Although AI is interested, there is little discussion on why AI is necessary, and on what kind of world you want to create with AI. In this talk, I will focus on this why and the technology we developed to answer this question. The reason for requiring AI is not because AI technology has been advanced. The reason why AI is necessary is that demand requires flexibility responding to change and diversity, whereas standardization and lateral development of work since Taylor cannot meet this requirement. This is called the conversion from "rule-oriented" to "outcome-oriented." AI is an important tool for making society outcome-oriented. We have developed AI (we call this "multipurpose AI") which enables flexible action according to circumstances for given outcome. It has already been utilized in more than 60 business cases in areas, such as financial, distribution, energy, and transportation.

In this paper, we evaluate methods of aggregating personal sensor data to estimate the degree of group stress. We compare the estimation accuracy of two aggregation methods, one without and one with personal distribution scaling. As a result of applying the data of 9 groups of people (105 people) to the methods, it is shown that the no-scaling method successfully estimates the degree of group stress better than the other (average error = 1.19, r = 0.964). At the conclusion of discussion, it is suggested that the method without scaling is valid because both the group stress state and method reflect the interaction among people.

A temporal network consists of a time series of interaction events, each of which is defined by a triplet composed of the indices of two nodes and the time of the event. Mapping a temporal network to a more tractable static network is often useful. A mapping method was recently proposed on the basis of the so-called transfer entropy (G. V. Steeg and A. Galstyan, in Proc. the 21st Int. Conf. WWW, p.509, 2012). In the proposed method, one generates the directed network of influence in which a directed link represents the causal relationship between activity patterns at two nodes. However, the significance of the inferred links and the sensitivity of results to the parameter values are still unclear. We propose a bootstrap sampling method to statistically configure the directed network of influence. We apply our method to the face-to-face interaction logs between office workers in Japanese companies.

A badge-shaped sensor and feedback system were developed. This system makes it possible to study human and organizational behavior in an office. By prompting changes in workers' behavior, it improves productivity as well as helps to solve individual's problems. Aiming to improve the productivity and quality of project management, the system was applied at a software development company. The results show that the system can improve the human communication process, as well as motivate workers by giving them the chance to reflect on their work styles and to help their colleagues.

Visualization of the actual conditions of an organization is a very challenging issue. We propose a new system called a Business Microscope that senses the activities of people in an organization and provides visual feedback to users. We use name-tag shaped sensor nodes to measure face-to-face interaction between employees. The massive amount of data collected by the sensor-network terminal are signal-processed by the server and displayed as an organization's topographic map that displays the frequencies of organizational activities. To depict the organization's topographic map, our system creates a novel relation tree using the interaction data from all pairs of members. In this kind of map, some groups in the organization hierarchically form islands. Members in those islands who have relationships with many others form mountains that are plotted with contours. We can comprehend the actual conditions of organizations from our topographic map. We tested our technique in several experiments to evaluate this system.

An ultra-small, low-power sensor-net module called ZN1 is developed. ZN1 integrates MCU, ZigBee RF into an ultra-small 15 -- 15-mm module with an ultra-low standby current less than 1 μA. The and highly reliable operation for more than 15 years of the ZN1 enable low-cost practical application-specific sensor nodes for HVAC, structure monitoring, office management, security, medicine, and healthcare. We describe architecture and technologies for developing the ZN1 module. Moreover, we demonstrate two applications that we developed simultaneously: food sanitation and home healthcare. We also show results of the ZN1 module evaluation and discuss reliability of the ZN1.

A power generator based on a vibration-to-electric energy converter using a variable-resonating capacitor is experimentally demonstrated. The generator consists of a complete system with a mechanical-variable capacitor, a charge-transporting LC tank circuit and an externally powered timing-capture controller. A practical design methodology to maximize the efficiency of the vibration-to-electric energy generation system is also described. The efficiency of the generator is estimated based on three factors: the mechanical-energy loss, the charge-transportation loss, and the timing-capture loss. Through the mechanical-energy analysis, the optimum condition for the resonance is found. The parasitic elements in the charge transporter and the timing management of the capture scheme dominate the generation efficiency. These analyses enable the optimum design of the energy-generation system. An experimentally fabricated and measured generator theoretically has a maximum power of 580 nW; the measured power is 120 nW, so conversion efficiency is 21%. This results from a 43% mechanical-energy loss and a 63% charge-transportation loss. The timing-capture scheme is manually determined and externally powered in the experiment, so its efficiency is not considered. With our result, a new system LSI application with an embedded power source can be explored for the ubiquitous computing era.

Starting with a brief review on the single-electron memory and its significance among various single-electron devices, this paper addresses the key issues which one inevitably encounters when one tries to achieve giga-to-tera bit memory integration. Among the issues discussed are: room-temperature operation; memory-cell architecture; sensing scheme; cell-design guideline; use of nanocrystalline silicon versus lithography; array architecture; device-to-device variations; read/write error rate; and CMOS/single-electron-memory hybrid integration and its positioning among various memory architectures.

The layout synthesis for pass-transistor cells (PTCs) is different from that for CMOS cells because of the various sizes of transistors used in a PTC and the imbalance in the number of pMOS and nMOS transistors. This makes it difficult to apply commonly used linear transistor placement to PTC layout. Moreover, the mixed placement with CMOS cells restricts the layout freedom of PTCs. Therefore a sandwiched selector structure and pass-transistor graph search are proposed for enabling a multi-row transistor layout and an efficient search algorithm for the diffusion layer sharing problem. Pass-transistor cells generated by ALPS (a_utomatic l_ayouter for p_ass-transistor cell s_ynthesis) are confirmed to have almost the same area density as that of manually designed cells.

The development of an experimental high-performance microprocessor chip based on a 0.3- mu m BiCMOS technology is discussed. It is designed to operate at a 250-MHz clock rate. It includes two processors, each of which executes two instructions in parallel. The chip performs 1000 MIPS when instructions and data are fetched from primary caches. It also includes a four-wave interleaved secondary cache assessed in parallel according to a split-bus protocol, to reduce shared memory conflicts. The VLSI architecture and design results of this chip are described.>