Dear cafe, I would like to announce that the Baysig programming language and the BayesHive analytics environment (http://bayeshive.com) are now available for beta testers. Baysig is a new probabilistic, functional and typed programming language that attempts to realise the vision of "fully Bayesian computing". That is, in Baysig almost all the work in data processing consists of building a probabilistic model of the incoming data. Almost everything else -- optimal decisions, categorisation, measuring hidden parameters or states, forecasting, testing hypothesis -- becomes trivial. This paradigm can in principle be applied to a large number of domains, although for the moment we are focusing on models that are based on continuous parameters. It will therefore be of interest to users of statistics and dynamical systems models, including in finance, physics and life sciences. To analyse data in Baysig, you write a program in the random-number supply monad that generates simulated data. A special construct, "estimate", then applies Bayes' theorem to this program and returns the probability distribution of the model parameters given observed data. The "estimate" procedure is difficult to implement in Haskell or similar languages, which encouraged us to develop a new language. However, in many respects Baysig should feel like Haskell, and we hope that Baysig will encourage the Haskell community to experiment with statistical modelling. We have built a web-based environment to help users, including those with little-to-no programming experience, use Baysig, at bayeshive.com. This web application allows you to upload data from spreadsheets or timeseries, and to build statistical models with a point-and-click web interface which ends up generating Baysig code. Code and the results of running it are collected in shareable and editable literate programming documents. We would appreciate any feedback from the Haskell community before releasing our platform to unsuspecting statisticians and researchers. Almost everything is written in Haskell, including the Baysig compiler. The BayesHive website is written using Yesod, with which we are mostly happy. We also use the Stan package (mc-stan.org), and the web front-end is written using AngularJS. For the moment the Baysig language is only available through the BayesHive web interface, but that will change. If you want to run Baysig on your own computer, please send me an email at tomn@openbrain.org. Finally, both the BayesHive web application and the Baysig language implementation are still prototypes and very much work-in-progress. We promise to work hard at fixing the bugs you find! Links: BayesHive, including a few videos: http://bayeshive.com Baysig quick tour ("QuickBAYSIG"): http://bayeshive.com/helppage/Baysig%20quick%20tour:%20fundamentals More documentation: http://bayeshive.com/help Regards, Tom Nielsen OpenBrain Ltd.