Source: cordis.europa.eu Designing algorithms for more challenging data Machine Learning researchers often have to overcome the ‘sim-to-real’ transfer, where algorithmic feats accomplished in computer simulations can be repeated in test performances. DESIRE has produced a data-driven, robust decision-making algorithm to achieve just that. Advancements in computing, such as the game AlphaGo, both rely on and Read More
Tag: Environments
Upgrade & Secure Your Future with DevOps, SRE, DevSecOps, MLOps!
We spend hours on Instagram and YouTube and waste money on coffee and fast food, but won’t spend 30 minutes a day learning skills to boost our careers.
Master in DevOps, SRE, DevSecOps & MLOps!
Learn from Guru Rajesh Kumar and double your salary in just one year.
Source: venturebeat.com In a recent paper published on the preprint server Arxiv.org, researchers at Carnegie Mellon, Facebook, and the University of Illinois Urbana-Champaign propose Active Neural Simultaneous Localization and Mapping (Active Neural SLAM), a hierarchical approach for teaching AI agents to explore environments. They say that it leverages the strength of both classical and AI-based path- and Read More
Source:- towardsdatascience.com Every artificial intelligence(AI) problem is a new universe of complexities and unique challenges. Very often, the most challenging aspects of solving an AI problem is not about finding a solution but understanding the problem itself. As paradoxically as that sounds, even the most experienced AI experts have been guilty of rushing into proposing deep Read More