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Gunnar_Zarncke
Testosterone influences brain function but not so much general IQ. It may influence to which areas your attention and thus most of your learning goes. For example, Lower testosterone increases attention to happy faces while higher to angry faces.
I think it is often worth for multiple presentations of the same subject to exist. One may be more accessible for some of the audience.
Interesting to see this just weeks after Generalized Stat Mech: The Boltzmann Approach
there’s a mental move of going up and down the ladder of abstraction, where you zoom in on some particularly difficult and/or confusing part of the problem, solve it, and then use what you learned from that to zoom back out and fill in a gap in the larger problem you were trying to solve. For an LLM, that seems like it’s harder, and indeed it’s one of the reasons I inside-view suspect LLMs as-currently-trained might not actually scale to AGI. [bold by me]
But that might already no longer be true with model that have short term memory and may might make moves like you. See my Leave No Context Behind—A Comment.
If I haven’t overlooked the explanation (I have read only part of it and skimmed the rest), my guess for the non-membership definition of the empty string would be all the SQL and programming queries where “” stands for matching all elements (or sometimes matching none). The small round things are a riddle for me too.
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Abstract:
Despite the impressive capabilities of Large Language Models (LLMs) on various tasks, they still struggle with scenarios that involves complex reasoning and planning. Recent work proposed advanced prompting techniques and the necessity of fine-tuning with high-quality data to augment LLMs’ reasoning abilities. However, these approaches are inherently constrained by data availability and quality. In light of this, self-correction and self-learning emerge as viable solutions, employing strategies that allow LLMs to refine their outputs and learn from self-assessed rewards. Yet, the efficacy of LLMs in self-refining its response, particularly in complex reasoning and planning task, remains dubious. In this paper, we introduce ALPHALLM for the self-improvements of LLMs, which integrates Monte Carlo Tree Search (MCTS) with LLMs to establish a self-improving loop, thereby enhancing the capabilities of LLMs without additional annotations. Drawing inspiration from the success of AlphaGo, ALPHALLM addresses the unique challenges of combining MCTS with LLM for self-improvement, including data scarcity, the vastness search spaces of language tasks, and the subjective nature of feedback in language tasks. ALPHALLM is comprised of prompt synthesis component, an efficient MCTS approach tailored for language tasks, and a trio of critic models for precise feedback. Our experimental results in mathematical reasoning tasks demonstrate that ALPHALLM significantly enhances the performance of LLMs without additional annotations, showing the potential for self-improvement in LLMs
https://arxiv.org/pdf/2404.12253.pdf
This looks suspiciously like using the LLM as a Thought Generator, the MCTS roll-out as the Thought Assessor, and the reward model R as the Steering System.This would be the first LLM model that I have seen that would be amenable to brain-like steering interventions.
Examples of blessed information that I have seen in the context of logging:
Stacktraces logged by a library that elide all the superfluous parts of the stacktraces.
A log message that says exactly what the problem is, why it is caused (e.g., which parameters lead to it), and where to find more information about it (ticket number, documentation page).
The presence of a Correlation IDs (also called Transaction ID, Request ID, Session ID, Trace ID).
What is a correlation ID? It is an ID that is created at the start of a request/session and available in all logs related to that request/session. See here or here, implementations here or here. There are even hierarchical correlation IDs
Esp. useful: A correlation ID that is accessible from the client.
Even more useful: If there is a single place to search all the logs of a system for the ID.
Aggregation of logs, such that only the first, ten’s, 100s… of a log message is escalated.
That’s a nice graphical illustration of what you do. Thanks.
Guys, social reality is one if not the cause of the self:
And the part of our minds we most fear losing control of is: our deep values.
PubMed: The essential moral self
folk notions of personal identity are largely informed by the mental faculties affecting social relationships, with a particularly keen focus on moral traits.
Conceptually, we could then sketch out the whole fractal by repeating this process to randomly sample a bunch of points. But it turns out we don’t even need to do that! If we just run the single-point process for a while, each iteration randomly picking one of the three functions to apply, then we’ll “wander around” the fractal, in some sense, and in the long run (pretty fast in practice) we’ll wander around the whole thing.
Not if you just run just that code part. It will quickly converge to some very small area of the fractal and not come back. Something must be missing.
Seems you did everything right. Life is not perfect and you seem to have struck a great balance. If you had to formulate guidelines for other parents living with housemates, what would you say? I mean, based on your post it sounds like:
A good time to consider moving is...
when the family is taking up so much of the common space the other housemates can’t make use of it. Unless they like it that way.
when there is not enough space for all the stuff of everybody, including in the fridge, shed, attic. Unless you can take that as an opportunity and declutter.
when the kids can’t sleep because of the adults’ activities (or the other way around). Sleep is important. And none of the countermeasures helped.
This is completely not about performance. Humans are not good at that either. It is the ability to learn fully general simulation. It is not exactly going full circle back to teaching computers math and logic, but close. It is more a spiral to one level higher; that the LLMs can understand these.
the English language is adapted to a world where “humans don’t fork” has always been a safe assumption.
If we can clone ourselves, language would probably quickly follow. The bigger change would probably be the one about social reality. What does it mean to make a promise? Who is the entity you make a trade with? Is it the collective of all the yous? Only one? But which one if they split? The yous resulting from one origin will presumably have to share or split their resources. How will they feel about it? Will they compete or agree? If they agree it makes more sense for them to feel more like a distributed being. The thinking of “I” might get replaced by an “us”.
So if something makes no physical difference to my current brain-state, and makes no difference to any of my past or future brain-states, then I think it’s just crazy talk to think that this metaphysical bonus thingie-outside-my-brain is the crucial thing that determines whether I exist, or whether I’m alive or dead, etc.
There is one important aspect where it does make a difference. A difference in social reality. The brain states progress in a physically determined way. There is no way they could have progressed differently. When a “decision is made” by the brain, then that is fully the result of the inner state and the environment. It could only have happened differently if the contents of the brain had been different—which they were not. They may have been expected to be different by other people (‘s brains), but that is in their map, not in reality. But our society is constructed based on the assumption that things could have been different, that actions are people’s ‘faults’. That is an abstraction that has shown to be useful. Societies that have people who act as if they are agents with free will maybe coordinate better—because it allows feedback mechanisms on their behaviors.
abstract redescriptions of ordinary life
If a brain-state A has quasi-sensory access to the experience of another brain-state B — if A feels like it “remembers” being in state B a fraction of a second ago — then A will typically feel as though it used to be B.
This suggests a way to add a perception of “me” to LLMs, robots, etc., by providing a way to observe the past states in sufficient detail. Current LLMs have to compress this into the current token, which may not be enough. But there are recent extensions that seem to do something like continuous short-term memory, see e.g., Leave No Context Behind—A Comment.
a magical Cartesian ghost
for people who haven’t made the intuitive jump that you seem to try to convey, this may seem a somewhat negative expression, which could lead to aversion. I recommend another expression such as “the Cartesian homunculus.”
I like it. It feels a bit incomplete and doesn’t live up to its title, but I’d like to see more like this.
2020-02-18 Anna pretend-playing with herself is the most impressive I have seen, though there are close competitors.
I asked ChatGPT
and it’s difficult to get examples out of it. Even with additional drilling down and accusing it of being not inclusive of people with cognitive impairments, most of its examples are either pretty smart anyway, savants or only from poor backgrounds. The only ones I could verify that fit are:
Richard Jones accidentally created the Slinky
Frank Epperson, as a child, Epperson invented the popsicle
George Crum inadvertently invented potato chips
I asked ChatGPT (in a separate chat) to estimate the IQ of all the inventors is listed and it is clearly biased to estimate them high, precisely because of their inventions. It is difficult to estimate the IQ of people retroactively. There is also selection and availability bias.