TheAceOfHearts

Does anyone have advice for getting it down? I feel like no matter what I mix it with, it grosses me out and it becomes extremely challenging to get it down. I've tried pouring the dry powder in my mouth and just chugging it down quick as well as mixing it with various liquids, but they sandy texture makes me gag. I've managed to sustain taking creatine for a while but it never gets any better.

I was recently talking to someone about that! I wasn't sure if it was my imagination, but I felt like Opus 4.6 was way more diligent about looking things up online and making sure that its response was accurate. While Opus 4.7 seems content to just throw out an answer as quickly as possible with little care for accuracy; I started to always remind it to do an online search and to double check its work, to the point where I had to add a custom memory.

That reminds me, do skilled players actually use the tilt keys? I remember being confused for years as to the purpose of tilt keys because I hadn't used a real pinball machine, and I can't remember it nudging the ball enough to merit the risk.

It's good, I have this song I generated last year with Suno which stuck with me and I just tried having Flow generate a variant and it was acceptable. Sometimes the lyrics get modified for no reason. It would be better if you could control emphasis by specifying tags or something along those lines, but it seems fun to play around. If there was an intermediate step where a symbolic or partial processing of your input was shown for tweaking, it would be immensely powerful.

One of the key issues that I encountered after a few song generations is that it feels very rushed, like it's constrained to this 3 minute limit per song so it forces every section of the song to conform to a very specific structure. I tried increasing the limit to 4 minutes but it still gave me 3 minute songs.

Honestly, I feel like this product is showing up a bit late to the party and it's not really feeling particularly innovative. There's nothing egregiously bad about it, but it doesn't seem to add anything new or special that I could notice.

I don't have a microphone hooked up so I can't try the voice interface, but it would be really fun if you could sing to it in order to iteratively compose a song. It could clean up your voice a bit and add music. Or being able to hum out a beat which it converts into a track which you slowly build up. Is anyone able to try if those capabilities are possible with the existing product?

Overall, I'm not sure if a chat interface is the best way to produce a song. It feels very restrictive to have full songs as the primary iteration mechanism. In a text file and in code you can inspect or modify different sections or components very easily. I think a more human-focused tool would provide an on-ramp towards full music production, where you can focus on the parts that you care about and enjoy, while the AI tool fills the other parts with sausage. Right now you can chat with the tool but it appears to be quite limited in the kind of changes that it can make.

It would be quite outstanding if MIT Plasma Science & Fusion Center released their core courses on OpenCourseWare. Considering the potential impact of this technology and how much it's needed, humanity doesn't seem to be trying that hard to make it work.

Gemini is great, but when I last tried it it wasn't as good as Claude Code with agentic workflows. When I tried Antigravity is was very unreliable, like the tooling had yet to catch up to the model such that it wasn't able to fully leverage the model's intelligence and capabilities. I think it comes down to how you're using the models, so I'll ask: how are you interfacing with the LLM?

Well, there's layers. When I started using nixOS I read through the guide and wiki but I also used LLM assistance to help create a stable starting point. Then over time I've incrementally added new things to my configuration through a mix of LLM assistance and reading online material.

I think the initial migration towards nixOS is the hardest point, since it requires learning a bunch of new things all at once in order to get the system into a usable state that matches your expectations and preferences. The key benefit of using an LLM is that it makes it really easy to get your system into a useful initial state, and then you can safely learn and experiment incrementally with a mix of tools.

When I started off I didn't understand everything, but at this point I feel I have a very good understanding of everything in my configuration file.

Replaceable cables have always been a high priority for me. I've been using SHURE SE215 for almost 2 decades at this point.

Pokemon cards have gone full circle, GameStop now has an online service where you can gamble on cards digitally just like lootboxes. You buy a roll at different price points to win a PSA graded card from a set of probabilities, and then you can sell it back for 90% market value to GameStop or have them ship it to you.

The proliferation of gambling over so many domains has radicalized me against it in a way that I didn't think would've been possible a few years ago.

I've been saying this for a while, but if I had to use Grok for anything programming-related I'd feel very sad and unproductive. I was playing around with a local TTS model codebase but having some issues getting it to work, so I tried explaining the problem to all the major models to see how they performed. Grok performed the worst by a significant margin, and the worst part was that it easily became stuck trying minor changes that didn't solve the key problem.

If we are to take any claims of Recursive Self Improvement seriously at all, then having a competent coding model seems like a key asset where you need to guarantee that you're remaining competitive. Why wouldn't you make coding models a top priority if you expect it to ultimately help your internal teams become more productive and effective?

There's also not an unlimited supply of researchers and engineers for them to keep burning through people at the rate at which they've been working. Although I guess for people with short timelines it makes sense to sprint hard, while people with longer timelines are more likely to treat this as a marathon. Maybe the years of burning bridges and developing such a toxic reputation are finally catching up to Elon. I think part of the harm that Elon has done is framing all the work in xAI as engineering while being highly dismissive of research, but a lot of research requires running experiments or thinking about problems and exploring them for long periods of time. If you're just grinding out work nonstop you don't really have time to let your mind wander and explore new ideas.

Honestly, I'm surprised they've done such a terrible job with programming. I remember around summer last year it was quite apparent how far behind they were with coding tools, but Elon was posting about taking that domain a bit more seriously. Why didn't any of those efforts materialize into real outputs? Something must be truly dysfunctional inside of xAI for them not to be shipping anything at all, especially considering Elon's propensity to ship undercooked products while continuing to iterate on them, as he has done in many previous cases.

I've noticed that Elon has also gone very hard on social media posting a ton of criticisms against the other big AI company CEOs like Daario Amodei. This suggests to me that he must feel very threatened, otherwise he wouldn't be resorting to such childish behavior. He must feel incredibly frustrated that no amount of money is able to make him more competitive within the AI space.

Surely any sane person vibe coding a note taking app just has it save all the notes as markdown files to disk? At that point making a backup is trivial and they're unlikely to get corrupted.

I vibe coded a tiny MUD-style world sim where LLMs control each character. It's basically a little toy sandbox where LLMs can play around. There's no real goal to this, I just thought that it would be fun, like a more advanced tamagochi.

One of the issues I encountered initially was that the LLMs were repeating a small set of actions and never trying some of the more experimental actions. With a bit of prompt tweaking I was able to get them to branch out a bit, but it still feels like there's a lot of room for improvement on that front. I still haven't figured out how to instill a creative spark for exploration through my prompting skills.

It has been quite exciting to see how quickly a few simple rules can lead to emergent storytelling. One of the actions I added was the ability for the agents to pray to the creator of their world (i.e. me) along with the ability for me to respond in a separate cycle. The first prayer I received was from an agent that decided to wade into a river and kneel, just to offer a moment in stillness. Imagining it is still making me smile.

Unfortunately, I don't have access to enough compute to run a bigger experiment, but I think it would be really interesting to create lots of seed worlds / codebases which exist in a loop. With the twist being that after each cycle the agents can all suggest changes to their world. This would've previously been quite difficult, but I think it could be viable with current agentic programming capabilities. I wonder what a world with different LLM distributions would look like after a few iterations. What kind of worlds would Gemini, Claude, Grok, or ChatGPT create? And what if they're all put in the same world, which ones become the dominant force?

Hypothesis: limiting usage / tokens could have a positive effect on project quality, since it forces the developer to think more carefully about the problems they're working on. When you're forced to stop and slow down, you try to be more deliberate with token usage. But if you have unlimited tokens you can just keep generating infinite lines of code without thinking as hard about the problem.

I've seen people on social media bragging about how they're able to produce a mountain of code as if this was praiseworthy.

Well, I'm currently reading through "Designing Virtual Worlds" by Richard Bartle. He's known for being one of the creators of MUD (multi-user dungeon). I'm not far along enough to make a judgement on the quality of the contents, but I keep seeing the book title pop up everywhere so it seems important.

Since we're on the subject of waste removal, most mammals also pee for roughly the same amount of time [0], around 20 seconds. If you look up a video of an elephant urinating, it's quite the spectacle and the flow is voluminous.

[0] https://www.nationalgeographic.com/animals/article/mammals-p...

That's really cute, it reminds me that Will Wright (creator of The Sims) has referenced this book "The Ants", by Bert Holldobler in multiple occasions as a key inspiration for his games (and in particular SimAnt) and systems thinking. Did you come across that during your research phase or had you not heard about it? I haven't read it yet, but maybe someday I'll get around to it.

I think the desire is that in the long-term AI should be able to use any human-made application to accomplish equivalent tasks. This email demo is proof that this capability is a high priority.

This guy's videos were immediately going viral after the conflict began. I enjoyed and found them educational, but I'm taking all of his claims with a grain of salt because I also don't know much about the region or its history. He talks very authoritatively which makes for compelling storytelling but conflicts of this magnitude require much more context to really understand.

For context, there's been a massive project to produce as close to perfect of a color-corrected version of Dragon Ball and Dragon Ball Z. It can be found online in traditional anime torrenting sites. It's really an outstanding labor of passion and a true testament to the global community's love for this series.

I'd imagine that there's some discussion about how to make the most out of the tool as well as discussion of experiments and capabilities. I'm not even sure what exactly "Microsoft Copilot" entails anymore because of the multiple rebrands, but having a place where you can discuss exploring plugins and other adjacent features seems useful.

Not quite the same, but recently I was recently looking around for communities centered around Claude Code for discussion about people's workflows as well as discussion about what plugins people are using and if they notice it making a significant difference.

Since the technology is still evolving, having an active community can help you discover new patterns and explore the space more effectively.

Colin and Samir have some really in-depth videos with MrBeast which help document and explain his rise in fame, influence, and prominence. He's one of the most dedicated optimizers of our time, and he's been responsible for shaping the YouTube meta for years at this point. At this point a significant portion of his brain is probably fully allocated towards optimizing for the most engaging YouTube videos possible. The "24 hours with MrBeast" video helped contextualize his fame to me, it's really rock-star level. It's a shame that not many people engage with him on a more technical level, I think he would have a lot of interesting insights over which to nerd out about.

Yeah, many podcasts are either: (1) an advertising platform for a guest's new book, (2) a platform for the guest to play their "greatest hits" without engaging critically or exploring new ideas, or (3) a platform for the host to tell you their half-baked opinion about $CURRENT_EVENT in order to keep the slop machine running.

Conversations With Tyler: he tends to ask some of the most creative and interesting questions. For a specific episode recommendation, I really enjoyed "Donald S. Lopez Jr. on Buddhism". He also has an older interview with Paul Graham (pg), but I don't think the questions were as deep or challenging.

Dwarkesh Patel: he gets extremely high quality guests and he doesn't just roll over completely when the guest makes a claim, at least he's willing to ask follow-up questions. His guest lectures with Sarah Paine are outstanding for helping to contextualize your understanding of the world order of the past 100 years from an American perspective.

Wookash Podcast: very technical and focused on more advanced programming topics. For specific episode suggestions I suggest the recent ones with Anton Mikhailov where they talk about ~~ECS~~ arrays of things.

Two's Complement: a podcast by the guy who made the Godbolt Compiler Explorer. It doesn't release very frequently but it provides interesting perspectives. Just

Ezra Klein Show: this is one of the guys that wrote the Abundance book, which I think was a much-needed message. Most recently he had an interview with Clark from Anthropic, but it's from a fairly normie / non-AI-obsessed perspective.

I have to rant about podcasts:

My biggest issue with most podcasts is that it often feels like there's very little effort put into preparing for the discussion and there's not many interesting follow-up questions. I think you can challenge people's claims in good faith to make for more interesting discussions. At least ask some reasonable follow-up questions when the guest makes outrageous claims! A lot of podcasts are just an advertising platform for people to talk about their new book; if you can listen to a guest give the same conversation with a different host then that's probably a sign that the questions are bad and shallow, so you shouldn't keep listening to that podcast.

One of the issues with asking deeper questions is that anything truly interesting or new will probably require having thought about the topic a lot ahead of time. Otherwise you just end up getting a very shallow answer because people can't usually think through complex topics on the fly so the best you can hope for is to get a pre-cached or partially computed answer. It would be great to have a podcast dedicated to exploring more challenging and underexplored questions which are shared with guests ahead of time so both parties can have time to think and explore. Most famous people just go on podcasts to play their "greatest hits" without saying anything substantially different or new.

I think vibe coding something and showing it off on Show HN is probably fine, but it boils my blood when people cannot even be bothered to write the post body themselves. If someone is using an AI generated post body and title that's usually a clear signal of slop for me. The post body is supposed to be part of the human connection element!

A minor correction, but Atlassian was founded in Australia, and their global headquarters is still in Australia.

For me the biggest benefit from using LLMs is that I feel way more motivated to try new tools because I don't have to worry about the initial setup.

I'd previously encountered tools that seemed interesting, but as soon as I tried getting it to run I found myself going down an infinite debugging hole. With an LLM I can usually explain my system's constraints and the best models will give me a working setup from which I can begin iterating. The funny part is that most of these tools are usually AI related in some way, but getting a functional environment often felt impossible unless you had really modern hardware.

I'm worried that this will lead to a Prop 65 [0] situation, where eventually everything gets flagged as having used AI in some form. Unless it suddenly becomes a premium feature to have 100% human written articles, but are people really going to pay for that?

> substantially composed, authored, or created through the use of generative artificial intelligence

The lawyers are gonna have a field day with this one. This wording makes it seem like you could do light editing and proof-reading without disclosing that you used AI to help with that.

[0] https://en.wikipedia.org/wiki/1986_California_Proposition_65

I'll take it one step further and say you should always ask yourself if the application or project even needs a beefy database like Postgres or if you can get by with using SQLite. For example, I've found a few self-hosted services that just overcomplicated their setup and deployment because they picked Postgres or MariaDB over SQLite, despite it being a much better self-contained solution.

I find enjoyment in everything you mentioned (been reading since the Slate Star Codex days!) and I read a good mix of all book types, so I want to offer some gentle push-back. Reading fun fantasy books allows you to take your inner child and imagination out to play, not everything needs to be serious, intellectually challenging, or highly stimulating. Sometimes you have to let your imagination run free and just have fun. Holding space for your imagination to run free also opens yourself up to receiving inspiration or new unexpected ideas.

At the start of this year I read through Rick Rubin's book, The Creative Act: A Way of Being. This book wasn't telling me anything new, but it reminded me of a lot of things that I had forgotten while making me hold space for those ideas related to creativity.

Sometimes I encounter criticism of Newton for having "wasted" time studying and learning alchemy, and people lament how much more he could've gotten done if it wasn't for those distractions. But we don't know if those alchemy-related detours are load-bearing for his achievements!

The sweetest of fruits is fertilized by mountains of shit.

This comment is a bit confusing and surprising to me because I tried Antigravity three weeks ago and it was very undercooked. Claude was actually able to identify bugs and get the bigger picture of the project, while Gemini 3 with Antigravity often kept focusing on unimportant details.

My default everyday model is still Gemimi 3 in AI Studio, even for programming related problems. But for agentic work Antigravity felt very early-stages beta-ware when I tried it.

I will say that at least Gemimi 3 is usually able to converge on a correct solution after a few iterations. I tried Grok for a medium complexity task and it quickly got stuck trying to change minor details without being able to get itself out.

Do you have any advice on how to use Antigravity more effectively? I'm open to trying it again.