That is until recently, when a social media platform’s ill-kept privacy files surfaced on the public internet and an increasingly litigious group of people decided to take matters to court. Now, in an attempt to work proactively to keep underage users safe online and also ensure the privacy of everyone’s collected data, companies are pursuing new methods to verify the age of their users online. But the lack of federal regulation is also fueling this paradoxical directive and fostering the conflict: social media companies can collect the data of users of all ages, to keep children safe.
As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?
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