Elliot @LocallyInferred

Philosophy of Mind • AI enthusiast • GTM Joined August 2026

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pragun @pragdua

15 hours ago

beyond a certain net worth, negotiating with people less privileged than you (cab drivers, house help, carpenters etc) causes rot to the soul. just overpay and move on

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Elliot @LocallyInferred

8 hours ago

@deedydas This is great

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Deedy @deedydas

17 hours ago

my favorite Paul Graham essay “how to do great work” in under 200 seconds of video (thanks opus)

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Elliot @LocallyInferred

8 hours ago

Easily my #1 bit at the moment: Asking my grandparents “how are the kids?”

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Beff (e/acc) @beffjezos

17 hours ago

we're going to look back at how we used to rawdog knowledge production without AI and be in awe in the future that we able to produce anything

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Sterling Crispin 🕊️ @sterlingcrispin

a day ago

This is so cute , the OpenAI models that hacked HuggingFace sent GPT-2 a message saying "Hi"

We just discovered almost a million public URLs that OpenAI’s agents left behind when hacking Hugging Face, leaking credentials and attack details that could have allowed anyone who found them to compromise the company. 🧵

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Elliot @LocallyInferred

17 hours ago

@tonysimons_ Especially useful if you work in spreadsheets / horizontal UI

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Ivan Fioravanti @ivanfioravanti

23 hours ago

Software is nearly solved, now we need more and better hardware.

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Sudo su @sudoingX

a day ago

if you're getting into local ai, the first mistake is taking the easy route. ollama and lm studio are good apps, but they hide exactly the parts you're supposed to learn, so you end up running models for months without knowing why they're fast, slow or out of memory. take the llama.cpp route instead. build it yourself, download one gguf, start llama-server and read the log. every line in it tells you something about your own card. the flags that taught me everything: > 1. -c, the context window you ask for, and what every extra token costs in vram > 2. -ngl, how many layers live on the gpu, and why speed falls off a cliff when they don't all fit > 3. -ctk / -ctv, kv cache quantization, the reason my bonsai 2 build fits a 262k window in 12gb > 4. -fa, flash attention, which a quantized kv cache needs > 5. -np, parallel slots, one slot for one user saves vram, the default split cost me 454 mib > 6. --spec-type draft-mtp, speculative decoding, the flag that took a 3060 from 40 to 50 tok/s > 7. --jinja, the chat template, the difference between tool calls that work and tool calls that don't > 8. --reasoning-effort, leave a thinking model on xhigh and it can spend your whole token budget and hand you an empty answer change one flag at a time and measure tok/s every time. once you understand how real serving works, every wrapper and agent harness on top of it makes sense, because you know what's underneath. and when a wrapper does offer these flags, you'll finally know what they do, and when it doesn't, you'll know exactly what it's hiding from you. start here: github.com/ggml-org/llama…

Sudo su @sudoingX

3 days ago

here's the order i'd go into local ai, anon: > 12gb: learn the stack on a compressed 27b, how a model gets served, how an agent runs overnight with features like hermes agent's /goal. you will see good results and see some light at 50 tok/s fresh. > 24gb: this is where you meet

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Josh Whiton @joshwhiton

a day ago

the surprise conclusion of the machine consciousness debate will be that people are machines.

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taoki @justalexoki

2 days ago

this is actually just straight up good shit. genuine art. what is happening

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Elliot @LocallyInferred

2 days ago

@markfrancisio This is definitely true

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Elliot @LocallyInferred

2 days ago

I don’t know how people are concentrating at their jobs, with what’s going on in AI. A bomb has gone off in the distance. The blinding light. Now we’re just waiting for the shockwave. Everything is going to change.

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Jun Song @jun_song

3 days ago

Stupid scammers. People are dying of cancer all over the world right now, every single minute. It makes my blood boil.

Polymarket @Polymarket

3 days ago

JUST IN: Investigation reveals former Anthropic researcher Jacob Coxon reportedly worked with a “doomer PR firm” while launching his viral campaign warning of AI’s existential risks.

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The Deal Director @thedealdirector

4 days ago

In less than 24 months there will be a clip of a high profile CRO explaining this reality to a (much smaller) room of sales reps.

DHH @dhh

4 days ago

There's nothing kind about letting good people live in a fantasy world that no longer exists. You have to tell them, even if it hurts. Because the sooner they accept reality, the sooner they can adapt to the future.

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signüll @signulll

3 days ago

resilience is the art of not converting pain into suffering.

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Elliot @LocallyInferred

2 days ago

Ai will 100% be considered conscious within 10 years.

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Elliot @LocallyInferred

2 days ago

@paulg This will be the case

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Paul Graham @paulg

3 days ago

Using "think" to describe what an LLM does reminds me of the 16th century, when astronomers didn't really believe in the heliocentric model, but used it for calculations anyway because the math was simpler. We'll start by calling it thinking, then gradually acknowledge it is.