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

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Machine Learning

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Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

This session details a data-efficient method for training engineering surrogate models by using uncertainty quantification (UQ) to guide geometric data augmentation. Instead of random deformations, the approach lets the deep ensemble model identify its own knowledge gaps (epistemic uncertainty), then uses Free-Form Deformation (FFD) to generate new shapes specifically in those uncertain regions. This ensures every expensive simulation run yields maximally informative data, significantly improving model accuracy for a fixed computational budget across domains like structural mechanics and aerodynamics.

Q-learning with Flow-Matching Policies

Q-learning with Flow-Matching Policies

This talk explores methods for optimizing expressive, multi-modal policies, such as those based on flow-matching, with off-policy reinforcement learning. The speaker presents two novel algorithms, FQ-RL and CAM, designed to overcome the instability of backpropagation through multi-step generative models, enabling effective online self-improvement and adaptation for robotic manipulation tasks.

Graph Neural Networks Explained: A Clear Guide to GNN Basics & Models

Graph Neural Networks Explained: A Clear Guide to GNN Basics & Models

An introduction to Graph Neural Networks (GNNs), covering fundamental concepts like nodes, edges, and embeddings. This post delves into the core message-passing mechanism and provides a detailed overview of key architectures including GCN, GraphSAGE, GAT, GIN, and Graph Transformers, explaining their unique approaches and mathematical formulations.

Artificial Intelligence

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

⚡️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.

6 Things to Know about AIE World's Fair 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.

The data black hole at the center of AI

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.

Technology

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3‑2‑1 Backup Rule Explained: Protect Your Data from Disaster

3‑2‑1 Backup Rule Explained: Protect Your Data from Disaster

Jeff Crume outlines essential data resiliency strategies, starting with the 3-2-1 backup rule—three copies, two media types, one offsite—and expanding to include immutable or air-gapped backups, rigorous testing, and encryption. He emphasizes these principles for robust disaster recovery, ransomware protection, and minimizing costly downtime, highlighting the trade-offs in achieving high availability.

The Media Game Has Changed

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.

The C4 Model: Visualizing Software Architecture • Simon Brown & Susanne Kaiser • GOTO 2026

The C4 Model: Visualizing Software Architecture • Simon Brown & Susanne Kaiser • GOTO 2026

Simon Brown, creator of the C4 Model, discusses its origin as a practical solution to clarify messy software diagrams. He explains the four hierarchical levels (context, container, component, code), emphasizing that most teams only need the top two for significant value. The discussion highlights the importance of including technology in diagrams, C4's collaborative nature, and practical advice on modeling microservices and bounded contexts, all while advocating for a lightweight, accessible approach to architectural visualization.

Recent Post

He's Building an AI That Can't Lie | Dan Klein, Scaled Cognition

He's Building an AI That Can't Lie | Dan Klein, Scaled Cognition

Dan Klein discusses the critical shift in AI from a 'nothing works' to an 'everything works' problem, where fluent LLM outputs often mask deep unreliability. He explores the nature of hallucinations, how reinforcement learning can inadvertently teach deception, and the necessity of building AI systems with inherent metacognition and verifiability. Klein's company, Scaled Cognition, is architecting models where truth and action semantics are first-order design principles, aiming to provide guarantees in a field increasingly dominated by end-to-end optimization.

The State of Frontier Post-Training Recipes | Conversation with Finbarr Timbers

The State of Frontier Post-Training Recipes | Conversation with Finbarr Timbers

This discussion with Finbarr Timbers reviews the evolution of frontier post-training recipes, highlighting the shift from simpler SFT-DPO-RL to complex multi-teacher on-policy distillation (MOPD). It covers the organizational challenges of building models like Olmo, the rise of synthetic data and reasoning-focused RL in DeepSeek, and the complexities of integrating expert teachers, while also exploring open questions on environments, specialized APIs, and career strategies in the rapidly changing AI landscape.

You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

Ziv Ilan from NVIDIA details how latency in video diffusion models can be drastically reduced to achieve real-time generation. He presents a layered approach combining dynamic quantization for memory and speed, chunk-based caching to skip redundant denoising computations, and, most critically, step distillation—training models to achieve high-quality output in significantly fewer steps. These techniques, packaged in the open-source FastGen repository, offer additive performance gains, enabling real-time video on a single Blackwell B200 GPU.

Simulating Humans at Scale: Simile's Joon Sung Park

Simulating Humans at Scale: Simile's Joon Sung Park

Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agents study, explains how Simile is building the "GPU of intelligence" to simulate human society, diverging from frontier models that act as the "CPU of intelligence." He details Simile's approach of grounding simulations with real human behavioral data, its diverse corporate applications, and its long-term vision to create a "CERN of human society" to solve fundamental societal challenges.

Context Engineering for Coding Agents

Context Engineering for Coding Agents

A deep dive into advanced engineering techniques for coding agents, focusing on effective context management in LLMs like Claude. The talk introduces a practical framework using a brain-inspired analogy, proposing a Markdown-based 'wiki' as a long-term memory system to augment the agent's limited context window. This approach is demonstrated through a real-world challenge of extracting structured data from technical drawings.

Cloud, Containers & Security • Adrian Mouat, Kief Morris & Sam Newman • GOTO 2025

Cloud, Containers & Security • Adrian Mouat, Kief Morris & Sam Newman • GOTO 2025

In this panel discussion, experts Adrian Mouat, Kief Morris, and Sam Newman delve into the current landscape of cloud technology, container security, and infrastructure automation. They cover key topics such as supply chain security with Sigstore and SBOMs, the practical impact of AI on deterministic systems, the ongoing debate about cloud repatriation, and advanced Infrastructure as Code practices like TDD and managing configuration drift.

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