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The Third Globalization: Can Wealthy Nations Stay Rich In The Twenty-First Century? (Book Chapter)

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Chapter 4 of this book "Services with Everything: The ICT-Enabled Digital Transformation of Services" was written by John Zysman, Stuart Feldman, Kenji E. Kushida, Jonathan Murray, and Niels Christian Nielsen. The book is edited by Dan Breznitz and John Zysman.

 

 

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The Future of Blockchain: How it will impact finance, industry, and society (Book Chapter)

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Kenji Kushida's new book chapter, "Blockchain, a Silicon Valley Vantage on its Potential and Challenges" was published in new book, "The Future of Blockchain: How it will impact finance, industry, and society edited by Yuri Okina, Noriyuki Yanagawa, and Naoyuki Iwashita.

The book is an investigation of the potential and challenges of adopting a disruptive technology such as blockchain. Experts on blockchain applications explain the concept of blockchain, how it is being utilized in a variety of areas, and its wide-range impact on economy, industry, business and society, based on cases in Japan and overseas.

 

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Kenji E. Kushida

A Strategic Overview of the Silicon Valley Ecosystem: Towards Effectively “Harnessing” Silicon Valley

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This report provides an overview of the Silicon Valley ecosystem. It draws upon existing scholarship and original insights to derive a picture that is only partially well-known in Japan. Characteristics such as the critical role of large firms for the startup firm ecosystem, the role of Japanese firms in creating the US firms’ “open innovation” paradigm, and the severe lack of local government coordination in providing public transportation creating opportunities for disruptive startups such as Uber, are all aspects of Silicon Valley that are not well-known in Japan. This report also delves into industry-university ties in the crucial research universities of Stanford and University of California Berkeley, highlighting the multifaceted and bidirectional interactions between universities and industry that are often not captured by the common “technology licensing office”-centered view. In the final section, this report briefly reviews a representative set of challenges often cited by large Japanese firms attempting to make use of the Silicon Valley ecosystem, concluding by suggesting areas for further research.

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Kenji E. Kushida

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

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Wheat is the most important staple crop grown in Australia, and Australia is one of the top wheat exporting countries globally. Timely and reliable wheat yield prediction in Australia is important for regional and global food security. Prior studies use either climate data, or satellite data, or a combination of these two to build empirical models to predict crop yield. However, though the performance of yield prediction using empirical methods is improved by combining the use of climate and satellite data, the contributions from different data sources are still not clear. In addition, how the regression-based methods compare with various machine-learning based methods in their performance in yield prediction is also not well understood and needs in-depth investigation. This work integrated various sources of data to predict wheat yield across Australia from 2000 to 2014 at the statistical division (SD) level. We adopted a well-known regression method (LASSO, as a benchmark) and three mainstream machine learning methods (support vector machine, random forest, and neural network) to build various empirical models for yield prediction. For satellite data, we used the enhanced vegetation index (EVI) from MODIS and solar-induced chlorophyll fluorescence (SIF) from GOME-2 and SCIAMACHY as metrics to approximate crop productivity. The machine-learning based methods outperform the regression method in modeling crop yield. Our results confirm that combining climate and satellite data can achieve high performance of yield prediction at the SD level (R2 ˜ 0.75). The satellite data track crop growth condition and gradually capture the variability of yield evolving with the growing season, and their contributions to yield prediction usually saturate at the peak of the growing season. Climate data provide extra and unique information beyond what the satellite data have offered for yield prediction, and our empirical modeling work shows the added values of climate variables exist across the whole season, not only at some certain stages. We also find that using EVI as an input can achieve better performance in yield prediction than SIF, primarily due to the large noise in the satellite-based SIF data (i.e. coarse resolution in both space and time). In addition, we also explored the potential for timely wheat yield prediction in Australia, and we can achieve the optimal prediction performance with approximately two-month lead time before wheat maturity. The proposed methodology in this paper can be extended to different crops and different regions for crop yield prediction.

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Agricultural and Forest Meteorology
Authors
David Lobell
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Do Innovation Subsidies Make Chinese Firms More Innovative?

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Takeo Hoshi
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Commentary
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The following item appears on VoxChina.org, an "independent, non-partisan and non-profit platform initiated by a group of experienced and accomplished economists."

Motivated by the realization that China’s economic growth model that relied on three major factors—cheap labor, capital deepening supported by high savings (depressed consumption), and technology, most of which came from advanced foreign countries—is about to become obsolete, the Chinese government has been trying to encourage innovations by Chinese firms through various subsidy programs (König et al., 2018). Using data from the China Employer Employee Survey (CEES), we study the allocation and impacts of the innovation subsidies in China in a recent NBER working paper (Cheng et al., 2019). We examine what type of firms are more likely to receive the innovation subsidies and if the subsidized firms are more likely to be innovative (measured by the number of patents and the likelihood of introducing new products), productive, and profitable....

Read the full article on VoxChina.

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Artificial Intelligence (AI), Intelligence Augmentation (IA), Human Machine Interfaces (HMI): Frontier Research and Policies for Navigating the Future Together

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The diffusion and deployment of technology is not simply shaped by the technology itself. Complementary technologies are often required to derive value from the technology, and other factors such as business models for which the technology solves significant “pain points.” Business organizations that can harness the set of technologies, along with societal factors such as regulations, employment regimes, demographics, social norms, and political dynamics can critically affect how technologies diffuse.

This conference is centered on the technological development, deployment, and diffusion of various forms of human-machine interfaces. In the morning, it examines technologies utilizing AI, IA, and pushing human-machine interfaces to the next level of commercial development (morning session A). It also introduces frontier research in medical fields and focuses on how a design approach has been effective for how medical products and solutions have been developed (morning session B). In the afternoon, it turns to a discussion of policy dynamics and considerations surrounding the use of AI and IA, particularly in broad societal deployments

This conference is a joint production of the Shorenstein Asia Pacific Research Center (APARC) Japan Program’s Stanford Silicon Valley - New Japan Project, and Japanese venture community, Mistletoe, Inc.

Agenda

*Agenda subject to change

9:00 - 9:30             Registration

9:30 - 9:40             Welcome Remarks

9:40 - 11:00           Morning Session A: Next Generation Human Machine Interfaces: From Science Fiction to Reality to Industrial Deployment

Presentations followed by discussion:

Ryoichi Togashi, Program Director, Komatsu

Andrew Pedtke, Co-founder and CEO, Lim Innovations

Lochlainn Wilson, CEO, SE4

Moderator: Kenji Kushida, Research Scholar, Stanford University

11:00 - 11:15         Break

11:15 - 12:30         Morning Session B: Bio Design and Medical Technologies, and University-Industry Ecosystems

Presentations followed by discussion:

Atsushi Taira, Chief Growth Officer, Mistletoe, Inc.

Gordon Miller Saul, Executive Director,  Stanford Byers Center for Biodesign

Christoph Leuze, Research Scientist, Stanford Radiological Sciences Lab

Pushkar Apte, Director of Strategic Initiatives, CITRIS and the Banatao Institute, UC Berkeley

Moderator: Kenji Kushida, Research Scholar, Stanford University

12:30 - 13:30        Lunch

1:30 - 15:00          Afternoon Discussion: Regulations, politics, and industry dynamic with considerations of accountability and ethics

Presentations followed by discussion:

Kenji Kushida, Research Scholar, Stanford University

Mei Lin Fung, Co-Founder, People-Centered Internet

Rosanna Guadagno, Director, Information Warfare Working Group, Stanford University

Mike Nelson, Head of Public Policy, CloudFlare

Moderator: Jaclyn Selby, Research Scholar, Stanford University

15:00                    Closing Remarks

RSVP REQUIRED

Limited seating available. Seats will be filled on a first come, first serve basis.

RSVP Deadline: May 20, 2019

RSVP link: http://www.stanford-svnj.org/52119conference

Stanford Silicon Valley-New Japan Project

Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans

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Eradicating hunger and malnutrition is a key development goal of the twenty first century. This paper addresses the problem of optimally identifying seed varieties to reliably increase crop yield within a risk-sensitive decision making framework. Specifically, a novel hierarchical machine learning mechanism for predicting crop yield (the yield of different seed varieties of the same crop) is introduced. This prediction mechanism is then integrated with a weather forecasting model and three different approaches for decision making under uncertainty to select seed varieties for planting so as to balance yield maximization and risk. The model was applied to the problem of soybean variety selection given in the 2016 Syngenta Crop Challenge. The prediction model achieved a median absolute error of 235 kg/ha and thus provides good estimates for input into the decision models. The decision models identified the selection of soybean varieties that appropriately balance yield and risk as a function of the farmer’s risk aversion level. More generally, the models can support farmers in decision making about which seed varieties to plant.

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Environment Systems and Decisions
Authors
David Lobell
Stefano Ermon
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Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data

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Accurate prediction of crop yields in developing countries in advance of harvest time is central to preventing famine, improving food security, and sustainable development of agriculture. Existing techniques are expensive and difficult to scale as they require locally collected survey data. Approaches utilizing remotely sensed data, such as satellite imagery, potentially provide a cheap, equally effective alternative. Our work shows promising results in predicting soybean crop yields in Argentina using deep learning techniques. We also achieve satisfactory results with a transfer learning approach to predict Brazil soybean harvests with a smaller amount of data. The motivation for transfer learning is that the success of deep learning models is largely dependent on abundant ground truth training data. Successful crop yield prediction with deep learning in regions with little training data relies on the ability to fine-tune pre-trained models.

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Working Papers
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COMPASS '18 Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies
Authors
David Lobell
Stefano Ermon
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Japan in the Bay Area: From Competition to Collaboration

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The Bay Area Council Economic Institute and the Walter H. Shorenstein Asia-Pacific Research Center Japan Program invite you to a forum on the critical transformations underway in Japan’s economy and the unique synergies that connect it to the Bay Area. The program will include a discussion of the high-level findings of a new report by the Bay Area Council Economic Institute on Japan’s economic engagement in the San Francisco/Silicon Valley Bay Area, and the role the region is playing as California and Japan look to expand trade and investment and accelerate innovation. Leading experts and practitioners from both Japan and the Bay Area will join us for this discussion. 

This event is brought to you by the Shorenstein Asia-Pacific Research Center Japan Program and the Bay Area Council Economic Institute, in cooperation with the Japan Society of Northern California.

 

Agenda

 

1:00pm          Welcome

     Jim Wunderman, President & CEO, Bay Area Council

     Hon. Tomochika Uyama, Consul General of Japan

     Takeo Hoshi, Director, Shorenstein APARC Japan Program

1:10pm          Introduction of Bay Area Council Economic Institute Report: High-Level Findings

     Sean Randolph, Senior Director, Bay Area Council Economic Institute

1:30pm          Observations and Silicon Valley Overview

     Kenji Kushida, Research Scholar, Stanford University

1:45pm          Panel 1: The Emerging New Japan 

     Kanetaka Maki, Associate Professor, Waseda Business School

     Mio Takaoka, CFO, Medical Note and Partner, Arbor Ventures

     Takeshi Ebihara, Founding GP, Rebright Partners

     Emre Yuasa, Principal, Globis Capital Partners

     Sean Randolph, Senior Director, Bay Area Council Economic Institute (Moderator)

2:45pm          Panel 2: Japanese Companies in Silicon Valley Creating Value in New Ways

     Hiroshi Menjo, Managing Partner, Net Service Ventures

     Tsunehiko Yanagihara, Executive VP, Mitsubishi Corp M-LAB

     Gen Isayama, General Partner & CEO, World Innovation Lab

     Dennis Clark, Managing Director, Honda Innovations

     George Saikalis, SVP & CTO, Hitachi America, Ltd.

     Kenji Kushida, Research Scholar, Stanford University (Moderator)

4:00pm         Closing Remarks 

Bechtel Conference Center
Encina Hall
616 Serra Mall, Stanford, CA 94305

Panel Discussions
Stanford Silicon Valley-New Japan Project

HOW DOES VENTURE CAPITAL WORK AND HOW DO JAPANESE CORPORATIONS LEVERAGE VENTURE CAPITAL?

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Since its establishment, DNX Ventures (formerly Draper Nexus Ventures) has acted as a bridge between growing Silicon Valley businesses and large Japanese firms. Since 2011, DNX Ventures has created more than 100 partnerships between its portfolio companies and its over 25 large Japanese corporate LPs. During this seminar, Managing Director of DNX Ventures Hiro Rio Maeda will extrapolate from his over 15 years of experience in both corporate venture capital and venture capital and extensive experience working with both startups and large Japanese corporations to discuss the basics of venture capital, and how Japanese corporations leverage venture capital to push forward open innovation initiatives. From a VC perspective: how are decisions about strategic investments made? How does money flow? What ratio of successful investments to non-successful investments do VCs aim for? From a large Japanese corporate perspective: how do large Japanese firms use VC to achieve open innovation goals? What are some of the obstacles to Japanese large firm-startup partnerships, and what are some of the ways to overcome these challenges? Maeda will answer these questions and more, as well as share examples of successful partnerships and large Japanese firms that are successfully harnessing Silicon Valley to further open innovation efforts.  

SPEAKER:

Hiro Rio Maeda, Managing Director, DNX Ventures (formerly Draper Nexus)

BIO:

Hiro Rio Maeda is a Managing Director at venture capital firm DNX Ventures (formerly Draper Nexus). Rio focuses on investing in innovative companies in Cyber Security, mobile, storage, and retail tech area that could work on a global scale. His portfolio companies include Cylance, SafeBreach, JASK, vArmour, AppDome, Ayasdi, Remotium, Klout, Fyde, JoyMode, and Hom.ma. 

Prior to joining DNX Ventures (formerly Draper Nexus), Rio spent six years at Globespan Capital Partners where he had put his resource on both investment and business development of Japan/US portfolio companies. Palo Alto Networks(NYSE: PANW) was a good example portfolio company that he took a lead on taking them to the Japanese market.

Prior to Globespan, Rio spent seven years at Sumitomo Corporation, a Japanese conglomerate trading company in which he had built expertise his international business skill in IT technologies and consumer web services in Tokyo and his capitalist career at Presidio Ventures (Sumitomo’s corporate venture capital arm) in Santa Clara.Japanese conglomerate trading company in which he had built expertise his international business skill in IT technologies and consumer web services in Tokyo and his capitalist career at Presidio Ventures (Sumitomo’s corporate venture capital arm) in Santa Clara.

AGENDA:

4:15pm: Doors open
4:30pm-5:30pm: Talk and Discussion
5:30pm-6:00pm: Networking

RSVP REQUIRED:

Register to attend at http://www.stanford-svnj.org/22819-public-forum

For more information about the Silicon Valley-New Japan Project please visit: http://www.stanford-svnj.org/

 

Hiro Rio Maeda, Managing Director, DNX Ventures (formerly Draper Nexus)
Seminars
Stanford Silicon Valley-New Japan Project
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