Review of Privileged Documents in Trial and Deposition Preparation of Witnesses in New York: When, if Ever, Will the Privilege be Lost?

This article will examine New York’s refreshing recollection doctrine in the context of trial and deposition preparation of witnesses as to the consequences of the witness’s review of privileged writings. Initially, Part II will discuss Rule 612 of the Federal Rules of Evidence. The discussion will serve as the backdrop for the analysis of the above-mentioned issues under New York law. Part III will then examine the refreshing recollection doctrine as developed and applied to testifying witnesses at a trial or deposition by the New York courts. The examination will point out the doctrine’s key rules. Part IV discusses the treatment of these key rules by the New York courts in the witness preparation situation, both pre-trial and pre-deposition, showing the shortcomings of this judicial treatment and advocating for change. Lastly, Part V makes some suggestions to the attorney in light of current New York law as to avoidance in the preparation of witnesses before they testify at a trial or a deposition of the disclosure of otherwise privileged writings

Asymptotically Unambitious Artificial General Intelligence

General intelligence, the ability to solve arbitrary solvable problems, is supposed by many to be artificially constructible. Narrow intelligence, the ability to solve a given particularly difficult problem, has seen impressive recent development. Notable examples include self-driving cars, Go engines, image classifiers, and translators. Artificial General Intelligence (AGI) presents dangers that narrow intelligence does not: if something smarter than us across every domain were indifferent to our concerns, it would be an existential threat to humanity, just as we threaten many species despite no ill will. Even the theory of how to maintain the alignment of an AGI's goals with our own has proven highly elusive. We present the first algorithm we are aware of for asymptotically unambitious AGI, where "unambitiousness" includes not seeking arbitrary power. Thus, we identify an exception to the Instrumental Convergence Thesis, which is roughly that by default, an AGI would seek power, including over us.Comment: 9 pages with 5 figures; 10 page Appendix with 2 figure

Diffusion through the ex vivo vitreal body - bovine, porcine, and ovine models are poor surrogates for the human vitreous

© 2018 The Authors. Published by Elsevier B.V.The human vitreous humour is a complex gel structure whose composition and physical properties can vary considerably from person to person and also change with age. To date, the viscoelastic properties of the human vitreous gel has not been thoroughly investigated and despite many years of intensive research, an ideal vitreous substitute remains a challenge. Understanding the physical structure and properties of the vitreous is of fundamental and therapeutic interest, providing a clear insight into diffusion and transport of administered ophthalmic drug molecules into the vitreous. A number of mammalian surrogates, mainly bovine, porcine and ovine vitreous humours have been greatly used in the literature as a means of studying ophthalmic drug transport and diffusion. In this study, the mechanical, physical and rheological properties of ovine, porcine, and bovine surrogates were investigated and compared to human vitreous. In addition, a bespoke Franz cell construct was used to compare the diffusion of a model drug (i.e. fluorescein) through vitreous samples. Despite the similarity in rheological properties between bovine, porcine and human vitreous samples (p > 0.05), diffusion of fluorescein through the different vitreous samples revealed great differences in values of steady-state flux and diffusion coefficient. In addition, a first-generation vitreous mimic, composed of 4.5 mg/mL hyaluronic acid with complex viscosity of 0.3 ± 0.01 Pa has been evaluated and was demonstrated to be a better mimic of the human vitreous than the mammalian samples investigated.Peer reviewedFinal Published versio

Pragmatist perspectives on valuation : an introduction

This book contains fifteen chapters on the ways in which things and ideas that are new or unknown are given their value. Long before items as diverse as wine, art, or technologies for cleaning slurry gain commercial value, they are evaluated by experts, reviewed by critics, and compared with earlier successes. An exploration of moments of valuation reveals the initial dissonance among those judging a newly proposed alternative and shows how they influence the emergence of newness in society. The deviant, the tenuous, the rough, is recognized and estimated. Several chapters deal with aesthetic valuation, as in the tasting of a new vintage, or in the socio-technical process that shaped successful synthesizer sounds. Other chapters discuss the judgment processes in organizations, like architect offices or consultancy firms, and processes of evaluation and valorization in larger fields of practice, like accounting or mathematics. The pattern of comparison relies on the controversies and interpretations expressed, the sites on which the events took place, and on the terms of value attributed. The studies are written by anthropologists, economic or cultural sociologists, organization researchers, historians or political scientists who share an interest in social valuation and a pragmatist approach. The episodes chosen come from the consumer sector, from processes of chapters contribute to an understanding of the social and cultural conditions under which innovations fail and succeed

Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces

In practical Bayesian optimization, we must often search over structures with differing numbers of parameters. For instance, we may wish to search over neural network architectures with an unknown number of layers. To relate performance data gathered for different architectures, we define a new kernel for conditional parameter spaces that explicitly includes information about which parameters are relevant in a given structure. We show that this kernel improves model quality and Bayesian optimization results over several simpler baseline kernels.Comment: 6 pages, 3 figures. Appeared in the NIPS 2013 workshop on Bayesian optimizatio