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src/pages/cv.astro

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<span class="cv-entry__date">January 2026</span>
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</div>
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<p class="cv-entry__pub-venue">
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NIAS and the Lorentz Center<br/>
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<em>NIAS and the Lorentz Center</em><br/>
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Grant to host an academic workshop on Quantum Gaming at the Lorentz
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Center in September 2026. Approved by The Computational and Digital
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Research, Informatics, NIAS-Lorentz (SSH) and Physics advisory boards and
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<span class="cv-entry__date">June 2022</span>
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</div>
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<p class="cv-entry__pub-venue">
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International Academy of Digital Arts & Sciences <br/>
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<em>International Academy of Digital Arts & Sciences</em> <br/>
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For Quantum AI Lab interactive experience (https://quantumai.google/learn/lab)
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and Quantum AI Map (https://quantumai.google/learn/map). Responsible for
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narrative, scientific validity, and art direction in collaboration with
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<span class="cv-entry__date">June 2022</span>
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</div>
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<p class="cv-entry__pub-venue">
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American Video Association<br/>
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<em>American Video Association</em><br/>
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For The Quantum Frontier (https://www.youtube.com/watch?v=FdlaQjYYbwo).
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Awarded for Creativity (Web Video) / Special Effects / Animation. Platinum
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winners are recognized for excellence in quality, creativity, and
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<span class="cv-entry__date">May 2022</span>
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</div>
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<p class="cv-entry__pub-venue">
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Greater San Francisco Advertising Club.<br/>
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<em>Greater San Francisco Advertising Club</em><br/>
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For <em>The Quntum Froniter</em> video production.
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</p>
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</article>
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<span class="cv-entry__date">June 2020</span>
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</div>
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<p class="cv-entry__pub-venue">
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Technology Services Industry Association <br/>
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<em>Technology Services Industry Association</em><br/>
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First year Google was finalist or winner for any STAR Awards. Recognized for
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Machine Learning education innovation.
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</p>
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<span class="cv-entry__date">June 2009</span>
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</div>
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<p class="cv-entry__pub-venue">
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National Science and Engineering Research Council, Industrial Research & Design Internship<br/>
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<em>National Science and Engineering Research Council, Industrial Research & Design Internship</em><br/>
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Partnered with Intelligent Mechatronic Systems to design conversation
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strategy for speech interface to email and calendar on BlackBerry.
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</p>

src/pages/index.astro

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</h2>
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<p class="showcase__body">
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Quantum computing needs an ecosystem, not just physicists. We created games
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where quantum mechanics are the core mechanics—not educational software with
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where quantum mechanics are the game mechanics—not educational software with
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points and badges, but actual games that let people build intuition by
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playing. The work runs on actual quantum computers, and continues growing
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through a global community of contributors.
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<p class="showcase__body">
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In 2016, less than 1% of Google's engineers could use machine learning in
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production. We needed to become an ML-first company, but declarations are
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worth their weight in air. We used education at scale as a strategic lever
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training that forced infrastructure, tooling, and culture to align
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simultaneously. The result: 40% of Googlers trained, 4 million people
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reached globally per year, and ML became a cultural primitive at
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Google.
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worth their weight in air. We used education at scale as a strategic lever—training
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that forced infrastructure, tooling, and culture to align simultaneously. The
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result: 40% of Googler engineers trained, 4 million people reached
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globally per year, and ML became a cultural primitive at Google.
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</p>
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<a href={`${import.meta.env.BASE_URL}work/ml-education`} class="showcase__link">
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Read more <span class="showcase__arrow">→</span>
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Wikis don't scale; engineers couldn't find what they needed or trust it was
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current. We put documentation in the code repository—same tools,
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same workflow, zero context switching. The pattern spread
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industry-wide as "docs as code." What started as shutting down a broken wiki
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became how the industry thinks about documentation.
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industry-wide, now known as "docs as code." What started as shutting down a
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frail wiki became how the industry thinks about documentation.
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</p>
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<a href={`${import.meta.env.BASE_URL}work/docs-as-code`} class="showcase__link">
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Read more <span class="showcase__arrow">→</span>

src/pages/work/docs-as-code.astro

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<p>
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Meanwhile, Google's infrastructure was changing and the people maintaining
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Goowiki couldn't keep up. We needed to shut it down, but we had nothing to
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replace it with.
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replace it.
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</p>
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</div>
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</section>
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with software engineers. What might have taken 6-9 months could be completed
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in about a month with one day of input from a small team. This enabled me to
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document systems like the auction in Display Ads, which implemented the
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notoriously subtle Vickrey-Clarke-Groves algorithm— work that saved a whole
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notoriously subtle Vickrey-Clarke-Groves algorithm—work that saved a whole
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class of engineers weeks of meetings and reviews.
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</p>
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<p>
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2. Some of my colleagues had a genius idea: why don’t we put a web server in
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2. Some of my colleagues had a genius idea: why not put a web server in
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front of Google's code repository (google3), and serve Markdown files as
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documentation. The brilliance was simple:
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<ul>
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<li>
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Engineers already navigated the source repository daily—putting docs beside
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Engineers already navigated the source repository daily. Putting docs beside
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code meant they always knew where to find them.
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</li>
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<li>
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Same toolchain that engineers used for code—zero cognitive load to extend
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their work to docs, no context switching.
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</li>
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<li>
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Physical proximity created logical proximitydocumentation lived where it
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Physical proximity created logical proximity: documentation lived where it
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was relevant.
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</li>
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</ul>

src/pages/work/ml-education.astro

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simultaneously.
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</p>
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<p>
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For the entire organization: ML became a cultural primitive—"in the air" as a
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way of thinking about problems, even for people who had never (and would never)
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<strong>For the entire organization</strong>: ML became a cultural primitive—an idea "in the air",
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as a way of thinking about problems, even for people who had never (and would never)
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write an ML algorithm.
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</p>
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<p>
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For the engineering organization: Product managers, UX designers, writers,
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<strong>For the engineering organization</strong>: Product managers, UX designers, writers,
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and engineers could have informed conversations about when ML was appropriate,
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asking questions like:
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</p>
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<li>Is there a simpler, mechanical solution?</li>
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</ul>
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<p>
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For engineers specifically: Hands-on capability to implement ML systems,
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<strong>For engineers specifically</strong>: Hands-on capability to implement ML systems,
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including the mindset shift from "I have an algorithm that transforms data"
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to "I can collect data that trains an algorithm."
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</p>
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and non-technical audiences on strategic thinking.
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</p>
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<p>
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The results: We trained more than 40% of Googlers and made the course
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publicly available, where it reached over 4 million people per year worldwide.
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The results: We trained more than 40% of Googlers and made the
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<a href="https://developers.google.com/machine-learning">Machine Learning Crash
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Course</a> publicly available, where it reached over 4 million people per year worldwide.
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</p>
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</div>
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</section>
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<div class="story-section__inner">
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<h2>How it propagated</h2>
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<p>
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The measure of cultural transformation isn't course completionit's behavior
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The measure of cultural transformation isn't course completion, it's behavior
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change. Internally, we tracked ML pipeline creation through to production:
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were engineers actually building ML systems, not just learning about them?
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were engineers actually building ML systems, or just learning about them?
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The trend was positive, and small ML-based features began appearing across
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most Google products—not as flagship launches, but as quiet evidence that the
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mindset shift had taken hold.
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</p>
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<p>
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The content was strong enough that its value became obvious beyond Google. We
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made MLCC publicly available, where it reached over 4 million people per year
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made the MLCC publicly available, where it reached over 4 million people per year,
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worldwide. Google Cloud recognized a commercial opportunity: bringing select,
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high-value customers on-site to receive the same training Googlers received,
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building ML systems alongside Google engineers. Training became a cornerstone

src/pages/work/quantum-gaming.astro

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But here's the deeper issue: quantum computing won't just need quantum
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physicists. Just as the internet requires thousands of people across
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hundreds of layers—from low-level electronic signal engineers to UX designers—
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quantum technologies will need an entire ecosystem of people with working
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quantum technologies will need an entire ecosystem of people with some
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intuition about quantum concepts.
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</p>
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<p>
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<h2>The insight</h2>
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<p>
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Games let people build intuition about abstract concepts through direct
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interaction. You don't need to understand the physics of projectile motion to
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develop intuition for ityou just need to throw a ball to a child, or enough
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experience. You don't need to understand the physics of projectile motion to
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develop intuition for it: you just need to throw a ball to a child, or enough
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angry birds at enough pigs.
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</p>
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<p>
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training MFA students to use quantum effects as game mechanics.
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</p>
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<p>
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Together with partners in Europe, we'll host a Lorentz Center Workshop in
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Together with partners in Europe, I'll host a Lorentz Center Workshop in
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the Netherlands in September 2026. The workshop will bring together
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scientists from multiple disciplines to establish research programs in
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quantum gaming.
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<span class="stat__label">global contributors to the open-source ecosystem</span>
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</div>
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<div class="stat">
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<span class="stat__num">3</span>
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<span class="stat__num">4+</span>
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<span class="stat__label">institutional partners in quantum education</span>
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</div>
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<div class="stat">

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