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.
Cursor's team discusses their latest Cloud Agents launch, which gives agents full cloud VMs to test changes, record demo videos, and provide remote access. We explore parallel model swarms, bug reproduction workflows, and the future of agentic coding where throughput and new bottlenecks in review and CI/CD take center stage.
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.
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.
Antje Barth from Amazon's AGI Labs discusses Nova Act, a new service for building reliable AI agents. She explores how they achieve over 90% reliability using reinforcement learning in 'web gyms', the shift towards 'normcore' agents for practical automation, and the future of AI as a digital co-worker.
Experts Jeff Crume and Josh Spurgin explore the critical security and governance challenges posed by autonomous AI agents. They detail common threats like prompt injection, data poisoning, and model theft, and discuss governance issues such as bias, transparency, and accountability, providing a set of actionable safeguards to build secure, trustworthy, and compliant AI systems.
Goldman Sachs CEO David Solomon and a16z cofounder Ben Horowitz discuss the current macro environment, the unique competitive dynamics of AI, enterprise adoption strategies like Goldman's "One GS 3.0" initiative, and the critical policy debates surrounding AI and crypto.
Varant Zanoyan and Nikhil Simha Raprolu of Zipline AI explain why traditional feature stores are the wrong abstraction. They detail the journey of Chronon, the open-source engine born at Airbnb and battle-tested at Stripe, which focuses on compute, orchestration, and real-time correctness to solve the hardest data engineering challenges in ML, from fraud detection to powering modern AI agents with features and embeddings.
Dr. Ewelina Kurtys of FinalSpark discusses the ambitious goal of building computers from living neurons, aiming for a 1-million-fold increase in energy efficiency over digital systems. The conversation delves into the technical challenges of neural encoding and plasticity, the use of brain organoids, and the profound ethical and philosophical questions surrounding determinism and consciousness in biological hardware.
YC's Aaron Epstein and Eve Bouffard detail the redesign of the YC homepage, shifting from a utilitarian, B2B-style site to an inspirational, founder-centric narrative. They discuss the new design's focus on storytelling, the unconventional AI-assisted development process, and the future of interactive web design.
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