Jane Wu

1/5 "When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind." -- ascribed to Lord Kelvin (yes of K!)

In case you missed it: @coeff_giving and @SloanFoundation launched a pop up journal and funding opportunity on studying the social returns to R&D. Here are the deets for funding: Grants of approximately $250,000 are available for studies that will provide key empirical insight into the social and economic returns to R&D investment. Larger requests may be considered for uniquely ambitious projects. Deadline: April 30, 2026 That's in a month, so better get your application ready! More info here: popupjournal.com/griliches

A big load of pure alpha —>

5/5 What can be measured can (and probably will) be automated. What is not measured must still be verified and underwritten by us. It stays within our domain for now, unless of course, we cannot resist the urge to quantify it.

4/5 ... by silicon. I'm not sure where the future lies. But seeing the progression of AI through a measurement-centric lens helps me, ironically, grapple with it, to feel some semblance of control. Kelvin's point was to measure is to know. But now, to measure is to relinquish.

1/5 "When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind." -- ascribed to Lord Kelvin (yes of K!)

Ben Horowitz on the infrastructure behind the AI economy: "Crypto is the natural money for AI because it’s internet-native money." "AI is global. Crypto is global." "There needs to be not just a ledger of money, but probably a ledger of truth for AI to really fulfill its potential." "I think people are probably underestimating how crypto and AI work together to form the AI economy." "Networks and computers tend to grow together, and I think that AI is obviously a new kind of computer and crypto is a new kind of network." @bhorowitz on Moonshots with @PeterDiamandis

This makes it all worth it! 🔥 We designed the MIT Bitcoin experiment for exactly this moment: to spark the next generation of innovators and entrepreneurs. So proud to see what that 2014 cohort has already built!

Ad for a webinar for my Phd program! @MITSloanPhD -------------- The MIT Sloan TIES PhD program trains scholars who bring an economics toolkit to answer questions related to technology, innovation, entrepreneurship, and strategy. This might be interesting if you are a scientist, engineer, or entrepreneur who is interested in studying the incentives and systems that govern the creation of new ideas and businesses. Or if you are an economist who is interested in how "innovation"—that thing that supposedly sustains all economic growth—actually works like in the real world. Or if you are someone who likes math and data, and wants to study big questions like what can be done to encourage more investment in “tough tech” sectors like nuclear research, or how new AI technologies might shape how research is done. If you have an undergraduate degree in engineering, science, or social sciences, and find the questions above intriguing, the PhD program in Technological Innovation, Entrepreneurship, and Strategy (TIES) at the MIT Sloan School of Management might be for you! We’re hosting a one-hour webinar on November 6th to give you a glimpse into what our PhD program is all about: ________________________________ PhD Information Webinar  Time: Nov 6, 2025 5:30-6:30 PM Eastern Time (US and Canada) Link: mit.zoom.us/j/99170444734?… Password: 460805 Meeting ID: 991 7044 4734 ________________________________ Application Deadline: December 1, 2025 Program details and application link are available at: mitsloan.mit.edu/programs/phd/a… Looking forward to seeing you there!Meet current PhD students, recent alum, and faculty members who will share their perspectives; Learn about our incredible track record of placing students in tenure track positions at top schools; Discover the mentorship opportunities that set our program apart from more traditional PhDs in economics, political science, or sociology.

Some people see crypto as tech. We see it as freedom. The freedom to build without asking permission. Do we build higher walls, or do we build open roads? History remembers only one of those choices. x.com/lightspark/sta…

I came to MIT to study in 1983 to pursue a PhD in the then-emerging field of Biochemical Engineering. Having arrived in North America a political refugee from war-torn Lebanon eight years earlier, the academic rigor of MIT courses and professors challenged me at a whole new level, and through those challenges, taught me what I was capable of achieving. It is safe to say my career trajectory – which has included co-founding more than 100 companies that have between them employed more than 20,000 American citizens over the last twenty five years – is due in large part to MIT opening its doors to me, encouraging me to use my voice and test the limits of my abilities, and rewarding my hard work and scientific achievement. Opening doors; protecting free speech; rewarding merit: these are MIT’s values, and I consider them to be the bedrock tenets of the United States, my adopted home. I stand proud of my alma mater, as an alumnus and a member of its board. nytimes.com/2025/10/10/us/…

The Trump administration has suspended the funding of Terence Tao and the Institute for Pure and Applied Mathematics at UCLA.

5/5 Managing only what you can measure has never been more costly. Read more in our latest piece @HarvardBiz with @ccatalini and @kevalexzhang hbr.org/2025/06/what-g…

4/5 And the tech keeps slashing the cost of that conversion, so measurement gets cheaper, faster, and quietly woven into everything we touch. That means that any job that can be measured can, in theory, be automated. Measurement isn’t an afterthought—it’s the AI roadmap.

3/5 That formula—capture the task as data → provide a reward → let silicon iterate -- is how AI models become increasingly capable at more and more "uniquely human" tasks. If you can shoehorn a phenomenon into numbers, AI will learn it and reproduce it back at scale.

1/5 When thinking about what's to come, we looked back at ImageNet -- not just the herculean effort of Fei-Fei Li to collect the dataset, but the real stroke of genius: a leaderboard that defined a metric and let researchers race to win. paperswithcode.com/sota/image-cla…

2/5 Scroll through @paperswithcode and you'll see that the underlying framework of ImageNet is far more general. It can be invoked whenever we can a) define the task and assemble its data; b) specify a target reward; and c) provide the computational power to iterate.

In 2015, @ccatalini helped me buy my first bitcoin. In many ways, it led to the founding of @ZeroHashX. So, we jumped at the opportunity (~10yrs later) to team up with him & @davidmarcus to help @lightspark build the future of payments. Crazy how things can come full circle.

Love solving challenges with top fintechs, neobanks & crypto innovators? Obsessed with details & building value via strategic partnerships? Join my team—let’s create something amazing! 🚀 @lightspark x.com/i/jobs/1903178…