A technical guide on migrating ML experiments from Neptune to Weights & Biases, covering the migration script, API-level code changes, and best practices for organizing projects and analyzing results in the W&B platform before the Neptune sunset.
W&B Models is the system of record for the entire model development lifecycle. This guide explores how to monitor training, tune hyperparameters, track artifacts and lineage for reproducibility, and automate MLOps workflows like evaluation and deployment using a central platform.
An expert overview of post-training techniques for language models, covering the entire workflow from data generation and curation to advanced algorithms like Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Learning (RL), along with practical advice on evaluation and iteration.
In a YC Founder Fireside chat, AssemblyAI founder Dylan Fox discusses his journey from a solo founder in 2017 to leading a major voice AI infrastructure platform. He covers the early challenges, the technological shifts that fueled growth, the development of intelligent, promptable voice models, and the lessons learned in scaling a deep-tech company.
Sudip Roy, Co-founder & CTO of Adaption Labs, discusses how "Adaptation" using gradient-free, inference-time techniques can solve the last 5% reliability gap that stalls enterprise AI adoption, offering a more dynamic and cost-effective alternative to traditional fine-tuning or simply waiting for the next frontier model.
This talk by Hakim Si-Mohammed explores the evolution of Brain-Computer Interfaces (BCIs) from clinical rehabilitation tools to integral components of immersive systems. It details research on integrating BCIs with Virtual and Augmented Reality (VR/AR), focusing on SSVEP-based interaction, user experience enhancements, and the development of passive, neuro-adaptive systems that respond to user mental states to mitigate issues like cybersickness.
Ajay Chankramath and Nic Cheneweth discuss the critical elements of effective platform engineering, emphasizing a product mindset, the foundational role of control planes and API-first design, the common pitfalls of implementing Backstage, and the emerging impact of AI and agents on the platform landscape.
Experts Sam Newman, Jacqui Read, and Simon Rohrer explore the nuances of software design, its intersection with architecture, and the critical role of communication in scaling technical clarity. The discussion covers practical advice on implementing Architectural Decision Records (ADRs), the evolving role of the architect as a facilitator, and strategies for creating agile enterprise architectures.
Docker educators Bret Fisher and Elton Stoneman discuss the second edition of Stoneman's book, "Learn Docker in a Month of Lunches". They explore why Docker fundamentals remain crucial in a Kubernetes-dominated world, the evolution of the container ecosystem over the past five years, and the key skills that differentiate a Docker expert from a beginner, such as multi-platform builds, security, and configuration management.
Matthew Keesan from IonQ discusses the imminent arrival of "Q-Day"—the moment quantum computers will break current public-key encryption. He explains the fundamentals of quantum computing, including superposition and entanglement, details the hardware roadmap that places this threat within the decade, and explores the promising applications of this new computing paradigm in AI, drug discovery, and materials science, issuing a call to action for software engineers to get involved.
Sid Sheth, CEO of d-matrix, details their memory-centric approach to AI inference hardware, focusing on their Digital In-Memory Compute (DIMC) architecture. He explains how DIMC, an augmented SRAM technology, minimizes data movement to solve the memory bottleneck, delivering significant gains in latency and energy efficiency, particularly for the 'decode' phase of large language models.
Rivian CEO RJ Scaringe discusses the company's complete pivot from a rules-based '1.0' autonomy system to a vertically integrated, neural network-based architecture. He outlines the essential ingredients for success in autonomous driving—from custom inference chips to a robust data flywheel—and explains why a software-defined vehicle architecture is non-negotiable for survival. Scaringe also touches on the upcoming R2 model, the importance of market choice, and how superior, proprietary data will be the key differentiator in the age of AI-driven vehicles.
In this panel discussion, Holly Cummins, Abby Bangser, and Adrian Mouat explore the inherent conflict between security and developer experience. They argue that traditional security, often driven by fear and restrictive policies, can lead to 'Shadow IT' and greater insecurity. The solution proposed is a platform engineering approach, which centralizes security expertise to provide secure defaults, infrastructure guardrails, and a clear shared responsibility model, thus enabling development teams to deliver value quickly and safely without needing to become security experts themselves.
A panel of cybersecurity experts discusses the security risks of the rapid adoption of AI agents, the "move fast and break things" development culture, the lessons from the Notepad++ supply chain breach, and the professionalization of ransomware by groups like DragonForce.
Kris Beevers, CEO of NetBox Labs, explores the hypergrowth in AI infrastructure, detailing how teams are compressing the design, build, and deployment cycle from years to months. The discussion covers the primary bottlenecks like power and logistics, the critical need for intent-driven automation, and the role of a standardized data model in managing the immense complexity from physical cabling to logical configuration.
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