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System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

Clarify and agree on the scope of the system

User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?

A simple Docker and Docker Compose install script for Ubuntu

Usage

sh install-docker.sh
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Sentient Systems Architecture (SSA): Unlocking Embodied Intelligence

Introduction

Artificial Intelligence (AI) has evolved rapidly, with language models like GPT-4 capturing attention. However, the real future of AI lies in embodied intelligence—systems that can interact with the physical world through robotics and sensory perception. Unlike disembodied language models that operate in digital spaces, embodied AI must navigate complex environments, interpret sensory data, and perform physical tasks. This shift towards embodied intelligence opens the door to groundbreaking applications and significant economic impact.

Unique Challenges of Embodied Intelligence

Developing embodied AI systems is far more complex than working with traditional language models. Embodied agents need to:

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>Z-Index Example</title>
	<style>
	@font-face {
	font-family: 'Win95F';
	src: url('data:application/font-woff2;base64,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

	package s3

	import (
	"context"
	"fmt"
	"github.com/aws/aws-sdk-go-v2/aws"
	"github.com/aws/aws-sdk-go-v2/config"
	"github.com/aws/aws-sdk-go-v2/service/s3"
	"github.com/magiconair/properties/assert"
	"github.com/testcontainers/testcontainers-go"

	@echo off
	:REM ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
	:REM
	:REM Batch file for establishing a WebDAV connection and bind it to a drive
	:REM letter (non-persistent).
	:REM
	:REM Please adopt WEBDAV_HOST and WEBDAV_USER to your needs as well as the
	:REM default password. You also might want to adopt the default drive the
	:REM WebDAV connection should be bound to.
	:REM

	[Unit]
	Wants=network-pre.target
	Before=network-pre.target shutdown.target

	[Service]
	User=root
	ExecStart=/bin/sh -ec '\
	[ -x /usr/bin/wslinfo ] && [ "$(/usr/bin/wslinfo --networking-mode)" = "mirrored" ] \|\| exit 0;\
	echo "\
	add chain ip nat WSLPREROUTING { type nat hook prerouting priority dstnat - 1; policy accept; };\

	use std::str;

	fn main() {
	// -- FROM: vec of chars --
	let src1: Vec<char> = vec!['j','{','"','i','m','m','y','"','}'];
	// to String
	let string1: String = src1.iter().collect::<String>();
	// to str
	let str1: &str = &src1.iter().collect::<String>();
	// to vec of byte

	use borsh::{BorshDeserialize, BorshSerialize};
	use solana_program::{
	account_info::{next_account_info, AccountInfo},
	entrypoint,
	entrypoint::ProgramResult,
	msg,
	program_error::ProgramError,
	pubkey::Pubkey,
	};