News, Views & Insights
It’s hard to believe we’ve been doing this for 35 years, building a taller and taller tower of ideas and technology that allow us to reach ever further. In earlier times we used to release the results of efforts only every few years. But in recent times we’ve started doing incremental (“.1”) releases that deliver our latest R&D achievements—both fully fleshed out, and partly as “coming attractions”—much more frequently.
We released Version 12.2 on December 16, 2020. And today, just five months later, we’re releasing Version 12.3. There are some breakthroughs and major new directions in 12.3. But much of what’s in 12.3 is just about making Wolfram Language and Mathematica better, smoother and more convenient to use. Things are faster. More “But what about ___?” cases are handled. Big frameworks are more completely filled out. And there are lots of new conveniences.
There are also the first pieces of what will become large-scale structures in the future. Early functions—already highly useful in their own right—that will in future releases be pieces of major systemwide frameworks.
Wolfram Application Server is a new platform developed by Wolfram Research enabling customers to deploy Wolfram Language–powered APIs and webpages into a scalable, highly available enterprise cluster.
Wolfram Application Server lets you:
manage data exchange in your deployments with a robust external services framework. create applications using the Wolfram Natural Language Understanding (NLU) System, the key semantic interpretation technology behind Wolfram|Alpha and Wolfram Language. generate content based on time and location, assign custom endpoints and integrate curated content from the Wolfram Knowledgebase.We have designed Wolfram Application Server for customers who for regulatory, security or business reasons may not wish to deploy onto the Wolfram Cloud but prefer to host their Wolfram Language applications on clusters they control.
Ever since Thomas Robert Malthus’s book An Essay on the Principle of Population, scientists have sought to determine the limit to the growth of human population due to finite resources. One such resource is groundwater. About 40% of global food production ultimately depends on irrigation and, increasingly, the source of irrigation water is groundwater aquifers. Groundwater irrigation allows farmers to increase crop yields, maintain them in dry spells and overcome temporal mismatches between growing seasons and seasonal rain. In many parts of the world, groundwater withdrawal (or pumping from wells) exceeds recharge, leading to groundwater depletion. In these regions, the “lifespan” of groundwater aquifers is limited, putting a bound on the amount of irrigation per year and the sustainability of groundwater-based agriculture. The goal of this study was to propose a dynamical systems framework capable of explaining past trends in groundwater-based irrigation and providing forecasts of food production.
Our annual Wolfram Technology Conference took place October 6–9, and along with it the 10th annual Wolfram Innovator Award Ceremony. This year, Stephen Wolfram recognized 13 outstanding individuals from around the globe for their significant work using the Wolfram Language across fields and disciplines.
NOTE: The following post contains real medical images.
As more technology is folded into medical environments all over the world, Wolfram’s European branch has taken on work with the United Kingdom’s National Health Service (NHS) in an effort to partially automate the process of cancer diagnosis. The task is to use machine learning to avoid checking thousands of similar-looking images of people’s insides by hand for signs of cancer.