Artificial Intelligence’s broken promise and its secret truth

The promise of AI is easily understood by anyone with an imagination, and for 40 years, venture capitalists have been enthusiastically investing in that promise.

However, it's been significantly harder for founders to turn that investment into sustainable business models.

Today we are going to look at why that is, and go over what might be a blueprint for startups to create business models around artificial intelligence.

Tatsuo Nakamura founded Valuenex in 2006 with the goal of using artificial intelligence to supplement the work being done by patent attorneys, and their software was instrumental in the resolution of one of Japan's most famous, and most valuable, lawsuits. the Blue LED patent case.

We also talk about how to sell to large companies as a small startup, the challenges in trying to make product strategy based on technology, why staying private longer is not always a good thing for startups, and how Valuenex technology accidentally discovered a secret collaboration between Honda and Google.

It's a great discussion with the founder of one of Japan's most successful AI companies, and I think you will really enjoy it.

Show Notes

Why AI can understand patents better than lawyers can Why the market should drive technology rather than the other way around How Valuenex helped resolve one of the biggest patent lawsuits in Japanese history How a new law if forcing change in Japanese universities How Valuenex discovered a secret collaboration between Honda and Google How to create sustainable business models in AI Why quantum computing will both break AI and save AI Why Valuenex IPOed early instead of staying private and growing Some unusual advice about when to do a market entry Why Japanese VC often make market entry difficult

Links from the Founder

Everything you wanted to know about Valuenex Connect with Tatsuo on LinkedIn Friend hin on Facebook

Leave a comment Transcript Welcome to Disrupting Japan, straight talk from Japan’s most successful entrepreneurs.

I’m Tim Romero and thanks for joining me.

Today, we're going to be talking about something that's frankly difficult to talk about on an audio podcast. Tatsuo Nakamura founded Valuenex in 2006 to use Artificial Intelligence and modern visualization techniques to help clients make sense of their patent portfolios and to keep an eye on what the competition is doing. In fact, this technology uncovered some of the core evidence that decided the famous blue LED case. It's highly effective but highly visual, so let me try to explain it.

Valuenex creates a kind of topographical map that shows companies where in the market, their IP is strong and where it's weak. This can let them spot new market opportunities or learn what their competition is about to do. It's all pretty intuitive when you see it, but today, we'll have to use our imagination as a kind of screen simulation.

Tatsuo and I also talk about Valuenex's US market entry - well, their two US market entries, actually. We cover what he sees as the best overall strategy for AI startups for them to find their product market fit, and Tatuo explains how he was accidentally able to discover a significant collaboration between two world-famous companies six months before the project was announced.

But you know, Tatsuo tells that story much better than I can, so let's get right to the interview.

[pro_ad_display_adzone id="1404" info_text="Sponsored by" font_color="grey" ] Interview Tim: I'm sitting here with Tatsuo Nakamura, the CEO and founder of Valuenex. So, thanks for sitting down with me.

Tatsuo Nakamura: Thank you very much.

Tim: Now, Valuenex is a leader in visualization and big data analytics and it's so hard to talk about visualizations on an audio podcast.

Tatsuo: Yes.

Tim: But we're going to try. So, what's the best way to explain? What does Valuenex do?

Tatsuo: Valuenex is a predictive analytics company using big data analytics. So, the main purpose is finding the future situation and making the strategy for our client.

Tim: Okay, and you specialize in intellectual property and patents, right?

Tatsuo: Because patent documentation is very, very good and useful for data source, because there's many fields in the data and they have a very clean documentation, so it is easy to analyze.

Tim: Patents, especially, are interesting. I've heard from a few people in AI that right now, AI can read patents better than humans can because the language is so specialized and unusual that's it's really well-suited to AI.

Tatsuo: Yes, so at first, when the people entered the IP field, "Oh, this is confusing because this is not language." It's a special words. However, when you apply machine learning technologies, it is easy to understand it because it is a very clear some kind of mechanism for the sentence. So, it is easy to transfer to the machine languages.

Tim: Okay, so once the algorithm goes through hundreds of thousands of patents and uses machine learning and AI to understand the contents, it builds kind of clusters of meaning around it, right?

Tatsuo: Mm-hmm. Can you imagine? It was a 400 documents are there so how many relationships each side?

Tim: Well, it is geometric, right? So, it will quickly get into the tens of millions of...

Tatsuo: Yes, it is huge relationships.

Tim: Right, so a human being cannot possibly understand that from text information.

Tatsuo: Yes, we use a very special person to try reading each by each, so probably, it takes over 10 years.

Tim: Have a bunch of patent attorneys, put them in a room.

Tatsuo: Yeah, but either he or she is in the Japanese major company, IP chains with over 50 people working for the reading for the analytics. After five years, good. So, that, of course, this is the old style. Now, the people are using the analytics tools.

Tim: And so, Valuenex creates the visualization. The output is sort of like an IP heat map, so the users can see where the IP is clustered.

Tatsuo: Basically, it's three layers. When we think about the next products or next markets based on the technologies, at first, we describe the technology mapping, technology landscaping, and finding the significant technology and connect it to the product, either the competitive product or service, so if there's no products or services, or this is a good opportunity.

Tim: Okay, so you could use the visualization to say, "Okay, we've got a hot cluster of technology in this space, but it looks open in terms of products in the market"?

Tatsuo: Well, most of the cases are market-driven analytics, so the people who want it have a lighter device, then they try to change the materials, but along this side, everybody is trying to make a new idea, so they want to know where is the market?

Tim: Oh, wow, yes! So, I guess it can go in both directions. So, tell me a bit about your customers. How are your customers mainly using this?

Tatsuo: At first, we started, our service is R and Design, so my original company is R&D division and IP division, they have many projects, many ideas, so I guess 99% idea in technology was not released. However, I think that there's more opportunities and more good services, then they have to use the panoramic view analytics describing, oh, this idea, this technology is very similar and they can be combined.

Tim: So, is that the most common use case where your customer is using it bottom-up?

Tatsuo: Ideally, it is a very good way. However, any company has divisions and they make a wall, secret walls, so they can’t reach into other fields.

Tim: I could see that, yeah, the technology, it seems ideal for just looking and saying, "Hey, you have an opportunity," but the different divisions in the company force them to have more of a product focus.

Tatsuo: So, if someone thinks about, "Oh, this technology is very good for the battery technologies," however, they are just materials, so they have to collaborate with electric filed persons. They can't work that.

Tim: So, for example, let's say I was the division chief at a big database company and responsible for the automotive industry, could I say, "Let's look at all of our patents and see what might be suitable for the automotive industry, what blank spaces there are that we could exploit?" Would that be a good use of Valuenex?

Tatsuo: Yes, although a concrete case is a chemical company, Asahi Kasei. At first, they rejected us because they had an analytics genius, but when they used our methodologies, this is good work for the Asahi Kasei president - company president - because the big company's president has some kind of image for each division's relationships. So, our or radar chart is almost the same with the president's idea. So, we can easily point out, oh, this division should be the collaboration or both divisions have white space, so collaborate on the bridge technologies.

Tim: This is really interesting. It sounds like you took the customer's biggest objection to your product that was bottom-up and we hit all these walls, and you said, "Oh, well, let me explain these walls to you." That's great.

Tatsuo: Yes, I established in 2006 this company, so always, the starting point is a negative start.

Tim: Well, actually, I want to drill down deep into the marketing and to the technology in a minute, but before that, let's step back a bit and talk about you, and when you founded Valuenex, so at Stanford, you and I were talking and you mentioned the importance of the blue LED case, and can you tell me? I think that's really interesting.

Tatsuo: So, this example case is very famous in Japan and this is a very big event for the society and also me. However, some parts are very confidential, but I can say I was the project leader at these court issues, I belonged to the Nichia Chemical Companies. At the time, 2005,