Consider the Kinder surprise egg, a quite astonishing commodity. The surprise of the Kinder Surprise egg is that this excessive object, the cause of your desire, is here materialized in the guise of an object, a plastic toy which fills in the inner void of the chocolate egg. The whole delicate balance is between these two dimensions. What you bought, the chocolate egg and the surplus, probably made in some Chinese gulag or whatever, the surplus that you get for free. I don’t think that the chocolate frame is here just to send you on a deeper voyage towards the inner treasure, what Plato calls the agalma, which makes you a wealthy person; which makes a commodity the desirable commodity. I think it’s the other way around. We should aim at the higher goal, the goal in the middle of an object precisely to be able to enjoy the surface. This is what is the anti-metaphysical lesson, which is difficult to accept.
Any previewers have hot takes? I've really preferred gpt-5.5 over Opus 4.8 for data analysis and scientific software work. It seems much more reliable. Fable is unusable for the type of work that I do (due to guardrails). Really looking forward to trying these new OpenAI models out.
This is a cool idea—I know from snooping on sumbit scripts and node utilization on the HPC that I use at my institution that most submissions leave some compute on the table (and many of them are egregiously bad). I'd probably vote in favor of sending every submitted sbatch script through an LLM (at least for everyone else, I'd would prefer tuning my own usage myself :) ).
Presumably the underlying model here is also an LLM? To what degree is it "fine-tuned", or is it just given a set of tools to build a good picture of cluster usage?
I wonder if the tendency to write short punchy sentences stems from deliberate RL efforts to avoid repetitive, consistent writing? I seem to remember that a critique of early LLMs was that they would produce sentences whose construction was too homogeneous. Would be interesting to know the answer to this.
You could say something similar about biology—just physics behind the curtains, and we understand a lot of the basics. The difficulty comes from complexity, not mysticism.
To be clear I don't think that LLMs are sentient, but the appeal in studying them is similar to biology in that you get to dissect a highly complex system with comparatively crude tools.
It feels like a lot of the folks who occupy the same biotechnologist genre as Venter (George Church, Eric Lander, etc.) can come off this way. I agree fully about the grifty nature of aging and longevity research (mostly because of the target audience), but I also think that you need an element of this willingness to entertain ideas that are borderline crazy to get to their status in the first place. Proposing to sequence (or, perhaps more timely—edit) the human genome would have seemed like a wild idea in the 80s, and yet they were thinking about it.
The end of this short interview with Stuart Schreiber has a similar vibe:
Note how interested he is in consciousness and AGI. This is something that he's been talking about for a long time, just formulated differently. You need to be able to temper true scientific rigor with a little bit of wackiness to even think about tackling these big questions.
This looks interesting and I will give it a try. I agree that the space-switching animation is painful.
I don't however think that this will solve spaces on MacOS, for the simple reason that opening new instances of apps is inconsistent and often doesn't behave how you'd expect it to once one more than one space is involved (in my experience, anecdotal).
I've come to peace with the fact that I will never be able to simultaneously experience the productivity of i3 and the necessary evil of MS Office/Illustrator on the same OS. The most important factor in my work is who I work with (rather than what I work with) so I'll remain on the latter train for now.
Maybe not, but I'd want to know beforehand either way. And looking through accounts near me suggests that a fair number of users add enough detail to make me think that they don't realize that their info is so public (selfies/profile pictures being the most problematic example imo).
I love this app, but it's also a significant doxxing risk especially for the large number of non-technical users that it has. A quick look at the map reveals the home addresses and names of many iNaturalist users in my neighborhood, lots of them older folks that probably don't realize that adding all of the neat wildlife that they see in their backyard (or uploading things they see on remote hikes without any 3G coverage once their phone connects to their home wifi network) is also putting their home address on display by adding a cluster of photos right next to their house that are all attached to their account.
The author wanted it to retain some practical value, hence the discussion of the four “layers” of time—departing from the 12-hour system completely, even if there is a better way to represent time outside of it, would make the clock difficult to use.
This is awesome, and is a great example of the type of funding structure that government orgs (looking at you, NIH) should be offering. Government-backed research is the bedrock upon which the US economy rests, and as science becomes more expensive, we need to support research at the intersection of academia and industry more explicitly.
ARPA-H was a great step towards this goal for public health-focused efforts (-omics experiments aren't going to pay for themselves, at least at first) but a more general funding mechanism has been needed. I think this is a great direction for the NSF, and to be honest it's refreshing to see something like this given the horrible stance that this government has taken towards science (which has been compounded by the biotech bubble/correction).
Can you fold very large proteins/complexes with the large amount of VRAM available on Macs? Ram limitations forcing folding runs to proteins ~<1500 is an annoying nit for a lot of protein folding workflows for me—I'd be curious to see if this helps.
Not parent, but in my opinion the answer here is yes. I agree that there is a real need here and a potentially solid value proposition (which is not the case with a lot of vscode-fork+LLM-based starups) but the whole point should be to combat the verbosity and featurelessness of LLM-generated code and text. Using an LLM on the backend to discover meaningful connections in the codebase may sometimes be the right call but the output of that analysis should be some simple visual indication of control flow or dependency like you mention. At a first look the output in the editor looks more like an expansion rather than a distillation.
Unrelated, but I don't know why I expected the website and editor theme to be hay-yellow and or hay-yellow and black instead of the classic purple on black :)
meet.hn/city/32.7174202,-117.162772/San-Diego