Jun 25, 2026

The Miranda Hypothesis: How Hamilton Poisoned Persona Evals - Jacob E. Thomas, Results Gen

This talk exposes "Miranda distortion," a critical flaw in AI personas where models, influenced by modern cultural narratives, produce convincing but anachronistic outputs. Current evaluations fail to detect this, prioritizing fluency over fidelity. The speaker proposes "epistemic simulation"—a new paradigm grounded in corpus-bounded, temporally-anchored, and expert-evaluated reasoning—and introduces the "Prism Experiment." This rigorous, pre-registered protocol uses Abraham Lincoln to demonstrate how a weighted rubric, created by historians and de-emphasizing rhetorical fluency, can detect anachronism. It advocates for the "humanist in the loop" as a technical requirement to ensure AI personas are true to their documentary records, not just convincing.

Jun 24, 2026

Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin

Dan Biderman and Jessy Lin of Engram introduce their "always training" paradigm, focusing on baking a team's knowledge directly into a model's weights to achieve true memory and continual learning. This contrarian approach, which they call a "RAG killer" for specific use cases, promises up to 100x token savings and superior performance by internalizing context rather than relying on ever-larger context windows or external retrieval, envisioning a future where everyone has their own continually learning, personalized AI model.

Jun 21, 2026

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

Ronuk Malde, CEO of Trajectory.ai, discusses his journey from building AI coding agents at Windsurf to his current focus on continual learning for enterprise AI. He shares insights on leveraging real-world user data, the unique challenges of model acquisition, and how Trajectory.ai's platform, powered by innovations like scaled SDPO and a novel training stack, enables dynamic, always-learning AI models for diverse industries from legal to finance.

Jun 21, 2026

6 Things to Know about AIE World's Fair 2026

Discover the AI Engineering World's Fair 2026, the largest iteration yet, offering an unparalleled deep dive into AI engineering with expanded tracks on auto research, GPU specialization, and new verticals like finance and healthcare. Highlights include an innovative expo experience, exclusive leadership initiatives like the "Token Billionaires Program," and unique side events fostering community, including "Posters on AI" where attendees can defend their tweets. This event is designed to be a curated hub for practical, cutting-edge insights and networking in the AI/ML professional landscape.

Jun 19, 2026

The data black hole at the center of AI

AI progress is fundamentally driven by vast amounts of data and compute, rather than improvements in sample efficiency, creating a stark contrast with human learning. This essay explores the "black hole of data" powering AIs, quantifies the massive sample-efficiency gap between humans and machines, counters common objections, and discusses the implications for white-collar automation and future AI research.

Jun 19, 2026

The Media Game Has Changed

The conversation explores the shift from legacy media to creator-led platforms, why authenticity has become a competitive advantage, and how founders can build audiences by communicating directly with customers, employees, and the public. They discuss podcasts, social media, storytelling, corporate communications, and the changing relationship between companies, journalists, and audiences. Along the way, they examine how founders can develop a public voice, why some leaders become influential communicators, and what it means to build a brand in a world where distribution is increasingly decentralized.