Posts

How I became a StoryTeller (and how YOU can too)

How I became a StoryTeller (and how YOU can too)

Distinguished Scientist Sumit Gulwani shares his personal journey from a skeptical researcher to a passionate advocate for storytelling, revealing how narratives built on human connection are more powerful than statistics. He breaks down the science behind why stories work and provides a toolkit of practical techniques—from crafting a strong start to knowing your audience—to help technical professionals transform their communication, research, and even their lives.

Make some noise: Teaching the language of audio to an LLM using sound tokens

Make some noise: Teaching the language of audio to an LLM using sound tokens

Shivam Mehta from KTH presents a method for teaching Large Language Models (LLMs) to understand and generate audio by treating it as a discrete language. The approach involves a two-step process: first, creating an ultra-low bitrate (0.293 kbps) audio representation using a causal variational autoencoder, and second, fine-tuning a Llama 7B model with these audio tokens using LoRA.

Building Better Language Models Through Global Understanding

Building Better Language Models Through Global Understanding

Dr. Mazi Fadai discusses the critical challenges in multilingual AI, including data imbalances and flawed evaluation methodologies. She argues that tackling these difficult multilingual problems is not only essential for global accessibility but also a catalyst for fundamental AI innovation, much like how machine translation research led to the Transformer architecture. The talk introduces new, more culturally aware evaluation benchmarks like Global MMLU and INCLUDE as a path toward building more robust and globally representative language models.

Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Preeti Somal from Temporal explains that as AI agents move to production, they face significant reliability and scalability challenges. She introduces Temporal as a platform to abstract away this complexity, allowing developers to build robust, stateful AI agents by focusing on business logic instead of infrastructure plumbing like retries and error handling.

Balaji Srinivasan: How AI Will Change Politics, War, and Money

Balaji Srinivasan: How AI Will Change Politics, War, and Money

Technologist Balaji Srinivasan joins a16z's Erik Torenberg and Martin Casado to discuss the limitations and societal impact of AI, framing the conversation around the concept of "Polytheistic AGI"—multiple, culturally-specific AIs—versus a singular, god-like intelligence. They explore the practical system-level constraints on AI, its surprising evolution, the critical role of cryptography in grounding AI in reality, and the future of work and security in an AI-driven world.

Scale, Flow & Microservices • James Lewis • YOW! 2019

Scale, Flow & Microservices • James Lewis • YOW! 2019

Drawing on research from complexity science, this presentation explores why organizations slow down as they grow and how architectural and organizational patterns, like those in microservices and at Amazon, can create superlinear scaling. It explains that by fostering networked structures over rigid hierarchies, companies can mimic the innovative and resilient properties of cities.