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a16z Goes Global: Why American Tech Must Lead the World

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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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a16z Goes Global: Why American Tech Must Lead the World

a16z Goes Global: Why American Tech Must Lead the World

This discussion explores a16z's expanding international strategy, emphasizing technology's pivotal role in economic growth and national security. The panel delves into why America's tech leadership is crucial globally, how AI is redefining government-private sector relationships, and the drive for countries to adopt frontier technologies while building local innovation ecosystems. Key topics include AI infrastructure, cybersecurity, defense tech, global startup expansion, and the elements of enduring tech ecosystems, highlighting trusted partnerships and the importance of Western technology.

GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

OpenAI's new GPT-5.6 Sol model sparks debate on AI safety and release strategies, while Wall Street expresses growing skepticism over the long-term economics of frontier AI models. The discussion also touches on AI's impact on the FIFA World Cup and a thought-provoking paper comparing LLM anthropomorphism to Age of Empires II "goats."

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.

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

RevenueCat: Powering Subscriptions for the App Economy

RevenueCat: Powering Subscriptions for the App Economy

In a YC interview, RevenueCat co-founders Jacob Eiting and Miguel Carranza discuss their journey from experiencing the pain of in-app purchases to building a critical piece of infrastructure for the mobile economy. They cover their early-stage conviction, the keys to selling to developers, and the operational and personal lessons learned while scaling to a globally distributed team.

The Future of Serverless • Nick Coult • GOTO 2025

The Future of Serverless • Nick Coult • GOTO 2025

Nick Coult from AWS explains that the future of serverless is not a replacement but an essential foundation for the rise of AI agents. This talk explores the core benefits of serverless, its synergy with event-driven architectures, and how agentic AI and agentic workflows will rely on serverless principles to scale and operate effectively.

How to scam an AI agent, DDoS attack trends and busting cybersecurity myths

How to scam an AI agent, DDoS attack trends and busting cybersecurity myths

A discussion on novel methods for hijacking AI agents through social engineering, the evolution of DDoS attacks, the legacy of Zero Trust, and the glaring security flaws in AI training data apps.

Introducing Sora 2

Introducing Sora 2

A detailed overview of OpenAI's announcement of Sora 2, a flagship video and audio generation model, and the new Sora app, which introduces novel features like "Cameo" for personalized content creation and a new social experience.

Building an AI Physicist: ChatGPT Co-Creator’s Next Venture

Building an AI Physicist: ChatGPT Co-Creator’s Next Venture

Former researchers from OpenAI and Google DeepMind, Liam Fedus and Ekin Dogus Cubuk, discuss their new venture, Periodic Labs. They aim to create an 'AI physicist' by integrating large language models with real-world, iterative experiments, moving beyond simulation to solve fundamental challenges in physics and chemistry, starting with high-temperature superconductivity.

How To Train An LLM with Anthropic's Head of Pretraining

How To Train An LLM with Anthropic's Head of Pretraining

Anthropic's Head of Pre-training, Nick Joseph, details the immense engineering and infrastructure challenges behind training frontier models like Claude. He covers the evolution from early-stage custom frameworks to debugging hardware at massive scale, balancing pre-training with RL, and the strategic importance of data quality and team composition.

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