I’m a data engineer who somehow ended up as a software developer. So many of my friends are working now with the OpenAI api to add generative capabilities to their product, but they lack A LOT of context when it comes to how LLMs actually works.
This is why I started writing popular-science style articles that unpack AI concepts for software developers working on real-world application. It started kind of slow, honestly I wrote a bit too “brainy” for them, but now I’ve found a voice that resonance with this audience much better and I want to ramp up my writing cadence.
I would love to hear your thoughts about what concepts I should write about next?
What get you excited and you find hard to explain to someone with a different background?
Learned optimizers look promising - training a neural network to train neural networks.
Unfortunately they’re hard to train and nobody has gotten them to really work yet. The two main approaches are meta-training or reinforcement learning, but meta-training is very expensive and RL has all the usual pitfalls of RL.