qiongzhouh

OpenAI says in their terms that you can't "use output from the Services to develop models that compete with OpenAI" [0], and it seems that people are interpreting it as training a model that directly competes with them, which we aren't doing. There are many companies out there built on using GPT-4 outputs to do task-specific fine-tuning, so it doesn't seem like it's a problem unless we were trying to make competing foundational model from GPT outputs.

(I'm not a lawyer, so this needs to be taken with a large grain of salt)

0: https://openai.com/policies/terms-of-use

We've looked a bit into CR and Wirecutter, not that deeply into CR yet though. I definitely used Wirecutter for a bit of things in the past, and they have a high level of trust that we'll need to seek to replicate.

I think this is a very good point. We've focused a lot on correctly matching reviews with products / brands, but haven't taken hard enough of a look at astroturfing.

Definitely feel this way too. Sometimes I think to myself that it'd be really great to have an LLM give me a well researched report on say like, recent trends on undisclosed marketing online, wished that we supported that on Lumona, but realized that we'll have to do it eventually, but pretty tough with the current infrastructure

We're working with dumps of Reddit data, which means we don't have to use their API or do any scraping on Reddit itself for now. The data is updated monthly though, so we'll have figure out how to get higher quality data for things that are more time sensitive. We're in contact with the folks at Reddit, so we'll try to see if there are ways to get better data later on.

True, I think I would agree with most of this sentiment. Unfortunately I'm not doing many of these things and am still using my skincare products.

Perhaps we should be surfacing opinions like this beyond just products.

Sorry about that, we didn't make it clear initially that Lumona only has skincare products for now, we'll be working to scale it beyond these products soon, but that message about skincare was probably not clear enough from our post

Wow, thanks for sharing this. I find it interesting that they chose to make it something that I have to wait 1-2 minutes for before I get my AI generated article.

Seems to do a good job for various types of research, will give it a try next time I'm curious about something and need it researched

That's a really good point. I think in our current iteration of the system, if we applied it to subreddits focused specifically on a particular brand, it would not be able to account for the bias there, even if it knows which subreddit the content is from. That's probably too much to ask of the LLM.

We'll have to think about good ways to handle this. Curious about your or others thoughts on these subreddits, how do you process content on these subreddits differently?

Do you have any pointers for learning more about this space? I've personally been pretty skeptical of sponsored products on YouTube, though I find myself getting tempted to / actually trying them out anyway, but haven't thought too hard about small Redditors or Tiktokers getting paid to shill products.

Curious what companies do this / how companies are going about conducting these unpublicized marketing campaigns?

Wow, that voice on the page sounds exactly like what I hear on TikTok / Instagram all the time. Definitely evokes the feeling that I'm about to be entertained by something.

Thanks for sharing that, we'll have to think hard about how to measure the quality / realness of content online beyond the simple things like upvotes and subscriber count

For now, it's just removing AutoModerators and things labeled as bots. Now that I'm reading this again, I realize doesn't really help, since bots pretending to be people recommending products, don't get filtered out.

Sorry for the confusion, we'll try to have general products soon.

I just pushed a change to give an error message explaining what's happening for non-skincare related searches.

I think that's what makes skincare interesting. We want our system to be able to understand your goal, lifestyle, budget, ... and pick out which product is the best for you, given what others who have used the product before said.

With less of this information, the ground truth would probably related to how popular the product is or the average sentiment of people reviewing the product. With this information though, you can compare each one to see which best fits the user's needs. Having compared enough products, you'll eventually figure out which one is the best.

The missing part of the story is when we made an early prototype using GPT-4, leaving it on overnight, and realizing that we've spent several thousand dollars of OpenAI credits...

https://www.reddit.com/r/BuyItForLife/comments/15b4iks/best_... This one seems to be a good thread. Hopefully we'll have it on Lumona soon.

r/SkincareAddiction Out of all posts comments from 2023:

and: #1 skin: #23 acne: #55 because #97 actually #263

You're right that there are some very effective prescription treatments that aren't shown, but it doesn't seem like prescription acne treatments are the usually the appropropriate / doctor prescribed choice for most people facing mild to moderate acne.

Personally, my pediatrician told me that acne is just something that happens to teens and recommended that I go try some acne washes from the drugstore instead of prescribing something like Tretinoin which could have some pretty intense side effects.

Reading r/SkincareAddiction has been really helpful for me, especially seeing the range of experiences that people have had, and that's why we made Lumona summarize these results.

What's happening here is that we put your search query into a model that tries to figure out what skincare product characteristics (e.g. Vitamin C, Retinol, etc) would be good for you, but when it sees something that isn't a skincare product or a skincare concern, it gets confused and doesn't return anything.

I'll put in an error handler for this soon.

Hmm, that's interesting. I've been getting a lot of Instagram and Tiktok reels with the robotic TTS voice nowadays, I've just been assuming that it's a funny thing that people do so that they don't have to record their own voice.

Wondering how / if we should be filtering out this content now that you can make TTS voices that sounds like they're completely real

We are not paying for Reddit's API to get our data, there are some really good and complete and publically available dumps of Reddit data available online. We are in contact with the folks at Reddit, which is of course a YC company, so they're aware of what we're doing.

As a user of our product, I'd really hate it if we were recommending crappy products. I suspect users will also feel the same and this thought will hold us accountable.

For now, we're excluding Reddit posts that are clearly automated and making sure the YouTube content is not sponsored, which you are required to disclose by the YouTube ToS.

We'll have to dig deeper into not to filter out spammy reviews. I can imagine analyzing a user's post history or detecting if content was clearly GPT written, but it's hard to really tell. I know there things like Amazon review analyzers out there, but we'll have to learn more about this. I wonder if the people of HN have any suggestions on this front.

There'll probably be a lot AI generated reels that look like they're from real people online soon too. I wonder what platforms like Tiktok and YouTube will do about this. If this ends up being a huge , we can probably try to use ML methods to check if the video was filmed in the real world

Thanks for trying it out!

As for the performance issues, we're looking into several things that could speed things up - Fine-tuning a small LLM for the results on the intermediate page and deploying on a provider with higher throughput and time to first token - Admittedly, there there are quite a few SQL query / index optimizations we need to make on the backend, along with making parts of our pipeline async - The frontend itself is also not very performant right now, but we're working on it.

We cache previous calls to the API, so that's why the demo queries or queries others have tried before you are faster. I'll ship a change that makes the results more consistent but not fully consistent later today.

As for the ingredients, citing sources is definitely a next step. In the meantime, I recommend looking up the ingredients that catch your eye on a place like EWG Skin Deep if it's a huge concern for you (I used to do this to make sure my ingredients weren't comedogenic for acne).

Great point about the distributor list UI, we'll think about a better way to show it!