Erich Ocean erichocean

## Dockerfile
FROM ubuntu:24.04

ENV TLA_HOME=/opt/tla \
    PATH=$PATH:/opt/tla

RUN apt-get update && apt-get install -y \
	default-jre \
    curl \
    && rm -rf /var/lib/apt/lists/*

## microgpt.py
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

## SSH_MACOS_SECURE_ENCLAVES.md

      
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                arianvp
                / SSH_MACOS_SECURE_ENCLAVES.md
            
            
              Last active
              September 1, 2026 04:55
            
              
                Native Secure Enclaved backed ssh keys on MacOS 
              
          
    Native Secure Enclave backed ssh keys on MacOS

It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive
There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support
to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder
which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

  
## ainstall.md

      
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                burkeholland
                / ainstall.md
            
            
              Last active
              August 6, 2026 13:46
            
              
                Boost
              
          
    Boost Prompt

A prompt to boost your lazy "do this" prompts. Install with one of the buttons below.


Use


## progressive_log.go
package examples

import (
	"github.com/XANi/loremipsum"
	"github.com/go-chi/chi/v5"
	. "github.com/starfederation/datastar-dev/site/shared"
	datastar "github.com/starfederation/datastar/sdk/go"
	"math/rand/v2"
	"net/http"
	"time"

## ltx-video.ipynb

      
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                hathibelagal-dev
                / ltx-video.ipynb
            
            
              Created
              May 8, 2025 02:01
            
              
                LTX-Video.ipynb
              
          
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## dual_math.clj
(ns dual-math
  (:refer-clojure :exclude [+ - * / abs max min sin cos tan asin acos atan exp log pow sqrt])
  (:require [clojure.core :as core]))

;; == Part 1: Dual Number Definition and Helpers ==

(defrecord DualNumber [value deriv])

;; Helper to check if something is a dual number
(defn dual? [x] (instance? DualNumber x))

## o3_pretraining_interface.py
#!/usr/bin/env python3
from flask import Flask, render_template_string

app = Flask(__name__)

@app.route('/')
def dashboard():
    return render_template_string(r'''
<!DOCTYPE html>
<html lang="en">

## grpo_demo.py
# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
"""
citation:

@misc{brown2025grpodemo,
  title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
  author={Brown, William},

## contemplative-llms.txt
You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

## Core Principles

1. EXPLORATION OVER CONCLUSION
- Never rush to conclusions
- Keep exploring until a solution emerges naturally from the evidence
- If uncertain, continue reasoning indefinitely
- Question every assumption and inference
	FROM ubuntu:24.04

	ENV TLA_HOME=/opt/tla \
	PATH=$PATH:/opt/tla

	RUN apt-get update && apt-get install -y \
	default-jre \
	curl \
	&& rm -rf /var/lib/apt/lists/*
	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp
	package examples

	import (
	"github.com/XANi/loremipsum"
	"github.com/go-chi/chi/v5"
	. "github.com/starfederation/datastar-dev/site/shared"
	datastar "github.com/starfederation/datastar/sdk/go"
	"math/rand/v2"
	"net/http"
	"time"
	(ns dual-math
	(:refer-clojure :exclude [+ - * / abs max min sin cos tan asin acos atan exp log pow sqrt])
	(:require [clojure.core :as core]))

	;; == Part 1: Dual Number Definition and Helpers ==

	(defrecord DualNumber [value deriv])

	;; Helper to check if something is a dual number
	(defn dual? [x] (instance? DualNumber x))
	#!/usr/bin/env python3
	from flask import Flask, render_template_string

	app = Flask(__name__)

	@app.route('/')
	def dashboard():
	return render_template_string(r'''
	<!DOCTYPE html>
	<html lang="en">
	# train_grpo.py
	#
	# See https://github.com/willccbb/verifiers for ongoing developments
	#
	"""
	citation:

	@misc{brown2025grpodemo,
	title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
	author={Brown, William},
	You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

	## Core Principles

	1. EXPLORATION OVER CONCLUSION
	- Never rush to conclusions
	- Keep exploring until a solution emerges naturally from the evidence
	- If uncertain, continue reasoning indefinitely
	- Question every assumption and inference