With the learning procedures used during machine learning, automatically focused on the most common cases, whereas when writing rules by hand it is often not at all obvious where the effort should be directed.
Automatic learning procedures can make use of statistical inference algorithms to produce models that are steady to unfamiliar input (e.g. containing words or structures that have not been seen before) and to incorrect input (e.g. with misspelled words or words accidentally omitted).
Generally, handling such input gracefully with handwritten rules, or, more generally, creating systems of handwritten rules that make soft decisions, can be very difficult, error-prone and time-consuming.
Systems
- Systems based on automatically learning the rules can be made more accurate simply by supplying more input data. However, systems based on handwritten rules can only be made more accurate by increasing the complexity of the rules, which is a much more difficult task.
- In particular, there is a limit to the complexity of systems based on handcrafted rules, beyond which the systems become more and more unmanageable.
- However, creating more data to input to machine-learning systems simply requires a corresponding increase in the number of man-hours worked, generally without significant increases in the complexity of the annotation process.
Machine Learning
Synnect AI is capable in offering superior performance from massive parallel processing and the feature-rich building blocks for machine learning pipelines let you explore and compare multiple approaches rapidly.
Natural Language Processing
Conversational AI primarily focuses on the application of two subtopics of NLP: natural language understanding and natural language generation.
Predictive Module
Automatically produce large-scale time series analyses and hierarchical forecasts – without human involvement. Reduced manual intervention means there’s less chance of personal bias in the forecasting process.
Computer Vision
Computer vision analyzes and interprets what’s in a picture or video. Our AI solutions use computer vision to accelerate intelligent automation with simple tools for image processing, image recognition and object detection.
Artificial intelligence (AI) has received increased attention in recent years. Innovation, made possible through the Internet, has brought AI closer to our everyday lives.
Machine learning algorithms have proved efficient in analyzing and identifying patterns in large amounts of data, commonly referred to as “Big Data”.
