AI for Frontend Developers — Day 18
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The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition
The geometric foundations you need to understand the dot product The post The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition appeared first on Towards Data Science .
AI Is Insatiable
While browsing our website a few weeks ago, I stumbled upon “ How and When the Memory Chip Shortage Will End ” by Senior Editor Samuel K. Moore. His analysis focuses on the current DRAM shortage caused by AI hyperscalers’ ravenous appetite for memory, a major constraint on the speed at which large language models run. Moore provides a clear explanation of the shortage, particularly for high bandwidth memory (HBM). As we and the rest of the tech media have documented, AI is a resource hog. AI electricity consumption could account for up to 12 percent of all U.S. power by 2028. Generative AI queries consumed 15 terawatt-hours in 2025 and are projected to consume 347 TWh by 2030. Water consumption for cooling AI data centers is predicted to double or even quadruple by 2028 compared to 2023. B
Fine-tuning Whisper-large-v3 for child reading assessment with numerals and proper names
Hi everyone, I’m working on a reading assessment product for children. Current setup: a child reads a known passage for about 1 minute our system then counts how many words were read correctly right now we use whisper-1 as a baseline we now want to move to an open model and fine-tune Whisper-large-v3 on our own infrastructure This is not a generic ASR task: we always know the reference text in advance our main metric is correct-word-count accuracy against the reference passage The main cases we want to improve through fine-tuning are: numerals / spoken-written forms, for example “three” vs “3” proper names and other rare words child reading speech in general I’d like advice specifically on the fine-tuning strategy for this type of task. My questions: For this use case, what training target
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The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition
The geometric foundations you need to understand the dot product The post The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition appeared first on Towards Data Science .
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