- Artificial Intelligence (AI) and Machine Learning (ML) are both branches of artificial intelligence that help computers make decisions and recognize patterns in data. They’re becoming increasingly popular in agriculture, where they can be used to automate tasks that require judgment and analysis. AI/ML has been successfully employed in animal husbandry, aquaculture, forestry, and fisheries, but adoption among cannabis growers is still in its early stages. Because the industry lacks standardized procedures and guidelines, many companies are left to trial-and-error methods of implementing AI/ML into their business practices. Some companies have taken matters into their own hands by developing custom solutions that leverage AI/ML, such as Smart Cannabis Solutions, who use AI/ML to monitor and control irrigation systems and water quality parameters; and Precision Agriculture, Inc., whose autonomous robot uses AI/ML to collect and analyze data from drones to detect the best time to harvest. In addition to software applications, hardware manufacturers like Greenleaf Robotics are creating robots that leverage AI/ML algorithms to perform tasks such as harvesting, trimming, and sorting buds.
- Deep Learning
Deep Learning (DL) is a subset of ML that allows computers to learn how to complete complex tasks without explicitly being programmed. DL enables computers to identify patterns in large amounts of data. This ability makes it possible for machines to learn skills from experience while retaining the flexibility to adapt to changing conditions. DL is primarily used in computer vision problems like face recognition, object detection, and image classification to name a few. Over the past decade, DL has evolved to include more sophisticated techniques known as Generative Adversarial Networking (GAN), Reinforcement Learning (RL), Autoencoders, Sequence models, etc.
- Neural Networks
Neural networks consist of interconnected nodes called neurons, which transfer signals through weighted connections. Each node receives input signals from other nodes and produces output based on these inputs. Neurons are arranged in layers, each layer transferring signals to the next, until the final outputs reach the end of the network. There are two types of neural networks: feedforward network and recurrent neural networks. Feedforward nets work well for simple linear relationships between variables, whereas recurrent nets are better suited for nonlinear relationships. Recurrent nets often involve feedback loops, allowing them to capture non-trivial dynamic behavior. To train these networks, one needs labeled training sets, which can be challenging to obtain in real-world scenarios.
Artificial Intelligence is the simulation of human intelligence processes by machines, especially computer systems. AI can be used in many different ways and it’s not uncommon to see AI being used in the workplace. There are two types of artificial intelligence; general and narrow. General AI is the ability for a machine to do anything that a human being can do including functions such as emotion, speech recognition, decision making and so on. Narrow AI is when an algorithm has been designed to perform one specific task such as playing chess or driving a car.
The general consensus among experts is that we are still far from achieving general artificial intelligence but we have already achieved narrow AI with programs like Siri and Alexa which understand our voice commands and respond accordingly.
Artificial intelligence is a branch of computer science that studies the simulation of intelligent behavior in computers. AI research has been around for a long time, but it was only recently that we started to see the first major breakthroughs in the field. AI is an umbrella term that covers many different types of systems and algorithms.
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI is a branch of computer science that studies building intelligent machines that work and react like humans. It has been around for a long time but in recent years it has become more popular because it has been used in many different fields such as healthcare, education, business, law enforcement, etc.
Some examples of artificial intelligence are: machine learning (ML), natural language processing (NLP), deep learning, neural networks, cognitive computing, and so on.