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The SaaS industry has been growing exponentially and AI can help accelerate the industry’s applications
Learn moreArtificial intelligence and increasing data literacy are reshaping the concept of being “data-driven” in financial services
Learn moreMarket growth presents a range of new job opportunities requiring new skillsets
Learn moreTechnologies like Generative AI are set to reshape the nature of human labor
Learn moreTruly harnessing the power of generative AI requires the right prompts or questions, which is why prompt engineering has become an integral discipline for the future of innovation
Learn moreNew AI advancements are leading to continued AI research and development by tech companies large and small
Read morePersonal AI is set to shape a transformative and tailored future
Learn moreWith an increasing focus on creating a circular economy, computer vision systems are helping segregate tons of wastes that can be reused, recycled and repurposed
Learn moreGenerative AI is disrupting the status quo and driving rapid adoption in business and consumer landscapes
Learn moreThe rise of publicly available AI tools has also led to the rise of AI-related cybercrimes and an increase the effectiveness of scams
Learn moreAI regulations must be prioritized by governments and organizations
Learn moreAmid the meteoric rise of ChatGPT, AI has been quietly driving a revolution in the healthcare industry
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Trending questions
The term "artificial intelligence" was coined by John McCarthy in 1956. Alan Mathison Turing, followed by Newell, Simon, McCarthy and Minsky, are key figures in AI development. Newell and Simon's 1956 "Logic Theorist" program marked a milestone. These pioneers, known as the founding fathers of AI, significantly advanced the field.
- Increased productivity
- Increased automation
- Smart decision-making
- Solve complex problems
- Managing repetitive tasks
- Strengthens economy
- Personalization
- Disaster management
- Enhances lifestyle
- Global defense
Machine learning is the brain of AI that emulates logical decision-making based on the data fed to it and an AI model is the creation, training and deployment of the ML algorithms. With advancements in intelligence methodologies, AI models support in tandem with real-time analytics, predictive analytics and augmented analytics using natural language processing (NLP), ML, statistical analysis and algorithmic execution.
Loaded with human capabilities and beyond, the importance of artificial intelligence (AI) is rising and gradually spreading to various industries, making way for new possibilities and better efficiencies. Data in today’s world is an asset and valued across industries. With AI, humans are now able to absorb, interpret and make complex decisions.
While artificial intelligence is a system that mimics or imitates human intelligence, machine learning is the brain that helps it work.
Generative AI refers to a subset of artificial intelligence algorithms and models designed to generate new data that resembles existing data. These sophisticated algorithms can create content in various forms, such as text, images, music and even complex structures like designs and models. Generative AI is primarily powered by advances in neural networks, particularly Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
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