Machine Intelligence

While computer technology advances beyond its constraints, businesses are looking for newer approaches to gain benefit. A sharp increase in computing speeds and capabilities has led to new and highly intelligent software systems, some of which are ready to replace or augment human services.

For instance, with smart chatbots ready to transform the world of customer service and beyond, the rise of natural language processing (NLP) is one of the best examples that can be deliberated upon.

Moreover, machine intelligence has played an important role in the evolution of NLP systems as it gives computers the ability to automatically learn and improve from experience.

What is machine intelligence?

Machine intelligence is referred to as progressive computing that allows a technology (a machine, device, or algorithm) to interact with its environment intelligently, which means it can apply actions to maximize its chance of effectively achieving its goals.

The idea of machine intelligence emphasizes the intersection of machine learning and artificial intelligence, as well as the comprehensive spectrum of opportunities in the field.

Simply put, machine intelligence is what’s created when machines are programmed with certain aspects of human intelligence, including learning, problem solving and prioritization. With these abilities, a machine can tackle a complex set of problems.

How machine intelligence and Natural Language Processing work together?

NLP uses machine intelligence and deep learning algorithms to analyze human language in a smart way. Machine learning doesn’t work with predefined rules. Instead, it learns by example. In the case of NLP, machine intelligence algorithms train on thousands and millions of text samples, word, sentences and paragraphs, which have been labeled by humans. By reviewing those examples, it gains an extensive understanding of the context of human language and utilizes that knowledge to analyze forthcoming excerpts of text.

This makes it possible for NLP software to comprehend the meaning of several nuances of human language without necessitating to be explicitly conveyed. With adequate training, NLP algorithms can also cognize the broader meaning of human-spoken or -written language.

Natural Language Processing via Sunartek

With the aim to support various industries namely corporates, banks, institutions, defense, and government security organizations, we at Sunartek offer Natural Language Processing (NLP) solutions that are designed to extract meaningful information from textual contents.

Sunartek’s technology is used for National security, Intelligence, Marketing, Recommendation engines, Customer insights, knowledge engines, Relevant search, and Cognitive computing. The solution automates, simplifies, and accelerates human understanding from an infinite pool of intercepted textual data.

Beneficial features:

Extracting entities: Companies, people, dollar amounts, key initiatives etc.
Categorizing content: Positive or negative (E.g. sentiment analysis), by operation, intention, or objective; by industry or other classifications for investigations and     trending.
Assembling content: To discover essential topics of discourse and/or to identify new topics.
Fact-extraction: To fill databases with systematic information for evaluation, visualization, trending, or notifications.
Relationship-extraction: To fill out graph-based databases to investigate real-world relationships.

In conclusion, NLP has transformed the way we network with computers and it’ll continue to do so in future. With more researches being conducted in this field, Sunartek expects to witness more innovations that will make machines smarter at distinguishing and understanding the human language.