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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

The Rise of the Full-Stack Builder and Hyper-Leveraged Generalist with Microsoft CEO Satya Nadella

The Rise of the Full-Stack Builder and Hyper-Leveraged Generalist with Microsoft CEO Satya Nadella

Microsoft CEO Satya Nadella discusses the future of AI at Microsoft Build, emphasizing an ecosystem approach where every company can create its own "frontier intelligence." He highlights the critical role of private evaluations as a new form of intellectual property, the strategic use of multi-modal harnesses for enterprise, and how autonomous AI agents are reshaping software development and business models. Nadella also shares insights on the societal impact of AI, from data center investments to the potential for AI-driven transformation in education.

Benchmarking semantic code retrieval on Claude Code — Kuba Rogut, Turbopuffer

Benchmarking semantic code retrieval on Claude Code — Kuba Rogut, Turbopuffer

A detailed benchmark analysis comparing raw Claude Code's performance with windowed grep and Turbopuffer's semantic search for code retrieval in LLM agents. The study reveals significant improvements in file precision (65% to 87%) and reduced wasted reads (1 in 3 to 1 in 8) with semantic search, while highlighting the importance of the agent's understanding of when to use retrieval tools.

BDD, ADR, PRD, WTF: Capturing Decisions for Humans and AI Alike — Michal Cichra, Safe Intelligence

BDD, ADR, PRD, WTF: Capturing Decisions for Humans and AI Alike — Michal Cichra, Safe Intelligence

Michal Cichra from Safe Intelligence explains how to maintain consistency in AI-driven software development by capturing decisions and enforcing rules. He argues for reviving Behavior-Driven Development (BDD) with Cucumber to close the loop left by spec-driven development. The core idea is to enforce architectural and product decisions (ADRs, PRDs) through an automated loop of git hooks and CI, ensuring both human and AI developers adhere to established standards.

The Moonshot Mindset with Adam Savage and Sergey Brin: The Moonshot Podcast

The Moonshot Mindset with Adam Savage and Sergey Brin: The Moonshot Podcast

Astro Teller, Captain of Moonshots at X, and Google co-founder Sergey Brin discuss the philosophy of radical innovation, X's unique culture of embracing failure and pressure testing ideas, and their reflections on past moonshots like Google Glass, Wing, and Waymo. They delve into the exponential nature of AI, its historical context, and the challenges of anticipating its future impact, while also highlighting crucial unsolved "white whale" moonshots for humanity, including education, battery technology, and redefining the intrinsic value of work beyond monetary compensation.

Task Fidelity Scaling Laws — Kobie Crawdord, Snorkel

Task Fidelity Scaling Laws — Kobie Crawdord, Snorkel

An experiment by Snorkel AI reveals that in agentic AI training, the quality of tasks is paramount. Using the same model and compute, fine-tuning on high-quality tasks yielded a 6% performance improvement, a 5x greater uplift compared to the 1% gain from low-quality tasks. The key difference lies in the nature of the tasks: high-quality tasks are genuinely harder, featuring more tool calls and cleaner failure modes that provide a meaningful learning signal. In contrast, low-quality tasks often fail due to ambiguity and environmental noise, hindering effective model improvement.

GitHub’s Agent Era: 14x Commits, 200M Developers, Copilot’s Next Act — Kyle Daigle

GitHub’s Agent Era: 14x Commits, 200M Developers, Copilot’s Next Act — Kyle Daigle

GitHub COO Kyle Daigle discusses the new era of AI agents from the inside. He covers how he uses AI for leadership, the shift from "mega-skills" to "micro-skills," and how GitHub is navigating a 14x growth in commits. The conversation goes deep on the evolution of Copilot, the future of PRs in an agent-driven world, the challenges of scaling, and Microsoft's vision for an ambient AI operating system.

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