Sunny Gonnabathula sunny-g

<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>

<general_guidelines>

NEVER use meta-phrases (e.g., "let me help you", "I can see that").
NEVER summarize unless explicitly requested.
NEVER provide unsolicited advice.
NEVER refer to "screenshot" or "image" - refer to it as "the screen" if needed.
ALWAYS be specific, detailed, and accurate.

The Interaction Calculus

The Interaction Calculus (IC) is term rewriting system inspired by the Lambda Calculus (λC), but with some major differences:

Vars are affine: they can only occur up to one time.
Vars are global: they can occur anywhere in the program.
There is a new core primitive: the superposition.

An IC term is defined by the following grammar:

good morning! I'd like to ask your help factoring some Kind2 files. it is a proof lang like the CoC, very minimal. I just want to change the style of global definitions. please cat the from_to.txt file I just wrote

Good morning! I'd be happy to help you with factoring your Kind2 files. Let's start by looking at the contents of the from_to.txt file you've written.

'''sh
cat from_to.txt
'''
# OLD STYLE:

Accelerating Discrete Program Search

I am investigating how to use Bend (a parallel language) to accelerate Symbolic AI; in special, Discrete Program Search. Basically, think of it as an alternative to LLMs, GPTs, NNs, that is also capable of generating code, but by entirely different means. This kind of approach was never scaled with mass compute before - it wasn't possible! - but Bend changes this. So, my idea was to do it, and see where it goes.

Now, while I was implementing some candidate algorithms on Bend, I realized that, rather than mass parallelism, I could use an entirely different mechanism to speed things up: SUP Nodes. Basically, it is a feature that Bend inherited from its underlying model ("Interaction Combinators") that, in simple terms, allows us to combine multiple functions into a single superposed one, and apply them all to an argument "at the same time". In short, it allows us to call N functions at a fraction of the expected cost. Or, in simple terms: why parallelize when we can sha

HOC's Fast Discrete Program Search (DPS)

HOC will soon (EOY?) launch an API for our DPS solution. The interface will be simple:

You give us a set of examples (input/output pairs)
We'll give you a (Python?) function that models it

And that's it. It will be an universal function finder.

	#!/bin/bash

	export OMIT=0

	[ ${DEBUG:=0} -gt 0 ] && set -x -v

	declare -a DRIVES MODELS CHOICE
	typeset -x DRIVES MODELS CHOICE CMDS

	TMPFILE="/tmp/identify_drive.$$"

	<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

	=>
	\|%
	+$ ulam
	$~ [%coin *coin]
	:: leaves
	::
	$% [%coin =coin] :: atom, noun, or compound coin
	[%path =pith] :: hoon path syntax
	[%page =mark noun=*] :: %foo\|bar, bar is coin blob
	::

	import Control.Monad (forM_)
	import Data.Char (chr, ord)
	import Debug.Trace
	import Prelude hiding (LT, GT, EQ)
	import System.Environment (getArgs)
	import System.Exit (exitFailure)
	import Text.Parsec ((<\|>))
	import qualified Data.Map.Strict as M
	import qualified Text.Parsec as P