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As others have said, this is the way ML is headed and it has been clear for the last couple of years. Assuming a multi-task and multi-modal architecture is ach
by axg11 5y ago
As others have said, this is the way ML is headed and it has been clear for the last couple of years.
Assuming a multi-task and multi-modal architecture is achievable, won't we reach a point in the future where preprocessing data is just as difficult as the machine learning component? Today, the input to ML models is almost always carefully curated and processed.
- bionhoward 5y agoYou can make sensor type components in NNs which reshape arbitrary arrays to a fixed size and shape (or a ragged shape which is consistent in 1 dimension and works with sequence models)
- zippy5 5y agoIt seems to me that there are two ways to learn well. One is to have a carefully curated curriculum and the other is to have enough experience to parse the world by yourself. In humans we might describe these as knowledge/education and wisdom. I see data preparation as improved knowledge transfer and more training data as the path to wisdom. Wisdom is usually heavily discounted by smart young people so I expect engineers will double down on better data prep than better data acquisition. Also which looks better on a resume?