Interview based show around AI Engineering. Episodes are also available as video on Youtube. Show notes have a summary and full transcript.
Episodes
25 Feb 2026
Physicists, machine learning experts, and materials scientists explore the intersection of their fields to accelerate material discovery and tackle challenges like climate change.
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24 Feb 2026
The limitations of AI's current capabilities are discussed, highlighting the need for meta-learning to improve it and achieve true effectiveness.
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23 Feb 2026
C-bench Verified, a coding benchmark, has faced challenges such as task saturation, biased tasks, and overlapping training data, prompting the need for more advanced alternatives and a reevaluation of broader issues in AI coding evaluation.
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19 Feb 2026
The podcast explores current shifts in AI investment dynamics, including emerging financing models and infrastructure development.
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12 Feb 2026
The discussion highlights the need to balance the development of highly capable AI models with efficient and cost-effective alternatives, emphasizing strategies for optimization and deployment.
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12 Feb 2026
Machine learning-based methods have revolutionized protein structure prediction and interaction modeling, with significant advancements in single-chain and multi-chain predictions, and efforts underway to replicate and improve these capabilities.
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28 Jan 2026
Molecular Dynamics and AI in protein research are contrasted, highlighting the former's limitations and the latter's efficiency and accuracy, with the goal of improving simulations and hypothesis generation.
Open episode23 Jan 2026
Researchers discuss AI advancements in areas such as spreadsheet automation, reinforcement learning, and large language models.
Open episode17 Jan 2026
Brex's AI strategy is structured around three pillars, aiming to improve internal processes, reduce costs, and integrate with customer AI strategies through operations, products, and corporate AI initiatives.
Open episode9 Jan 2026
Artificial Analysis, an independent AI benchmarking platform, provides standardized evaluations and reports to address the lack of comprehensive and impartial AI benchmarks.
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