It’s now a given that countries worldwide are battling for AI supremacy. To date, most of the public discussion surrounding this competition has focused on commercial gains flowing from the technology. But the AI arms race for military applications is racing ahead as well, and concerned scientists, academics, and AI industry leaders have been sounding the alarm.
Compared to existing military capabilities, AI-enabled technology can make decisions on the battlefield with mathematical speed and accuracy and never get tired. However, countries and organizations developing this tech are only just beginning to articulate ideas about how ethics will influence the wars of the near future. Clearly, the development of AI-enabled autonomous weapons systems will raise significant risks for instability and conflict escalation. However, calls to ban these weapons are unlikely to succeed.
In an era of rising military tensions and risk, leading militaries worldwide are moving ahead with AI-enabled weapons and decision support, seeking leading-edge battlefield and security applications. The military potential of these weapons is substantial, but ethical concerns are largely being brushed aside. Already they are in use to guard ships against small boat attacks, search for terrorists, stand sentry, and destroy adversary air defenses. Read More
Daily Archives: April 20, 2021
MLOps: Comprehensive Beginner’s Guide
MLOps, AIOps, DataOps, ModelOps, and even DLOps. Are these buzzwords hitting your newsfeed? Yes or no, it is high time to get tuned for the latest updates in AI-powered business practices. Machine Learning Model Operationalization Management (MLOps) is a way to eliminate pain in the neck during the development process and delivering ML-powered software easier, not to mention the relieving of every team member’s life.
Let’s check if we are still on the same page while using principal terms. Disclaimer: DLOps is not about IT Operations for deep learning; while people continue googling this abbreviation, it has nothing to do with MLOps at all. Next, AIOps, the term coined by Gartner in 2017, refers to the applying cognitive computing of AI & ML for optimizing IT Operations. Finally, DataOps and ModelOps stand for managing datasets and models and are part of the overall MLOps triple infinity chain Data-Model-Code.
While MLOps seems to be the ML plus DevOps principle at first glance, it still has its peculiarities to digest. We prepared this blog to provide you with a detailed overview of the MLOps practices and developed a list of the actionable steps to implement them into any team. Read More
Artificial intelligence looks for a ‘language’ of cancer and Alzheimer’s
Researchers use machine learning to look for a biological language for disease in protein sequences.
Artificial intelligence is being used to try to crack open all kinds of problems. Some experts think that techniques used to predict what types of movies or TV shows someone will like or what word will come next in a sentence could be applied to biology. A group of researchers is hoping to use algorithms and language processing to find mistakes in cells that are causing disease, like cancer, Alzheimer’s disease and neurodegenerative disorders.
A team based at St John’s College, University of Cambridge think that machine learning technology can be used to find a kind of “biological language” for disease in the body. “Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer,” says Tuomas Knowles, one of the authors of the paper and a Fellow at St John’s College, in a press release. “Ultimately, the aim will be to use artificial intelligence to develop targeted drugs to dramatically ease symptoms or to prevent dementia happening at all.” Read More
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