In the 2010s, there was considerable interest in and VC funding for quantum algorithms for machine learning, based largely upon the Kerenidis and Prakash quantum recommendation system. [Ewin Tang undergrad project](https://arxiv.org/abs/1807.04271) de-quantized this algorithm, effectively killing the field of quantum machine learning (QML).
Her PhD work de-quantized many of the known quantum algorithms. Another thread recounted a joke that *"it's no use coming up with new quantum algorithms as Ewin Tang will de-quantize them anyway."*
To be precise, these quantum algorithms had unrealistic assumptions about accessing data within the quantum computer. Tang provided a classical analog of the QRAM assumption and suitable fast classical algorithms.
In 2025, [Ewin Tang](https://en.wikipedia.org/wiki/Ewin_Tang) received a Maryam Mirzakhani New Frontiers Prize for *"developing classical analogs of quantum algorithms for machine learning and linear algebra, and for advances in quantum machine learning on quantum data."* She'll start a professorship at Princeton this year.
Although overly breathless and miss-naming her prize, this videos tells her interesting story, with a healthy amount of context and citations to papers. Other post have not found significant errors, other than in the name of the prize.
If I understood the ending, Ewin Tang has ongoing work on running quantum algorithms directly within experiments on quantum systems. That's a clever research direction, one of the few which could make "small" quantum computers actually socially beneficial. In general, the known "small" quantum algorithm are socially harmful, ala breaking cryptography.
There is nothing too directly relevant to applied cryptography here, but this explains why we now have so many VC startups working towards quantum computers that break cryptography: After QML died, the VC back QC startups were forced to pivot their sunk costs toward algorithms where quantum advantage remained. I suppose this relates to why some of the QC startups harass Scott Aaronson & others who criticise them too.
