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APRIL 2024
Artificial Intelligence
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Economics of Artificial Intelligence Governance
Artificial intelligence (AI) related institutions are a key factor influencing the economic benefits of these innovations and how such benefits are distributed. This article examines the current stage of AI governance institutions and barriers hindering the widespread adoption of such institutions.
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Data-Centric Green Artificial Intelligence: A Survey
Elevating green AI, this survey delves into data-centric methods to boost the energy efficiency of AI algorithms. It explores innovative approaches such as active learning and dataset distillation, advocating for eco-friendly AI advancements and pondering future challenges and directions.
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Growing Demand – Careers in Machine Learning
AI and Machine Learning are revolutionizing various sectors, creating high demand for skilled professionals. With AI imitating human cognition and Machine Learning enabling systems to learn from data, the career opportunities in this innovative field are both diverse and rewarding.
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Resource
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Five AI Trends That Will Shift Hiring Practices in 2024
40% of executives plan to increase AI investment. Learn how these five trends are increasing demand for researchers and engineers in computer vision, AI, and deep learning to roll out new products and integrations.
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A Conversation with Katerina Michou, Student Scholarship Recipient
Katerina Michou, a dedicated ECE student at NTUA and IEEE leader, excels academically and in organizing impactful tech events. Awarded prestigious scholarships, she aims for a future in Theoretical Computer Science. Explore her journey and insights for aspiring engineers.
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Webinars
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Intersection of AI and Project Management
Thursday, 16 May, 2024, 11:00 AM EDT
This webinar delves into AI's impact on Project Management, highlighting how AI tools enhance efficiency, risk reduction, and decision-making by automating tasks and providing data insights, preparing professionals for a data-driven business environment.
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SE Radio Podcast
534: Andy Dang on AI / ML Observability
Andy Dang discusses AI/ML observability and data ops challenges, including concept drift, high dimensionality, and organizational issues, highlighting the role of explainability.
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Featured Jobs on our Career Center
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