We are excited to announce the latest installment in the Wolfram SystemModeler series, Version 5.1, where our primary focus has been on pushing the scope of use for models of systems beyond the initial stages of development.
Since 2012, SystemModeler has been used in a wide variety of fields with an even larger number of goals—such as optimizing the fuel consumption of a car, finding the optimal dosage of a drug for liver disease and maximizing the lifetime of a battery system. The Version 5.1 update expands SystemModeler beyond its previous usage horizons to include a whole host of options, such as:
- Exporting models in a form that includes a full simulation engine, which makes them usable in a wide variety of tools
- Providing the right interface for your models so that they are easy for others to explore and analyze
- Sharing models with millions of users with the simulation core now included in the Wolfram Language
February 15, 2018 — Jérôme Louradour, Advanced Research Group
Are you ever certain that somewhere in a text or set of texts, the answer to a pressing question is waiting to be found, but you don’t want to take the time to skim through thousands of words to find what you’re looking for? Well, soon the Wolfram Language will provide concise answers to your specific, fact-based questions directed toward an unstructured collection of texts (with a technology very different from that of Wolfram|Alpha, which is based on a carefully curated knowledgebase).
Let’s start with the essence of FindTextualAnswer. This feature, available in the upcoming release of the Wolfram Language, answers questions by quoting the most appropriate excerpts of a text that is presumed to contain the relevant information.
October 10, 2017 — Etienne Bernard, Lead Architect, Advanced Research Group
Automated Data Science
Imagine a baker connecting a data science application to his database and asking it, “How many croissants are we going to sell next Sunday?” The application would simply answer, “According to your recorded data and other factors such as the predicted weather, there is a 90% chance that between 62 and 67 croissants will be sold.” The baker could then plan accordingly. This is an example of an automated data scientist, a system to which you could throw arbitrary data and get insights or predictions in return.
One key component in making this a reality is the ability to learn a predictive model without specifications from humans besides the data. In the Wolfram Language, this is the role of the functions Classify and Predict. For example, let’s train a classifier to recognize morels from hedgehog mushrooms:
October 4, 2017 — John Fultz, Director of User Interface Technology
Ten months ago, I announced the beginning of our open beta program for Wolfram Player for iOS. The beta is over, and we are now shipping Wolfram Player in the App Store. Wolfram Player for iOS joins Wolfram CDF Player on Windows, Mac and Linux as a free platform for sharing your notebook content with the world.
Wolfram Player is the first native computational notebook experience ever on iOS. You can now take your notebooks with you and play them offline. Wolfram Player supports notebooks running interfaces backed by Version 11.1 of the Wolfram Language—an 11.2 release will come shortly. Wolfram Player includes the same kernel that you would find in any desktop or cloud release of the Wolfram Language.
Microscopes were invented almost four hundred years ago. But today, there’s a revolution in microscopy (as in so many other fields) associated with computation. We’ve been working hard to make the Wolfram Language a definitive platform for the emerging field of computational microscopy.
It all starts with getting an image of some kind—whether from a light or x-ray microscope, transmission electron microscope (TEM), confocal laser scanning microscope (CLSM), two-photon excitation or a scanning electron microscope (SEM), as well as many more. You can then proceed to enhance images, reconstruct objects and perform measurements, detection, recognition and classification. At last month’s Microscopy & Microanalysis conference, we showed various examples of this pipeline, starting with a Zeiss microscope and a ToupTek digital camera.
September 7, 2017 — Greg Hurst, Wolfram|Alpha Math Content Manager
In our continued efforts to make it easier for students to learn and understand math and science concepts, the Wolfram|Alpha team has been hard at work this summer expanding our step-by-step solutions. Since the school year is just beginning, we’re excited to announce some new features.
Our goal with SystemModeler is to provide a state-of-the-art environment for modeling, simulation—and analytics—that leverages the Wolfram technology stack and builds on the Modelica standard for systems description (that we helped to develop).
SystemModeler is routinely used by the world’s engineering organizations on some of the world’s most complex engineering systems—as well as in fields such as life sciences and social science. We’ve been pursuing the development of what is now SystemModeler for more than 15 years, adding more and more sophistication to the capabilities of the system. And today we’re pleased to announce the latest step forward: SystemModeler 5.
June 6, 2017 — Keiko Hirayama, Wolfram|Alpha Developer, Wolfram|Alpha Scientific Content
As the next phase of Wolfram Research’s endeavor to make biology computable, we are happy to announce the recent release of neuroscience-related content.
The most central part of the human nervous system is the brain. It contains roughly 100 billion neurons that act together to process information, subdivided functionally and structurally into areas specialized for certain tasks. The brain’s anatomy, the characteristics of neurons and cognitive maps are used to represent some key aspects of the functional organization and processing abilities of our nervous system. Our new neuroscience content will give you a sneak peek into the amazing world of neuroscience with some facts about brains, neurons and cognition.
May 25, 2017 — Devendra Kapadia, Kernel Developer, Algorithms R&D
Derivatives of functions play a fundamental role in calculus and its applications. In particular, they can be used to study the geometry of curves, solve optimization problems and formulate differential equations that provide mathematical models in areas such as physics, chemistry, biology and finance. The function D computes derivatives of various types in the Wolfram Language and is one of the most-used functions in the system. My aim in writing this post is to introduce you to the exciting new features for D in Version 11.1, starting with a brief history of derivatives.
May 17, 2017 — Itai Seggev, Mathematica Algorithm R&D
Calling all command-line junkies: the new WolframScript is here!
Now you can evaluate Wolfram Language code, call deployed APIs and execute standalone scripts directly from your favorite command-line interface. WolframScript works like any other command-line utility, enabling flexible connections between the Wolfram System and other programs and I/O.