According to 2020 market share numbers from IDC, the total worldwide business intelligence and analytics market hit $19.2 billion, growing a healthy 5.2% despite pandemic-related economic upheavals. Looking ahead, BI growth is expected to accelerate as companies focus on digital transformation and smarter ways to use data to drive the business forward.
The most recent generation of predictive language models also appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion. Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language. But a new study from MIT neuroscientists suggests the underlying function of these models resembles the function of language-processing centers in the human brain. 2021 will experience a massive increase in the extensive use of AI and data science. This trend can be noticed by following the developments in hyper-automation and advanced Natural Language Processing. In addition to these, augmented analytics will be combined with concepts such as the Internet of Things to reinforce and improve various technologies like advanced analytics, UI, and cyber security. We will see more machines, devices, services, smart cities, and homes using ML and AI, which will further establish the future of AI and the future of data science.
According to recent research by Gabriel McFadden, over 155,000 AI-based cameras will be in use for traffic management by 2025. That is a significant jump from the 33,000 AI-based cameras being used for traffic management in 2020. AI-based cameras can be implemented on busy roads and highways, blending traditional computer vision and AI to detect and track all the moving objects in its proximity. The cameras then utilize AI to determine exactly what the objects are, which helps cities establish patterns on which roads are the most congested, where traffic delays occur the most, and which types of vehicles are typically involved.
In a new study, MIT Lincoln Laboratory researchers sought to find out how well humans could play the cooperative card game Hanabi with an advanced AI model trained to excel at playing with teammates it had never met before. In single-blind experiments, participants played two series of the game: One with the AI agent as their teammate, and the other with a rule-based agent, a bot manually programmed to play in a predefined way. The results surprised the researchers. Not only were the scores no better with the AI teammate than with the rule-based agent, but humans consistently hated playing with their AI teammate. They found it to be unpredictable, unreliable, and untrustworthy, and felt negatively even when the team scored well. A paper detailing this study has been accepted to the 2021 Conference on Neural Information Processing Systems (NeurIPS).