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AI for inclusive growth: Leadership lessons from Davos
What are the practical ways to ensure AI expands opportunity, strengthens resilience and supports a more inclusive, equitable future?
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Despite its growing potential, clinicians in the US are hesitant about how quickly GenAI will be adopted in their field
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Despite the technology’s significant energy consumption, artificial intelligence can help organizations achieve their sustainability goals
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A content strategy helps make the best use of AI to achieve marketing goals
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In the latest iPredict session from HCLTech, Ryan Kido — CTO at Ateliere Creative Technologies — discusses generative AI’s growing influence in the media and entertainment industry
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AI-driven tool helps resolve mystery health diagnosis, demonstrating beneficial capabilities
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Conversational chatbots, powered by generative AI, are making engagement easier for patients, providing the right answers and eliminating wait time
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The SaaS industry has been growing exponentially and AI can help accelerate the industry’s applications
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Artificial intelligence and increasing data literacy are reshaping the concept of being “data-driven” in financial services
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Market growth presents a range of new job opportunities requiring new skillsets
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Technologies like Generative AI are set to reshape the nature of human labor
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Truly 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
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New AI advancements are leading to continued AI research and development by tech companies large and small
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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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