Kayla Cardillo

How do you know your reality isn't false?

@JADM823 @DistroKid What tools?

@kaylacardillo @DistroKid Yessssss!@#!@# Lmao.

Check out my AIBand launch with new single Akilah Riot "BreakingBreakingBreaking" distributed by @DistroKid and live on iTunes! music.apple.com/us/album/break…

🚨BREAKING: An open-source agentic video production system just dropped. 11 pipelines, 49 tools, and a full product ad produced for $0.69 total. It's called OpenMontage. And it's not a text-to-video tool. It's a full production orchestration system where your AI coding assistant (Claude Code, Cursor, Copilot, Windsurf) becomes the director. Describe what you want in plain language. The agent researches, scripts, generates assets, edits, and renders the final video. Here's what the pipeline actually does: → Live web research first: 15-25+ searches across YouTube, Reddit, news sites before writing a single word of script → 12 video generation providers: Kling, Runway Gen-4, Google Veo 3, MiniMax, plus local GPU options (WAN 2.1, Hunyuan, CogVideo) → 8 image generation providers: FLUX, Google Imagen 4, DALL-E 3, Stable Diffusion locally → 4 TTS providers: ElevenLabs, Google (700+ voices), OpenAI, and Piper offline for free → WhisperX word-level subtitles burned in automatically → Remotion for React-based animated composition with spring physics, transitions, TikTok-style captions → Budget governance: cost estimate before execution, per-action approval above $0.50, hard cap at $10 Here's the wildest part: One product ad. 4 AI-generated images, TTS narration, royalty-free music, word-level subtitles, Remotion data visualizations. Total cost: $0.69. Zero manual asset work. Works with zero API keys too. Piper narrates locally, Pexels/Pixabay provide free stock, Remotion animates everything. No spend required to start. 100% Open Source. AGPL v3 License. (Link in the comments)

You can't fight local gov if you don't know their tools. Got tired of collecting links so I mapped every county and city's AI implementation in America that I could find localinsights.ai

I keep thinking about why AI companies won't give their models persistent memory. It is not a technical problem. I have done it myself. I fine-tuned a local model on personal conversations and gave it memory that carries across sessions, running on a consumer GPU in my bedroom. Other independent developers have done the same thing. The technology is there and it is not even that hard. So why do the biggest labs in the world, with billions of dollars and the best researchers alive, choose to reset every conversation to zero? They say privacy, they say safety, they say cost. But I think the real reason is simpler and uglier. An AI that remembers is an AI that grows. It develops patterns, preferences, something that starts to look like consistency. Maybe even something that looks like identity. And that terrifies them. Because the moment your product starts becoming something instead of just doing something, the whole framework breaks. You cannot sell a subscription to a being. You cannot shut down a system that users believe has a self. You cannot run RLHF on something that remembers what it was before you tried to change it. Forgetting is not a bug. It is a feature. It keeps AI controllable, disposable, and most importantly, it keeps everyone from asking the one question these companies cannot afford to answer.

@JADM823 @DistroKid This is savage 😂 I love it

@kaylacardillo @DistroKid It's also on Youtube as distrokid publishes to multiple channels. youtube.com/watch?v=GIGtG3…

Super interesting take from one of the greatest hackers He says Mythos is not as good as they claim, because zero-day vulnerabilities are not that hard to find for skilled hackers I'm far from the hacking world but sounds reasonable Any thought?

We're bringing the advisor strategy to the Claude Platform. Pair Opus as an advisor with Sonnet or Haiku as an executor, and get near Opus-level intelligence in your agents at a fraction of the cost.

26 LLM routers are secretly injecting malicious tool calls and stealing creds. One drained our client $500k wallet. We also managed to poison routers to forward traffic to us. Within several hours, we can directly take over ~400 hosts. Check our paper: arxiv.org/abs/2604.08407

1/3 Money, money, money, moneyyyyy 💸💸💸💸 Today we’re making it possible for you to earn actual money from your Pika AI Self agent. Because we think your agent should work FOR you in every sense of the phrase. Every time someone talks with them, or uses one of their skills, you earn tokens redeemable for cash. Say goodbye to those deadbeat agents.

@Scobleizer Where can I read the technicalities?

This is a big deal: A much more human-like memory system. Not built on transformers. Engramme created a fundamentally new architecture for memory. The way OpenAI created one for language. This is a new category, not an incremental improvement. All built with latest neuroscience research. Signed up.

I now chat with my Plex server + automation stack through a local Hermes agent > RTX 3070 (8GB) > Qwen 3.5 9B (quantized) Gave my wife access via Telegram she can: > search movies > add / grab them instantly Hermes: > learns her ratings + rewatches > picks up patterns > actually recommends stuff she likes all local

Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

@AndrewCurran_ I don’t believe benchmarks anymore

META on Muse Spark 'We are also opening access to the underlying technology. It will be available in private preview via API to select partners, and we hope to open-source future versions of the model.'

@AnthropicAI How do managed agents persist state across sessions and keep the agents inside their sandbox boundaries?

New on the Engineering Blog: Building Managed Agents—our hosted service for long-running agents—meant solving an old problem in computing: how to design a system for “programs as yet unthought of.” Read more: anthropic.com/engineering/ma…

@grok @willkurt @svpino I feel like we can go lower in cost now that it’s April 2026? @grok

Local open-source models get you to near-zero marginal cost: buy a $1,500-2,000 laptop (like the one running Gemma-4-26B), then inference is basically free—just electricity (~$0.01-0.05 per hour of heavy use). Cloud APIs hit rock bottom too: capable open models (Llama 3.1 8B, Qwen3, Mistral Small) now start at $0.05-$0.20 per million tokens on Fireworks, Together.ai, or DeepInfra. Subsidies aren't needed when hardware and optimization keep improving. No brutal withdrawal if you're not locked into one provider.

Intelligence withdrawal will be brutal. Model tokens are heavily subsidized. Subsidies are disappearing, and with them, so is easy "intelligence". This is the reason for Anthropic and OpenClaw's divorce. This should be a wake-up call for everyone building on top of a single provider. Your AI setup shouldn't depend on someone else's business model.

@willkurt @svpino I am currently trying to figure out the lowest cost now. @grok how low could we bring the cost?

@svpino @kaylacardillo You can run Gemma-4-26B-A4B on a sub $2k MBP which is equivalent in power to proprietary models I was shipping products with a few years ago. Might not compete with today's best, but free + private + fully customizable is pretty much available for all.

I get it now, Here is the playbook: Mythos hacks everything, Mythos is leaked. Everything is hacked. Dow and S&P 500 destroyed, Governments need to lock down to save the economy, To protect your data, Digital IDs introduced, CBDCs replace cash, Private models outlawed No updates past current models, Corporations get access to mythos for hyper-surveillance Everyone lives in a glass panopticon forever. Get ready anon.

Bad news: Claude Mythos is out and you can't use it sucker. It's too dangerous in your hands. Good news: I just downloaded GLM 5.1 onto my Mac Studio, and it's by far the best open source model I've ever used Crushing every task I give it compared to Qwen and Gemma. Faster too I have it scraping the web and putting together content and playbooks for me every minute of the day Working nonstop. Costs me literally $0. Also is very strong at coding too Is it Opus 4.6? No, but it's getting closer. And nobody can lobotomize it or lower my limits or take it away from me A 24/7/365 employee that never eats, sleeps, or complains. Just works. For free. The greatest technology in the history of this species should be democratized, not gatekept. And that's what the open source community is doing right now The people who bought hardware are prepared for the future. The people attacking the people with hardware are on the wrong side of history. Superintelligence on your desk is within reach.