nopinsight

8 ms·

91.
by nopinsight 2y ago
A standard term people use for what you describe is superintelligence , not AGI. Current frontier models are better than average humans in many skills but worse in others. Ethan Mollick calls it “jagged frontier” which sounds about right.
92.
by nopinsight 2y ago
Research by METR suggests that frontier LLMs can perform software tasks over exponentially longer time horizon required for human engineers, with ~7-month for each doubling. o3 is above the trend line. https://x.com/METR_E
93.
by nopinsight 2y ago
The fact that much of physics can be so elegantly described by math suggests the structures of our math could be quite universal, at least in our universe. Check out the problems in the MATH dataset, especially Level 5 problems. They are fa
94.
by nopinsight 2y ago
My request: “Could you explain this sentence concisely? For the skeptics: Scoring just 10% or so in Math-Perturb-Hard below the original MATH Level 5 (hardest) dataset seems in line with or actually better than most people would do.” Gemini
95.
by nopinsight 2y ago
Please check out the post on Math-Perturb-Hard conveniently linked to above before making a comment without responding to it. A relevant bit: “for MATH-P-Hard, we make hard perturbations, i.e., small but fundamental modifications to the pro
96.
by nopinsight 2y ago
Solving hard math problems requires understanding the structure of complex mathematical reasoning. No animal is known to be capable of that. Most definitions and measurements of intelligence by most laypeople and psychologists include the
97.
by nopinsight 2y ago
For the skeptics: Scoring just 10% or so in Math-Perturb-Hard below the original MATH Level 5 (hardest) dataset seems in line with or actually better than most people would do. Does that mean most people are merely parrots too? https:&#x2F
98.
DeepMind: An Approach to Technical AGI Safety and Security [pdf](storage.googleapis.com)
3 points by nopinsight 2y ago|0 comments
99.
by nopinsight 2y ago
If by “several” orders of magnitude, you mean 3-5, then we might be there by 2030 or earlier. https://situational-awareness.ai/from-gpt-4-to-agi/
100.
by nopinsight 2y ago
>> unaided humans cannot operate successfully in many situations > Absolute nonsense driven by a total lack of historical perspective or knowledge. An LLM can give you a list of examples: Historical Examples: - During historical ep
101.
by nopinsight 2y ago
Can our brains recall precise citations to tens of papers we read a while ago? For the vast majority, no. LLMs function somewhat similarly to our brains in many ways, as opposed to classical computers. Their strengths and flaws differ from
102.
KAIST Develops Foundational Technology to Revert Cancer Cells to Normal Cells(news.kaist.ac.kr)
3 points by nopinsight 2y ago|0 comments
103.
by nopinsight 2y ago
1) It’s an example of a domain an LLM can do better than humans. A 2012 system was not able to do myriad other things LLMs can do and thus not qualified as general intelligence. 2) As mentioned in the chart label, earlier systems requir
104.
by nopinsight 2y ago
Figure 1 shows a significant improvement of o1-preview over earlier models. Perhaps it’s better that you ask a statistician you trust.
105.
by nopinsight 2y ago
If we talk about a median well-educated human, o1 likely passes the bar. Quite a few tests of reasoning suggests that’s the case. An example: “Preprint out today that tests o1-preview's medical reasoning experiments against a baselin
106.
by nopinsight 2y ago
Dario said in mid-2023 that his timeline for achieving "generally well-educated humans" was 2-3 years. o1 and Sonnet 3.5 (new) have already fulfilled that requirement in terms of Q&A, ahead of his earlier timeline.
107.
by nopinsight 2y ago
Superintelligence (along with some definitions): https://en.wikipedia.org/wiki/Superintelligence Also, "Dario Amodei says what he has seen inside Anthropic in the past few months leads him to believe that in the n
108.
by nopinsight 2y ago
The goal is Artificial Superintelligence (ASI), based on short clips of the press conference. It has been quite clear for a while we'll shoot past human-level intelligence since we learned how to do test-time compute effectively with R
109.
by nopinsight 2y ago
It's far from obvious that thought space is much less complex than physical space. Natural language covers emotional, psychological, social, and abstract concepts that are orthogonal to physical aptitude. While the linguistic represent
110.
by nopinsight 2y ago
Walking is indeed a complex skill. Yet some animals walk minutes after birth. Human babies are most likely born premature due to the large brain and related physical constraints. Young children learn to bike or skate at an older age after t
111.
by nopinsight 2y ago
The brain is predisposed to learn those skills. Early childhood experiences are necessary to complete the training. Perhaps that could be likened to post-training. It's not a one-to-one comparison but a rather loose analogy which I did
112.
by nopinsight 2y ago
Many of humans' capabilities are pretrained with massive computing through evolution. Inference results of o3 and its successors might be used to train the next generation of small models to be highly capable. Recent advances in the ca
113.
by nopinsight 2y ago
Their reasoning models can learn from procedures and methods, which generalize far better than data. Software tasks are diverse but most tasks are still fairly limited in scope. Novel tasks might remain challenging for these models, as they
114.
by nopinsight 2y ago
Thanks! I added some comments on this at the bottom of the post above.
115.
by nopinsight 2y ago
Thanks! I've analyzed some easy problems that o3 failed at. They involve spatial intelligence including connection and movement. This skill is very hard to learn from textual and still image data. I believe this sort of core knowledge
116.
by nopinsight 2y ago
Great point. I'd love to see what these easy tasks are and would be happy to revise my hypothesis accordingly. o3's intelligence is unlikely to be a strict superset of human intelligence. It is certainly superior to humans in some
117.
by nopinsight 2y ago
I'd need to see what kinds of easy tasks those are and would be happy to revise my hypothesis if that's warranted. Also, it depends a great deal on what we define as AGI and whether they need to be a strict superset of typical hum
118.
by nopinsight 2y ago
One possibility is that it may not yet have sufficient experience and real-world feedback for resolving coding issues in professional repos, as this involves multiple steps and very diverse actions (or branching factor, in AI terms). They
119.
by nopinsight 2y ago
Let me go against some skeptics and explain why I think full o3 is pretty much AGI or at least embodies most essential aspects of AGI. What has been lacking so far in frontier LLMs is the ability to reliably deal with the right level of abs
120.
Study: Better Large Language Models Process Text More Like Human Brains Do(arxiv.org)
2 points by nopinsight 2y ago|0 comments

More ›