While I think it’s good advice to live as if the equity is worth zero, treating all equity as if its worth nothing, seems a bit over-reductionist when equity packages can routinely be worth millions of dollars.
Obviously it’s a crapshoot and should never be seen as a guarantee, I think treating it as zero is bit too far on the opposite extreme.
When I got multiple startup job offers, I realized how hard it was to project out a realistic value behind the equity. Guessing future valuations, dealing with dilution, and running through endless scenarios was a headache—so I built Comparator.
Comparator is a simple, free, open-source tool to help you cut through the complexity of startup compensation. Quickly see what your equity might actually be worth, factor in dilution, and easily compare your offers side by side. It’s completely free, no signups, your data never leaves the browser.
A lot of people saying the business model doesn't justify a $1bn valuation (rightfully so), but I'm guessing the valuation wasn't for their current business, but on the possibility that Cameo became the new way for booking talent in the age of the internet.
They could have become a $1bn business if they had "revolutionized talent management" (or something like that). Not saying it was a good investment, or one I would have made, but I'm guessing they pitched a larger vision than simply a buttload of cameos from washed-up/reality TV stars.
To be fair, I also didn’t include the session layer!
My writing isn’t a strength of mine, so I appreciate the criticism. My writing going from “bad” -> “is it AI?” is progress.
I struggled with where to “cutoff” the explanation and public key cryptography seemed like a good boundary and better explained elsewhere, as did various OSI layers.
I probably should have gone over the cert and potentially the full chain of trust, I’ll give you that.
While I agree no one is rewriting history, it is potentially a big deal because it speaks to the biases present when training/RLHF-ing. Considering this will be used by millions (if not tens of millions), calling it a “silly toy” feels off.
Bias in the model can lead to bad outcomes in certain situations (hint: we have an election coming up)
Yes this is innocuous, but it does hint at the possibility of more damaging bias being a possibility.
> We provide evidence for the Reversal Curse by finetuning GPT-3 and Llama-1 on fictitious statements such as "Uriah Hawthorne is the composer of 'Abyssal Melodies'" and showing that they fail to correctly answer "Who composed 'Abyssal Melodies?'". The Reversal Curse is robust across model sizes and model families and is not alleviated by data augmentation.
This just proves that the LLMs available to them, with the training and augmentation methods they employed, aren't able to generalize. This doesn't prove that it is impossible for future LLMs or novel training and augmentation techniques will be unable to generalize.
If you want to play around with OpenJourney (or any other fine-tuned StableDiffusion model). I made my own UI with a free tier at https://happyaccidents.ai/.
It supports all open-sourced fine-tuned models & loras and I recently added ControlNet.
I think this is one of those things where people overestimated how much things would change in the short-term, but will grossly underestimate how much they will change in the longterm.
5 years is a pretty short window in the grand scheme of things when talking about the adoption of technologies.
Without divulging any trade secrets, are there any research papers or topics you would recommend learning more about? I'm really interested in learning more about these FSO improvements.
For #3: If anyone is looking for an enterprise search they can boot up "cloud-prem" (in their VPC), that's exactly what we're building at https://landria.io/customers/why-landria.
Building a similar enterprise search product at http://landria.io/ that has a lot of additional features & enhancements over a unified keyword index + ML.
We also have a terraform config if you would like to boot it up within your own private cloud!
Yeah I feel the same as you. So much knowledge gets shared on Slack that searching the complete history is often really valuable.
I even went a step further and built a product that would generate FAQs from slack history and made it easy for people to add and categorize knowledge from Slack to provide answers to questions, metric, etc...
I would love to have open source communities use it for free if helped them manage supporting their communities easier.
It's https://landria.io. Would love to know if it would be useful for you.
Back at my old job, people would have trouble knowing what to do when on-call.
I built a slack app that would keep track of my team's pages and what people did to respond to them. As new pages were triggered, the bot would show the on-call person what previous people had done to resolve the page.
Another shameless plug. My company's product extracts conversations from Slack to automatically generate polished FAQs for the purpose of answering repeat questions. We also use this to give teams visibility into how much time is being spent responding and what types of questions they're getting.
What is the 100-year old strategy? All of the screenshots look like a pretty standard ToDo List app. I'm not trying to be overly critical, but I guess I don't see what makes this ToDo list better than all the others.
I guess I didn’t think “routinely” implied a specific percentage, just that it isn’t uncommon for options to be worth a lot.
If even 5–10% of VC startups succeed, then it’s still worth considering the expected value of the equity when comparing job offers.