Technology

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For decades, scientists have tried to use artificial intelligence techniques and algorithms to provide computers with human-like knowledge and behavior. Although more sophisticated than traditional programming, the techniques used have focused primarily on manually growing and improving the system's knowledge base, which has always been limited. Limited domain knowledge has proven to be a poor substitute for human expertise; i.e. AI systems are only as good as their programming (done manually by a human) The new approach is to build systems that learn from themselves, becoming experts that model and abstract rules from the data they are fed. These systems are improving in their precision, adapting to the unknown and expanding their capabilities beyond the original programming. Traditional techniques of natural language processing (NLP), rule-based reasoning, and knowledge representation are being augmented with machine learning—especially deep learning—to improve AI (see Figure 1). Pr

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The burgeoning requirement for agricultural products such as fruits and vegetables, on account of the booming global population, is driving the demand for advanced farming methods that can fuel higher agricultural productivity. As per the United Nations (UN), the total population across the world will rise from 7.7 billion in 2019 to 9.7 billion by 2050. Due to this factor, farmers are increasingly adopting devices such as drones in farming processes. Moreover, drones provide various benefits to farmers such as the real-time monitoring of crops, soil analysis, and crop spraying. The other major factor propelling the demand for agricultural drones is the relaxation of regulations regarding the deployment of drones by the governments of several countries such as the U.S., Germany, China, India, and Brazil. This is, in turn, pushing up the deployment of drones, which is, in turn, driving the expansion of the global agricultural drones market. The market is expected to grow at a CAGR

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In today's digital era, where cyber threats are constantly evolving, protecting an organization's network is essential to preserving data integrity and the confidentiality of critical information. In this context, Zero Trust Architecture (ZTA) emerges as a promising strategy to strengthen a network's security defenses. In this article, we will explore in depth the concept of Zero Trust Architecture, understand its fundamental principles and discuss why its implementation is crucial to ensuring cybersecurity in an increasingly vulnerable business environment. What is Zero Trust Architecture (ZTA)? Zero Trust Architecture (ZTA) is a network security model that operates on the fundamental premise that no entity should be trusted by default, regardless of its location, inside or outside the network. Instead, the Zero Trust approach requires that all access attempts be verified and validated, regardless of the user's or device's location. This model aims to eliminate implicit trust in t

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Hence, MEAN stack is the best option if you are seeking a versatile and powerful web development stack. This blog will explore the MEAN Stack Development in depth, including its benefits, components, and use case

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But none of those films won five Golden Globes, as did Oppenheimer: best drama film, best director (Christopher Nolan), best drama actor (Cillian Murphy), best supporting actor (Downey), and best original score (Ludwig Göransson).

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