Off topic: are $1M/$2M seed rounds realistic during YC demo day?
Even with some traction/users/conversion/revenue, and a grand long-term vision, a suggested 15%-25% dilution [1] gives $4-10M valuation. Outside SV, this is already Series A valuation. Any thoughts ?
These are certainly realistic, and happen quite often during and after demo day.
Fwiw - series A valuations around the world certainly vary, but it is rare to see an A done in the $4-10m range, at least for companies that we've funded.
Yes getting $1M to $2M raised because of demo day is reasonable. Yet closing $2M on demo day without subsequent follow up meetings would be very impressive!
That only pays for the salaries of 5 engineers. And what about rent? That takes one salary itself. Which only leaves you with enough money for 4 engineers.
Is there any research that spiking/dopamine type learning is good at "animal level" behaviour, but abstract and complex thinking is enabled by different mechanisms ?
On the AI side of the fence the approach has been "let's see just how far Reinforcement Learning can take us, and then start making up stories (hypothesis) about what the secret ingredients are that are missing." On the neuroscience side of things my sense is that that's not a question that can be empirically answered any time soon. This experiment was interesting because they new what they were looking for going in. "What algo are these cells running?" is a hard question, "are these cells' firing activities consistent with this given algo is comparatively easy. Inference vs hypothesis testing.
Can u mention how much human Dev time is involved?
We have a stupid-basic single machine Deep reinforcement Self play setup. It takes about 24 hrs to run a full experiment. The NN is the bottle neck. Using Tensor flow. Nothing fancy.
How much dev time for a good enginner (backend, kernel, multi core experience) to get this down to say 1hr ?
Obviously a very general question. Thanks for any input.
HN is the best place to find devs, without exception.
> I think the real problem is cutting down the initial 1000 CVs no ?
Yeah that's a time sink. Most applicants are unqualified. Good ones tend to stand out immediately though. Whatever you're after, you can find someone with the exact requirements you asked for.
Yes you can! The "mix" part is key. It's the sequential learning which screws up networks today. If you randomly sample from tasks you're fine, or if you can replay older tasks while you're learning new ones (essentially another form of random sampling) the network can learn multiple tasks. But the moment you drop a task from a distribution of training data you're going to start losing competency on it. By default neural networks don't have mechanisms to protect data (weights) from being over-written.
Even with some traction/users/conversion/revenue, and a grand long-term vision, a suggested 15%-25% dilution [1] gives $4-10M valuation. Outside SV, this is already Series A valuation. Any thoughts ?
[1] https://blog.ycombinator.com/how-to-raise-a-seed-round/