drusepth

What is the search bar for (that populates with other cities)? I tried both SF and Seattle and both just move the map ~50 miles away from NYC.

Does this only visualize NYC, or does it also work elsewhere?

Do those random posts have a "Reposted by (person you follow)" line at the top of them?

The two feeds on Bluesky are "Following" (only posts by people you follow show up) and "Discover" (largely dominated by posts by people you don't follow). There are two huge tabs at the top of your feed to switch between them.

If you are following 0 people, the "Following" feed acts similar to the "Discover" feed. As soon as you follow a single person, it works as you'd expect (only showing content from people you've followed).

> As is often postulated though, how would a network of rogue AIs power themselves?

Smaller and smaller models are reaching higher and higher benchmarks; the 35B I can run on consumer hardware today is better than a 605B from years ago. I bet there are also advancements reducing the power usage at each model size.

I think the answer boils down to the same answer as any other rogue software "roaming" the internet: hacked consumer devices.

Do you still trust that system when your friends-of-friends are the ones gaming the system? Given the inherent network effects of manipulating webs of trust, I wouldn't be surprised if everyone had at least one friend-of-a-friend they shouldn't necessarily trust.

> There was an absolutely insane comment on HN a few months ago where the poster said that they felt a sense of accomplishment after "producing" a song on Suno. I mean... how could that possibly be true?

They "created" something that, until now, would have required skills they didn't have. You don't see how someone could feel a sense of accomplishment for the end result, the thing they poofed into existence and like?

We use tools to make things (even art) easier to create. I don't make my paints from scratch (anymore), or string my paintbrushes (anymore), or now sometimes choose my color palettes or general composition -- tools (like genAI) exist to let artists create art easier, and saying "you didn't put in enough thought/work/etc for it to count as art!" feels dismissive of the creative process and the joy people find in expressing themselves, regardless of how they got there.

3. Off-by-1 errors

I think those of us drawn to Perl by its beautiful name (and potentially-art syntax...) have long since migrated to Ruby, for better or for worse.

LLMs have been a personal tutor to me for the last year, able to explain anything and everything I've been curious about professionally and personally. I changed jobs to new technologies in large part because I effectively had an assistant able to help cover any gaps in knowledge I had, train me up quickly, and offer ongoing help on the job.

They can make stuff up, but saying "60% of the time they lie to you" hasn't been true for years.

What's the difference between the two? I can log into my laptop with a password or a PIN; I assume anyone that steals or hacks my laptop can _also_ log in with a password or a PIN. PINs are inherently shorter and more simpler than passwords; why would anyone use a PIN over a password?

We're preparing to use video generation (specifically image+text => video so we can also include an initial screenshot of the current game state for style control) for generating in-game cutscenes at our video game studio. Specifically, we're generating them at play-time in a sandbox-like game where the game plays differently each time, and therefore we don't want to prerecord any cutscenes.

Technically, they also demand you have a computer, internet access, and enough education to be able to read. I'd also still call it "free" though.

Why is that a huge advantage over AI competitors? Just not having to fight for limited Nvidia supply?

We actually had almost the exact same thing happen to Notebook.ai last month:

- automated notice of trademark infringement from some posted user content, accusing us of "fraud and phishing" (filed by a third party on behalf of Meta)

- that user content was immediately deleted upon receiving the notice

- exactly a week later, our host (Heroku) banned our account with a generic no-reason "Your account has been banned."

Total downtime of about 24 hours until it was resolved; luckily, Heroku's support simply unbanned the account whenever I reached out to ask why we were banned. Migrating to another host wouldn't have taken much longer, but would have been a pain.

Goes to show layering a couple automated processes together can have pretty devastating false-positives. I'm glad there was a human in the loop at Heroku I could reach to get things sorted out relatively quickly; also glad to see Itch.io is back up and got it sorted out relatively quickly as well.

Ironically, the freelance consulting world is largely on fire due to the lowered barrier of entry and flood of new consultants using AI to perform at higher levels, driving prices down simply through increased supply.

I wouldn't be surprised if AI was also eating consultants from the demand side as well, enabling would-be employers to do a higher % of tasks themselves that they would have previously needed to hire for.

>This plan might be beneficial to e.g. CEO-types, but I question who at OpenAI thought it would be a good idea to lead their 12 days of hollowhype with this launch, then; unless this is the highest impact release they've got (one hopes it is not).

In previous multi-day marketing campaigns I've ran or helped ran (specifically on well-loved products), we've intentionally announced a highly-priced plan early on without all of its features.

Two big benefits:

1) Your biggest advocates get to work justifying the plan/product as-is, anchoring expectations to the price (which already works well enough to convert a slice of potential buyers)

2) Anything you announce afterward now gets seen as either a bonus on top (e.g. if this $200/mo plan _also_ includes Sora after they announce it...), driving value per price up compared to the anchor; OR you're seen as listening to your audience's criticisms ("this isn't worth it!") by adding more value to compensate.

I started incorporating LLMs into my workflows around the time gpt-3 came out. By comparison to its performance at that point, it sure feels like my junior is starting to become a senior.

Yeah, my best guess is they're probably including the previous N frames as context into generating the next model. This works to preserve continuity over a short amount of time (as you say, briefly looking at the ground and then back up), but only a short period of time.

For these kinds of models to be "playable" by humans (and, I'd argue, most fledgling AI agents), the world state needs to be encoded in the context, not just a visual representation of what the player most recently saw.

We generate 2d art, 3d models, some other in-world data, and soon animations at our game studio. The huge problems of generating pure pixels without a persistent game state behind it is illustrated well by the recent MinecraftAI craze (where it's a cool demo, but absolutely unplayable for anything other than novelty), and exacerbated on the dev side by missing out on tons of "free" stuff you get from existing engines that already do almost every kind of physics ops for you.

The company was formed as Niantic Labs in 2010 as an internal startup within Google, founded by the then-head of Google's Geo Division (Google Maps, Google Earth, and Google Street View).

It became an independent entity in October 2015 when Google restructured under Alphabet Inc. During the spinout, Niantic announced that Google, Nintendo, and The Pokémon Company would invest up to $30 million in Series-A funding. Not sure what the current ownership is (they've raised a few more times since then), but they're seemingly still very closely tied with Google.

> It is rather about improving some vision models to predict how the backside of a building looks, right?

This, yes, based on how the backsides of similar buildings have looked in other learned areas.

But the other missing piece of what it is seems to be relativity and scale: I do 3D model generation at our game studio right now and the biggest want/need current models can't do is scale (and, specifically, relative scale) -- we can generate 3d models for entities in our game but we still need a person in the loop to scale them to a correct size relative to other models: trees are bigger than humans, and buildings are bigger still. Current generative 3d models just create a scale-less model for output; it looks like a "geospatial" model incorporates some form of relative scale, and would (could?) incorporate that into generated models (or, more likely, maps of models rather than individual models themselves).

I potentially like the concept, but it's kind of hard to take serious when you open the page and are immediately greeted by a large-busted anime girl (and an animated ticker spanning the bottom of the page, full of zoomed-in crops of said busts).

> What are your investment areas?

> Memes, for now.

Oh, I guess it actually is a joke?

Edit: Oh, it's managed by "Marc AIndreesen" [sic], not "Marc Andreesen". If not a joke, seems like a scam (especially now that I realize they're selling some kind of crypto coin with it...). Yikes.

"Popular" tweets (of which these bot accounts often fall into, because they're propped up by bot responses and engagement farming) are pushed into your feed even if you're not following (or engaging) with them.

What makes you think the FBI hates Trump?

> I've always dreamed of full blown sandbox games with extremely advanced NPCs (which the current LLMs can already kinda emulate)

The future of gaming is going to get weird fast with all this new tech, and there are a lot of new mechanics emerging that just weren't possible before LLMs, generative AI, etc.

At our game studio we're already building medium-scale sandbox games where NPCs form memories, opinions, problems (that translate to quests), and have a continuous "internal monologue" that uses all of this context plus sensory input from their place in a 3D world to constantly decide what actions they should be performing in the game world. A player can decide to chat with an NPC about their time at a lake nearby and then see that NPC deciding to go visit the lake the next day.

A paper last year ("Generative Agents: Interactive Simulacra of Human Behavior", [0]) is a really good sneak-peek into the kind of evolving sandboxes LLMs (with memory and decisionmaking) enable. There's a lot of cool stuff that happens in that "game", but one anecdote I always think back to is this: in a conversation between two NPCs, one happens to mention they have a birthday coming up to the other; and that other NPC then goes around town talking to other NPCs about a birthday party, and _those_ NPCs mention the party to other NPCs, and so on until the party happened and most of the NPCs in town arrived on time. None of it was scripted, but you very quickly start to see emergent behavior from these sorts of "flocks" of agents as soon as you add persistence and decision-making. And there are other interesting layers games can add for even more kinds of emergent behavior; that's what we're exploring at our studio [1], and I've seen lots of other studios pop up this last year to try their hand at it too.

I'm optimistic and excited about the future of gaming (or, at least some new genres). It should be fun. :)

[0] https://arxiv.org/abs/2304.03442

[1] https://www.chromagolem.com/games

I'm glad there are different kinds of podcasts for different people now.

I've always absolutely hated the focus on the individual humans and their personalities behind the podcast, and wished they'd be a better source of well-structured "information".

I never listened to a podcast I didn't get frustrated with, even at 2x speed. These NotebookLM podcasts have been exactly what I've always wished podcasts were.

I'm glad that Kagi (and others) exist as an alternative for people who don't want generative AI in their searches.

Personally, I'm excited about more generative AI being added to my search results, and I'll probably switch to whichever search engine ends up with the best version of it.

I hate podcasts because they're so often focused on the speakers' personalities and windy, undirected things. I've tried to listen to so many podcasts and always dip an episode or two in because they devolve into people just chatting instead of actually presenting well-organized facts about what I want to listen to / learn about.

The structure and bare-minimum "human" aspect of this seems perfect for people like me to actually get into podcasts. I do wish I could further cut out all the disfluencies (um, like, uh, etc) though.

The only barrier for me IMO is wondering how accurate those facts actually are (typical research-with-AI concern).

I'm very much looking forward to a more interactive form of this, though, where I can selectively dive deeper (or delve ;) ) into specific topics during the podcast, which is admittedly very surface-level right now.

If this is the case, I imagine it'd be pretty easy to spoof your UA and see the demo, even from Chromium.

Scrapers have always been notoriously brittle and prone to breaking completely when pages make even the smallest of structural changes.

Scraping with LLMs bypasses that pitfall because it's more of a summarization task on the whole document, rather than working specifically on a hard-coded document structure to extract specific data.