Machine Learning @GoogleDeepMind @GoogleAI @GoogleHealth / Mathematics / Computer Science / MIT / KAIST / Piano / Street Photography. All views are personal.
Joined June 2009
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Inactive account - please feel free to connect on LinkedIn or @tedyun.bsky.social
linkedin.com/in/tedyun
Ted Yun retweeted
An advanced version of Gemini with Deep Think has officially achieved gold medal-level performance at the International Mathematical Olympiad. 🥇
It solved 5️⃣ out of 6️⃣ exceptionally difficult problems, involving algebra, combinatorics, geometry and number theory. Here’s how 🧵
Ted Yun retweeted
Very excited to share that an advanced version of Gemini Deep Think is the first to have achieved gold-medal level in the International Mathematical Olympiad! 🏆, solving five out of six problems perfectly, as verified by the IMO organizers! It’s been a wild run to lead this effort and I am grateful to everyone in the team for such an amazing achievement! Blog post in the thread and more to share soon!
Super thrilled to share that our AI has has now reached silver medalist level in Math at #imo2024 (1 point away from 🥇)! Since Jan, we now not only have a much stronger version of #AlphaGeometry, but also an entirely new system called #AlphaProof, capable of solving many more Olympiad problems. This is a large-scale project that I was fortunate to co-lead at @GoogleDeepMind! See our blog & NYT articel below!
Blog: dpmd.ai/imo-silver
NYT: nytimes.com/2024/07/25/scien…
Ted Yun retweeted
REGLE, a new method to understanding the genetic basis of organ function, leverages high-dimensional clinical data, requires no disease labels, and can incorporate expert-defined knowledge to reveal deeper insights into how our organs work. Learn more → goo.gle/3y5UdD7
ALT REGLE consists of three steps: 1) learning the lower-dimensional embeddings, 2) performing GWAS on each coordinate of the embeddings, and 3) creating a polygenic disease risk score while requiring only a small number of disease labels.
Ted Yun retweeted
Yesterday’s Research@ Seoul event was a success — Google Researchers led lightning talks on ML fairness, Genomics, Materials Science, Generative AI in Search, & Quantum. We're grateful to them for presenting their work & fueling progress in the field!
ALT A speaker onstage at Research@ Korea. The screen behind them reads, "Applying generative AI responsibly".
ALT A speaker onstage at Research@ Korea. The screen behind them displays a slide from the Breakthroughs in Quantum Computing talk.
ALT A speaker onstage at Research@ Korea. The screen behind them reads, "Using the Monk Skin Tone Scale to develop more inclusive technologies".
ALT A panel of Research@ Korea speakers seated onstage for a Q&A.
Ted Yun retweeted
The demos from Research@Korea also showcased Google Researchers’ work across important topics like ML fairness, Genomics, Materials Science, Generative AI in Search, and Quantum. Dive deeper into the work of our researchers here → goo.gle/48Wi2e9
ALT Research@ Korea attendees check out the Genomics demo booth.
Ted Yun retweeted
We’re excited to describe new @GoogleHealth work that makes phenotyping more scalable. An unsupervised deep learning method, REpresentation learning for Genetic discovery on Low-dimensional Embeddings (REGLE), to perform GWAS on high-dimensional clinical data.
Ted Yun retweeted
Our recent @GoogleHealth AI Genomics work showing that deep learning approaches identify new genetic loci and improve risk models for chronic obstructive pulmonary disease (COPD) was published today in @NatureGenet !
Paper: rdcu.be/c96zx
Code: github.com/Google-Health/gen…
Ted Yun retweeted
Every single person who confuses correlation and causation ends up dying.
People more likely to be victims of crime in Labour-run areas, new study shows.
telegraph.co.uk/news/2023/02…
Ted Yun retweeted
Have you ever wanted a guide that explains how to maximize results with #DeepLearning? Introducing The Deep Learning Tuning Playbook, which describes a systematic approach to training and tuning neural networks. Check it out ↓ goo.gle/3QVnqG2
Ted Yun retweeted
SF, who’s ready to ride? 🚘🤖
After receiving the driverless pilot permit from the @californiapuc, Waymo One is opening to members of the public in San Francisco. Available 24/7—without anyone in the driver’s seat: cpuc.ca.gov/news-and-updates…
This is probably a good time to export my Twitter data (not that I have much). xitter.cf/settings/download_your…
Ted Yun retweeted
awesome visualization of europe’s changing powers, 1500-2022
xitter.cf/WallStreetSilv/status/…
An interesting experiment in scientific publishing.
Today, we’re introducing a new model that eliminates accept/reject decisions.
By publishing every paper with eLife reviews as a Reviewed Preprint, we plan to restore autonomy to authors, ensuring that they will be judged by what, not where, they publish. elifesciences.org/inside-eli…
Ted Yun retweeted
Is the Pixel 7 Pro as good as a "real" camera? With @madebygoogle bragging of its "pro-level zoom" and AI smarts, I wanted to see how close it got to my $10,000 of DSLR gear. Answer: closer than any other phone. Here's my assessment & a thread. 1/ cnet.com/tech/mobile/i-spent…
Ted Yun retweeted
Excited to share our paper in @Nature: We revisit the 50+ year-old maths problem with AI: how efficiently can we multiply two matrices? Surprisingly, the answer is still not known - even for 3x3 matrices! With AI, we discover many new efficient and exact algorithms. 1/13
Today in @Nature: #AlphaTensor, an AI system for discovering novel, efficient, and exact algorithms for matrix multiplication - a building block of modern computations. AlphaTensor finds faster algorithms for many matrix sizes: dpmd.ai/dm-alpha-tensor & dpmd.ai/nature-alpha-tensor 1/
Ted Yun retweeted
Today in @Nature: #AlphaTensor, an AI system for discovering novel, efficient, and exact algorithms for matrix multiplication - a building block of modern computations. AlphaTensor finds faster algorithms for many matrix sizes: dpmd.ai/dm-alpha-tensor & dpmd.ai/nature-alpha-tensor 1/
Ted Yun retweeted
BREAKING NEWS:
The 2022 #NobelPrize in Physiology or Medicine has been awarded to Svante Pääbo “for his discoveries concerning the genomes of extinct hominins and human evolution.”
Ted Yun retweeted
The Tripitaka Koreana - carved on 81258 woodblocks in the 13th century - is the most successful large data transfer over time yet achieved by humankind. 52 million characters of information, transmitted over nearly 8 centuries with zero data loss - an unequalled achievement. 1/
Ted Yun retweeted
Excited to share new phenotyping methods for COPD, improving COPD GWAS
Collaborative work with IU and BWH, co-authors @cosentiyes, B Besaz , @babak_alipanahi, Z McCaw, last author @FHormozdiari, eng manager C McLean.
Paper: medrxiv.org/content/10.1101/…
Code: github.com/Google-Health/gen…
