Everything AI, Robotics, and IoT
Why it matters: The dictionary is a list of words that are alphabetically defined. Using complex algorithms and amazingly large data sets to garner deeper insights into language pattern and etymology of words, AI can build the dictionary and very well expand it too.
Why it matters: A Digital Worker is a virtual employee who augments and enhances human productivity by combining artificial intelligence, machine learning, robotic process automation (RPA) and analytics in order to automate a range of business functions.
Why it matters: AI can help film makers by saving time, improving process, engagement, production decisions, content creation and distribution.
Why it matters: With datasets becoming larger on average, understanding how to effectively work with data in memory boosts your productivity and flexibility as a data professional. Understanding how to process these data in pandas will allow you to manage data at scale with ease.
Why it matters: Kotlin and Python are currently two very popular programming languages that are currently being used in many different fields. It is useful to know the difference between so you know when to use one language over the other when developing an application.
Why it matters: Artificial intelligence is improving transportation and logistics by improving critical process and unclogging bottle necks.
Why it matters: The advent of online dating has transformed the way we connect with potential partners, and the growth of social media has created new opportunities for building relationships. But as our interactions with technology become more and more intimate, what role will artificial intelligence (AI) play in our search for love?
Why it matters: How close are we to simulating how the human brain really works and to creating intelligent machines modeled on human brain intelligence?
Why it matters: Have you or your team ever had to go through the tedious process of mining large data sets for particular information like names, numbers, or keywords? AI data labeling helps with data acquisition tasks in high visibility areas. In short, AI labeling is used to identify and track the divergent markers among data—what makes objects different from one another.
Why it matters: XLand is a digital 3D training environment for artificial intelligence agents. The environment resembles a colorful video-game-like playground. In this playground, the players face billions of different tasks they need to resolve.