What’s the difference between Artificial Intelligence and Machine Learning
Artificial Intelligence (AI), in contrast to the natural intelligence of humans, is machine taught and learned technology. Coined in the 1950’s, Artificial Intelligence is one of the biggest buzzwords impacting big data tech companies today. The 6 major goals of AI are as follows:
- AI automates repetitive learning and discovery through data.
- AI adds intelligence
- AI adapts through progressive learning algorithms
- AI analyzes more and deeper data
- AI achieves incredible accuracy
- AI gets the most out of data.
In Contrast, Machine Learning is a subset of artificial intelligence, like deep learning and natural language processing, machine learning is the latest branding for artificial intelligence to take off in the tech world. The major difference between AI and ML is the computer’s ability to teach itself things without being programmed. Machine learning developed from continuing pattern recognition and computational learning theory. Here are the 4 different types of machine learning techniques:
- Supervised learning algorithms trained to use labeled examples, such as an input where the desired output is known.
- Unsupervised learning is used against data that has no historical labels
- Semi-Supervised learning is used for the same applications as supervised learning.
- Reinforcement learning is often used for robotics, gaming, and navigation.
AI and ML do not need to be the shiny gold ticket for large tech companies, small and mid-size businesses can also benefit greatly from AI and ML innovative technology they just need the means of steering towards this new direction. Sunvera Software is here for small and mid-size businesses to help guide them towards a bright future of technology. Call +1 949-284-6300 for a free half-hour consultation to discuss how your company can be on the cutting edge of Artificial Intelligence and Machine Learning.