making.
I am not saying that speed is not important, but it only accounts for one-third, and the other two-thirds is the value of the content. False news is a good example. Although it has been disseminated through distribution channels, over time, it is not based on high quality to create value?
McLaughlin: In the field of artificial intelligence, why isn't IBM like M&A like other companies like Google?
Kenny: We have a clear roadmap for cloud infrastructure, data capabilities, supervised learning and unsupervised learning. I think we have surpassed other companies in many ways. We have been in the field for a longer period of time, with a professional perspective, and many companies have started from the consumer sector.
Therefore, we have not found many M&A opportunities. Sometimes, we do see something that will help us push our roadmap faster and accelerate the introduction of talent. The acquisition of The Weather Company is an example of this. In this way, we have successfully converted massive sensor data into 26 million weather forecasts per day. The acquisition shortened IBM's IoT roadmap implementation cycle by a few years and helped IBM seize a talent pool.
Kenny: At the end of the day, we use search to find information and tend to use artificial intelligence to provide guidance for decision making. I don't think all the talents are flocking to Google. They certainly attracted many people, especially those at Stanford University. This is really admirable. But if you have expertise in a particular field, I think IBM Watson is a better choice because we are experts in the vertical field. The most valuable people are often experts in a certain field. You will not seek real estate advice from your oncologist or seek advice on buying a car from a real estate agent. Therefore, we are building professional vertical artificial intelligence, which is very beneficial for those who are concerned about the professional field.
Consumers want to talk to Google Home or Amazon Echo, which is very helpful, and the search function helps consumers find a lot of information. Many people today pay attention to these horizontal areas. But what I want to say is that there are still many people around the world who are concerned with vertical fields and expertise, and this is the long-term advantage of IBM. We have also designed our artificial intelligence in this way. These are two different design ideas, but they are all important.
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