All content
Insights from the Analyst and Advisor Day reveal how an AI-intrinsic narrative is reshaping financial services through scalable platforms, agentic automation and domain-driven innovation
Read the articleThe Raise of AI CEO's What Agentic AI Means for Leadership & Strategy
Govind Chandranani, Practice Head of Engineering and R&D Services at HCLTech, discusses how enterprises adopting GenAI must embed responsible governance to balance innovation with trust and compliance
Read the articleEnterprises adopting generative AI at scale must address sector-specific risks
Insights from the Digital Innovation Valley and HCLTech partnership
Watch nowBy trading depth for speed, cost efficiency and privacy, the increased adoption of small language models could democratize AI technology
Read the articleCompeting frameworks are shaping the next software revolution. Who will win between open source and Big Tech?
Read the articleVibe coding shifts how developers interact with code, using natural language prompts instead of detailed instructions
Read the articleThe growing adoption of AI and GenAI in healthcare, along with data modernization, responsible AI practices and strategic partnerships are key to improving patient care and operational efficiency
Read the articleAt HCLTech’s Data and AI Forum for Leaders in Capital Markets, the transformational impact of AI on financial services was explored
Read the articleAgentic AI is a fully autonomous system that automates complex tasks and enhances human decision-making
Read the articleWhat’s next for the ASEAN insurance industry?
Learn morePagination
- Previous page
- …
- 4
- 5
- 6
- …
- Next page
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).
Subscribe to the HCLTech Newsletter
for our latest news and insights







