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]


Q:

How to detect low-spec mobile devices meaningfully?

Right now I only know about Scientiamobile's WURFL and a few others. Those libraries or databases tell you quite a lot of things about the device but none of them can clearly indicate that you shouldn't use CSS transitions or other sorts of animation because even if the device supports it, its a complete different story that those features will run smoothly and this is my major concern when building mobile web apps. 
Is it technically possible to 'classify' devices in this direction, using the 'WURF' database ? And which device capabilities I should use to 'group' devices as 'fast' in terms of graphic power ? 
Finally, I just need a rating of the device from 1-5 in order to decide which gfx operations I can use.   
well, any thought is welcome. It turns out as real brainer and the researches on internet didn't bring up anything useful except lots of data about device caps.
Update-1 : I just got a response from ScientiaMobile : "we have been playing around with the idea of some form of Javascript performance index (possibly based on one of the existing benchmarks) that could give some indication of that, but we are still not there yet. The problem is complex."
Update-2 : The biggest bottlenecks we discovered in mobile web apps 

animation power
PNG transparency 
text and box shadows
image resizing

For us its really enough to figure out that we need to disable those features as they can bring any application to its knees. Possibly, there are also other approaches.
Thank you.

A:

Unfortunately, I do not believe this is possible today for the general case.
If you are only interested in a limited number of devices, of course you could test each and target those specifically via user agent or JavaScript-based detection.
Within the context of a thick app (e.g., you "wrap" your web site with something like Apache Cordova), it would be possible to provide JavaScript access to some of the device internals (e.g., amount of total memory, amount of free memory, processor speed), but otherwise, this information is not available from the browser. As you've hinted at, having access to this type of device information may still be insufficient (e.g., seemingly "high spec" devices that perform poorly).
JavaScript feature detection libraries like Modernizr can answer whether something such as box-shadow and text-shadow is supported by the user's current browser, but does not provide information about how well or how quickly supported features will be rendered.
Likewise, the datasets from Browserscope and related project ringmark (somewhat of a JavaScript analog to WURFL) answer these browser support questions on a per-browser-version basis through crowdsourced benchmarking tests (e.g., does the iPhone support CSS3 transitions?), and for the general case, this is what would be necessary. You would need to run a benchmark test for the various features in question and assess real-time performance. However, even this has its limitations:

Because the necessary conditions for speed (available memory, processor, battery, network connection, etc.) are constantly in flux as mobile users move around, receive calls, change hardware settings, launch background applications, etc., the result of the benchmark is likely to be unreliable/unrepeatable.
Benchmarking takes time and will invariable add a (hopefully unnoticable) delay.
Depending on the feature, benchmarking may not be practical.
Features may behave differently in combination (e.g., animating transparent PNGs with shadows) or at scale (e.g., every image on the page is animating) than individually in the benchmarking test.
If you rely on benchmarking datasets instead of performing your own real-time benchmarking, the sample size, scope, and age of the dataset greatly limits its usefulness.

A final point is that I haven't even addressed is the fact that performance is rather subjective. Say it were somehow possible to assess/predict the speed of an animation. If the animation will run at 15 fps, should the user see that animation? What about 5 fps? Who gets to be the ultimate arbiter that decides the threshold for whether or not a given feature performs well enough? 
The best advice I can offer today is to reduce (or eliminate) your reliance on the troublesome features for the time being. It may seem terrible to suggest going back to "the old way" of using images with precomposed shadows or making background gradients without CSS3, but at the end of the day the user experience should take precedence over using the shiney new technology. Many mobile devices are simply not there yet, and neither are the detection methods. If you must use these features, perhaps consider a simple but unobtrusive way for users to opt-in/opt-out like Gmail's "standard" vs. "basic HTML" view options, or consider automatically doing the opt-in for known good browsers.