The Healthcare sector is one sector that is always in demand. Lately, the rate and necessity of patient responsibility and innovative medicines have developed. With the growth in such requirements, the latest technologies have been adopted in the industry. One such significant development that had to take place is the application of Big Data and Analytics in the Healthcare sector. It has been observed that big data are predicted to expand faster in healthcare than in areas like financial services, manufacturing, and so on…
In our previous blog post, “Master Your ML/AI Success with Enterprise Data Management”, we outlined the need for Enterprise Data Management (EDM) and ML/AI initiatives to work together in order to deliver the full business value and expectations of ML/AI. We made a set of high-level recommendations to increase EDM maturity and in turn enable higher value from ML/AI initiatives. In this post, we will present a specific instantiation of technology for bringing those concepts to life.
here are a lot of issues in big data that warrant discussion. It is important to be aware of the different online data analytics metrics and tools used to track people online, since they shape the direction of big data technology. It is interesting how one word – cookies can mean different things. In the modern world of IT technology, you will think first regarding cookies, not as homemade fresh sweet things made by granny; you will imagine something that helps you not insert everyday passwords on different websites.
If you make decisions based upon averages, at best, you’ll get average results” During the 1950s, United States Air Force pilots were having trouble controlling their planes. The problem turned out to be the cockpit, or more specifically, the fact that the cockpit had just one design: one designed for the 1920’s average pilot. The Air Force concluded that they simply needed to update their measurement of the average pilot, adjust the cockpit accordingly, and the pilot handling troubles would go away.
Artificial intelligence has had a dramatic impact on the efficiencies of daily human tasks as well as complex intellectual tasks that require substantial human intelligence. AI is taking over the automotive industry as well, handling the reins in every department ranging from designing and manufacturing cars to car maintenance, safety, and AI-enabled cockpits. Self-driving cars like 2021 Tesla Model S are now a reality, thanks to the rapid advancements in AI technologies over the years.
For all the photographers out there who haven’t mastered the art of the steady hand: this one’s for you. Researchers at Duke University in North Carolina have applied an AI-based solution to touching up blurry photographs, creating a program capable of touching up blurry faces into an image sixty times sharper. It’s not going to turn you into an artist, but it could work wonder on your holiday snaps! The Duke team’s system is called PULSE, standing for Photo Upsampling via Latent Space Exploration.
Big data analytics has already had a transformative influence across a wide range of sectors, and it’s perhaps no more prevalent than in the world of healthcare. With the sheer volume of information that patients are capable of producing and the heightened emphasis on the industry in the wake of the COVID-19 pandemic, big data may yet develop into one of the most significant tools in maintaining the health of individuals and even anticipating the emergence of conditions that are yet to manifest in patients…
Artificial Intelligence (AI) is one of the main weapons by which companies or medium-sized corporations can combat numerous cyber threats successfully. According to Warren Buffet, “Cyber-attack is the biggest threat to mankind, even more of a bigger threat than the nuclear weapon.” Therefore, organizations should consider applying the concepts of AI within their workplaces if they want to prosper in the future without compromising their digital anonymity. Continue reading this post to know what is AI and how it is transforming cybersecurity for all the right reasons…
Limitations on physical interactions throughout the world have reshaped our lives and habits. And while the pandemic has been disrupting the majority of industries, e-commerce has been thriving. This article covers how reinforcement learning for dynamic pricing helps retailers refine their pricing strategies to increase profitability and boost customer engagement and loyalty. In dynamic pricing, we want an agent to set optimal prices based on market conditions. In terms of RL concepts, actions are all of the possible prices and states, market conditions, except for the current price of the product or service.
Artificial Intelligence has the potential to revolutionize the social visibility of brands, paving the way for more incisive approaches towards marketing. The huge potential of AI in social media has led to Markets and Markets forecasting that the industry of deep learning, machine learning and NLP within sales marketing, customer experience management and predictive risk assessment within social platforms will grow to more than $2.1 billion in value by 2023.