Big data

AI, Radio Astronomy, and the Search for Life Beyond Earth

AI, Radio Astronomy, and the Search for Life Beyond Earth

Ramiro Caisse Saide presents a multimodal deep-learning approach for technosignature detection in radio astronomy, using observations from Breakthrough Listen at MeerKAT. He investigates combining spectrograms with I/Q signal representations to improve signal detection and classification, particularly in low signal-to-noise environments. The talk also covers his extensive background in AI education, software development, the motivations behind SETI, fundamental radio astronomy concepts, and studies on Earth's own radio leakage.

The Real AI Frontier Isn't Smarter Machines (with Catherine Williams)

The Real AI Frontier Isn't Smarter Machines (with Catherine Williams)

Dr. Catherine Williams, a former black-hole physicist and early data science leader, explores the field's evolution from Bayesian models to LLMs. She passionately argues that deep mathematical understanding and the ability to build robust mental models are more crucial than ever, even as AI automates technical tasks. Williams also discusses the impact of embeddings, the changing economics of frontier AI, and her work at the nonprofit Candid, advocating for a human-centric approach to intelligence in the age of AI.

The Pathologies of Big "Messy" Data in Telco • Jay Fenton • YOW! 2015

The Pathologies of Big "Messy" Data in Telco • Jay Fenton • YOW! 2015

Jay Fenton discusses the challenges of "big messy data" in the telecommunications industry, highlighting how legacy systems fail to handle the scale and complexity. He presents a suite of modern tools, including Graphistry, IPython, and D3.js, for large-scale data visualization and analysis, advocating for a "human-computer symbiosis" to empower engineers in managing complex networks.