HN user
Really cool concept but so much of the data is wrong. Anthropic ARR is an order of magnitude higher, Replicate did a Series B as well which is not mentioned. There is probably a lot more.
Surprised this isn't getting more attention. It is one of those papers that is very elegant and simple, yet very effective.
Seems like the best way to monetize this. Doubt anyone will regularly pay for the website and banner ads are annoying. Buying a VPN is the logical next step if you find a movie in a different country, might be nice to have multiple affiliate links but this seems like a win-win, it makes it easier to get a VPN for someone who isn't too familiar and the creator earns a bit for their work.
Interesting that they haven't release DBRX MoE-A and B. For many use-cases, smaller models are sufficient. Wonder why that is?
This guide (and most other guides) are missing a massive tip: Separate the crawling (finding urls and fetching the HTML content) from the scraping step (extracting structured data out of the HTML).
More than once, I wrote a scraper that did both of these steps together. Only later I realized that I forgot to extract some information that I need and had to do the costly task of re-crawling and scraping everything.
If you do this in two steps, you can always go back, change the scraper and quickly rerun it on historical data instead of re-crawling everything from scratch.
I'm using a multi-modal LLM to extract floor sizes from property descriptions and floorplans. Working to expand this to other information such as the floor level, if the property has an open plan kitchen etc. (Working on flats.fyi)
Looks really interesting but its a shame that it's primarily built around text only. There has been a lot of research around multi-modal LLMs, any plans to support those?
This looks really cool. Does your API also support follow up questions and a longer conversations?
Do you run Vicuna locally or have you had any success in deploying it somewhere? I have been thinking of using a fine-tuned model but haven't found anything cost effective where I cab deploy it. You either run the machine where it's served consistently and the cost is in the hundreds or you accept extremely slow starts.
Why did you decide to use both OpenAI and Bard?
Shame you have to enter your credit card details before even being able to try it. This discouraged me from even signing up.
My cousin worked in finance but then due to a health issues he was not able to look at screens (or artificial light in general) for extended periods of time.
He was forced to switch to another profession which had to be outdoor based to avoid artificial light and doesn't use any screens.
He decided to train dogs. Initially it was a bit rough (working long hours a day Monday to Saturday) but fast forward 2 years later he is now considered to be one of the best dog trainers in his area. This allowed him to triple his prices and reduce his working hours. He now earns more than he did in his finance job working shorter hours.
If you find your niche and become an expert in that area, I think you can earn a good living no matter what that niche is. But some niches make it easier than others as the base earnings are higher.
I have found that self-taught programmers are better at debugging as they frequently had no one to turn to when learning as compared to someone who started studying in university. They are frequently also more passionate about programming than someone who just studied at school to get good grades or to secure a job.
But agree with other comments that if you are completely self-taught you will likely miss some fundamental knowledge which is crucial when you go from working on small side-projects to building large systems.
Loving Deepnote so far. Being able to seamlessly collaborate with others during the pandemic is a lifesaver!
It would be great if you had automatic versioning similar to Google Docs, using Git with notebooks is a nightmare.