shock-value

I explicitly stated in a different comment that Rednote will not replace TikTok. I don’t think anyone seriously believes that. It’s subject to the same ban after all.

The interesting aspect here is rather the magnitude of dissatisfaction that a large percentage of users feel towards the other mainstream US social content platforms.

I don’t think anyone thinks RedNote will replace TikTok — it’s potentially subject to the same ban after all.

But it illustrates the general dissatisfaction among TikTok users with the other mainstream US social content platforms.

Rednote has been shown as the top free app (per Apple’s own App Store in my device at least) for going on a week, so the magnitude may be larger than you imply.

Also, having tried it myself, the algorithm works much like TikTok whereby it learns to show English speakers English content pretty quickly.

Also the general consensus among people who have used IG and TikTok (I personally don’t use IG) seems to be that the former does not at all substitute for the latter, particularly in terms of the subjective “authentic” feel of the content (IG often said to be lacking the community feel of TikTok).

P and B frames are compressed versions of a reference image. Frames resulting from DLSS frame generation are predictions of what a reference image might look like even though one does not actually exist.

Speaking of Bitcoin specifically, if this is your view then you should take some time to understand the severe societal and economic problems that come with persistent deflation. And more generally, determining the optimal level of the money supply to match the needs of a dynamic economy is not trivial — there is no simple formula involving straightforwardly measurable variables that I am aware of.

LLMs/transformers are a breakthrough on the level of convolutional neural networks — significant, and one that opens up lots of new interesting applications as well as invites lots more R&D — but like the neural net it’s not gonna fundamentally transform society or industry.

(And as far as I can tell this current craze is entirely predicated on LLMs/transformers.)

No you just decide what movie you want to watch and pay $4 to rent it on demand. Very common experience available to anyone with a smart TV or connected streaming device.

I think the companies pursuing VR see that as a momentary technical deficiency, not an inherent limitation of VR generally. So to characterize their efforts as a long-term “bet” against multitasking seems silly to me.

VR covers your entire field of view, so not sure why you’d claim that it precludes multitasking, even if the current iterations aren’t yet geared toward that.

It's obviously a productive change and kudos for taking it on, but much of the enthusiasm being generated here was driven by the entirely unanticipated prospect of running a model at full speed using less memory than the model's own footprint, and by the notion that inference with a dense model somehow behaved in a sparse manner at runtime. Best to be a bit more grounded here, particularly with regard to claims that defy common understanding.

It appears that this was just a misreading of how memory usage was being reported and there was actually no improvement here. At least nothing so sensational as being able to run a larger-than-RAM model without swapping from disk on every iteration.

> ... these large language models are already intelligent enough to matter.

I'm definitely not contesting that.

I've always considered the idea of "AGI" to mean something of the holy grail of machine learning -- the point at which there is no real point in pursuing further advances in artificial intelligence because the AI itself will discover and apply such augmentations using its own capabilities.

I have seen no evidence that these transformer models would be able to do this, but if the current models can do so do then perhaps I will eat my words. (Doing this would likely mean that GPT-4 would need to propose, implement, and empirically test some fundamental architectural advancements in both multimodal and reinforcement learning.)

By the way, many researchers are equally convinced that these models are in fact not AGI -- that includes the head of OpenAI.

The debate over what kind of intelligence these models possess is rightly lively and ongoing.

It’s clear that at the least, they can decipher very numerous patterns across a wide range of conceptual depths — it’s an architectural advance easily on the the level of the convolutional neural network, if not even more profound. The idea that NLP is “solved” isn’t a crazy notion, though I won’t take a side on that.

That said, it’s equally obvious that they are not AGI unless you have a really uninspired and self-limiting definition of AGI. They are purely feedforward aside from the single generated token that becomes part of the input to the next iteration. Multimodality has not been incorporated (aside from possibly a limited form in GPT-4). Real-world decision-making and agency is entirely outside the bounds of what these models can conceive or act towards.

Effectively and by design these models are computational behemoths trained to do one singular task only — wring a large textual input though an enormous interconnected web of calculations purely in service of distilling everything down to a single word as output, a hopefully plausible guess at what’s next given what’s been seen.

> Opting out would just mean all your missing data alerts fire every time Datadog has an incident and you would then check, see that everything is missing, and then identify the cause as the Datadog incident.

You are missing the last step, which is that, knowing alerts are down, you can actively monitor using other tools/reporting for the duration of their incident.

And why would you have no logs? Even assuming you ingest logs through Datadog (they monitor on much than just logs and not everyone uses all facets of their offering), you would presumably have some way to access them more directly (even tailing output directly if necessary).

And lastly, why would you communicate to your customers without any idea of the scope or cause of the issue? It would likely be clear very quickly that Datadog was having issues when you see that all your metrics are suddenly discontinued without other ill effect.

This is convenient behavior up until you actually have an incident that coincides with theirs, in which case it becomes catastrophic because you had no idea that outside vigilance was required on account of their ingestion downtime. Not sure why you would laud this. Is it possible to opt out?

> emergent behavior in this context is defined as: "emergent abilities, which we define as abilities that are not present in small models but are present in larger models"

Then I don't know why you brought up Game of Life because it obviously has nothing to do with this alternative definition of emergent behavior.

> this is a meaningless distinction.

It's meaningful with respect to the claim that LLMs exhibit emergent behavior in the same way in which Game of Life does.

I'm arguing against the notion that these LLMs exhibit "emergent behaviour" as you stated. I don't believe they do, as the term is commonly understood. Emergent behavior usually implies the exhibition of some kind of complexity from a fundamentally simple system. But these LLMs are not fundamentally simple, when considered together with the vast corpus of training data to which they are inextricably linked.

The emergent behavior of Conway's Game of Life arises purely out of the simple rules upon which the simulation proceeds -- a fundamental difference.

It's modeling patterns found across the massive corpus of textual training input it has seen -- not the true concepts related by the words as humans understand them. If you don't believe me then ask ChatGPT some bespoke geometry-related brain teasers and see how far it gets.

I want to be clear that the successful scale-up of this training and inference methodology is nonetheless a massive achievement -- but it is inherently limited by the nature of its construction and is in no way indicative of a system that exudes agency or deliberative thought, nor one that "understands" or models the world as a human would.

The advancement with these LLMs lies in the fact that they can effectively learn to recognize patterns within “large-ish” input text sequences and probabilistically generate a likely next word given those patterns.

It’s a genuine advancement. However it is still just pattern matching. And describing anything it’s doing as “behavior” is a real stretch given that it is a feed-forward network that does not incorporate any notion of agency, memory, or deliberation into its processing.

The anthropomorphism is indeed exactly why this is a big problem. If the user thinks the responses are coming from an intelligent agent tasked with being helpful, but in reality are generated from a text completion model prone to mimicking adversarial or deceptive conversations, then damaging outcomes can result.

As far as I am concerned, if the Chinese state is pushing a grassroots recognition of this event that could lead to accountability and improved safety practices, then they are doing us a public service.

I don’t know or care what Chinese internal media is reporting — this is a significant story in the U.S. that is getting less play than it should. It’s an ecological disaster with potentially significant health concerns, and likely involves corporate negligence as well as a failure of governance by both political parties who recently forced rail workers back to work despite complaints related to possible causes of this derailment (and others).

The spy/balloon thing is way less significant and has been ongoing by both sides for years or even decades if my understanding is correct.

I’m on a 14 Pro and cannot find these settings either.

It’s not just a matter of degree or quantity of post processing. Some techniques are qualitatively different than others.

Good practice would be leaving a comment with a TODO, an explanation of the problem, and some basic instructions as to a possible fix.

Leaving your email and phone number is absurd and should not be promoted as good practice. No sane company would take you up on the offer anyway.

Lowering rates will give a boost to the stock market in the short to medium term. In the long term, returns will settle closer to the interest rate in question (plus a risk premium). See: Japan over the last couple of decades.

There isn’t much information available on how its indexing works internally, whether tag existence / tag values can be indexed, etc. So it’s hard to judge the extent to which this could be a replacement for Postgres with PostGIS.

I think it’s a bit of a point of no return for both sides. Musk wanted all chips on the table, got them, and it turns out his hand isn’t as strong as he thought. There is no going back to status quo after this email stunt, it literally made clear that the majority of employees are just sticking around until they find something else, and would even leave sooner if at all pushed to. This is a sinking ship.

It's unclear if there will be a solution (possibly not supported by Sony) to use it as a display for PC.

It's better than having integrated headphones I think. If the included ones (however basic they are) are in-ear, then the immersion and sound quality would likely be better than anything that would be attached to the headset.

Onboard audio is just a waste of money for something that neither casuals nor enthusiasts would care about (former by definition, latter because they would prefer to use their own audio gear).

Lack of wireless is a definite minus though.