Insights from recent episode analysis
Audience Interest
Podcast Focus
Publishing Consistency
Platform Reach
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
Brands & references
Total monthly reach
Estimated from 20 chart positions in 20 markets.
By chart position
- 🇬🇧GB · Mathematics#28100K to 300K
- 🇨🇦CA · Mathematics#30100K to 300K
- 🇩🇪DE · Mathematics#46100K to 300K
- 🇺🇸US · Mathematics#50100K to 300K
- 🇦🇺AU · Mathematics#6230K to 100K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
550K to 1.7M🎙 Weekly cadence·60 episodes·Last published 4mo ago - Monthly Reach
Unique listeners across all episodes (30 days)
1.1M to 3.4M🇬🇧9%🇨🇦9%🇩🇪9%+17 more - Active Followers
Loyal subscribers who consistently listen
330K to 1.0M
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
—
Total Plays
—
Total Reviews
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
From 10 epsHosts
Recent guests
Recent episodes
CUGA Agent: From Benchmarks to Business Impact of IBM's Generalist Agent
Feb 11, 2026
23m 04s
TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture
Nov 24, 2025
23m 44s
Meta AI Researcher Explains ARE and Gaia2: Scaling Up Agent Environments and Evaluations
Nov 10, 2025
22m 34s
Georgia Tech's Santosh Vempala Explains Why Language Models Hallucinate, His Research With OpenAI
Oct 14, 2025
31m 24s
Atropos Health’s Arjun Mukerji, PhD, Explains RWESummary: A Framework and Test for Choosing LLMs to Summarize Real-World Evidence (RWE) Studies
Sep 22, 2025
26m 22s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 2/11/26 | CUGA Agent: From Benchmarks to Business Impact of IBM's Generalist Agent✨ | IBMGeneralist Agent+4 | — | Computer Using Generalist Agent (CUGA)IBM+1 | — | IBMCUGA+5 | — | 23m 04s | |
| 11/24/25 | TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture✨ | multi-agent systemstool-use strategies+3 | Yongchao Chen | GoogleArize AI | — | TUMIXmulti-agent+3 | — | 23m 44s | |
| 11/10/25 | Meta AI Researcher Explains ARE and Gaia2: Scaling Up Agent Environments and Evaluations✨ | AI observabilityagent environments+4 | Grégoire Mialon | AREGaia2+2 | — | AIMeta AI+5 | — | 22m 34s | |
| 10/14/25 | Georgia Tech's Santosh Vempala Explains Why Language Models Hallucinate, His Research With OpenAI✨ | language modelsAI research+3 | Santosh Vempala | Georgia TechOpenAI | — | language modelshallucination+3 | — | 31m 24s | |
| 9/22/25 | Atropos Health’s Arjun Mukerji, PhD, Explains RWESummary: A Framework and Test for Choosing LLMs to Summarize Real-World Evidence (RWE) Studies✨ | large language modelsreal-world evidence+3 | Arjun Mukerji | RWESummaryAtropos Health | — | large language modelsRWESummary+3 | — | 26m 22s | |
| 9/6/25 | Stan Miasnikov, Distinguished Engineer, AI/ML Architecture, Consumer Experience at Verizon Walks Us Through His New Paper✨ | AIMachine Learning+4 | Stan Miasnikov | VerizonCategory-Theoretic Analysis of Inter-Agent Communication and Mutual Understanding Metric in Recursive Consciousness | — | AIMachine Learning+5 | — | 48m 11s | |
| 9/5/25 | Small Language Models are the Future of Agentic AI✨ | agentic AIsmall language models+3 | Peter Belcak | NVIDIASmall Language Models are the Future of Agentic AI | — | small language modelsagentic systems+3 | — | 31m 15s | |
| 7/30/25 | Watermarking for LLMs and Image Models✨ | watermarkinglarge language models+3 | John Kirchenbauer | Arize AIA Watermark for Large Language Models | — | watermarkinglarge language models+3 | — | 42m 56s | |
| 7/8/25 | Self-Adapting Language Models: Paper Authors Discuss Implications✨ | language modelsself-adaptation+3 | — | Arize AISelf-Adapting Language Models | — | self-adapting language modelsLLMs+3 | — | 31m 26s | |
| 6/20/25 | The Illusion of Thinking: What the Apple AI Paper Says About LLM Reasoning✨ | AILarge Reasoning Models+4 | — | Apple | — | Apple AILLM reasoning+5 | — | 30m 35s |
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Chart Positions
20 placements across 20 markets.
Chart Positions
20 placements across 20 markets.