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Plans to build ‘exascale’ machines are moving forward, but still face major technological challenges. Plans to build ‘exascale’ machines are moving forward, but still face major technological challenges.

Google and IBM recently announced their own approach to cloud computing. They say that they will offer free use of a cluster of several hundred servers to the computer-science departments of six top US research universities. The machines will provide researchers with vast amounts of computer power for their data-crunching.

UK and US governments establish efforts to democratize access to supercomputers that will aid studies on AI systems. UK and US governments establish efforts to democratize access to supercomputers that will aid studies on AI systems. Credit: Chris J. Ratcliffe/Bloomberg via Getty Rishi Sunak, UK prime minister, centre, prepares to host a plenary session during the AI Safety Summit 2023 at Bletchley Park.

The demand for electricity related to Information and Communications Technologies is constantly growing and significantly contributes to the increase in global greenhouse gas emissions. To reduce this harmful growth, it is necessary to address this problem from different perspectives. Among these is changing the computing scale, such as migrating, if possible, algorithms and processes to the most energy efficient resources. In this context, this paper explores the possibility of running scientific and engineering programs on personal computers and compares the obtained power efficiency on these systems with that of mainframe computers and even supercomputers. Anecdotally, this paper also shows how the power efficiency obtained for the same workloads on personal computers is similar to that obtained on supercomputers included in the Green500 ranking.

An increasing volume of business activity appears to be occurring via alliances or other interfirm arrangements in which complex contracts are featured, yet there has been relatively little study of contract design in the strategy or management literatures. The economics literature on contracting has been extensive, but it has been less concerned with learning and evolution-phenomena in which strategy and organization scholars are deeply interested. In this paper, we investigate the relationship between two types of contractual provisions that are important in high-technology contracts, or contracts for which environmental uncertainty or technological complexity are significant, namely, contingency planning and task description. Previous research suggests that contracts can vary significantly in the degree of detail with which such key provisions are written, and that they are each subject to learning. In this paper, we find evidence from a sample of 386 contracts that contingency planning and task description behave as complements in contractual design. We argue that this complementarity reflects patterns of learning to contract. We also find that repeated exchange between two firms leads to greater effort at contingency planning in subsequent contracts, a finding that is also consistent with learning effects, but not with frequently made claims that contracts and trust are substitutes.

IBM has collaborated with several cancer care providers to develop and train the IBM supercomputer Watson to help clinicians make informed treatment decisions. When a patient is seen in clinic, the oncologist can input all of the clinical information into the computer system. Watson will then review all of the data and recommend treatment options based on the latest evidence and guidelines. Once the oncologist makes the treatment decision, this information can be sent directly to the insurance company for approval. Watson has the ability to standardize care and accelerate the approval process, a benefit to the healthcare provider and the patient.

Most studies of the impact of information systems in organizations tend to see the implementation process as a “rollout” of technology, as a technical matter removed from organizational dynamics. There is substantial agreement that the success of implementing information systems is determined by organizational factors. However, it is less clear what these factors are. The authors propose to characterize the introduction of an information system as a process of mutual shaping. As a result, both the technology and the practice supported by the technology are transformed, and specific technical and social outcomes gradually emerge. The authors suggest that insights from social studies of science and technology can help to understand an implementation process. Focusing on three theoretical aspects, the authors argue first that the implementation process should be understood as a thoroughly social process in which both technology and practice are transformed. Second, following Orlikowski's concept of “emergent change,” they suggest that implementing a system is, by its very nature, unpredictable. Third, they argue that success and failure are not dichotomous and static categories, but socially negotiated judgments. Using these insights, the authors have analyzed the implementation of a computerized physician order entry (CPOE) system in a large Dutch university medical center. During the course of this study, the full implementation of CPOE was halted, but the aborted implementation exposed issues on which the authors did not initially focus.

Voice mail. E-mail. Bar codes. Desktops. Laptops. Networks. The Web. In this exciting book, Gene Rochlin takes a closer look at how these familiar and pervasive productions of computerization have become embedded in all our lives, forcing us to narrow the scope of our choices, our modes of control, and our experiences with the real world. Drawing on fascinating narratives from fields that range from military command, air traffic control, and international fund transfers to library cataloging and supermarket checkouts, Rochlin shows that we are rapidly making irreversible and at times harmful changes in our business, social, and personal lives to comply with the formalities and restrictions of information systems. The threat is not the direct one once framed by the idea of insane robots or runaway mainframes usurping human functions for their own purposes, but the gradual loss of control over hardware, software, and function through networks of interconnection and dependence. What Rochlin calls the computer trap has four parts: the lure, the snare, the costs, and the long-term consequences. The lure is obvious: the promise of ever more powerful and adaptable tools with simpler and more human-centered interfaces. The snare is what usually ensues. Once heavily invested in the use of computers to perform central tasks, organizations and individuals alike are committed to new capacities and potentials, whether they eventually find them rewarding or not. The varied costs include a dependency on the manufacturers of hardware and software--and a seemingly pathological scramble to keep up with an incredible rate of sometimes unnecessary technological change. Finally, a lack of redundancy and an incredible speed of response make human intervention or control difficult at best when (and not if) something goes wrong. As Rochlin points out, this is particularly true for those systems whose interconnections and mechanisms are so deeply concealed in the computers that no human being fully understands them. The complete text ofTrapped in the Netis available online at http://pup.princeton.edu

Why do successful organizations often move in new directions and then fail? We propose that this pattern is especially likely among organizations that have survived a history of competition. Such experience adapts organizations to their environment, through so-called \"Red Queen\" evolution, but being well adapted for one context makes moving into new contexts more hazardous. Meanwhile, managers in such organizations infer from their histories of competitive success a biased assessment of their organization's ability to change. Consequently, although surviving competition makes organizational change especially hazardous, managers in surviving organizations are especially inclined to such initiatives. We develop these ideas in an empirically testable model, and find supportive evidence in estimates of the model using data from the history of the U.S. computer industry.