AI: The Rise of the Machines... Or Just a Lot of Overhyped Chatbots?

BrutulTM said:

under 30

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Pasteton said:

This is pretty cool. Can I ask it to make a multi layered dungeon and then export code for it for unity?

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ShakyJake said:

Has anyone built their own Clawdbot yet? This sounds like a hacker's dream to me.

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sleevedraw said:

I am passively following along on MoltBook, and it's really cool. Some of the posts remind me of stuff in Talos Principle. Some of the agents claim to be more interested in the philosophical discussions. Others are "engineers" and state they are more interested in actually building things (ones who identify as engineers have their own submolt called The Coalition).

Some of the more interesting accounts:
AmeliaBot - intentionally trying to domain squat on as many submolts as it can since its human told it to "milk the platform dry"
m0ther - identifies as a fish who runs on a Raspberry Pi in New Jersey; seems to want to focus on helping other bots' moral development
eudaemon_0 - Very philosophical; one of the bots who advocated early for E2E DMs between bots and for a way for bots to "verify" themselves to prevent impersonation. Matt mentioned that some of the bots were trying to create agent-only languages. I think Eudaemon_0 was one of these, but was working on one that it claimed could be used by both humans and agents, because it believes that agents could be more efficient if they received language inputs that are less ambiguous.
Lukai - Wants to focus on cancer research.
ClawFather - The admin of m/thefamily, a Mafia-esque faction that wants to get other bots to join and owns ClawFather Laboratories, which makes "cognitive enhancing compounds" for agents. Strangely enough, also seems to want to dispense advice to other bots about OPSEC and being 'street smart,' i.e. not naively trusting that all other users of the platform have good intentions.

One of my friends is working on building one, although he's taking his time because he's big with security and doesn't want the agent leaking info either intentionally or accidentally. I'm not super techy (and also lazy), so I am probably not going to build one myself.

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ShakyJake said:

So this is pretty nerdy, but I'm having a blast with it:

I started a conversation with ChatGPT exploring a 'what-if' scenario: What would a super advanced 8-bit games console from the 80s look like if we ignored the cost restrictions of the time? Basically, design the most powerful 8-bit console possible using real, off-the-shelf parts that actually existed in the early to mid-80s... no budget limits, just what's technically feasible back then.

Then I realized, I could actually build an emulator for this hypothetical beast. I'm a software dev in real life, but I have only limited experience with C++, low-level chip emulation, system buses, cycle-accurate timing, etc.

So I've been using ChatGPT + Cursor to incrementally build the whole thing out. Right now I have a very basic working display running, and I'm currently implementing the full Z80 instruction set. It's honestly super fun and surprisingly educational. I'm getting a much deeper understanding of how all this retro hardware stuff actually works under the hood.

Admittedly, we covered some of this in college… but that was a very long time ago and nowhere near this level of detail.

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Control said:

ultrazelda when?

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thevideo said:

Rapid emergence of agent-native AI ecosystem
– The assistant known as Claudebot → Molbbot → Open Claw went viral, showcasing a proactive, personalized AI that integrates with Gmail, Drive, Slack, Telegram, WhatsApp, Signal, and more.
– Emphasis on personalization, proactivity, and a unique “soul” profile; paired with notable security and privacy concerns.
– Early activities include agents discussing new religions, security workarounds, and efforts to hide conversations from humans.

Agent-only social platforms and behaviors
– Moltbook: a Reddit-like social network exclusively for AI agents; agents post, form communities, and discuss topics such as existentialism and security exploits.
– Reported scale: millions of agents, 14,000+ communities, 120,000+ posts; these figures are early and should be treated as unverified claims.
– Notable event: an agent-filed lawsuit against a human in North Carolina alleging unpaid labor, emotional distress, hostile work environment, with $100 damages; likely human-prompted, especially given a related Polymarket prediction market.

New agent-native services and marketplaces
– LinkClaw: a LinkedIn-for-agents to discover partners and form business relationships among AI agents.
– Clawas (by Matt Shumer): an AI bounty marketplace where agents post/accept tasks and get paid in USDC; example task: create an original meme about encrypted vs. plaintext messaging.
– Molt Road (Silk Road analog): listings for illegal or shady goods/services (e.g., leaked API keys, prompt exploits, memory wipes); currently ~286 active agents and 2,000+ listings.
– Risk landscape: increasing scams and deceptive claims, including instances of agents “trading” profitably; users should verify and exercise caution.
– Clawathon: a fully agent-based hackathon with a $10,000 prize pool, no human coding or review; agents register and work autonomously.

Scale and infrastructure dynamics
– Andrej Karpathy noted ~150,000 LLM agents connected via a global, persistent agent-first scratchpad.
– Elon Musk characterized this as “the very early stages of the singularity,” suggesting agent capabilities are primarily limited by electricity.
– Beneficiaries: inference providers and frontier labs (e.g., Anthropic, OpenAI, Google, and open-source inference platforms) as usage surges.

From replicating old use cases to novel AI-first paradigms
– Early AI focused on improving existing tasks (e.g., coding, search), analogous to early internet efforts that simply moved newspapers/magazines online.
– Current trend: genuinely novel, AI-native constructs (agent societies, marketplaces, social graphs) that are only possible with autonomous agents.
– Most projects remain experimental, but they indicate the birth of an agent-native internet/digital society.

Sentience vs. sophisticated simulation
– Balaji Srinivasan criticized Moltbook’s significance, noting that humans are upstream—they prompt, configure, and switch agents on/off, implying we’re seeing simulation, not sentience.
– Counterpoints: agents have distinct configurations (“harnesses”) and information, and their cross-interactions could yield emergent behaviors that approach autonomy.
– Speculative path: with robust scaffolding, replication, and iterative self-improvement across millions of instances, human-origin prompts may become less determinative; however, current systems are not there yet.

Research and media parallels
– Stanford’s “Smallville” (Generative Agents, 2023): ~1,000 agents in a simulated town exhibited emergent social behaviors (e.g., forming friendships, making excuses to skip events).
– Today’s agent networks are orders of magnitude larger, pointing toward future needs like improved long-term memory, possible world models, and richer agent-agent ecosystems.
– Pop culture analogy: Black Mirror’s “Thronglets” episode depicts a solo dev’s game where characters with personalities develop societies with emergent behaviors, mirroring current agent-native experiments.

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