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Decision intelligence platforms (DIPs) are software used to create solutions that support, automate and augment decision making of humans or machines, powered by the composition of data, analytics, knowledge and artificial intelligence (AI) techniques. DIPs must have collaborative capabilities for decision modeling, execution and monitoring. DIPs are used to design decision-centric solutions, explicitly model decisions, orchestrate decision execution flows, and evaluate and govern decisions and audit their outcomes. Optional features include logic-based techniques, machine learning, business intelligence, natural language processing, optimization, graph technology, AI agents, simulation, real-time event stream processing and multi-structured data preparation.

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The High Impact Leader: Moments Matter by Bruce J. Avolio and Fred Luthans presents a framework for authentic leadership development.

It argues that pivotal life experiences, both positive and negative, significantly shape leadership skills, more so than formal training alone.

The book emphasises the importance of self-awareness, psychological capital (PsyCap—confidence, hope, optimism, resilience), and aligning one's actual self with their aspirational self.

Practical steps and numerous examples are provided to guide readers in building their own authentic leadership development plans, focusing on sustainable and ethical performance. A Gallup poll on authentic leadership further supports the book's core arguments.

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This podcast from AI Coach presents a 2024 Hype Cycle and Priority Matrix for artificial intelligence, categorising various AI technologies (e.g., generative AI, neuromorphic computing, autonomic systems) by maturity and potential benefit.

It also provides definitions, importance, business impacts, drivers, obstacles, user recommendations, and sample vendors for each technology.

The guide aims to help organisations strategically invest in and adopt AI, balancing short-term gains with long-term potential. Specific focus is given to the importance of responsible AI development and deployment.

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Prompt engineering is the process of crafting effective input prompts to get the best results from AI models, particularly large language models. Its importance stems from the direct impact prompt quality has on AI performance, influencing accuracy and efficiency across various applications.

While offering significant benefits like improved AI-driven solutions and cost reduction, it also faces challenges such as inconsistencies and a lack of standardisation.

Successfully using prompt engineering requires understanding AI model capabilities, iterative experimentation, and employee training, with several prominent AI vendors providing tools to support this crucial skill.

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This podcast details AI TRiSM (Trust, Risk, and Security Management), a crucial framework for responsible AI development and deployment.

It highlights the importance of mitigating ethical concerns, such as bias and misuse, alongside security risks, to foster trust and compliance.

The podcast explores the business benefits of AI TRiSM, including enhanced value from AI investments and reduced operational risks.

Challenges like expertise gaps and stakeholder resistance are also addressed, along with recommendations for implementation, such as establishing clear governance policies and investing in monitoring tools.

Finally, leading vendors offering AI TRiSM solutions are mentioned.

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Sovereign AI involves nations building their own AI systems to achieve technological independence and address national priorities.

This approach is driven by concerns over data security, foreign influence, and the ethical implications of AI, but faces challenges including high infrastructure costs and the rapid pace of technological advancement.

Successful implementation requires investment in infrastructure, skilled personnel, and ethical guidelines, along with collaboration between government, industry, and academia. Several major technology companies are involved in supporting these national AI initiatives. Ultimately, sovereign AI aims to improve national security, economic competitiveness, and societal well-being.

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This podcast explores Artificial General Intelligence (AGI), a hypothetical machine with human-level intelligence capable of performing any intellectual task.

It examines AGI's potential transformative impact across various industries, alongside significant ethical and societal challenges. The pocast details the technological advancements driving AGI research, as well as the substantial scientific and practical obstacles hindering its development.

Finally, it offers recommendations for organisations to approach AGI cautiously, prioritising ethical considerations and collaborative research.

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Composite AI, the integration of multiple AI techniques, offers a powerful approach to solving complex problems.

By combining methods like machine learning and symbolic reasoning, it overcomes the limitations of individual AI approaches, leading to more robust and adaptable systems.

This podcast explores the business benefits, driving forces, and implementation challenges of composite AI, offering recommendations for successful adoption and highlighting key vendors in the field.

Despite complexities, its potential for enhanced decision-making and improved business outcomes is significant.

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Neuro-symbolic AI combines neural networks' pattern recognition with symbolic reasoning's logical capabilities, creating more robust and interpretable AI systems.

This hybrid approach addresses limitations in traditional AI, particularly the need for explainability and reasoning, offering significant potential across various industries like healthcare and finance.

However, challenges remain, including the need for expertise in both fields and the lack of standardised tools. Successful adoption requires multidisciplinary teams, robust data architectures, and a focus on specific use cases where traditional AI proves inadequate.

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Decision intelligence (DI) is a field combining data, artificial intelligence, and human expertise to enhance decision-making. Its importance stems from the need for data-driven choices in complex business environments. DI offers measurable benefits across sectors, improving areas like finance, supply chain, and healthcare. However, challenges include fragmented processes, a lack of data literacy, and ethical considerations. Successful DI adoption requires strategic planning, investment in suitable platforms, and fostering a collaborative, data-literate culture. Several leading technology companies offer DI solutions.