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Title & Speakers	Event
From Algorithms to Agents: Lessons from Building Copilot 2025-09-15 · 13:00 What Generative AI Has Changed and Which Fundamentals Still Matter - Vadim Smolyakov Vadim’s path spans from algorithmic ML and MIT research to building Copilot at Microsoft, providing him with a front-row view of how practice has shifted from hand-built algorithms to agentic systems. In this conversation, he reflects on what genuinely changed with generative AI and what fundamentals still matter. We’ll discuss assistants as complements to human thinking, why embodiment (“physical AI”) may be the next step, and how goal-setting and sharing knowledge shape work that lasts. We plan to cover: What Copilot taught about scope, trade-offs, and evaluation Agents as assistants: avoiding over-reliance while gaining real leverage Fine-tuning, synthetic data, and how the craft of ML has evolved Physical AI: what to build in vs. what to learn from the environment Purpose, habits, and leaving durable digital/physical artifacts About the speaker Vadim Smolyakov is a Machine Learning Engineer at Microsoft, working on Copilot AI, an author of Machine Learning Algorithms in Depth, and a former MIT PhD student. He focuses on generative AI (agents, RL), self-development, knowledge sharing, and the societal impact of intelligent systems. Join our slack: https://datatalks.club/slack.html	From Algorithms to Agents: Lessons from Building Copilot

What Generative AI Has Changed and Which Fundamentals Still Matter - Vadim Smolyakov

Vadim’s path spans from algorithmic ML and MIT research to building Copilot at Microsoft, providing him with a front-row view of how practice has shifted from hand-built algorithms to agentic systems.

In this conversation, he reflects on what genuinely changed with generative AI and what fundamentals still matter.

We’ll discuss assistants as complements to human thinking, why embodiment (“physical AI”) may be the next step, and how goal-setting and sharing knowledge shape work that lasts.

We plan to cover:

What Copilot taught about scope, trade-offs, and evaluation
Agents as assistants: avoiding over-reliance while gaining real leverage
Fine-tuning, synthetic data, and how the craft of ML has evolved
Physical AI: what to build in vs. what to learn from the environment
Purpose, habits, and leaving durable digital/physical artifacts

About the speaker

Vadim Smolyakov is a Machine Learning Engineer at Microsoft, working on Copilot AI, an author of Machine Learning Algorithms in Depth, and a former MIT PhD student. He focuses on generative AI (agents, RL), self-development, knowledge sharing, and the societal impact of intelligent systems.

Join our slack: https://datatalks.club/slack.html

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