Hosted by hogarthian.art · 🇺🇸 US · EN · 29 episodes
Established thought leaders with verified media credentials.
Dive deep into the exciting realm of Generative AI without the jargon! 🚀 Here, we transform the latest GenAI technologies – sourced from pioneering research papers and top blogs – into easy-to-follow podcast discussions. Join our community of AI enthusiasts, learn something new every week, and become a GenAI expert with us!
hogarthian.art hosts GenAI Learner, a technology show with 29 episodes published.
Tired of wasted compute? UC Berkeley is addressing the inefficiencies of exclusive GPU access by proposing a unified resource management layer to enable multitasking, potentially reclaiming the 90% of resources often lef
Scaling large AI models to meet dynamic traffic is slow and leads to significant resource waste. Researchers at Microsoft Azure Research and Rice University are rethinking this process, finding that scaling the entire mo
Researchers at MIT and Harvard argue that true intelligence requires constructing internal world models, proposing a generative game benchmark to prove if AI can adapt to unseen environments without millions of training
The Surprising Limits of RL in LLM Reasoning Arxiv: https://arxiv.org/pdf/2504.13837The promise of RL for LLM growth hits a wall: Tsinghua University's study shows RLVR only improves efficiency but is bounded by and does
Research from Samsung SAIL Montréal introduces the Tiny Recursive Model (TRM), which uses a single, 2-layer network to outperform massive LLMs on tough puzzles like ARC-AGI. Arxiv: https://arxiv.org/pdf/2510.04871 Hear t
Ensemble LLMs: The Power of Multiple AI Minds Arxiv: https://arxiv.org/pdf/2502.18036 The LLM Commitee: Why 182,000 AI Models Aren't Enough and How Ensembles Beat the Single Perfect Oracle? Why rely on one LLM when you c
Cloud wars over custom hardware? Perplexity AI solved it. Discover the TransferEngine provides a portable, vendor-agnostic RDMA point-to-point communication interface for LLM systems, avoiding hardware lock-in with a sim
Straight from KAIST, the revolutionary PaperCoder automates functional code generation from raw machine learning papers, and the "GenAI learner" podcast breaks down this multi-agent LLM framework simply. Arxiv: https://a
How to Learn Games in Minutes (No NNs!) Researchers at VERSES AI built a new AI agent that masters games in minutes without using neural networks or gradient optimization. Arxiv: https://arxiv.org/abs/2505.24784 The GenA
Researchers at Meta just taught LLMs to reason without language, letting them explore multiple paths simultaneously. Arxiv: https://arxiv.org/abs/2412.06769v1 The GenAI Learner podcast breaks down how this "COCONUT" meth
A new system from Microsoft Research shows how EvoTest evolves an agent's entire configuration using narrative transcript analysis, outperforming gradient-based and reflection methods. Arxiv: https://arxiv.org/pdf/2510.1
An individual's DreamCoder-inspired method proved to be the most performance-cost efficient approach to the complex ARC-AGI Prize challenge. Original Article: https://substack.com/home/post/p-172998849 Understand the det
Jeremy Berman's Substack reveals a state-of-the-art 79.6% ARC-AGI score by using an evolutionary process that refines plain English instructions instead of code—tune into GenAI learner for a simple breakdown. https://jer
Hear how Anthropic's Sonnet 3.5 smashed the ARC-AGI record by using Evolutionary Test-time Compute to overcome generalization limits. Substack: https://jeremyberman.substack.com/p/how-i-got-a-record-536-on-arc-agi Get th
Google, Inc.'s François Chollet argues that we should stop measuring AI's performance and start measuring intelligence as the efficiency of skill acquisition over a range of tasks, accounting for priors and experience. A
The ARC Prize Foundation just dropped ARC-AGI-2, a new, harder AI benchmark designed to assess general fluid intelligence at higher cognitive complexity levels. Arxiv: https://arxiv.org/abs/2505.11831 Tune into GenAI lea
ARC Prize 2024 revealed that Test-Time Training (TTT) and program synthesis drove the state-of-the-art ARC-AGI score from 33% to 55.5%. Arxiv: https://arxiv.org/abs/2412.04604 Tune into GenAI Learner for a simple, non-te
Researchers from Tencent and Renmin University of China discovered the reasoning reward equals a last-token self-rewarding score, a game-changer for efficient LLM verification—get the simple breakdown on GenAI Learner. A
Wonder why LLMs struggle with multi-step logic? A new paper from MBZUAI shows the Fano-style accuracy upper bound proves single-pass LLM reasoning collapses when task complexity exceeds output capacity. Arxiv: https://ar
Engineers from ByteDance and Carnegie Mellon University just scaled LLM agents 10x with Context-Folding, a method that summarizes complex sub-tasks to manage memory. Arxiv: https://arxiv.org/abs/2510.11967 Get the simple
Sponsor detection runs nightly. Check back soon.
No public pitch examples yet for this show.
Generate your own personalised pitchBased on semantic analysis of episode topics and host coverage, this show is a strong guest fit for executives in:
Industry fit is computed by PitchCentric using vector embeddings of the show's episode catalog.
Shows with the most semantically similar episode content. Pitch one, pitch all; producers cluster.
To pitch GenAI Learner, visit https://genai-learner.podbean.com for contact information, then craft a tight one-paragraph hook that ties your expertise to a gap in their recent technology coverage.
GenAI Learner is hosted by hogarthian.art. The show is categorised under technology and has published 29 episodes.
GenAI Learner has published 29 episodes.
GenAI Learner regularly covers technology. It sits in the technology category.
GenAI Learner is accessible for guests with genuine technology expertise. A personalised, episode-aware pitch will still outperform a generic one every time.
GenAI Learner hasn't explicitly signalled guest openness in recent episodes. That doesn't rule out pitching. your hook just needs to be especially compelling and relevant to their recent content.
Episodes of GenAI Learner average 17 minutes. a focused format where a clear narrative arc and tight preparation matter most.
Our data rates GenAI Learner's guest bar at 80/100 (Premium tier). Established thought leaders with verified media credentials. Sign in to PitchCentric to see how your own Pod Score compares against this show.
Methodology. Booking Probabilityâ„¢ blends Listen Score, 30-day Virality, open-to-guests detection, and Apple ratings. Data refreshed every 60 minutes. Listen Score and Booking Probability are calculated by PitchCentric. Last enriched today.
