Tag: AI
Payment Intelligence: Unlocking Potential With Data Science
This powerful amalgamation, of Physics, Payment Intelligence, and cutting-edge innovations, has empowered FinTech to transcend boundaries and offer cost-effective, personalized, and swift services. With data science as its driving force, this quantum-infused fusion is expected to assume an increasingly pivotal role in shaping the payments sector’s future. By leveraging big data analytics, it creates novel gateways, poised to revolutionize the digital payments industry.
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The ABC of Deep Learning – A New Frontier in The Digital Age
Deep learning can learn and understand complex patterns in a way that’s similar to how humans can do it. Deep learning models can understand raw data without any help, but regular machine learning methods need people to recognize specific features before using the data to learn. We do this by using deep neural networks, which have many layers and work like the human brain.
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The Fundamentals Of Machine Learning
The main purpose of ML (machine learning) is to create an automatic data model for the purpose of analysis. Thus ML is to create a system that can learn from the data according to the algorithm used. The result can be found by mapping the output to the input or finding patterns/structures or learning by rewarding/punishing.
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Payment Intelligence | Powerful And Strong Combo With AI
The fusion of Artificial Intelligence technology with payment processes has led to a remarkable enhancement in efficiency, creating a mutually beneficial partnership between the two domains. Artificial intelligence was acknowledged and employed before this era, although its utilization was considered inadequate. More research is necessary to clarify the correlation among blockchain, payments, financial technology, and artificial intelligence.
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Natural Intelligence to Demystify Artificial Intelligence
Natural Intelligence or Human Intelligence: We are all so preoccupied with producing, reading, taking, and using artificial intelligence by utilizing our natural intelligence that we hope there will be no time or need to reverse this tendency, i.e., employing artificial intelligence to generate natural intelligence.
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Top 5 Deep Learning Applications on Social Media For Businesses
How do top brands create content that is always appealing and filled with a sense of humor to go viral in no time? Advanced tools help businesses understand their competitors and build new strategies to outrank them with better brand positioning. And how do social media platforms offer you intelligent recommendations?
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Not What You Think – Robots and Artificial Intelligence
Robot failure can occur for the basic and widely known reason that their machine learning models may not be precise enough or require extensive data and training to be precise. Robots excel in tasks that pose a substantial threat to humans, have low economic value, are menial in nature, and are significant in humanitarian endeavors with high risk involved. It is unlikely that robots or AI with advanced capabilities will replace our jobs in the next 50 years or beyond.
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Intelligence Augmentation – Powerful or Dangerous
The start of the year 2021 came with lots of expectations that should bring huge advancement in the AI field. Now there has been a significant shift in perspective. AI appears to be gradually infiltrating various facets of our everyday existence.
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Real-Time AI Powered Trends Business Can’t Survive Without in 2021
AI is getting more and more prominent across industries which is a plus point to move away from hype. It was once over-hyped for marketers, but now it’s the most powerful tools to automate their day-to-day operations. According to McKinsey, the AI industry is expecting to have more than $2.6 trillion worth of business in sales and online marketing. As most of the companies will seek an enhanced customer experience for their end-users, there will be tough competition against each other for a more stable future. Here are the top 5 AI-powered tools that businesses can’t sustain without in 2021.
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Digital Wallets and Security – Payments Landscape
If sensitive data is left unprotected, it can result in severe consequences for the service provider’s business, including financial fraud, violations of legal regulations, penalties from the regulators, loss of consumer trust, and identity theft etc. By implementing security measures at the hardware level, a payment processing application can become more resilient to attacks. This effectively secures against malicious attempts prior to reaching the actual application layer.
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DATA – Blue Ocean Shift Strategy (Boss)
BOSS – Blue Ocean Shift Strategy can actually help and create vision to focus on areas such as AI, blockchain for education, health & agriculture, create ecosystems using BigData analytics and IoT. To capture a quick snapshot of this strategy, certainly, Big Data appears to be most effective and efficient driver for Blue Ocean Strategy. Based on a limited set….
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Deep Learning – Introduction to Generative Adversarial Networks (GANs)
GANs consist of two neural networks i.e. Generator that generates a fake image of our currency note example and a disa criminator that classifies it into real or fake. The generator’s role is to map the input to the desired data space (image as in the example above). On the other hand second neural network models i.e. the discriminator classify the output with probability as real or fake compared with real datasets.
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Artificial Intelligence As A Transformative Technology
AI is “A somewhat successful attempt to create intelligent machines that work and react like humans.” It is created by humans to behave like a human helping to make human life better. How AI will be transforming the future, to elaborate on this I am sure we all will agree even a couple of books will not be enough. In just five next years it would surpass all the innovations, and technology market work. The handshake of this emerging technology bundle with quantum computing will be a blessing to see.
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Machine Learning – Introduction to Reinforcement Learning
Reinforcement learning is closely related to dynamic programming approaches to Markov decision processes (MDP). MDP solve a partially observable problem. POMDPs received a lot of attention in the reinforcement learning community. As its a process of discrete-time stochastic control to provide a mathematical framework for decision-making modelling.
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Machine Learning – Introduction to Unsupervised Learning
Unsupervised learning is classified as one of the three categories of machine learning, alongside Supervised Machine Learning, and Reinforcement Learning. Specifically, it falls under the domain of Unsupervised Machine Learning (UML). The predominant technique utilized in the Unified Modeling Language (UML) is cluster analysis. Cluster analysis is employed as a means of discovering concealed patterns or categories within data beyond conventional analytical methods.
