Established thought leaders with verified media credentials.
A podcast for learning about the latest cutting edge AI research.
Unknown Host hosts Artificially Speaking.
The provided text introduces Cognitive Architectures for Language Agents (CoALA), a theoretical framework designed to standardize the development of artificial intelligence systems that use large language models as their
Show notesSkillOpt is a novel optimization framework designed to improve the performance of AI agents by treating their skills as a trainable, external text document. Unlike traditional methods that rely on manual prompting or mod
Show notesThe document introduces Vending-Bench, a novel simulated environment designed to evaluate the long-term coherence of autonomous agents powered by Large Language Models (LLMs). The benchmark tasks agents with managing a v
Show notesThis research paper explores the capabilities of large language models (LLMs) in competitive programming. It compares the performance of OpenAI's o1 and o3 LLMs, highlighting the significant improvement in performance ac
Show notesThis research paper explores using executable Python code as actions for Large Language Model (LLM) agents. The authors introduce CodeAct, a framework enabling LLMs to generate and execute Python code, dynamically adapti
Show notesThis research paper investigates the effectiveness of ensembling different large language models (LLMs) to improve performance. The authors introduce Self-MoA, a method that aggregates multiple outputs from a single, top
Show notesThis technical report introduces the Qwen2.5-1M series of large language models, significantly enhancing long-context capabilities (up to 1 million tokens) through novel training and inference techniques. Key improvement
Show notesThe Paper details the development and capabilities of MiniMax-01, a series of large language models (LLMs) and vision-language models (VLMs). Key features include superior long-context processing (up to 4 million tokens)
Show notesThis research paper explores the development and evaluation of Process Reward Models (PRMs) for improving mathematical reasoning in Large Language Models (LLMs). The authors identify limitations in using Monte Carlo esti
Show notesThis research paper explores using generative AI, specifically ChatGPT, to automate Test-Driven Development (TDD). The authors propose two interaction patterns: a collaborative approach where developers and AI work toget
Show notesThe paper introduces rStar-Math, a novel method that significantly improves the mathematical reasoning capabilities of small language models (SLMs). It achieves this through a self-evolving process using Monte Carlo Tree
Show notesHumanity's Last Exam (HLE) is a new, extremely difficult, multi-modal benchmark designed to evaluate large language models (LLMs). Created by a global team of experts, HLE features 3,000 questions spanning numerous acade
Show notesResearchers from Mondragon University and the University of Seville conducted a pre-deployment safety evaluation of OpenAI’s o3-mini large language model (LLM). They used their tool, ASTRAL, to automatically generate 10,
Show notesThis technical report details the development and evaluation of Kimi k1.5, a multi-modal large language model (LLM) trained using reinforcement learning (RL). The researchers emphasize a novel approach focusing on long-c
Show notesA deep dive into the DeepSeek-R1: Reasoning via Reinforcement Learning research paper. DeepSeek-R1, a large language model enhanced for reasoning capabilities through reinforcement learning (RL). Two versions are describ
Show notesThis research paper introduces Titans, a novel family of neural architectures designed to improve long-term memory in sequence modeling. Titans incorporate a deep neural long-term memory module that learns to memorize hi
Show notesSponsor detection runs nightly. Check back soon.
No public pitch examples yet for this show.
Generate your own personalised pitchShows with the most semantically similar episode content. Pitch one, pitch all; producers cluster.
To pitch Artificially Speaking, visit https://podcasters.spotify.com/pod/show/henrymoran for contact information, then craft a tight one-paragraph hook that ties your expertise to a gap in their recent general coverage.
Artificially Speaking is hosted by Unknown Host. The show is categorised under General and has published 0 episodes.
Artificially Speaking is accessible for guests with genuine general expertise. A personalised, episode-aware pitch will still outperform a generic one every time.
Artificially Speaking 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 Artificially Speaking average 18 minutes. a focused format where a clear narrative arc and tight preparation matter most.
Our data rates Artificially Speaking'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 Probability™ 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.
