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Machine Learning

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Frontier results, on device - RL Nabors, Arize

Frontier results, on device - RL Nabors, Arize

RL Nabors discusses the significant costs associated with using frontier AI models, covering security, latency, and financial implications. She introduces a framework for right-sizing AI solutions by leveraging smaller, task-specific models and Small Language Models (SLMs). The framework details how to prove task feasibility, establish success criteria with golden datasets, conduct capability evaluations (using tools like Phoenix), and select the most appropriate "Small And Good Enough" (SAGE) model. Nabors further demonstrates how prompt engineering, particularly few-shot prompting, and post-processing can close performance gaps with larger models, while advocating for continuous regression evaluations to maintain performance integrity. The overarching message is to "prototype big, deploy small" to optimize AI deployments.

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Vaidas Razgaitis, Senior Research Engineer at Higharc, shares three tactical tips to accelerate the transition of novel AI/ML research into production-ready features. He emphasizes addressing the critical handoff challenge between ML researchers and software engineers through structured documentation (Research Prototype Taxonomy Document), a well-organized monorepo utilizing decoupled microservices, and a systematic approach to code decomposition and PR review. These strategies aim to improve legibility, maintainability, and delivery speed for ML-driven products.

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.

Artificial Intelligence

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The AI Agents Helping Home Services Book More Jobs

The AI Agents Helping Home Services Book More Jobs

Avoca (YC W23) has achieved eight-figure revenue and a $1 billion valuation by building an AI workforce for home services, turning missed calls into revenue. Founders Apurva Shrivastava and Tyson Chen explain how AI expands software's market share beyond 1% by automating labor and operational costs, leading to a 15x larger opportunity. They emphasize that their AI agents augment human workers, reducing attrition in challenging CSR roles and creating new positions for training AI, driven by a deep customer obsession learned at YC.

What Is AI Code Review? Fixing Slow PRs & Broken Workflows with AI

What Is AI Code Review? Fixing Slow PRs & Broken Workflows with AI

Anna Gutowska explains how AI code review enhances software development by addressing the slowness and inconsistency of traditional methods. The video delves into the benefits of AI in accelerating reviews, improving code quality, fostering developer learning, and reducing technical debt. It covers the underlying technologies like static/dynamic analysis and LLMs, discusses critical considerations such as over-reliance and context, and provides best practices for integrating AI while emphasizing the indispensable role of human oversight.

The Blueprint for Autonomous Work Agents | Gavriel Cohen, NanoClaw

The Blueprint for Autonomous Work Agents | Gavriel Cohen, NanoClaw

Kovid Goyal, founder of NanoClaw, discusses his journey from a serendipitous encounter with Singapore's Foreign Minister to evolving NanoClaw into an enterprise AI deployment company. He shares insights on personal vs. team-managed agents, the "second brain" as a killer use case, NanoClaw's security-first architecture, and the future challenges of managing open-source projects and enterprise AI deployments in an era of rapidly evolving agent technology.

Technology

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Platforms: Build Abstractions, not Illusions • Gregor Hohpe • GOTO 2025

Platforms: Build Abstractions, not Illusions • Gregor Hohpe • GOTO 2025

Gregor Hohpe explains the critical role of platforms in managing the growing cognitive load on developers due to complex distributed systems. He contrasts platforms, driven by "economies of speed" and fostering innovation through diversity, with traditional IT services and oversimplified abstractions that create dangerous illusions. Hohpe emphasizes building platforms that provide intuitive, domain-specific abstractions to solve real business problems, rather than just repackaging existing cloud services.

Full Stack Greenfield Projects : Are they still relevant?

Full Stack Greenfield Projects : Are they still relevant?

Bharat Goenka, co-founder of Tally, discusses the company's unconventional approach to software development through "Full Stack Greenfield" projects. He explains why building every component from scratch, despite being a high-risk strategy, has been crucial for Tally's success in serving the SMB market, fostering extreme customer loyalty, and aspiring to connect 200 million businesses. The talk delves into the historical context, the philosophy of questioning and choosing constraints, and the distinction between product and custom engineering.

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.


Recent Post

The $9B startup that wants to create a billion new developers

The $9B startup that wants to create a billion new developers

Replit co-founder and CEO Amjad Masad discusses the company's 10-year journey from a browser IDE to an AI-native "vibe coding" platform, empowering non-technical domain experts to build and deploy real software, and what the future holds with parallel agents and a post-prompting world.

[FULL WORKSHOP] AI Coding For Real Engineers - Matt Pocock, AI Hero (@mattpocockuk )

[FULL WORKSHOP] AI Coding For Real Engineers - Matt Pocock, AI Hero (@mattpocockuk )

A workshop on building a complete AI-assisted development workflow, covering how to translate ambiguous requirements into agent-ready plans and run autonomous coding agents to ship production-ready features.

What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench

What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench

Despite benchmarks showing relentless progress, many users remain dissatisfied with LLM responses in real-world scenarios. This summary explores two key analyses—a custom 'nonsense question' benchmark and trends from Chatbot Arena's 'dislike both' data—to reveal the persistent gaps in model reasoning, reliability, and domain-specific understanding.

How To Build A Company With AI From The Ground Up

How To Build A Company With AI From The Ground Up

Y Combinator Partner Diana Hu explains how to build an AI-native company where AI is the core operating system, not just a tool. She covers how to make a company queryable, the impact on team structures, and why startups have a massive edge in this new paradigm.

Tech Truth: Teaching Kids to Code with Sonic Pi • Sam Aaron & James Lewis • GOTO 2025

Tech Truth: Teaching Kids to Code with Sonic Pi • Sam Aaron & James Lewis • GOTO 2025

A deep dive with Sam Aaron, the creator of Sonic Pi, exploring his journey from early programming on a ZX Spectrum to creating a global platform for code-based music. The conversation covers the technical architecture of Sonic Pi, the critical role of Erlang's BEAM for concurrency, and the future direction with his new project, Tau5, which leverages AI for development and security testing.

Building Hardware is Hard but AI Agents Help, with Kishore Subramanian

Building Hardware is Hard but AI Agents Help, with Kishore Subramanian

Kishore Subramanian, CTO of Propel Software, discusses how AI is revolutionizing physical product development. He explains how Propel's AI platform, built on Salesforce's Agentforce 360, uses agentic AI to "shift left" quality control, reviewing engineering changes to prevent costly downstream errors in hardware, high-tech, and med-tech manufacturing. The conversation also covers best practices for deploying enterprise-grade AI agents and the surprising benefits of yoga and meditation for creative problem-solving in tech.

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