Let The Weak Say I Am Strong Mp3 Download

We present a new research direction for superalignment, together with promising initial results: can we leverage the generalization properties of deep learning to control strong models with weak supervisors?

A simple analogy for superalignment: In traditional machine learning (ML), humans supervise AI systems weaker than themselves (left). To align superintelligence, humans will instead need to supervise AI systems smarter than them (center). We cannot directly study this problem today, but we can study a simple analogy: can small models supervise larger models (right)?

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There are still important disanalogies between our current empirical setup and the ultimate problem of aligning superhuman models. For example, it may be easier for future models to imitate weak human errors than for current strong models to imitate current weak model errors, which could make generalization harder in the future.

Nevertheless, we believe our setup captures some key difficulties of aligning future superhuman models, enabling us to start making empirical progress on this problem today. There are many promising directions for future work, including fixing the disanalogies in our setup, developing better scalable methods, and advancing our scientific understanding of when and how we should expect good weak-to-strong generalization.

I think this latter syntax is very clear in its intent. We all know the 'weak/strong' dance. So simply using it literally as the reference modifier seems intuitive if that's what you're trying to do. In terms of simplicity, I think it's clear that all this does is only execute the closure if the weakStrong reference exists. I don't know how difficult this would be to implement, but at some level, all it really would be doing is adding a guard to check for the existence of the reference type at the beginning of the closure.

I've solved this issue for myself by using a special container type that can store a weakly held object alongside the closure. The trick that is used by the container type is to check if the object still exists before calling the closure. If the object still exist, it is passes it as a non-optional parameter to the closure. If it doesn't exist anymore, the closure isn't called at all.

Inexperienced users will be using weakStrong by default because it is convenient. But in the example above completion must be called with error/result, if self was deallocated. Using of weakStrong here will lead to floating bugs, because sometimes completion will not be executed, which is unexpected.

I know this is very rare case. So this feature for example can only be allowed if closure has no closures in its arguments.

Any thoughts about this?

The network call is guaranteed to run to completion. For exactly-once called closures, there should seldom be any need for weak capture. The strong capture will only delay deinit of self by at most a few seconds.

It is my experience that this is often the case. That people ask for more ergonomic weak/strong syntax, when the real solution is just to use the default capture with no special syntax and be done with it.

While it's true that this often works, you still have to spend mental energy to decide if this would create a memory leak and if you need an unowned or weak annotation. In general it is of course a good idea to think about retain cycles in callbacks, but especially in view-related code it's getting boring after a few hundred callbacks, and it's also error-prone.

This is why many developers (including me) come to the conclusion that it's a more robust approach to always use the [weak self] annotation in view-related code and to always write callback code with the assumption that it will not be executed if the view was closed.

Sure. But imho people vastly overuse the weak capture, to the point where it often leads to buggy code. Most times people ask for more ergonomic syntax for weak/strong, the better solution is usually to avoid weak capture at all.

But imho people vastly overuse the weak capture, to the point where it often leads to buggy code. Most times people ask for more ergonomic syntax for weak/strong, the better solution is usually to avoid weak capture at all.

The way I usually handle the latter problem is by wrapping all completion handler APIs into blocking calls and running them on background queues. Which means that almost all completion handlers in my apps (ignoring the wrapper code) are event handlers that ideally capture self weakly. IMO the event handler use case would deserve better language support.

The proposed spelling of [weakStrong self] is a little unfortunate, because it doesn't communicate that the closure may not be executed. If something like this would be added to the language I would prefer the spelling [if self]:

During the trough of disillusionment, entrepreneurs and others who invested in strong technologies sometimes lose faith and switch their focus to weak technologies, because the weak technologies appear nearer to mainstream adoption. This is usually a mistake.

"A book whose entire message can be summed up in a 2-inch by 2-inch chart at first may seem overly simplistic and unworthy of its 186 pages, but Crouch effectively digs beyond the surface of his message. He rewards readers with helpful insights into how Christians can flourish by acknowledging vulnerability instead of suppressing it. Both the pastor and the layperson will walk away from Strong and Weak with a fresh outlook on how God's power is perfected in weakness."

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Handgrip strength is an important biomarker of healthy ageing and a powerful predictor of future morbidity and mortality both in younger and older populations. Therefore, the measurement of handgrip strength is increasingly used as a simple but efficient screening tool for health vulnerability. This study presents normative reference values for handgrip strength in Germany for use in research and clinical practice. It is the first study to provide normative data across the life course that is stratified by sex, age, and body height. The study used a nationally representative sample of test participants ages 17-90. It was based on pooled data from five waves of the German Socio-Economic Panel (2006-2014) and involved a total of 11,790 persons living in Germany (providing 25,285 observations). Handgrip strength was measured with a Smedley dynamometer. Results showed that peak mean values of handgrip strength are reached in men's and women's 30s and 40s after which handgrip strength declines in linear fashion with age. Following published recommendations, the study used a cut-off at 2 SD below the sex-specific peak mean value across the life course to define a 'weak grip'. Less than 10% of women and men aged 65-69 were classified as weak according to this definition, shares increasing to about half of the population aged 80-90. Based on survival analysis that linked handgrip strength to a relevant outcome, however, a 'critically weak grip' that warrants further examination was estimated to commence already at 1 SD below the group-specific mean value.

TLA+ specifications must be stutter-invariant. A stutter is a temporal step where we reassign all of the variables to the same values. To an outside observer, this looks like nothing has happened. Stutter-invariance is what makes composing specs in TLA+ a miserable experience, as opposed to other specification languages, where composing specs is a punishment for sinners in hell.

Weak fairness applies to specific actions- descriptions of how the state can change- in the spec, not the whole spec. This is gives us a lot more flexibility. If I instead implemented the spec as

Low-field magnetoresistance is ubiquitous in low-dimensional metallic systems with high resistivity and well understood as arising due to quantum interference on self-intersecting diffusive trajectories. We have found that in graphene this weak-localization magnetoresistance is strongly suppressed and, in some cases, completely absent. The unexpected observation is attributed to mesoscopic corrugations of graphene sheets which can cause a dephasing effect similar to that of a random magnetic field.

Economists and biologists have proposed a distinction between two mechanisms--"strong" and "weak" reciprocity--that may explain the evolution of human sociality. Weak reciprocity theorists emphasize the benefits of long-term cooperation and the use of low-cost strategies to deter free-riders. Strong reciprocity theorists, in contrast, claim that cooperation in social dilemma games can be sustained by costly punishment mechanisms, even in one-shot and finitely repeated games. To support this claim, they have generated a large body of evidence concerning the willingness of experimental subjects to punish uncooperative free-riders at a cost to themselves. In this article, I distinguish between a "narrow" and a "wide" reading of the experimental evidence. Under the narrow reading, punishment experiments are just useful devices to measure psychological propensities in controlled laboratory conditions. Under the wide reading, they replicate a mechanism that supports cooperation also in "real-world" situations outside the laboratory. I argue that the wide interpretation must be tested using a combination of laboratory data and evidence about cooperation "in the wild." In spite of some often-repeated claims, there is no evidence that cooperation in the small egalitarian societies studied by anthropologists is enforced by means of costly punishment. Moreover, studies by economic and social historians show that social dilemmas in the wild are typically solved by institutions that coordinate punishment, reduce its cost, and extend the horizon of cooperation. The lack of field evidence for costly punishment suggests important constraints about what forms of cooperation can or cannot be sustained by means of decentralised policing. e24fc04721