Gavin Leech
Now:
research company
We focus on forecasting and other important niche areas (large-scale data collection; machine learning for epistemics). Consultancies are reactive, but we have our own agenda - some ideas sketched here.
Current work:
- I lead a team investigating AI talent for the new Emergent Ventures programme.
- Improving the state of AI forecasting
- Processing an author's entire corpus and automatically evaluating their forecasting ability
- Following my Covid work, I’m helping Jan Kulveit set up the Active Long-termist Emergency Response Team.
against AI risk
Besides that, I’m working on a large project upstream of AI forecasting and leading a Mercatus Center project on AI talent, with the aim of bringing in non-financial support like technical mentors, visas, and excitement.
So I am trying to become less rounded. This boils down to more maths. One carrot: I aim to fully understand the great explanations: relativity, QM, evolutionary dynamics, Bayes, reinforcement learning, and computational complexity.
💪 Work 💪
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Public work:
Researching AI, forecasting, metascience, and cause prioritisation.
Clients include Open Philanthropy, the Future of Humanity Institute, Mercatus, Alvea.
* Forecasters vs experts
* Scoring the Big 3
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I am chair of the Emergent Ventures / Schmidt Futures panel on AI Talent.
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Modelled COVID with Oxford / Imperial / Harvard colleagues. Probabilistic programming, technical writing, data cleaning, literature reviews.
7 papers in 14 months. I led a major study of mask effectiveness.
Buzzwords: PyMC3, MRP (hierarchical Bayes), AWS, Azure, Seaborn
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Solo instructor in CS tutorials, training other TAs. Bayesian ML & Algos 2.
Buzzwords: Gaussian processes, Markov Random Fields, Bayesian opt., variational inference, dynamic programming, graph theory, complexity
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Buzzwords: Python, Spark, Keras, XGBoost, Tableau, Avro, Pytest, GDPR
Built dozens of ML models (GLMs, GBMs, neural nets) for actuarial pricing, medical risk, & image recognition. Web scraping at scale; migration from SAS to Hadoop, & Hadoop to Azure. Came in as a graduate data scientist, left as tech lead for a team of 4.
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Jumped into web dev; my code deployed worldwide within 2 weeks.
Products: a medicine pump device manager & a pharmacy record system.
Buzzwords: C#, WPF, node.JS, MEAN, Ractive, Mongo, Vagrant, VMware
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Made official statistics, Education Analytics. Testing for a data visualisation tool for teachers: SAS/SQL. Prep for the Social Care Survey 2015.
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A quiet business. Read all of Arts & Letters Daily, all of 3 Quarks Daily, all of Crooked Timber, and all of Marginal Revolution every day for 9 months.
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Dogsbody work at a small software company in Beijing. Handled expenses, learned Mandarin, looked at inefficiencies, saved face.
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Awards
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3 month residency at the FTX EA Fellowship.
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Emergent Ventures grant for a few wild ideas.
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1st prize, Advanced Modelling of Cybercrime hackathon.
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EA Forum Prize: how much AI safety is done indirectly?
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1st place, Value Forecasting Tournament.
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UKRI studentship for PhD (~$150k).
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Publications
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Education
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AI PhD
Probabilistic programming, AI safety. Long detour on COVID models.First year was a de-facto research Master’s (uncertainty modelling, NLP, GOFAI, legal aspects).
Second year: COVID modelling. EPSRC Centre for Doctoral Training studentship (4 years fully funded).Thesis: Tensorised Probabilistic Programming
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BSc Maths & Stats
89% GPA ≈ 96th percentile.
Probability up to diffusion processes, regression to GLMMs, numerics to BFGS, linear algebra to multi-linear, RCTs. Part-time during FT work. Reviewed here.
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MSc Software Development
82% GPA ≈ 85th percentile.
Fairly vocational. Java, SQL, HTML/CSS/PHP, assembly, design patterns, data structures & algos.Thesis: Hidden Markov Models for Linguistic Accommodation.
Full-ride Scottish Funding Council scholarship.
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MA Economics & Philosophy
85% GPA ≈ 90th percentile.
Micro and macro, Ethics, global justice, Continental philosophy, development policy, formal logic, social statistics, health policy, development policy.
Dissertation: On the Abolition of Foreign Aid. Alumni Fund scholarship.
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Tech
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New Pycolab environments and implementations of DQN and MaxEnt IRL in Tensorflow. Reused in Deepmind papers.
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Brought modern language modelling (Flair) into Prolog for some reason.
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Journal-grade modern Bayesian workflow in PyMC3. Probabilistic programming for epidemic modelling and effect estimation. End to end with data getters.
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Python wrapper for the Hidden Markov ToolKit.
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Just a Jekyll site, but a particularly satisfying one.
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Volunteering
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Co-founder / board member of the Active Longtermist Emergency Response Team, an on-call org watching the skies.
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The European Summer Programme on Rationality: a grand maths / experiential ed camp. I ran 4 sessions on personal agency, research skills, speculative astronomy, and cultural literacy.
I'm running one of the 2022 camps.
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Vetting & interviewing for a scrappy intro to AI safety research.
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I started a thing to help people with executive dysfunction. Fully funded by a bitcoin rando! Thanks!
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Resolution Council member of a short-lived AI prediction market.
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