Brainstorm AI Singapore 2024: The Future Of E-Commerce

Fortune

Ewa SZYMANSKA, Global Head, Rakuten Institute of Technology (RIT); Executive Officer, Rakuten Group Moderator: Clay CHANDLER, FORTUNE

Transcript

00:00So Yua, thank you so much for joining us today.

00:02We've had a lot of discussion about Southeast Asia,

00:06Southeast Asian firms and policies.

00:08So it's refreshing to be able to get a chance to have a little bit

00:11of a discussion about a Japanese company.

00:14Show of hands, how many know who, what Rakuten is?

00:19Everyone?

00:20Pretty good.

00:21All right.

00:23So why don't we just start there and you can tell us a little bit

00:24about Rakuten and maybe about the Rakuten Institute

00:29of Technology, but this is a company that's

00:32into all kinds of businesses, right?

00:33Right, right, right, right.

00:34So starting from the beginning, Rakuten was founded in 1997.

00:39So it's a time of economic downturn in Japan.

00:44Many businesses are struggling, shutting down.

00:48Small businesses need help and this is

00:51when Rakuten Online Marketplace opens up new markets to small

00:57and medium merchants, to rice sellers and sake brewers

01:01that before could only sell in their cities, in their regions.

01:06Now the whole Japan opens up to them.

01:09Now fast forward to today, we have 57,000 merchants

01:15on our platform and e-commerce still at the very heart of Rakuten,

01:22but since then we expanded and we are now in fintech,

01:26in digital content, in telco.

01:30So we have over 70 businesses overall.

01:33You can think of if you want to do travel booking or hair salon

01:40or horseback racing, there's just a wide variety of payments,

01:48car, credit card, insurance, you know, I can go on.

01:52There's 70, right?

01:53Sports also, yeah.

01:55Overall we have over 100 million users in Japan.

02:00So now most of people in Japan are involved with at least one

02:06of our businesses with a cross usage of over 76%.

02:11And 40 million users a month engaging with Rakuten

02:18which is basically a third of Japan's population.

02:22So it is very much a household name in Japan.

02:26So you're based here in Singapore.

02:28Tell us about the Rakuten Technology Institute and what that does.

02:31Right, right, right.

02:33So Rakuten Institute

02:34of Technology is Rakuten's research and development center.

02:38And our mission is to bridge the science with business applications

02:42and ensure that Rakuten benefits

02:44from this tremendous advance in AI.

02:49So we work with computer vision, language, our customer behavior

02:54from our 70 businesses.

02:57And we do both work traditional AI as well as now generative AI.

03:03Fascinating.

03:04And your background is that you're an expert in the science

03:07of human decision making, right?

03:09Right, right, right.

03:10So before artificial intelligence I was studying human intelligence.

03:13That's a good combination.

03:16You make an interesting point about Japan which is that although,

03:21you know, I mean we rank its giant companies in the Fortune 500 list

03:26and they're probably globally well known that Japanese,

03:30Japan's economy overall is very heavily dependent on small

03:33and medium sized enterprises who are often not as technically savvy

03:37or sophisticated as Sony or Toyota or something like that.

03:43And these are kind of the bread and butter customers for Rakuten.

03:48Tell us a little bit about their level of kind

03:51of technological sophistication and what, how we should think

03:55about how tech savvy they are.

03:58Sure. So we're committed to serving all our partners so regardless

04:06of their technological proficiency.

04:08So we make sure that they have the know-how and skills

04:13to make the most out of our platform.

04:16You know, when we started most

04:19of these sellers actually didn't know much about internet at all.

04:23I mean we're talking about late 90s.

04:26So very early on we established this function

04:29of the e-commerce consultant.

04:32So that's a person that works very closely with the merchant

04:39and assists them with, you know, whatever it is that they need.

04:43It might be help with setting up a storefront,

04:47running a marketing campaign, educating them about, you know,

04:50search engine optimization, what are the social media out there,

04:53what is Facebook, what's Instagram

04:56and how to take advantage of those.

04:58So very much this partnership between the consultants

05:04and the merchants is at the heart of Rakuten Marketplace.

05:09So a lot of these folks would maybe be, you know, small merchants,

05:13maybe live in a kind of rural area, might be older,

05:18kind of mom and pop type businesses.

05:20So that's very intense to reach out directly to those people.

05:27So how big is the kind of force of these consultants?

05:32Right. So we have our regional offices all over Japan

05:35and we have e-commerce consultants in all

05:38of those regional offices making visits to merchants,

05:41sitting at the table with them and working out the strategy,

05:45you know, for sales for next year, for, you know,

05:49Valentine's campaigns, et cetera.

05:52And so do you see that AI will make it easier

05:56or actually more complicated for those kinds of merchants to operate?

06:01Yeah, no, that's a great question.

06:02I mean, we're extremely positive about this technology, about AI.

06:08I mean, Rakuten was founded on this belief

06:11that technology brings people closer together.

06:15Right, right.

06:16You know, even internet, our online service people can think,

06:19you know, online means impersonal, it's convenience,

06:23it's like a vending machine.

06:25Whereas Rakuten have the very different approach, right?

06:28And from the very beginning, it was all about allowing merchants

06:31to express their personality of their business, tell their story

06:36of the product, of the family.

06:38So with generative AI, we see a lot of opportunity

06:43to help merchants, you know, do this even better.

06:48So, you know, a lot of them, as you pointed out, are small merchants.

06:53They may not have marketing teams or designers on their team

06:57and getting in their hands tools that allow them to, you know,

07:01create more beautiful storefronts,

07:04tell their story in a more visually compelling way.

07:07It's something that we're really excited about.

07:10Another area is just to give them ways to connect

07:13with their customers better, allow for personalization,

07:18help them to craft responses to the customers, which, of course,

07:23they have full, you know, control over the final output.

07:27We believe that this will help them be, you know,

07:30even closer to their end customer.

07:34Which kind of plays also on this idea of omotenashi,

07:39and we discussed this at Clay earlier, which is very central

07:43to Japanese culture, and it goes back to the tea ceremony,

07:50and this is this mindfulness and the principle of really care

07:57and hospitality, understanding the needs of your guest,

08:03of your customer, and then going above and beyond to, you know,

08:07meet and exceed those expectations.

08:10So we believe those tools will now allow our merchants

08:14to practice that omotenashi.

08:15Right, right.

08:17Very Japanese kind of idea.

08:19Let me ask you just a quick question about language and culture

08:23and how it combines with AI.

08:24I mean, obviously, you both develop in-house RockGen's own large

08:29language models in GenAI, and you're also working with companies

08:33like OpenAI and others to collaborate in rolling things out.

08:38So you kind of pick and choose as to when and where

08:41to make use of which one.

08:43Can you give us a Japanese perspective on this question

08:48that we discussed earlier this morning about whether

08:52or not large language models that are trained mostly in English

08:56can actually be very responsive and useful in different cultures,

09:00you know, like Japan, Japanese language,

09:02where the culture is so specific?

09:03Right. Very good question.

09:05A few months ago, I would give a different answer.

09:09Today, my answer is that these models are pretty good.

09:14Yeah, yeah.

09:15They are not as good as they are in English.

09:19There is still certain cultural differences,

09:23and I think the panel discussed this before as well

09:26for other Asian languages, the politeness levels.

09:29Yes.

09:30There is some kanji might not be correct, but it is close.

09:37Having said that, it's still a little bit more effort

09:40for the Japanese user to utilize that,

09:44and their reasoning skills are not as good as they are in English.

09:50But yeah, it's actually pretty impressive.

09:53So an interesting perspective.

09:54I think it's a question about which there's a lot

09:56of different opinions and points of view,

10:00especially the more advanced the technology.

10:03Right, right.

10:04But I would like to note something, however,

10:06and that there are certain.

10:08So tokenization for Japanese was not working so well.

10:15And basically, tokenization is that when you go from text

10:20to numeric encoding, you need to kind of parse these text input

10:27into tokens that can be as long as a word

10:30or a subword or a character.

10:32And basically, these commercial large language models

10:36that have been available, they were very inefficient in the way

10:40that they tokenized Japanese language.

10:44And they would use multiple tokens for a single kanji,

10:48for example, which was very inefficient, very costly.

10:51So what we put effort into when we developed

10:55and open sourced our Rakuten LLM 7 billion parameter model,

11:02we put effort into developing a tokenizer

11:04that is much more efficient and, you know, is able to take

11:10in more context into and be just more,

11:17less computationally intense.

11:21So that was kind of the contribution that we made.

11:24And that was something that had to,

11:26that was very language specific, right?

11:29So, you know, my view is that, you know, we are very close,

11:36but certain things have to be solved in order to close the gap.

11:42So.

11:43Yeah.

11:45That's all the time we've got.

11:46But fascinating Japanese perspective, Iwa.

11:47Thank you so much.

11:50Pleasure.

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