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Back to this week
Week ofFebruary 24 / 202605 stories / 3 bonus / ~51 min total

The Reading List.

Contents01How McKinsey Is Deploying AI...02Gemini 2.0 Model Updates: Flash,...03How Generative AI Can Boost...04Regulating General-Purpose AI: Areas of...05Mixture of Experts Explained
01
/ LEADRead Sunday
Bucketbusiness
LevelAccessible
SourceMcKinsey Global Institute
Read12 min

How McKinsey Is Deploying AI Across Its Consulting Workforce

McKinsey has rolled out AI tools to over 40,000 consultants, automating research synthesis and first-draft writing. Productivity benchmarks show 20-30% time savings on research tasks, though client judgment and relationship work remain firmly human. Worth reading for the honest assessment of what automation can and cannot replace.

Read on McKinsey Global Institute ->
# consulting# enterprise
02
Read Wednesday
Bucketmodels
LevelAccessible
SourceGoogle DeepMind
Read8 min

Gemini 2.0 Model Updates: Flash, Flash-Lite, and Pro Experimental

Google's official breakdown of what changed in the Gemini 2.0 family — Flash goes generally available with higher rate limits, Flash-Lite arrives as the most cost-efficient option yet, and Pro Experimental targets complex coding tasks. Useful for understanding how model tiers are designed and what "generally available" signals about production readiness versus experimental releases.

Read on Google DeepMind ->
# google# llm# benchmarks
03
Read Wednesday
Buckettools
LevelAccessible
SourceMIT Sloan
Read6 min

How Generative AI Can Boost Highly Skilled Workers Productivity

MIT Sloan's summary of the landmark BCG/Harvard field experiment on AI and knowledge worker productivity. Consultants using AI finished 12% more tasks, 25% faster, and produced 40% higher quality output. The nuance — AI helped most on tasks inside its capability frontier, and hurt performance on tasks outside it. Practical implications for how to decide which work to delegate to AI.

Read on MIT Sloan ->
# productivity# tools
04
Read Friday
Bucketregulation
LevelAccessible
SourceBrookings Institution
Read10 min

Regulating General-Purpose AI: Areas of Convergence and Divergence Across the EU and the US

Brookings maps where EU and US AI regulation is converging — transparency requirements, risk tiering, liability frameworks — and where it's diverging, particularly on enforcement mechanisms and foundational model obligations. Essential reading for any organization operating across both jurisdictions as compliance timelines approach.

Read on Brookings Institution ->
# eu# regulation# compliance
05
Read Friday
Bucketmodels
LevelTechnical
SourceHugging Face
Read15 min

Mixture of Experts Explained

A thorough technical explainer on Mixture of Experts (MoE) architectures — the design powering Mixtral, DeepSeek, and Gemini 1.5. Covers how sparse routing enables larger parameter counts without proportional compute costs, load balancing challenges, and why MoE models behave differently from dense models at inference time. Assumes comfort with transformer fundamentals.

Read on Hugging Face ->
# moe# architecture# llm

Bonus material

For the curious.

Optional / 03 reads
Stanford HAI

AI Index Report 2025

The most comprehensive annual data snapshot on AI's real-world progress and impact.

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