Introduction to Third-Wave of AI
Most of the business decisions today are based on big data as it has the ability to allow visibility into future market trends and consumer preferences. In that direction, Artificial Intelligence (AI) has become the non-disposable ally for modern organizations. But AI has its own limitations.
Manually-curated data serves as the biggest of challenges as they hinder AI programs’ from deciphering patterns from within complex contextual information. Big data needs to go through a lot of cleansing to filter out duplicate and corrupt datasets before being fed into any AI or machine learning application. Here the role of data scientists becomes crucial as they need to ensure the general integrity of data by maintaining accuracy and consistency of data.
But the third wave of AI is set to bring in a new dimension of data analytical capabilities by the virtue of combining machine learning, advanced text analytics, and natural language processing. The third wave in the development of AI will allow us to identify statistical links among large datasets and draw patterns that afford insights.
Characterized by something called contextual normalization, new-generation AI programs cannot only draw patterns but also construct algorithms to justify the patterns. The final data rendered by this new wave of AI will be cleaner and more centralized than what we have seen before and will rest us with the power to discover insights that otherwise used to get lost amongst heaps of structured and unstructured data.