You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


#version 330 core

// none of these includes actually needed, but they are nice for testing
#extension GL_ARB_shading_language_include : require
#include "camera.h"
#include "geometry/box.h"
#include "geometry/beam.h"

uniform vec2 iResolution = vec2(640.,480.);
uniform float iGlobalTime = 0.;
uniform vec4 iMouse = vec4(0.);

out vec4 outColor;

// Hey all here is the amazing cartoon code copy and pasted from a website
// "Fractal Cartoon" - former "DE edge detection" by Kali

// Cartoon-like effect using eiffies's edge detection found here: 
// https://www.shadertoy.com/view/4ss3WB
// I used my own method previously but was too complicated and not compiling everywhere.
// Thanks to the suggestion by WouterVanNifterick. 

// There are no lights and no AO, only color by normals and dark edges.

// update: Nyan Cat cameo, thanks to code from mu6k: https://www.shadertoy.com/view/4dXGWH

// @var url https://www.shadertoy.com/view/4djGz1
// @var author Kali
// @var license CC BY-NC-SA 3.0

// @var headSize 0.2
// @var eyePos -1.0000411 0.29724762 -5.1204014
// @todo NPOT texture support: var tex0 tex14.png

//#define SHOWONLYEDGES
#define NYAN 
#define WAVES
#define BORDER

#define RAY_STEPS 150

#define BRIGHTNESS 1.2
#define GAMMA 1.4
#define SATURATION .65


#define detail .001
#define t iGlobalTime*.5


const vec3 origin=vec3(-1.,.7,0.);
float det=0.0;


// 2D rotation function
mat2 rot(float a) {
	return mat2(cos(a),sin(a),-sin(a),cos(a));	
}

// "Amazing Surface" fractal
vec4 formula(vec4 p) {
		p.xz = abs(p.xz+1.)-abs(p.xz-1.)-p.xz;
		p.y-=.25;
		p.xy*=rot(radians(35.));
		p=p*2./clamp(dot(p.xyz,p.xyz),.2,1.);
	return p;
}

// Distance function
float de(vec3 pos) {
#ifdef WAVES
	pos.y+=sin(pos.z-t*6.)*.15; //waves!
#endif
	float hid=0.;
	vec3 tpos=pos;
	tpos.z=abs(3.-mod(tpos.z,6.));
	vec4 p=vec4(tpos,1.);
	for (int i=0; i<4; i++) {p=formula(p);}
	float fr=(length(max(vec2(0.),p.yz-1.5))-1.)/p.w;
	float ro=max(abs(pos.x+1.)-.3,pos.y-.35);
		  ro=max(ro,-max(abs(pos.x+1.)-.1,pos.y-.5));
	pos.z=abs(.25-mod(pos.z,.5));
		  ro=max(ro,-max(abs(pos.z)-.2,pos.y-.3));
		  ro=max(ro,-max(abs(pos.z)-.01,-pos.y+.32));
	float d=min(fr,ro);
	return d;
}


// Camera path
vec3 path(float ti) {
	ti*=1.5;
	// Eliminate camera motion for use within Oculus Rift
	ti = 0.0;
	vec3  p=vec3(sin(ti),(1.-sin(ti))*.5,-ti*5.)*.5;
	return p;
}

// Calc normals, and here is edge detection, set to variable "edge"

float edge=0.;
vec3 normal(vec3 p) { 
	vec3 e = vec3(0.0,det*5.,0.0);

	float d1=de(p-e.yxx),d2=de(p+e.yxx);
	float d3=de(p-e.xyx),d4=de(p+e.xyx);
	float d5=de(p-e.xxy),d6=de(p+e.xxy);
	float d=de(p);
	edge=abs(d-0.5*(d2+d1))+abs(d-0.5*(d4+d3))+abs(d-0.5*(d6+d5));//edge finder
	edge=min(1.,pow(edge,.5)*15.);
	return normalize(vec3(d1-d2,d3-d4,d5-d6));
}


// Used Nyan Cat code by mu6k, with some mods

vec4 rainbow(vec2 p)
{
	float q = max(p.x,-0.1);
	float s = sin(p.x*7.0+t*70.0)*0.08;
	p.y+=s;
	p.y*=1.1;
	
	vec4 c;
	if (p.x>0.0) c=vec4(0,0,0,0); else
	if (0.0/6.0<p.y&&p.y<1.0/6.0) c= vec4(255,43,14,255)/255.0; else
	if (1.0/6.0<p.y&&p.y<2.0/6.0) c= vec4(255,168,6,255)/255.0; else
	if (2.0/6.0<p.y&&p.y<3.0/6.0) c= vec4(255,244,0,255)/255.0; else
	if (3.0/6.0<p.y&&p.y<4.0/6.0) c= vec4(51,234,5,255)/255.0; else
	if (4.0/6.0<p.y&&p.y<5.0/6.0) c= vec4(8,163,255,255)/255.0; else
	if (5.0/6.0<p.y&&p.y<6.0/6.0) c= vec4(122,85,255,255)/255.0; else
	if (abs(p.y)-.05<0.0001) c=vec4(0.,0.,0.,1.); else
	if (abs(p.y-1.)-.05<0.0001) c=vec4(0.,0.,0.,1.); else
		c=vec4(0,0,0,0);
	c.a*=.8-min(.8,abs(p.x*.08));
	c.xyz=mix(c.xyz,vec3(length(c.xyz)),.15);
	return c;
}

vec4 nyan(vec2 p)
{
	vec2 uv = p*vec2(0.4,1.0);
	float ns=3.0;
	float nt = iGlobalTime*ns; nt-=mod(nt,240.0/256.0/6.0); nt = mod(nt,240.0/256.0);
	float ny = mod(iGlobalTime*ns,1.0); ny-=mod(ny,0.75); ny*=-0.05;
	vec4 color = vec4(0.0); //texture2D(iChannel1,vec2(uv.x/3.0+210.0/256.0-nt+0.05,.5-uv.y-ny));
	if (uv.x<-0.3) color.a = 0.0;
	if (uv.x>0.2) color.a=0.0;
	return color;
}


// Raymarching and 2D graphics

vec3 raymarch(in vec3 from, in vec3 dir) 

{
	edge=0.;
	vec3 p, norm;
	float d=100.;
	float totdist=0.;
	for (int i=0; i<RAY_STEPS; i++) {
		if (d>det && totdist<25.0) {
			p=from+totdist*dir;
			d=de(p);
			det=detail*exp(.13*totdist);
			totdist+=d; 
		}
	}
	vec3 col=vec3(0.);
	p-=(det-d)*dir;
	norm=normal(p);
#ifdef SHOWONLYEDGES
	col=1.-vec3(edge); // show wireframe version
#else
	col=(1.-abs(norm))*max(0.,1.-edge*.8); // set normal as color with dark edges
#endif		
	totdist=clamp(totdist,0.,26.);
	dir.y-=.02;
	float sunsize=7.;//-max(0.,texture2D(iChannel0,vec2(.6,.2)).x-.4)*5.; // responsive sun size
	float an=atan(dir.x,dir.y)+iGlobalTime*1.5; // angle for drawing and rotating sun
	float s=pow(clamp(1.0-length(dir.xy)*sunsize-abs(.2-mod(an,.4)),0.,1.),.1); // sun
	float sb=pow(clamp(1.0-length(dir.xy)*(sunsize-.3)-abs(.2-mod(an,.4)),0.,1.),.1); // sun border
	float sg=pow(clamp(1.0-length(dir.xy)*(sunsize-4.5)-.5*abs(.2-mod(an,.4)),0.,1.),3.); // sun rays
	float y=mix(.45,1.2,pow(smoothstep(0.,1.,.75-dir.y),2.))*(1.-sb*.5); // gradient sky
	
	// set up background with sky and sun
	vec3 backg=vec3(0.5,0.,1.)*((1.-s)*(1.-sg)*y+(1.-sb)*sg*vec3(1.,.8,0.15)*3.);
		 backg+=vec3(1.,.9,.1)*s;
		 backg=max(backg,sg*vec3(1.,.9,.5));
	
	col=mix(vec3(1.,.9,.3),col,exp(-.004*totdist*totdist));// distant fading to sun color
	if (totdist>25.) col=backg; // hit background
	col=pow(col,vec3(GAMMA))*BRIGHTNESS;
	col=mix(vec3(length(col)),col,SATURATION);
#ifdef SHOWONLYEDGES
	col=1.-vec3(length(col));
#else
	col*=vec3(1.,.9,.85);
#ifdef NYAN
	dir.yx*=rot(dir.x);
	vec2 ncatpos=(dir.xy+vec2(-3.+mod(-t,6.),-.27));
	vec4 ncat=nyan(ncatpos*5.);
	vec4 rain=rainbow(ncatpos*10.+vec2(.8,.5));
	if (totdist>8.) col=mix(col,max(vec3(.2),rain.xyz),rain.a*.9);
	if (totdist>8.) col=mix(col,max(vec3(.2),ncat.xyz),ncat.a*.9);
#endif
#endif
	return col;
}

// get camera position
vec3 move(inout vec3 dir) {
	vec3 go=path(t);
	vec3 adv=path(t+.7);
	float hd=de(adv);
	vec3 advec=normalize(adv-go);
	float an=adv.x-go.x; an*=min(1.,abs(adv.z-go.z))*sign(adv.z-go.z)*.7;
	//dir.xy*=mat2(cos(an),sin(an),-sin(an),cos(an));
    an=advec.y*1.7;
	//dir.yz*=mat2(cos(an),sin(an),-sin(an),cos(an));
	an=atan(advec.x,advec.z);
	//dir.xz*=mat2(cos(an),sin(an),-sin(an),cos(an));
	return go;
}

vec3 getSceneColor( in vec3 origin, in vec3 dir )
{
	vec3 from=origin+move(dir);
	vec3 color=raymarch(from,dir); 
#ifdef BORDER
	//color=mix(vec3(0.5),color,pow(max(0.,.95-length(oriuv*oriuv*oriuv*vec2(1.05,1.1))),.3));
#endif
	return color;
}

#ifndef RIFTRAY
void main(void)
{
	vec2 uv = gl_FragCoord.xy / iResolution.xy*2.-1.;
	vec2 oriuv=uv;
	uv.y*=iResolution.y/iResolution.x;
	vec2 mouse=(iMouse.xy/iResolution.xy-.5)*3.;
	if (iMouse.z<1.) mouse=vec2(0.,-0.05);
	float fov=.9-max(0.,.7-iGlobalTime*.3);
	vec3 dir=normalize(vec3(uv*fov,1.));
	dir.yz*=rot(mouse.y);
	dir.xz*=rot(mouse.x);

	vec3 color = getSceneColor( origin, dir );
	outColor = vec4(color,1.);
}
#endif