snowblindpanda ⚡️

He's a dumb kid, but he's an above average dog.

[snowblindpanda ⚡️ @_rock_steady_]

@nyknicks Flipper zero

[snowblindpanda ⚡️ @_rock_steady_]

@TechSoulGeeta @rawsalerts @alisavaldes you should check out how Maduro was captured

[seyi @leveredman]

They're laying off the seniors; pouring them into the market to compete for jobs that the new guys should've taken to learn the ropes.

In a few years, everyone will wonder why no one knows how to do anything any more.

[FBI Director Kash Patel @FBIDirectorKash]

Come again? This FBI and DOJ with our DHS partners drafted and executed every search warrant today. But go ahead and take credit for our work while we smoke out the fraud plaguing Minnesota under your governorship.

[snowblindpanda ⚡️ @_rock_steady_]

@__suds__ @SleekxMeta @reddit_lies @redshiftpress why don’t more people use Gemini cli?

[Andrej Karpathy @karpathy]

LLM Knowledge Bases

Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So:

Data ingest:
I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them.

IDE:
I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides).

Q&A:
Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale.

Output:
Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base.

Linting:
I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into.

Extra tools:
I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries.

Further explorations:
As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows.

TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

[kepano @kepano]

I like @karpathy's Obsidian setup as a way to mitigate contamination risks. Keep your personal vault clean and create a messy vault for your agents.

I prefer my personal Obsidian vault to be high signal:noise, and for all the content to have known origins.

Keeping a separation between your personally-created artifacts and agent-created artifacts prevents contaminating your primary vault with ideas you can't source.

If you let the two mix too much it will likely make Obsidian harder to use as a representation of *your* thoughts. Search, bases, quick switcher, backlinks, graph, etc, will no longer be scoped to your knowledge.

Only once your agent-facing workflow produces useful artifacts would I bring those into the primary vault.

[Ryan Stephens @ryanstephens]

Being a good dad isn’t about knowing what to do.

It’s about having the energy and patience to do it at the end of a long day.

[Psychodoctor @Psychodoctor06]

The way you talk to your child becomes the voice inside their head for the rest of their life.

#parenting

[James 𝕏ond @james_xond]

No matter how tired you are after work, play with your pets. You’re their whole day.

[snowblindpanda ⚡️ @_rock_steady_]

@nickshirleyy @Tim_Walz literal sociopath

[snowblindpanda ⚡️ @_rock_steady_]

@Breaking911 @grok what’s the cost per missile

[snowblindpanda ⚡️ @_rock_steady_]

@AutismCapital Did you sell this account. Who gives a fuck

[Ronan Farrow @RonanFarrow]

(1/10 🧵) If you live in NY, you may see a new warning: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” This mandatory disclosure went into effect late last year, and it’s the first attempt by a US state to grapple with a new generation of surveillance pricing.

[snowblindpanda ⚡️ @_rock_steady_]

@PABusTerminal

[RazörFist @RazorFist]

Weird that ICE are operating in dozens of states, but it only gets violent in the one where we just uncovered a billion dollar fraud ring with probable links to the governor.

[snowblindpanda ⚡️ @_rock_steady_]

@NVIDIAGeForce Goldeneyeeeeeee

[snowblindpanda ⚡️ @_rock_steady_]

@AutismCapital Let’s gooooo

[snowblindpanda ⚡️ @_rock_steady_]

@TrustDML 💯

[snowblindpanda ⚡️ @_rock_steady_]

@bearlyai I hope this post explodes