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Durable workflows, streaming interfaces, operational context, and external security controls turn an agent loop into a usable application.
Shared experiments, deliberate code review, simulated shoppers and specialized models show what it takes to turn abundant generation into useful work.
Part 3 of 3 examines why simulated materials data can miss experimental needs, how training accommodates laboratory timescales, and why better GPU utilization could free money for lab work.
Human simulation combines personal histories, observed choices, and controlled experiments to model how people respond—and help decision makers explore what to do next.
Foundation models let developers begin with trained capabilities, then build the data connections, infrastructure and interfaces that make them useful. A 2023 view of the engineering role emerging around that change.
Fast speaking drills, adaptive curricula, and patient turn detection show what it takes to turn capable models into a language tutor.
Part 3 of the ChatGPT voice preview tests the gap between conversational control and precise audio behavior: recognizing an illusion, producing a tuning note, copying pitch, and thinking before speaking.
Coding agents move the work toward asking questions, supervising execution, and integrating changes. The promise comes with a learning curve—and a bottleneck that more code cannot solve.
Part 1 follows the path from production outages to dependable model interfaces: constrained decoding, tool execution, refusals, schema design, evaluation, and model selection.
Code execution, open weights and long context expanded what developers could build. Evaluation, deployment control and reliable behavior determined whether those capabilities could become useful products.
How generated textbooks, rewritten web pages and synthetic labels support capable models that cost less to run and can stay on the device.
AI can generate a starting interface. Choosing a direction, making its behavior coherent, and developing a distinctive product still demand design judgment.
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A conversation with Greg Brockman about OpenAI’s path to AGI, alongside our analysis of GPT-5, Codex, and the shift to agentic coding.
Thariq Shihipar on Claude Code’s next era: prompts, harnesses, plugins, and agents—and what it takes to keep pace with the frontier.
Marc Andreessen on the future of the browser, Pi and OpenClaw, and why this wave of AI feels different.
Priscilla Chan and Mark Zuckerberg on Biohub’s plans for frontier AI and virtual biology, and the ambition to cure or prevent disease.
Anima Anandkumar on modeling the physical world, from weather to fusion reactors, and why physics needs more than language models.
John Platt on automating science, tackling climate change, and how the next generation can contribute in the age of AI.
Anthropic brings interactive apps into Claude with an open MCP standard for richer AI interfaces.
What Sam Altman’s town hall reveals about building startups in the age of AI.
Moonshot’s multimodal model brings competitive coding, native image and video understanding, and parallel agents.
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