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.
Onshore founder Dominic Vitucci discusses how AI is causing a tectonic shift in the accounting industry, moving from a model based on billable hours to one of technology-driven outcomes, and what this means for the future of the profession and the legacy firms that dominate it.
A detailed breakdown of the updated OWASP Top 10 vulnerabilities for Large Language Models (LLMs), explaining threats like prompt injection, data poisoning, and supply chain risks, along with practical defense strategies.
In this episode, Ben Lorica and Evangelos Simoudis discuss how AI is fundamentally reshaping the modern workplace. They explore the necessary evolution of knowledge work, from a focus on routine execution to problem definition and spec-driven development, and outline the critical skills professionals must cultivate—including rapid experimentation, AI agent orchestration, and systems thinking—to remain valuable and navigate a more volatile labor market.
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.
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.
A deep dive into orchestrating swarms of AI agents for large-scale code refactoring. Learn practical workflows, task decomposition strategies, and context-sharing patterns, demonstrated with a real-world case study on migrating a large codebase.
To build secure AI systems, we must first learn to break them. Katharine Jarmul explores the landscape of adversarial AI, detailing how attackers exploit fundamental weaknesses in deep learning models—from poisoned training data and overparameterization to the attention mechanism itself. This talk provides a practical taxonomy of attacks and a primer on building robust defenses.
Matthew Glickman, CEO of Genesis Computing, discusses the rise of AI data agents designed to automate complex data engineering workflows. He covers the "last 10%" problem in enterprise AI, the unique value of targeting the data engineer persona, and how these agents can tackle challenges like legacy system migration and knowledge capture, ultimately giving valuable time back to data teams.
NVIDIA CEO Jensen Huang discusses the state of AI as we begin 2026, covering rapid improvements in reasoning, the profitability of inference, why AI will increase productivity without taking jobs, the future of robotics, the importance of open source, and which sectors are poised for their 'ChatGPT moment'.
Nikesh Arora, CEO of Palo Alto Networks, shares his unconventional journey and leadership philosophy. He provides a masterclass in building a multi-platform company through strategic M&A, explains why founders should sometimes ignore customers, and reveals how to lead with conviction while managing imposter syndrome.
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