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From citizen engagement to healthcare and education, AI is being adopted to transform a range of public sector services
Read the articleAddressing fears, fostering trust, implementing responsible AI and empowering employees are crucial steps for navigating AI’s transformative impact on the workforce
Read the articleThe capability of Agentic AI to navigate complex workflows and take autonomous decisions across channels will give way to “Service as Software” (SaS)
Read the articleThe introduction of AI agents will transform the future of industrial operations
Read the articleWEF’25 Accredited Panel Discussion | Ice Village, Davos
Watch nowWEF’25 Accredited Panel Discussion | HCLTech Pavilion, Davos
Watch nowHCLTech Chairperson speaks to Vishnu Som, NDTV in Davos
Watch nowHCLTech Trends and Insights video podcast from WEF’25, Davos
Watch nowAI, automation, collaboration and upskilling are shaping the continuous transformation of the manufacturing industry
Read the articleAs artificial intelligence continues to advance at a rapid pace, the need to deploy the technology responsibly has become crucial for competitive advantage
Read the articleFrom the rising trend of Agentic AI to the need for scalable and responsible implementation, HCLTech’s CTO shares his insights on an AI-driven world
Read the articlePagination
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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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