The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen - #382
Jun 11, 2020
In this fascinating discussion, Andreas Madsen, an independent researcher from Denmark, shares his insights on neural arithmetic units and the challenges of independent research. He emphasizes the importance of collaboration and community support while navigating the competitive landscape of academic publishing. Madsen highlights difficulties in extrapolation with neural networks, proposing innovative benchmarks to enhance performance. His journey from academia to freelancing brings attention to the resource demands and perseverance needed for successful research in machine learning.
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Independent Research Challenges
- Avoid independent ML research if you aim for novel contributions.
- It requires extensive resources, collaboration, and peer feedback, which are hard to access alone.
From Freelancer to Researcher
- Andreas Madsen transitioned from freelancing in JavaScript to independent ML research after publishing a paper.
- Despite this, he faced difficulties securing research positions due to a lack of top-tier publications.
Tips for Independent Researchers
- Collaborate with experienced peers for critical feedback on your research.
- Have realistic expectations about publication success rates and be prepared for rejections.
