This guide assumes you have some familiarity with MLX and want to make your MLX model or algorithm as efficient as possible.
The guide covers the following:
<div style="position:absolute;top:-999px;left:-999px"> | |
<svg | |
id="effectSvg" | |
width="200" | |
height="200" | |
viewBox="0 0 200 200" | |
xmlns="http://www.w3.org/2000/svg"> | |
<filter id="displacementFilter4"> |
import Control.Monad (when) | |
import Data.Char (chr, ord) | |
import Data.IORef | |
import Data.Word | |
import Debug.Trace | |
import System.IO.Unsafe (unsafePerformIO) | |
import Text.Parsec hiding (State) | |
import qualified Data.IntMap.Strict as IntMap | |
import qualified Data.Map as Map | |
import qualified Text.Parsec as Parsec |
This guide assumes you have some familiarity with MLX and want to make your MLX model or algorithm as efficient as possible.
The guide covers the following:
The Interaction Calculus (IC) is term rewriting system inspired by the Lambda Calculus (λC), but with some major differences:
An IC term is defined by the following grammar:
# The Interaction Calculus | |
The Interaction Calculus (IC) is term rewritting system inspired by the Lambda | |
Calculus (λC), but with some major differences: | |
1. Vars are affine: they can only occur up to one time. | |
2. Vars are global: they can occur anywhere in the program. | |
3. There is a new core primitive: the superposition. | |
An IC term is defined by the following grammar: |
Relax, I only have one Sunday to work on idea, literally my weekend project. So I tried Deepseek to see if it can help. Surprisingly, it works and it saves me another weekend...
Just chat.deepseek.com (cost = free) with prompts adapted from this gist.
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 |
import React, { useState, useEffect, useCallback, useRef } from 'react'; | |
/** | |
* Represents a point in 3D space within the Lorenz system. | |
*/ | |
interface Point { | |
x: number; | |
y: number; | |
z: number; | |
} |
import React, { useState, useEffect, useCallback, useRef } from 'react'; | |
type ColoredChar = { | |
char: string; | |
color: string; | |
}; | |
const defaultConfig = { | |
scale: 0.05, |
Date: November 20, 2024
Author: Jeremy Howard
Categories: AI Education, fast.ai, Answer.AI
In the rapidly evolving world of artificial intelligence, the need for accessible, practical education has never been more crucial. Today, I am excited to announce that fast.ai is joining forces with Answer.AI to bring you a new era of AI education. This partnership is not just about combining resources; it's about creating a new kind of learning experience that leverages the power of AI to solve real-world problems.