Artificial Intelligence (AI) and robotics have by a lot evolved in recent years, but AI is still only in It's beginning. And AI in robotics will be next thing after AI softwares witch are even now incredibly good. In this Article we will look at Artificial Intelligence in Robotic and explain It so you better understand It
3 Core elements of AI in Robotics
How Robots Learn
1. Supervised learning when are AI robots trained with supervised learning they are trained from labeled data that have input and output pairs and these pairs are made by human and are set. This method is the simplest from all of these 3, but It allow robots to identify patterns and make predictions based on the past experiences.
2. Unsupervised learning simply allow robots to learn based on data that are unlabeled that can connect these data together and find patters to make prediction witch is always different with new data. This method is mostly used in AI systems today, because It is more advanced and have lot of use cases.
3. Reinforcement learning is most advanced and most powerful way how can robots learn, It works based on learning on mistakes, so if the system makes wrong It learn from the feedback It receives if It was good or bad and It will do It until It's correct and this is how reinforcement learning is so good.
Understand robotics brain
1. Deep learning is subset of machine learning and is mostly used in AI systems that use neural networks to process big amounts of data. The point is that It tries to be same as human brain's structure. And this enables robots to process very complex information and perform advanced tasks.
2. Recurrent Neural Networks (RNNs) are types of neural networks that are able process sequences of data and make them ideal for tasks that specificly involves time series or natural language processing and this way RNNs get the robots to understand and generate human language or predict future events based on past observations almost perfectly.
3. Convolutional Neural Networks (CNNs) are like specialized neural networks, but made for image processing and identifying the place around and these super complicated networks can allow robots to identify different objects or navigate in environments or even easily recognize emotions in human faces better then people.
Natural Language Processing: Teaching Robots to Communicate
1. Understand NLP - Natural Language Processing is technique that allows the AI robots to communicate, It is for example used in ChatGPT and lately It really progressed thanks to OpenAI. For explanation how NLP works go to our article out Natural Language processing.
2. Sentiment Analysis is common NLP technique can allow the robots to simply understand and gauge all peoples emotions based on text that was written by human. This ability of robots can be used for example in customer service or social media monitoring or even personal assistant applications, there are no limits.
AI robots can transform Industries and Lives
You know as AI keeps getting better and better we're going to see some really cool stuff happening with robots.
I believe they will be exploring space and that could also help us find new planets and resources out there.
And it's not just about space, I also think that robots will be everywhere like personal assistants. Of course there is still a lot to figure out, but that's what makes it so exciting.
Artificial Intelligence robots in Future
We already could see some AI robots or self-driving cars like tesla and more then physical robots more software, but I know that this is stone age of AI. Some of the AI robots we could see in masses in AI future:
Personal robot assistants
AI in healthcare
It's clear to me that AI will be huge in future and It's huge opportunity like when Internet was starting.
I mean, from the tech to the way it's shaking up industries and our lives, we're just seeing the beginning of AI-driven robots.
But we also have to keep discussing and pondering the challenges and responsibilities that come with this AI.