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- [2108.02497] How to avoid machine learning pitfalls: a guide for academic researchers https://arxiv.org/abs/2108.02497 12 comments
- Tesla’s Optimus robot presentation was intriguing—but questions remain – TechTalks https://bdtechtalks.com/2022/10/03/teslas-optimus-robot/ 9 comments
- Understanding the AI factory - TechTalks https://bdtechtalks.com/2020/12/02/competing-in-the-age-of-ai/ 2 comments
- DeepMind AlphaTensor: The delicate balance between human and artificial intelligence – TechTalks https://bdtechtalks.com/2022/10/10/deepmind-alphatensor/ 1 comment
- New deep learning model brings image segmentation to edge devices - TechTalks https://bdtechtalks.com/2021/05/07/attendseg-deep-learning-edge-semantic-segmentation/ 1 comment
- The challenges of adversarial machine learning in constrained-feature applications – TechTalks https://bdtechtalks.com/2022/09/19/adversarial-machine-learning-constrained-features/ 0 comments
- Self-attention can be big for TinyML applications - TechTalks https://bdtechtalks.com/2022/09/26/self-attention-tinyml/ 0 comments
- One researcher’s mission to encourage reproducibility in machine learning - TechTalks https://bdtechtalks.com/2021/03/01/papers-without-code-machine-learning-reproducibility/ 0 comments
- The challenges of applied machine learning - TechTalks https://bdtechtalks.com/2021/04/19/applied-machine-learning-challenges/ 0 comments
- What AI researchers can learn from the self-assembling brain - TechTalks https://bdtechtalks.com/2021/08/16/self-assembling-brain-book/ 0 comments
- AI research papers - TechTalks https://bdtechtalks.com/tag/ai-research-papers/ 0 comments
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