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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

The Blind Spots of Platform Engineering • Matt McLarty & Erik Wilde

The Blind Spots of Platform Engineering • Matt McLarty & Erik Wilde

Matt McLarty and Erik Wilde explore the blind spots in platform engineering, arguing that a narrow focus on developer velocity and toolchains overlooks the critical need for creating reusable, API-driven business capabilities that deliver tangible value and organizational optionality.

Zero-Click Attacks: AI Agents and the Next Cybersecurity Challenge

Zero-Click Attacks: AI Agents and the Next Cybersecurity Challenge

Explores the mechanics of zero-click attacks, which require no user interaction, and details how the integration of autonomous AI agents can amplify these threats. The summary covers historical examples like Pegasus and proposes a multi-layered defense strategy, including AI firewalls, the principle of least privilege, and a zero-trust architecture.

Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

Dhanji Prasanna, CTO of Block, discusses the company's AI transformation, centered on their open-source agent, Goose. He details how Goose leverages the Model Context Protocol (MCP) to automate complex workflows, saving engineers 8-10 hours weekly. Prasanna also explains Block's strategic shift to a functional organizational structure to accelerate AI adoption and shares his vision for the future, where swarms of smaller AI models will outperform today's monolithic LLMs.

Alex: Your AI Recruiting Partner

Alex: Your AI Recruiting Partner

Co-founders Aaron Wang and John Rytel discuss Alex, their AI recruiting partner that automates interviews and administrative tasks. They cover how AI is fixing the broken hiring market, the technical challenges of building conversational agents, and their vision for a future where AI supercharges, rather than replaces, human recruiters.

Quantized LLM Training at Scale with ZeRO++ // Guanhua Wang // AI in Production 2025

Quantized LLM Training at Scale with ZeRO++ // Guanhua Wang // AI in Production 2025

Guanhua Wang from Microsoft's DeepSpeed team explains ZeRO++, a system that tackles the communication bottleneck in large-scale LLM training. By quantizing weights and gradients, ZeRO++ reduces communication volume by 4x, leading to training speedups of over 2x, particularly in low-bandwidth and small-batch-size environments.

Beyond Chatbots: How to build Agentic AI systems with Google Gemini // Philipp Schmid

Beyond Chatbots: How to build Agentic AI systems with Google Gemini // Philipp Schmid

A deep dive into the evolution from static chatbots to dynamic, agentic AI systems. Philipp Schmid of Google DeepMind explores how to design, build, and evaluate AI agents that leverage structured outputs, function calling, and workflow orchestration with Google Gemini, covering key agentic patterns and the future of AI development.

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