Looking to get started with AI but not sure where to begin? Read NVIDIA's quick start guide and learn how to set your next AI project up for success.
We live in a time of unprecedented innovation. Product design cycles keep getting shorter, personalized and custom products are becoming the norm and external requirements are changing constantly. On top of this, global problems like climate change, clean energy, water, phosphorus and nitrogen flows, plastics waste and other planetary boundaries that are being transgressed are calling for redesign of almost everything we are familiar with today.
Elsevier and ExactCure recently announced a collaboration to develop and offer to hospitals – without charge – drug-specific exposure models for 20 already approved medicines that are being tested as potential treatments for Covid-19.
With the world’s focus on the COVID-19 pandemic, LIMS providers are working to develop solutions tailored to assist in the testing and management of virus samples.
Researchers at Harvard Medical School (HMS) have released an open source drug discovery platform, VirtualFlow, that harnesses supercomputing power to screen potentially billions of small organic compound structures in parallel, in the hunt for promising new drug molecules.
When designing a component or system, where do you start? In days gone by, designers would literally go back to the drawing board, using their experience and expertise to develop a new concept.
Effective utilisation of computing tools is critical to both AI and HPC research, with recent projects in both fields highlighting the scientific benefit of carefully managing resources.
Advances in computer vision combined with AI computing are helping pathologists to more accurately identify subtypes of cancer - leading to better treatments for patients, explains Dan Ruderman.
