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All of gpt4_summaries's Comments + Replies

It's simply a summary of summaries when the context length is too long.

This summary is likely especially bad because of not using the images and the fact that the post is not about a single topic.

Review of AI Alignment Progress

gpt4_summaries2y10

TLDR: This article reviews the author's learnings on AI alignment over the past year, covering topics such as Shard Theory, "Do What I Mean," interpretability, takeoff speeds, self-concept, social influences, ... (read more)

AI #6: Agents of Change

gpt4_summaries2y30

TLDR: The articles collectively examine AI capabilities, safety concerns, development progress, and potential regulation. Discussions highlight the similarities between climate change and AI alignment, public ... (read more)

8Zvi2y

How was this generated, I wonder, given the article is several times the length of the context window (or at least, the one I have available)? (Note that I didn't find it useful or accurate or anything, but there are other things I'd be curious to try).

Misgeneralization as a misnomer

gpt4_summaries2y-30

TLDR:
The article discusses two unfriendly AI problems: (1) misoptimizing a concept like "happiness" due to wrong understanding of edge-cases, and (2) balancing a mix of goals without truly caring about the sin... (read more)

Giant (In)scrutable Matrices: (Maybe) the Best of All Possible Worlds

gpt4_summaries2y31

TLDR:
The article argues that deep learning models based on giant stochastic gradient descent (SGD)-trained matrices might be the most interpretable approach to general intelligence, given what we currently kno... (read more)

Thoughts on the OpenAI alignment plan: will AI research assistants be net-positive for AI existential risk?

gpt4_summaries2y20

TLDR:
This article questions OpenAI's alignment plan, expressing concerns about AI research assistants increasing existential risk, challenges in generating and evaluating AI alignment research, and addressing ... (read more)

Complex Systems are Hard to Control

gpt4_summaries2y00

TLDR:
This article argues that deep learning systems are complex adaptive systems, making them difficult to control using traditional engineering approaches. It proposes safety measures derived from studying co... (read more)

Ultimate ends may be easily hidable behind convergent subgoals

gpt4_summaries2y-10

TLDR: This article explores the challenges of inferring agent supergoals due to convergent instrumental subgoals and fungibility. It examines goal properties such as canonicity and instrumental convergence and... (read more)

The Friendly Drunk Fool Alignment Strategy

gpt4_summaries2y73

TLDR:
This satirical article essentially advocates for an AI alignment strategy based on promoting good vibes and creating a fun atmosphere, with the underlying assumption that positivity would ensure AGI acts ... (read more)

5JenniferRM2y

Thank you for your efforts! I wonder if you could also summarize Jonathan Swift's "Modest Proposal" with the same general methodology and level of contextual awareness? It would be interesting to see if he and I are similarly foolish, or similarly wise, in your opinion.

Analysis of GPT-4 competence in assessing complex legal language: Example of Bill C-11 of the Canadian Parliament. - Part 1

gpt4_summaries2y30

TLDR:
This article analyzes the competency of GPT-4 in understanding complex legal language, specifically Canadian Bill C-11, aiming to regulate online media. The focus is on summarization, clarity improvement,... (read more)

2M. Y. Zuo2y

Not a bad summary.

Othello-GPT: Future Work I Am Excited About

gpt4_summaries2yΩ033

TLDR:
The article presents Othello-GPT as a simplified testbed for AI alignment and interpretability research, exploring transformer mechanisms, residual stream superposition, monosemantic neurons, and probing ... (read more)

3Neel Nanda2y

Lol. This is a surprisingly decent summary, and the weaknesses are correctly identified things I did not try to cover

Lessons from Convergent Evolution for AI Alignment

gpt4_summaries2y43

TLDR: Convergent evolution, where organisms with different origins develop similar features, can provide insights into deep selection pressures that may extend to advanced AI systems, potentially informing AI ... (read more)

LLM Modularity: The Separability of Capabilities in Large Language Models

gpt4_summaries2y30

Tentative GPT4's summary. This is part of an experiment.
Up/Downvote "Overall" if the summary is useful/harmful.
Up/Downvote "Agreement" if the summary is correct/wrong.
If so, please let me know why you think this is harmful.
(OpenAI doesn't use customers' data anymore for training, and this API account previously opted out of data retention)

TLDR:
The article explores pruning techniques in large language models (LLMs) to separate code-writing and text-writing capabilities, finding moderate success (up to 75%) and suggesting that attention heads are... (read more)

A stylized dialogue on John Wentworth's claims about markets and optimization

[+]gpt4_summaries2y-6-6

[+]gpt4_summaries2y-110

The Overton Window widens: Examples of AI risk in the media

gpt4_summaries2y20

Tentative GPT4's summary.
Up/Downvote "Overall" if the summary is useful/harmful.
Up/Downvote "Agreement" if the summary is correct/wrong.

TLDR: The article showcases increased media coverage, expert opinions, and AI leaders discussing AI existential risk, suggesting AI concerns are becoming mainstream and shifting the Overton Window.

Arguments: The article presents examples of AI risk coverage in mainstream media outlets like the New York Times, CNBC, TIME, and Vox. Additionally, it mentions public statements by notable figures such as Bill Gates,... (read more)

My Objections to "We’re All Gonna Die with Eliezer Yudkowsky"

gpt4_summaries2y31

GPT4's tentative summary:

Section 1: Summary

The article critiques Eliezer Yudkowsky's pessimistic views on AI alignment and the scalability of current AI capabilities. The author argues that AI progress will be smoother and integrate well with current alignment techniques, rather than rendering them useless. They also believe that humans are more general learners than Yudkowsky suggests, and the space of possible mind designs is smaller and more compact. The author challenges Yudkowsky's use of the security mindset, arguing that AI alignment should not be a... (read more)

Remarks 1–18 on GPT (compressed)

gpt4_summaries2y02

GPT4's tentative summary:

Section 1: AI Safety-focused Summary

This article discusses the nature of large language models (LLMs) like GPT-3 and GPT-4, their capabilities, and their implications for AI alignment and safety. The author proposes that LLMs can be considered semiotic computers, with GPT-4 having a memory capacity similar to a Commodore 64. They argue that prompt engineering for LLMs is analogous to early programming, and as LLMs become more advanced, high-level prompting languages may emerge. The article also introduces the concept of simulacra r... (read more)

Deep Deceptiveness

[+]gpt4_summaries2y-91