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The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

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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 Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

Ted Johnson argues that current AI interfaces, particularly prompting, operate on an outdated "batch processing" protocol akin to punch cards. Despite advanced LLM capabilities, this interface design forces humans to adapt to machines, hindering natural interaction. He advocates for a shift towards human-compatible interfaces where AI actively participates in real-time conversation, leveraging its intelligence to remove user burdens and amplify human potential.

How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor

How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor

Valar Atomics founder Isaiah Taylor discusses how his company is rapidly advancing nuclear energy through hardware iteration, manufacturing, and a unique regulatory pathway. He explains their intrinsic safety philosophy, the strategic importance of vertical integration for speed and cost reduction, and their venture-backed approach to building gigasites. Taylor highlights how the demand for AI compute is a major driver for nuclear, showcasing their direct powering of an NVIDIA Blackwell chip, and casts a compelling vision for a future of "hyper-technoindustrialism" enabled by abundant, cheap atomic energy.

The Platform Engineer’s Handbook • Ajay Chankramath & Kaspar von Grünberg • GOTO 2026

The Platform Engineer’s Handbook • Ajay Chankramath & Kaspar von Grünberg • GOTO 2026

This conversation with Ajay Chankramath, author of 'The Platform Engineer’s Handbook,' delves into why practical, code-first guidance is essential for building Internal Developer Platforms. He argues that developer adoption failures stem from a "product discipline gap," not a technology one, emphasizing developer experience as a first-class outcome. The discussion covers the book's arc from foundations to enterprise-grade features and its focus on 100% open-source, vendor-agnostic tooling. Crucially, it highlights how agentic AI raises the stakes for platform engineering, requiring new IDP layers for agent context, memory, and guardrails, asserting that these must be built, owned, and operated internally for safe and productive AI adoption.

Technology

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Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Trisha Gee delivers a compelling talk on Developer Productivity Engineering (DPE) for testing, dissecting common pain points in writing, troubleshooting, and running tests. She advocates for strategic use of IDEs, advanced tooling like build caches and predictive test selection (leveraging ML), and a disciplined approach to test design to overcome these challenges, emphasizing that good tests serve as crucial living documentation.

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

This episode delves into Q-Day, the anticipated future when quantum computers can break public key cryptography, and the U.S. Executive Order accelerating the transition to post-quantum cryptography. Experts discuss why Q-Day is a gradual process rather than a sudden event, the critical importance of "crypto-agility" as a long-term strategy, and the necessity for organizations to begin immediate discovery and planning to secure data against "collect now, decrypt later" threats. The discussion also touches upon the broader, transformative benefits of quantum computing beyond just security.

Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Jim Kleewein's talk outlines the immense challenges and critical research opportunities in building and operating global hyperscale services like Microsoft 365 and Azure. He emphasizes that at this scale, traditional approaches fail, necessitating a "new golden age of applied research" across areas like continuous availability, data management, security, and sustainability. Kleewein also discusses AI's powerful but limited role, stressing the ongoing need for human expertise, and highlights the ethical imperative to prevent failures that can have life-or-death consequences.

Recent Post

Moonshot Podcast Deep Dive: Emily Ma on Solving Food Waste

Moonshot Podcast Deep Dive: Emily Ma on Solving Food Waste

In a discussion with Astro Teller, Emily Ma from X (formerly Google X) delves into the multifaceted problem of food waste and the moonshot projects developed to tackle it. They explore Project Delta, an initiative that created an "air traffic control" system for surplus food, and Project Chorus, a broader supply chain moonshot designed to give every object a voice through advanced sensors and software.

Ben Horowitz on Investing in AI: AI Bubbles, Economic Impact, and VC Acceleration

Ben Horowitz on Investing in AI: AI Bubbles, Economic Impact, and VC Acceleration

Ben Horowitz of Andreessen Horowitz discusses how AI is reshaping venture capital, detailing the firm's strategy for managing partners, verticalizing teams, and evaluating investments in real-time. He breaks down the current AI cycle, arguing that application design and model orchestration are key, and explains why the current market's growth is driven by real demand, not just hype.

957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva

957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva

Ashwin Rajeeva, cofounder and CTO of Acceldata, details the architecture and philosophy behind their Agentic Data Management (ADM) platform. He explains how the Xlake reasoning engine provides crucial context for AI agents to operate across petabyte-scale enterprise data, enabling capabilities like self-healing data pipelines and automated data quality assurance, while also discussing strategies for leading technical teams in the age of AI.

AI on campus

AI on campus

A panel of university students from LSE, Princeton, Berkeley, and ASU discuss the real-world impact of AI on campus life. They cover how AI is used as both a powerful learning tool and a crutch, the innovative projects students are building, how universities are adapting, and the challenges of navigating cheating, job applications, and 'AI slop' in a rapidly changing educational landscape.

OpenAI + @Temporalio : Building Durable, Production Ready Agents - Cornelia Davis, Temporal

OpenAI + @Temporalio : Building Durable, Production Ready Agents - Cornelia Davis, Temporal

Explore how Temporal, a durable execution framework, brings resilience and scalability to AI agents built with the OpenAI Agents SDK. This summary covers Temporal's core concepts of Workflows and Activities, the official integration that makes OpenAI agents durable, and patterns for orchestrating multiple micro-agents.

Introducing Our Approach to Design Document Review Using Business-Specific Large Language Models

Introducing Our Approach to Design Document Review Using Business-Specific Large Language Models

Hitachi's Financial Business Unit developed a specialized LLM to automate the review of system design documents, addressing the inadequacy of general-purpose AI for mission-critical systems. This presentation details the model's development using Continued Pre-training and LoRA on proprietary data, its integration into a multi-agent architecture, and the use of Weights & Biases for MLOps, which led to a 70% reduction in manual review workload.

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