Just imagine what your business could do if it recouped 6500 man-hours annually. Or a power supply savings comparable to all the Austin, TX usage?
Demand forecasting is done by analyzing statistical data and looking for patterns and correlations. Machine learning takes the practice to a higher level.
November brought a lot of significant AI-related breaking news. Machine learning and deep learning models were folding proteins, deriving the laws of physics from fictional universes and mimicking the human brain in a way never before seen. This edition of AI Monthly digest looks at scientific improvements made by AI with significant support from tech giants. Stories from November show that AI is clearly a great tool to improve countless lives […]
Among both traditional carmakers and cutting-edge tech behemoths, there is massive competition to bring autonomous vehicles to market.
As the fourth industrial revolution approaches, factories can harness the power of machine learning to reduce maintenance costs.
Fake images of hamburgers, the autonomous trolley problem, BERT for NLP and more stories from October, curated by deepsense.ai’s team, right here in AI Monthly Digest.
AI-based stock trading, a record-breaking competition on Kaggle and more stories cherry-picked from all the interesting ML- and AI-related news from September.
In our previous post, we gave you an overview of the differences between Keras and PyTorch, aiming to help you pick the framework that’s better suited to your needs. Now, it’s time for a trial by combat. We’re going to pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!
As a huge amount of computing power and time are required to train RL agent, it is no surprise that researchers are looking for ways to shorten the process.
Object recognition is common for diagram analysis and text recognition. The technique may soon be used to popularize art and culture.