Important AI Milestone at Mass General Brigham in Boston -- 1) Mass General Brigham is using an AI model that has reduced the waiting period for breast imaging results from days to 15 minutes. This helps hospitals reduce time and effort needed to annotate new datasets.

Rising need for AI Ethics workers is leading to exceedingly overworked and woefully underappreciated ... [ ] considerations. If there is one thing that we can almost all entirely agree on, I dare say it might be the abundance of worker burnout. Nary a day goes by that there aren't some blazing headlines about this worker or that worker-related burnout happening here or there. Some attribute burnout to concerns over wanting to keep their job and make a living. Others suggest that the burnout mania got especially underway when remote working became acceptable, pushing workers to potentially work nonstop and not have the conventional leave the office at 6 o'clock basis for curtailing work for the day. A slew of reasons exists and are continually bandied around for worker burnout. Those that work in the realm of Artificial Intelligence (AI) are right there in the worker burnout zone too. Yes, with all that excitement and hoopla about the present and future prospects of AI, there are humans toiling away to craft and field the AI. Software developers that specialize in making AI applications are dearly sought by companies. Once onboard, the AI programmers are bound to discover that there is a lot of AI work going on. Indeed, the odds are that a veritable fifteen pounds of AI are needed and yet the AI teams are barely able to produce five pounds given the team size and AI complexities involved.

One hundred seventy-four new packages made it to CRAN in October. Here are my “Top 40” selections in sixteen categories: Astronomy, Biology, Business, Computational Methods, Data, Ecology, Finance, Genomics, Mathematics, Machine Learning, Medicine, Pharma, Statistics, Time Series, Utilities, Visualization. Astronomy skylight v1.1: Provides a function to calculate sky illuminance values (in lux) for both the sun and moon. The model is a verbatim translation of the code by Janiczek and DeYoung (1987). There are vignettes for Use and Advanced Use. Biology palaeoverse v1.0.0: Provides tools to support data preparation and exploration for palaeobiological analyses including functions for data cleaning, binning (time and space), summarisation and visualisation with the goals of improving code reproducibility and accessibility and establishing standards for the palaeobiological community. See Jones et al. for details, and the contribution guide to get involved. pirouette v1.6.5: Implements a method to create a Bayesian posterior from a phylogeny that depicts the true evolutionary relationships. See Richèl et al. (2020) for background. There are several vignettes including a Tutorial, a demo, and a guide showing how to use the package in a scientific experiment. Business bupaverse v0.1.0: Facilitates loading the packages comprising the bupaverse, an integrated suite of R packages for handling and analysing business process data, developed by the Business Informatics research group at Hasselt University, Belgium. See the Getting Started Guide. Computational Methods fastWavelets v1.0.1: Provides an Rcpp implementation of the Maximal Overlap Discrete Wavelet Transform (MODWT) and the À Trous Discrete Wavelet Transform. See Quilty & Adamowski (2018) for background and README for examples. gips v1.0.0: Employs the methods described in Graczyk et al. (2022) to find the permutation symmetry group under which the covariance matrix of the data is invariant. See the vignettes Optimizers, Theory, and gips. HomomorphicEncryption v0.1.0: Implements the Brakerski-Fan-Vercauteren (2012), Brakerski-Gentry-Vaikuntanathan (2014), and Cheon-Kim-Kim-Song (2016) schema for fully homomorphic encryption. There are seven short vignettes including BFV, BGV, and CKKS. rxode2random v2.0.9: Implements parallel random number generation. See Wang et al. (2016) and Fidler et al (2019) for background and README for an example.. Data airnow v0.1.0: Provides functions to retrieve U.S. Government AirNow air quality data. See README to get started. amazonadsR v0.1.0: Provides functions to collect data on digital marketing campaigns using the Windsor.ai API. See the tutorial for an example and also look at the related new packages: bingadsR, facebookadsR, googleadsR, instagramadsR, linkedinadsR, pinterestadsR, redditadsR, snapchatadsR, ticktokadsR, twitteradsR. Pablo Sanchez was on a roll in October. congress v0.0.1: Provides functions to download and read data on United States congressional proceedings through the Congress.gov API of the Library of Congress. See README for an example. Ecology canaper v1.0.0: Provides functions to analyze the spatial distribution of biodiversity especially useful in the categorical analysis of neo- and paleo-endemism (CANAPE) as described in Mishler et al. (2014) and for statistical tests to determine the types of endemism that occur in a study area while accounting for the evolutionary relationships of species. There are vignettes on CANAPE, randomization, and parallel computing. EcoEnsemble v1.0.1: Provides functions to fit and sample from the ensemble model described in Spence et al (2018). There is an Introduction and there are two additional vignettes: ExploringPriors and SyntheticData. rTRIPLEXCWFlux v0.2.0: Encodes the carbon uptake submodule and evapotranspiration submodule of the TRIPLEX-CW-Flux model to run the simulation of carbon-water coupling. See Zhou et al. (2008) Monteith (1965) for background and the vignette for examples. stopdetection v0.1.1: Enables stop detection in time stamped trajectory by implementing the Stay Point detection algorithm originally described in Ye (2009) that uses time and distance thresholds to characterize spatial regions as stops. See the vignette for examples. Finance highOrderPortfolios v0.1.0: Implements methods to select portfolios using high order moments to characterize return distributions. See Zhou & Palomar (2021) and Wang et al. (2022) for the theory and the vignette to get started. MSTest v0.1.0: Implements hypothesis testing procedures described in Hansen (1992), Carrasco, Hu, & Ploberger (2014) and Dufour & Luger (2017) that can be used to identify the number of regimes in Markov switching models. See README for an example. Genomics metevalue v0.1.13: Implements the e-value method to correct p-values in omics data association studies. See Hebestreit & Klein (2022) and Akalin et.al (2012) for background and the vignette for an example. SCpubr v1.0.4: Implements a system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data. Look here for an online reference manual. Mathematics Boov v1.0.0: Provides functions to perform the Boolean operations union, difference and intersection on volumes. Computations are done by the C++ library CGAL. See README for some examples. Also, have a look at the package MinkowskiSum. fitode v0.1.1: Provides methods and functions for fitting ordinary differential equations that use sensitivity equations to compute gradients of ODE trajectories with respect to underlying parameters. See the vignette for details. manifold v0.1.1: Implements operations for Riemannian manifolds including geodesic distance, Riemannian metric, and exponential and logarithm maps, and also incorporates a random object generator on the manifolds. See Dai, Lin, and Müller (2021) for details. Machine Learning SoftBart v1.0.1: Implements the SoftBart model of described by Linero and Yang (2018) with the optional use of a sparsity-inducing prior to allow for variable selection. The vignette contains theory and examples. tidyfit v0.5.1: Extends the tidy data environment with functions to fit and cross validate linear regression and classification algorithms on grouped data. There are several vignettes including Predicting Boston House Prices, Multinomial Classification, and Rolling Window Time Series Regression. Medicine cities v0.1.0: Provides functions to simulate clinical trials and summarize causal effects and treatment policy estimands in the presence of intercurrent events. Have a look at the demo. RCT2 v0.0.1: Implements various statistical methods for designing and analyzing two-stage randomized controlled trials using the methods developed by Imai, Jiang, and Malani (2021) and Imai, Jiang, and Malani (2022). There are vignettes on Interference and Causal Inference. Pharma DTSEA v0.0.3: Implements a novel tool to identify candidate drugs against a particular disease based on the drug target set enrichment analysis. It assumes the most effective drugs are those with a closer affinity in the protein-protein interaction network to the specified disease. See Gómez-Carballa et al. (2022) and Feng et al. (2022) for disease expression profiles, Wishart et al. (2018) and Gaulton et al. (2017) for drug target information, and Kanehisa et al. (2021) for the details of KEGG database. There is a vignette. nlmixr2lib v0.1.0: Provides tools to create model libraries for nlmixr2. Models include pharmacokinetic, pharmacodynamic, and disease models used in pharmacometrics. See the vignette Creating a model library. Statistics aIc v1.0: Implements set of tests for compositional pathologies including for coherence of correlations as suggested by Erb et al. (2020), compositional dominance of distance, compositional perturbation invariance as suggested by (Aitchison (1992) and singularity of the covariation matrix. See the vignette for details and examples. ktweedie v1.0.1: Uses Reproducing Kernel Hilbert Space methods to implement Tweedie compound Poisson gamma models with high-dimensional predictors for the analyses of zero-inflated response variables. See the vignette for examples. missoNet v1.0.0: Implements efficient procedures for fitting conditional graphical lasso models linking predictor variables to response variables or tasks, when the response data may contain missing values. See the vignette for examples. ShalpeyOutlier v0.1.0: Provides methods to use Shapley values to detect, explain, and cell wise impute multivariate outliers. See Mayrhofer and Filzmoser (2022) for details and the vignette for examples. SpatialfdaR v1.0.0: Provides functions to that implement finite element analysis methods to spatial functional data analysis. See Sangalli et al. (2013) and Bernardi et al. (2018) for background and the vignette for an example. Time Series dfms v0..1.3: Provides a user friendly and computationally efficient approach to estimate linear Gaussian dynamic factor models using Kalman filter and EM algorithm methods. See Doz et al. (2011) and Banbura & Modugno (2014) for background and the vignette for examples. Utilities ExclusionTable v1.0.0: Provides functions for creating tables of excluded observations by reporting the number before and after each subset() call together with the number of observations that have been excluded. See the vignette. shiny.tailwind v0.2.2: Allows TailwindCSS to be used in Shiny apps with just-in-time compiling including custom CSS with @apply directive, and custom tailwind configurations. See README for examples. Visualization AlphaHull3D v1.1.0: Provides functions to compute the alpha hull of a set of points (informallly: the shape formed by these points) in 3D space. See README for some visualizations, and also have a look at the related packages MeshesTools, and PolygonSoup. bangladesh v1.0.0: Provides sf objects, shape files, and functions to draw regional chorpleth maps for Bangladesh. See the vignette. ggstats v0.1.0: Provides functions to create forest plots of regression model coefficients along with new statistics to compute proportions, weighted mean and cross-tabulation statistics, as well as new geometries to add alternative background color to a plot. There are vignettes on plotting coefficients and on computing cross-tabulation, custom proportions, and weighted means. jagshelper v0.1.11: Provides tools to streamline Bayesian analyses in JAGSincluding functions for extracting output, streamlining assessment of convergence, and producing summary plots. See the vignette for examples. roughsf v1.0.0: Provides functions to draw maps, including “sketchy”, hand-drawn-like maps using the Javascript library Roughjs. See README for examples.

NASA's Artemis programme is already breaking records, less than two weeks after its very first spaceflight launched. The agency has confirmed its Artemis 1 Orion capsule smashed the record for the furthest distance travelled from Earth by any craft designed to carry humans. At 08:40 EST (13:40 GMT) on Saturday (November 26), Orion reached 248,655 miles from Earth, beating the record set by Apollo 13 in April 1970. Then, at 16:06 EST (21:06 GMT) on Saturday, it reached the farthest point in its orbit – a maximum distance of 268,553 miles. Artemis 1 is an uncrewed test flight for NASA's Artemis programme, comprising the Orion spacecraft, Space Launch System (SLS) rocket.

"AI algorithms have made it through the FDA approval process, and people are now looking at and trying to figure out how to build them into their clinical practice and what the economics of it are, what makes these worth while and what adds value," Kahn explained. "One of the challenges is, what do you want these things to do? What role do they fill?" While more than 300 AI algorithms are now cleared by the FDA, and a large number of these are in radiology, radiologists need to determine what is useful to their practice. "For things in radiology, it has to improve the productively of the radiologist," Kahn said.

Cybersecurity firms were early adopters of AI -- those in the industry use as many tools as possible to stop the bad guys -- but increased processing power has expanded AI's security uses and investors have taken note by investing billions of dollars in recent years.

The Department of Defense's Chief Digital and Artificial Intelligence Office is seeking vendors to develop software prototypes for the Joint AI Test Infrastructure Capability project. CDAO Test and Evaluation Directorate issued a call to industry notice on Nov. 21 in pursuit of AI technologies capable of object detection and computer vision classification. The office's test and evaluation directorate is building a software infrastructure to support trials of AI and machine learning adoption across DOD operations. The goal of the JATIC program is to advance AI T&E and address out-of-scope testing issues such as natural language processing, systems integration, human-machine evaluation and performance monitoring. Interested parties may register until Jan. 3, 2023.

Machine learning has achieved great success in electroencephalogram (EEG) based brain-computer interfaces (BCIs). Most existing BCI research focused on improving its accuracy, but few had considered its security. Recent studies, however, have shown that EEG-based BCIs are vulnerable to adversarial attacks, where small perturbations added to the input can cause misclassification. Detection of adversarial examples is crucial to both the understanding of this phenomenon and the defense. This paper, for the first time, explores adversarial detection in EEG-based BCIs. Experiments on two EEG datasets using three convolutional neural networks were performed to verify the performances of multiple detection approaches. We showed that both white-box and black-box attacks can be detected, and the former are easier to detect.

With rapid development of blockchain technology as well as integration of various application areas, performance evaluation, performance optimization, and dynamic decision in blockchain systems are playing an increasingly important role in developing new blockchain technology. This paper provides a recent systematic overview of this class of research, and especially, developing mathematical modeling and basic theory of blockchain systems. Important examples include (a) performance evaluation: Markov processes, queuing theory, Markov reward processes, random walks, fluid and diffusion approximations, and martingale theory; (b) performance optimization: Linear programming, nonlinear programming, integer programming, and multi-objective programming; (c) optimal control and dynamic decision: Markov decision processes, and stochastic optimal control; and (d) artificial intelligence: Machine learning, deep reinforcement learning, and federated learning. So far, a little research has focused on these research lines. We believe that the basic theory with mathematical methods, algorithms and simulations of blockchain systems discussed in this paper will strongly support future development and continuous innovation of blockchain technology.

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.