mscbuck

To be fair, there is a different way to get to Mohg. You can talk to Varre at the Rose Church in the Lakes of Liurnia, and he gets you on the quest line that gets you there. You basically have to invade 3 (i think) people's worlds, PvP, doesn't matter if you win or lose, or there is one NPC that you can do an invasion on in Altus Plateau. Then he'll give you an item that just needs to be soaked in the blood of a maiden (and it's made explicit what you need to do, not just left for you to figure out). After that you get the letter and he will take you to Mohg.

I'm lucky enough to be able to send my child to day care where he doesn't get any screen time (obviously), so typically his only time he gets to watch something is when we are out and about, and even then we have a rule of timers before he can watch, or if we are at a tap house or something, we've made him actually have to sit and talk to people/friends, ask them how they are doing, introduce himself, etc. Once he does that, he can choose a Pixar movie of his choice or a live concert video to watch.

And even with all that, I still feel guilty due to the reddit mob telling me it's going to destroy his brain.

Yup, the advice is geared towards being very conservative, rather than lenient. An example I like to give people is that here in Wisconsin, drinking culture is huge. A friend of mine's father had pancreatic cancer and went to see his doc and wasn't given too much time to live. He was a big fan of having a nice glass of scotch with his fish fry, so he asked if it was still okay to have it, especially with how much time he was given. The doctor was like: "I have to tell you no, it's not okay. But the reason why is because if I tell my other patients that they can have a drink on "special occasions", well, suddenly, Monday becomes a special occasion, and Tuesday becomes a special occasion, and you see where this is going."

I think that'd be cool, but I'd say that Claude Code/Codex is often used for this exact thing and they do a decent job of it (at least in my experience with R). Usually once I've kind of wrapped up my model or data work I'll just ask "okay, now organize this so it makes sense", and it usually does a great job at organizing the helpers, etc.

Not that TIOBE or PyPl are the end all be all, but R was in the Top 10 for the first time since 2020 and PyPl has it at #4. A lot of people use R in 2026, because it's still great for data science work, "tidy" language is still fantastic for working with data, and also it's caught up to Python in almost every way when it comes to putting models into production. Both are great "orchestrator" languages, and I've put both into production on sites that get hundreds of thousands of hits a day.

In my opinion, RStudio is still the best data science IDE and it's not even close. I've been using Positron a bit more lately just for Claude Code reasons, as I prefer having the pane itself rather than using the terminal, but man it's really tough to shake RStudio. Even with the work put into configuring VSCode to get it kind of close to it, it still just always feels a bit janky.

Yeah, once you move onto legitimate business evaluation metrics (where Precision@k or Recall@k don't actually fit your business model without modification), GPTs just seem to suffer without context, and hey, knowing the context is part of what gives a data scientist his value.

I still feel like they are in an incredible position when it comes to AI because of their hardware integration/advantage across all of their devices. I think they see immense value in getting things on-device and not having to rely on any of these other companies.

From what I saw in the latest "language" surveys or whatever, R does seemingly seem to be making a slight comeback. I was actually surprised at its place above Ruby, iirc. Again, not that these surveys are the end-all-be-all, but I've also started to see a lot more data science postings that have R or Python be a requirement, where I feel like for a few years it was ALL Python.

Yes, I've absolutely noticed this. I feel like I can always tell when something is up when it starts trying to do WAY more things than normal. Like I can give it a few functions and ask for some updates, and it just goes through like 6 rounds of thinking, creating 6 new files, assuming that I want to write changes to a database, etc.

Awesome site and speed!

My advice from someone who has built recommendation systems: Now comes the hard part! It seems like a lot of the feedback here is that it's operating pretty heavily like a content based system system, which is fine. But this is where you can probably start evaluating on other metrics like serendipity, novelty, etc. One of the best things I did for recommender systems in production is having different ones for different purposes, then aggregating them together into a final. Have a heavy content-based one to keep people in the rabbit hole. Have a heavy graph based to try and traverse and find new stuff. Have one that is heavily tuned on a specific metric for a specific purpose. Hell, throw in a pure TF-IDF/BM25/Splade based one.

The real trick of rec systems is that people want to be recommnded things differently. Having multiple systems that you can weigh differently per user is one way to be able to achieve that, usually one algorithm can't quite do that effectively.

Will echo that one thing that would prevent me from trying this is def the source control. Otherwise it does look pretty slick!

I have also anecdotally noticed it starting to do things consistently that it never used to do. One thing in particular was that even while working on a project where it knows I use OpenAI/Claude/Grok interchangeably through their APIs for fallback reasons, and knew that for my particular purpose, OpenAI was the default, it started forcing Claude into EVERYTHING. That's not necessarily surprising to me, but it had honestly never been an issue when I presented code to it that was by default using GPT.

As laughable as Apple's efforts have been so far, I think they still have an advantage precisely because of the unified architecture.

I've found his hybrid approach pretty good for the majority of use cases. BM25 (maybe Splade if you want a blend of BOW/Keyword), + Vectors + RRF + re-rank works pretty damn well.

The trick that has elevated RAG, at least for my use cases, has been having different representations of your documents, as well as sending multiple permutations of the input query. Do as much as you can in the VectorDB for speed. I'll sometimes have 10-11 different "batched" calls to our vectorDB that are lightning quick. Then also being smart about what payloads I'm actually pulling so that if I do use the LLM to re-rank in the end, I'm not blowing up the context.

TLDR: Yes, you actually do have to put in significant work to build an efficient RAG pipeline, but that's fine and probably should be expected. And I don't think we are in a world yet where we can just "assume" that large context windows will be viable for really precise work, or that costs will drop to 0 anytime soon for those context windows.

I think generally I agree with you that this is a stepping stone towards bigger/potentially more important things......but that doesn't change the fact that they've packaged it to consumers as something that seems like it has, at best, close to zero utility and at worst has incredible downsides. I'm not sure why releasing this to consumers helps achieve those goals.

I can't help but see these technologies and think of Jeff Goldblum in Jurassic Park.

My boss sends me complete AI Workslop made with these tools and he goes "Look how wild this is! This is the future" or sends me a youtube video with less than a thousand views of a guy who created UGC with Telegram and point and click tools.

I don't ever think he ever takes a beat, looks at the end product, and asks himself, "who is this for? Who even wants this?", and that's aside from the fact that I still think there are so many obvious tells with this content that make you know right away that it is AI.

And if you still prefer the language of tidyverse, use tidytable and you get the best of both worlds!

This is really a non issue now. R's problem back in the day was that it was really specialized in analysis and interactivity, but a lot of the general purpose stuff that made Python popular is now easily achievable in R and well-developed and maintained. RestRServe and Plumber are both excellent tools for REST APIs.

I'd love to know what the definition of "publicly available" is, because I'm guessing there's quite a bit of violation of ToS here (regardless of if you believe the info should be scrapeable or not)

I love my Comma 3X. You just need to have the right expectations. I honestly think their motto of "making driving chill" is a really apt description. I use it in traffic and on the interstate almost all the time, and then on more suburban drives in that 30-40mph range, which is where my Ioniq's HDA doesn't activate. Also IIRC the Ioniq's HDA is map based so very frequently in the city it would just straight up deactivate without any warning due to construction I'm guessing messing with maps. The lateral steering is so much better than the stock LKAS on my car which is jerky and probably scares the living shit out of other drivers. HDA2 is probably a 4/10, Comma is probably an 8/10 in terms of just general driver experience. I've done multiple long (150mi+) drives where I don't touch the wheel for nearly 95% of the trip.

The one thing I worry about though is that they really were promising a lot with the new MLSIM training architecture, and consensus (and my own anecdotal experience) is that these newer models have not been great. They've been working on MLSIM for a whiiiiiile now and there really hasn't been any improvement, though I fully endorse why they are going that way and I understand the difficulty of the problem.

With you on this one. The Pro's just never fit my ears. I tried all sorts of tips. Foam, silicon, even the ones that fit "into" the ear curve fail and leads to a really inconsistent experience.

The regular AirPods work well ENOUGH for me that when I walk I don't need anything to keep them in, but running would be an absolute no go. And I feel like they never actually "stay put" in the ear even when walking. I always have to push them in again.

Will try these new ones, but most likely will fall back to my usual AirPods.

I also really love mine. It has done what it has advertised extremely well, in my opinion. Makes driving chill. I have a '24 Ioniq with HDA2 and it's a night and day difference between Comma's implementation of HDA/LKAS and stock. If the stock version is like a 3/10, OpenPilot is like a 8 or 9/10. Stock HDA would just turn off randomly in the middle of turns. Its LKAS was very jerky which not only scares you, but scares other people on the road as well.