Energetics of the brain and AI

Does the energy requirements for the human brain give energy constraints that give reason to doubt the feasibility of artificial intelligence? This report will review some relevant estimates of brain bioenergetics and analyze some of the methods of estimating brain emulation energy requirements. Turning to AI, there are reasons to believe the energy requirements for de novo AI to have little correlation with brain (emulation) energy requirements since cost could depend merely of the cost of processing higher-level representations rather than billions of neural firings. Unless one thinks the human way of thinking is the most optimal or most easily implementable way of achieving software intelligence, we should expect de novo AI to make use of different, potentially very compressed and fast, processes

Probing the Improbable: Methodological Challenges for Risks with Low Probabilities and High Stakes

Some risks have extremely high stakes. For example, a worldwide pandemic or asteroid impact could potentially kill more than a billion people. Comfortingly, scientific calculations often put very low probabilities on the occurrence of such catastrophes. In this paper, we argue that there are important new methodological problems which arise when assessing global catastrophic risks and we focus on a problem regarding probability estimation. When an expert provides a calculation of the probability of an outcome, they are really providing the probability of the outcome occurring, given that their argument is watertight. However, their argument may fail for a number of reasons such as a flaw in the underlying theory, a flaw in the modeling of the problem, or a mistake in the calculations. If the probability estimate given by an argument is dwarfed by the chance that the argument itself is flawed, then the estimate is suspect. We develop this idea formally, explaining how it differs from the related distinctions of model and parameter uncertainty. Using the risk estimates from the Large Hadron Collider as a test case, we show how serious the problem can be when it comes to catastrophic risks and how best to address it

Should we campaign against sex robots?

In September 2015 a well-publicised Campaign Against Sex Robots (CASR) was launched. Modelled on the longer-standing Campaign to Stop Killer Robots, the CASR opposes the development of sex robots on the grounds that the technology is being developed with a particular model of female-male relations (the prostitute-john model) in mind, and that this will prove harmful in various ways. In this chapter, we consider carefully the merits of campaigning against such a technology. We make three main arguments. First, we argue that the particular claims advanced by the CASR are unpersuasive, partly due to a lack of clarity about the campaign’s aims and partly due to substantive defects in the main ethical objections put forward by campaign’s founder(s). Second, broadening our inquiry beyond the arguments proferred by the campaign itself, we argue that it would be very difficult to endorse a general campaign against sex robots unless one embraced a highly conservative attitude towards the ethics of sex, which is likely to be unpalatable to those who are active in the campaign. In making this argument we draw upon lessons from the campaign against killer robots. Finally, we conclude by suggesting that although a generalised campaign against sex robots is unwarranted, there are legitimate concerns that one can raise about the development of sex robots

Balanced truncation of linear time-varying systems

In this paper balanced truncation of linear time-varying systems is studied in discrete and continuous time. Based on relatively basic calculations with time-varying Lyapunov equations/inequalities we are able to derive both upper and lower error bounds for the truncated models. These results generalize well-known time-invariant formulas. The case oftime-varying state dimension is considered. Input-output stability of all truncated balanced realizations is also proven. The method is finally successfully applied to a high-order model

An a posteriori error estimate for Symplectic Euler approximation of optimal control problems

This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading order term consisting of an error density that is computable from Symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations. The performance is illustrated by numerical tests

Periodic Motion Planning for Virtually Constrained (Hybrid) Mechanical Systems

The paper presents sufficient and almost necessary conditions for the presence of periodic solutions for zero dynamics of virtually constrained under-actuated Euler-Lagrange system. This result is further extended to detect periodic solutions for a class of hybrid systems in the plane and analyze their orbital stability and instability. Illustrative examples are given

Airway management in simulated restricted access to a patient - can manikin-based studies provide relevant data?

<p>Abstract</p> <p>Background</p> <p>Alternatives to endotracheal intubation (ETI) are required when access to the cranial end of the patient is restricted. In this study, the success rate and time duration of standard intubation techniques were compared with two different supraglottic devices. Two different manikins were used for the study, and the training effect was studied when the same manikin was repeatedly used.</p> <p>Methods</p> <p>Twenty anaesthesiologists from the Air Ambulance Department used iGEL^™, laryngeal tube LTSII^™and Macintosh laryngoscopes in two scenarios with either unrestricted (scenario A) or restricted (scenario B) access to the cranial end of the manikin. Different manikins were used for ETI and placement of the supraglottic devices. The technique selected by the physicians, the success rates and the times to completion were the primary outcomes measured. A secondary outcome of the study was an evaluation of the learning effect of using the same manikin or device several times.</p> <p>Results</p> <p>In scenario A, all anaesthesiologists secured an airway using each device within the maximum time limit of 60 seconds. In scenario B, all physicians secured the airway on the first attempt with the supraglottic devices and 16 (80%) successfully performed an ETI with either the Macintosh laryngoscope (n = 13, 65%) or with digital technique (n = 3, 15%). It took significantly longer to perform ETI (mean time 28.0 sec +/- 13.0) than to secure an airway with the supraglottic devices (iGel™: mean 12.3 sec +/- 3.6, LTSII™: mean 10.6 sec +/- 3.2). When comparing the mean time required for the two scenarios for each supraglottic device, there was a reduction in time for scenario B (significant for LTSII^™: 12.1 versus 10.6 seconds, p = 0.014). This may be due to a training effect using same manikin and device several times.</p> <p>Conclusions</p> <p>The amount of time used to secure an airway with supraglottic devices was low for both scenarios, while classic ETI was time consuming and had a low success rate in the simulated restricted access condition. This study also demonstrates that there is a substantial training effect when simulating airway management with airway manikins. This effect must be considered when performing future studies.</p