The world produces quintessentially vast amounts of data--more than it can consume. Statista report dated September 08, 2022, states that the total amounts of data created, captured, copied, and consumed globally had reached 64.2 zettabytes in 2020. Furthermore, data creation is projected to grow by more than 180 zettabytes by 2025. Companies need to collect huge volumes of data produced to extract valuable insights via data analysis to survive, let alone thrive in the competitive marketplace. It is the lifeblood of most business decisions, functions, and processes.

This article is sponsored by Oracle – redefining data management with the world's first autonomous database. In the coming years, the amount of data we create worldwide will grow to 175 zettabytes of data per year by 2025, up from 33 zettabytes in 2018. Over half of this data will be created by the Internet of Things devices and over 60% of it will be enterprise data. By 2025, 30% of all the data created will be in real-time, offering organisations great opportunities to constantly optimise their business. Clearly, the organisation of tomorrow is a data organisation.

Adoption of Artificial Intelligence (AI) has accelerated since the pandemic hit as the whole world moved towards digitization. A study by Oxford University and Yale University indicates that AI will outperform humans in many ways and will automate all human jobs in the next 120 years. By 2024, AI will be better than humans at translation, will write bestselling books by 2049, and will perform surgeries by 2053. Machine learning (ML), the proficiency of a machine to mimic human ability to accumulate knowledge and use it to drive insights, is generally considered the basis of AI. Although AI might depend on its machine learning abilities, we need to take a step back and realize ML doesn't happen in vacuum. ML is driven by big data, without which it can't take place.

Adoption of Artificial Intelligence (AI) has accelerated since the pandemic hit as the whole world moved towards digitization. A study by Oxford University and Yale University indicates that AI will outperform humans in many ways and will automate all human jobs in the next 120 years. By 2024, AI will be better than humans at translation, will write bestselling books by 2049, and will perform surgeries by 2053. Machine learning (ML), the proficiency of a machine to mimic human ability to accumulate knowledge and use it to drive insights, is generally considered the basis of AI. Although AI might depend on its machine learning abilities, we need to take a step back and realize ML doesn't happen in vacuum. ML is driven by big data, without which it can't take place.

Industry (or Manufacturing) 4.0 started as a German government initiative in 2011. It refers to a Fourth Industrial Revolution characterized by smart factories using robotics, autonomous operations, the Internet of Things, big data, analytics, artificial intelligence, and a convergence of IT and OT. The goal is to create efficient, agile and intelligent manufacturing. There wasn't a prescriptive Industry 4.0 methodology for manufacturers to follow, so early adopters tried various approaches to see which worked best. "We focus on the capabilities that [Manufacturing 4.0] technology can deliver for our clients," said Stephen Laaper, principal and smart factory leader at Deloitte.

In this post, we discuss how to use the AWS Cloud and its services to accelerate observational studies for life sciences customers. We provide a reference architecture for architects, business owners, and technology decision-makers in the life sciences industry to automate the processes in clinical studies. Observational studies lead the way in research, allowing you to formulate hypotheses and test those hypotheses in controlled experiments. These studies are a powerful tool to help researchers learn what happens in real-life studies. You can use this research as a precursor to drug discovery and new drug indications.

To solve client problems, effective information management, and Artificial intelligence services together have proven to be an excellent combination for organizations. Without delivering products, it is essential to understand consumer behavior in order for any business to survive and thrive. Any communication with clients can be a huge data source. It can be used to analyze their behavior, solve problems, change process policy and operations, and change the user journey. However, integrating AI with CRM is by far the most revolutionary step.

Deployed for healthcare, environmental and even bartending duties around the world, robots have just been enlisted to sort through waste flowing through a Florida recycling plant, where they perform faster and safer than humanly possible. The 14 high-speed, precision robots installed this summer at Single Stream Recyclers (SSR) in Sarasota are guided by an artificial intelligence platform that applies computer vision and machine learning to direct the robots' rapid-fire movements. "The average human can pick 30-40 items per minute. The robots can pick 80 items per minute," said John Hansen, co-owner of SSR, which processes materials from numerous Southwest Florida communities at its nearly 100,000-square-foot recovery facility. Developed by Denver-based AMP Robotics, the robots identify and sort plastics, cartons, paper, cardboard, metals and other materials streaming through their cube-like housing.

I actually got my degree in Business Administration, Political Science and International Relations. After graduating, my first job was in sales for a company that pioneered in Artificial Intelligence (AI) and Natural Language Processing (NLP) for enterprise back in 2006, called Nstein Technologies. This is where I fostered an interest in AI, NLP and machine learning and from there I moved to Lexalytics, where I saw the need for democratised, cloud-based analytics. I left Lexalytics and started Semantria which was later acquired by Lexalytics, before starting People.ai in 2016. How did you come to found People.ai and what were your reasons for believing in your proposition?

This article is sponsored by Oracle – redefining data management with the world's first autonomous database. In the coming years, the amount of data we create worldwide will grow to 175 zettabytes of data per year by 2025, up from 33 zettabytes in 2018. Over half of this data will be created by the Internet of Things devices and over 60% of it will be enterprise data. By 2025, 30% of all the data created will be in real-time, offering organisations great opportunities to constantly optimise their business. Clearly, the organisation of tomorrow is a data organisation.