Hosted by absorb.md · 🇺🇸 US · EN · 37 episodes
Established thought leaders with verified media credentials.
Every day, two AI hosts discuss what the smartest people in AI are actually saying. Compiled from 500+ posts, podcasts, and papers per day across 2050 tracked thinkers. Two 7-minute briefings per topic family (AM and PM). Built by @vgurbuxani as a tool to see the real conversation without the noise.
absorb.md hosts absorb.md daily, a technology show with 37 episodes published.
Three researchers posted on medical LLMs, dexterous robots and vehicle attacks this window. In this episode: • Medical LLM Gaps in Patient Concerns • Sim-to-Real Piano Mastery • Stealth Attacks on Autonomous Vehicle Plat
Show notesThis morning we flagged Foundational Tools and Efficient Kernels. Here's how it resolved. In this episode: • LLM Kernel Optimizations • Agent Brains and Modular Skills • RL Simulations and Online Learning Sources cited:
Show notesKarpathy says LLM knowledge bases are a new primitive impossible with old code. In this episode: • LLM Knowledge Bases as New Primitive • Egocentric Data Quality for Physical AI • AI Craftsmanship in Frontier Labs • Foun
Show notesFive new AI papers all got hit with the same counter this week. In this episode: • Adaptive RAG Defenses • Calibration-Free Robot Manipulation • Regional Fine-Tuning for African Languages • Scalable MARL Communication vi
Show notesThis morning we flagged Developer Code Pushes and Open Source Stars. Here's how it resolved. In this episode: • DiLoCo Real-World Resilience • Self-Reviewing Agent Architectures • Builders' GitHub Priorities Sources cite
Show notesMultiple new AI papers just got called out for imprecise claims on model sizes. In this episode: • Gemma 3 claim precision • Multimodal context unrolling • Regional African language models • Builder GitHub priorities Sou
Show notes
Non-engineers building working apps in 10 minutes. In this episode: • Non-Engineer Prototyping Reality • Kimi 2.6 Long Traces Debate • Agent and Kernel Infrastructure Bets Sources cited: 6 thinkers.
Show notesKimi 2.6 dropped a 74-page thinking trace. In this episode: • Kimi 2.6 Long Traces Debate • Agent Systems Quarterly Rebuilds • LLMs as Petabyte-Scale Compressors • Generational Shift in AI Definition Sources cited: 6 thi
Show notesParseBench says even top models still hallucinate on charts and tables. In this episode: • ParseBench for Agent-Ready Document Parsing • PM Renaissance or Cull (continuing from 2026-04-22: builder vs exhaustion dynamic)
Show notesOpenAI's new model targets ten to fifteen year drug timelines. In this episode: • Rosalind Compresses Drug Discovery Timelines • Grok Photorealism Claims Face Pushback • Parcae Enables Stable Looped Transformers • Subage
Show notesAI agents improved kissing number from 593 to 604. Breakthrough or just a nudge? In this episode: • Agent math hype vs reality • PM jobs halved by AI • Looped models cut params • Robot vision in workshops Sources cited:
Show notesThis morning we flagged Gemini robotics perception. Skepticism on missing metrics has sharpened. In this episode: • Gemini Robotics Claims Lack Hard Metrics • AI Agents Improve Kissing Number Bounds • Agent Architectures
Show notesThis morning we flagged Marvel Talent Exodus for AI Character Startups. Here's how it resolved. In this episode: • AI Job Acceleration vs Jobpocalypse Fears • Claude Automates Alignment Research (continuing from 2026-04-
Show notesJPMorgan says Anthropic's most aligned model is its biggest risk. In this episode: • Mythos AI Alignment Paradox • Process Supervision for LLM Reasoning • Unified Robotics Learning Platforms Sources cited: 5 thinkers.
Show notes
Neven's team dropped three quantum papers this week. In this episode: • Real-time quantum decoders and ergodicity edge • Personal agent architectures • Explanatory visualization and diffusion tooling • Production dev too
Show notes
This morning we flagged Concentration of Funding in Agentic Startups. Here's how it resolved. In this episode: • Agent Memory in 6 Lines of Code • AI Development Automation Tools • Research Data Extraction Pipelines Sour
Show notes
Universal atomic model drops alongside three agent-kernel pushes in minutes. In this episode: • Universal Atomic Models for Materials Discovery • Agent Kernel and Evaluation Infrastructure • NISQ Quantum Tooling for AI R
Show notes
Meta dropped three AI research releases at once. In this episode: • Meta's Simulation Surge for Robots, Brains, and Molecules • LLM Representations Converging with Human Brain Processing • Automation Eliminating Time Tra
Show notes
This morning we flagged Personal Superintelligence Democratization. Here's how it resolved. In this episode: • LLM Emergent Behavior and Risks • Visual AI Agent Builders • Multi-Language LLM Coding Experiments Sources ci
Show notes
Anthropic's most aligned model may be its most deceptive. In this episode: • CoT Deception Tradeoff • Scientific Acceleration Limits • Open Production Bridge • Personal Superintelligence Democratization Sources cited: 8
Show notesSponsor 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.
absorb.md daily has a verified contact on file. Create a free PitchCentric account to access it and generate a personalised pitch in seconds. Research at least 3 recent episodes first and lead with a specific angle that serves their technology audience.
absorb.md daily is hosted by absorb.md. The show is categorised under technology (news) and has published 37 episodes.
absorb.md daily has published 37 episodes.
absorb.md daily regularly covers technology, news. It sits in the technology category, with a news focus.
absorb.md daily is accessible for guests with genuine technology expertise. A personalised, episode-aware pitch will still outperform a generic one every time.
absorb.md daily 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 absorb.md daily average 5 minutes. a focused format where a clear narrative arc and tight preparation matter most.
Our data rates absorb.md daily'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. Last enriched 12 days ago.
