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Dan Shipper is seeking questions to ask Sam Altman during an interview at OpenAI's Developer Day event.
A tweet discusses an interview with Shopify CEO Tobi Lütke, highlighting commentary on AI's limitations, the importance of responsibility, and insights on AI use in business and personal learning.
Shane Parrish shares insights from a conversation with Shopify CEO Tobi about leveraging AI in business and fostering learning.
A conversation with Shopify CEO Tobi Lütke discussing the company's use of AI, including internal tools like River and reflections on AI in decision-making and learning.
Patrick OShaughnessy interviews Gabe Stengel, CEO of Rogo, about the future of AI in investing and Rogo's development towards that vision.
An interview with Thibault, head of OpenAI's Codex team, discussing Codex's development, the choice of Rust for its core, open-source strategy, and shifts in engineering practices at OpenAI.
Sam Altman discusses the future GPT-7 AI model in a conversation, highlighting advancements and potential impacts in artificial intelligence.
In the interview, Greg Brockman discusses leadership changes at OpenAI, ChatGPT's billion-user scale, the rise of AI agents, improvements in model capabilities (such as the upcoming Astra model), and the importance of safety incidents for AI development.
In a Bloomberg interview, AI pioneer Kai-Fu Lee discussed emerging AI technologies from China, including Kimi K3 and 01.AI's TrueNorth and Boss AI products.
Eiso Kant, co-founder of Poolside AI, discusses their 'Model Factory' approach to rapidly training frontier models, the release of Laguna S 2.1, and the economics of AI model development.
An AI model called Fable conducts a fictional interview with Norbert Wiener, discussing the alignment problem and current AI developments, based on Wiener's writings.
Andrej Karpathy emphasizes that true AI understanding comes from building, not collecting prompts, in a 2-hour interview.
Recommends the Stanford open course CS336: Language Modeling from Scratch, which systematically explains the full training pipeline of language models from scratch, suitable for those preparing for AI interviews or wanting to deeply learn LLM.
Max Lamparth discusses the evolution of AI, the misunderstanding of AI as a monolithic technology, where AI creates real value (e.g., code, math, drug discovery) versus hype, and the importance of trust and reliability in high-stakes settings.
A curated list of foundational AI papers recommended for interview prep, covering transformers, efficient fine-tuning, vision models, and generative networks.
Verso used AI to build a nearly fully autonomous company, automating customer research delivery, bug fixes, and other processes through a "company brain", serving about thirty clients with only a four-person team.