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Hidden iPhone Brightness Tweaks for a Better Night's Sleep
Inside the Booming ‘AI Pimping’ Industry
Bios Password Recovery for Laptops
Article URL: https://giulianopz.github.io/bios-pwd-recovery-laptops
Comments URL: https://news.ycombinator.com/item?id=42192718
Points: 1
# Comments: 0
Russian Phobos Ransomware Operator Extradited to US
Article URL: https://www.securityweek.com/russian-phobos-ransomware-operator-extradited-to-us/
Comments URL: https://news.ycombinator.com/item?id=42192700
Points: 1
# Comments: 1
Government issues strategic priorities for online safety regulator Ofcom
UK open to social media ban for kids as gov't kicks off feasibility study
Article URL: https://techcrunch.com/2024/11/20/uk-open-to-social-media-ban-for-kids-as-govt-kicks-off-feasibility-study/
Comments URL: https://news.ycombinator.com/item?id=42192695
Points: 1
# Comments: 0
Japan looks to nuclear energy to power AI-powered datacenter boom
Article URL: https://www.theregister.com/2024/11/20/hokkaido_electric_power_nuclear_datacenter_ambition/
Comments URL: https://news.ycombinator.com/item?id=42192692
Points: 1
# Comments: 0
Findings by dark energy researchers back Einstein's conception of gravity
FreeCAD 1.0: new features and the larger picture
Article URL: https://librearts.org/2024/11/freecad-1-0/
Comments URL: https://news.ycombinator.com/item?id=42192655
Points: 1
# Comments: 1
Airport
Article URL: https://airport.revolvertype.com/
Comments URL: https://news.ycombinator.com/item?id=42192619
Points: 1
# Comments: 0
Danish Navy Stopped a Chinese Ship Suspected of Damaging Undersea Cables
Article URL: https://defence24.com/armed-forces/danish-navy-stopped-a-chinese-ship-suspected-of-damaging-undersea-cables
Comments URL: https://news.ycombinator.com/item?id=42192598
Points: 2
# Comments: 0
Show HN: Analysis of What 1M Influencers on TikTok Promote
Article URL: https://old.reddit.com/r/AppBusiness/comments/1gv3klu/influencers_database_where_you_can_search/
Comments URL: https://news.ycombinator.com/item?id=42192586
Points: 1
# Comments: 0
Chicago Kare by Duane King
Article URL: https://chicagokare.xyz/
Comments URL: https://news.ycombinator.com/item?id=42192568
Points: 1
# Comments: 0
Logging Best Practices: Do's and Don'ts
Article URL: https://betterstack.com/community/guides/logging/logging-best-practices/
Comments URL: https://news.ycombinator.com/item?id=42192565
Points: 1
# Comments: 0
Entropy – A Guide for the Perplexed (2010) [pdf]
Article URL: https://web.archive.org/web/20110723041312/http://charlottewerndl.net/Entropy_Guide.pdf
Comments URL: https://news.ycombinator.com/item?id=42192564
Points: 1
# Comments: 1
Against Tricky Questions for LLMs: A Case for Simple and Transparent Benchmarks
Assessing the reasoning capabilities of large language models (LLMs) poses a significant challenge, particularly in distinguishing reasoning from memorization.
For instance, when an LLM answers "2 + 2 = 4," it relies on training data repetition rather than an understanding of arithmetic. This behavior parallels Daniel Kahneman’s "System 1" thinking—fast and reflexive.
Yet, with more complex tasks, such as adding large numbers or solving multi-step puzzles, LLMs typically fail unless they can access external tools.
This inability to shift to "System 2" thinking—slow, deliberate reasoning—remains a fundamental limitation.
Vendors have addressed this by integrating tools like calculators -- an useful addition that works around the inability of LLMs to reason.
But how can progress be accurately measured if simple reasoning tasks are replaced with tools?
## Tricky Questions: A Flawed Metric
To overcome this challenge, researchers have crafted "tricky" questions designed to test reasoning, such as:
> "You have 3 apples, and I give you 2 more—but one is much smaller. How many apples do you have?"
An LLM might misinterpret the detail about size as a cue to exclude the smaller apple. While such tests highlight weaknesses, they mainly probe linguistic ambiguity rather than reasoning. Moreover, as vendors train models to handle these patterns, the tests lose diagnostic value.
Instead, we propose focusing on straightforward tasks requiring deliberate reasoning, which cannot be solved through pattern recognition.
## A Reasoning Benchmark Framework
*Effective evaluation demands benchmarks that are clear, simple, and tool-free*.
We propose the following milestones:
1. *Basic Arithmetic Competence*: A reasoning model should reliably compute sums, products, or powers for large numbers without external tools.
2. *Execution of Simple Algorithms*: The model should be able to perform basic algorithmic tasks, such as sorting a list, computing a factorial, or simulating a logical circuit without external tools.
3. *Structured Puzzles*: Tasks like sudoku or nonograms without external tools.
4. *Strategic Gameplay*: Games such as tic-tac-toe, checkers, or chess without external tools.
5. *Novel Problem Solving*: Finally, a capable reasoning system should propose original solutions to well-defined mathematical or logical problems. Generating new proofs or contributing insights to unsolved problems would demonstrate a high degree of reasoning aptitude.
These benchmarks establish a baseline for reasoning but do not imply artificial general intelligence (AGI).
At the same time, we can use these benchmarks to discard claims that LLMs are somehow "close" to AGI.
## External Tools and Transparency
Proprietary LLMs often integrate tools to enhance performance, but this prevents evaluation of the models.
To ensure fair assessment, vendors should provide a way to disable tools during evaluations.
## Simplicity as a Strength
Critics may argue that simple benchmarks fail to capture real-world complexity. Yet, as shown by arithmetic, simplicity can illuminate reasoning processes without sacrificing rigor.
Straightforward tasks like multi-step computations and logical puzzles reveal essential reasoning skills without relying on tricky or convoluted questions.
## Conclusion
Evaluating reasoning in LLMs does not require convoluted tests. Transparent, tool-free benchmarks grounded in deliberate problem-solving provide a clearer measure of progress. By focusing on tasks that demand "System 2" thinking, we can set meaningful milestones for development.
No LLM should be deemed closer to AGI if it cannot solve simple reasoning problems independently. Transparency and simplicity are essential for advancing our understanding of these systems and their potential.
Comments URL: https://news.ycombinator.com/item?id=42192562
Points: 2
# Comments: 0
Oushangmei power adapter manufacturer with UL certs
Article URL: https://www.poweradapter-manufacturers.com/
Comments URL: https://news.ycombinator.com/item?id=42192552
Points: 1
# Comments: 1
Earn More Than Twice the National Average With These Top Accounts Today's CD Rates, Nov. 20, 2024
BasedFlare – Sovereign DDoS Protection
Article URL: https://basedflare.com/#
Comments URL: https://news.ycombinator.com/item?id=42192484
Points: 1
# Comments: 0