What makes it so great for me is the effortlessness.
I often use Python for quick one off scripts. With UV I can just do `uv init`, `uv add` to add dependencies, and `uv run` whatever script I am working on. I am up and running in under a minute. I also feel confident that the setup isn't going to randomly break in a few weeks.
With most other solutions I have tried in the Python ecosystem, it always seemed significantly more brittle. It felt more like a collection of hacks than anything else.
Yeah, the endorsement was mentioned - while the assassination attempt was not.
Here is a quote from that study:
> In Phase Two, comparing Republican-leaning and Democrat-leaning accounts, we again observed an engagement shift around the same date, affecting all metrics
It's so obvious that an assassination attempt on a republican candidate will boost republican engagement MORE than democrats. It's just as obvious that a corona virus outbreak in close proximity to a laboratory which works on corona viruses, escaped very likely from that lab. Common sense. Also for weeks after the event, of course republicans continued to be more riled up about it.
This is not science. If the claim is that Musk tuned the algorithms at that special date, you have to prove it by other means, other than engagement being boosted at that day and weeks to follow.
It seems to me that when taken together, these two make a fair case that there was a change in algorithm on the given date?
Besides, the study you are claiming "is not science" did not even make strong claims as to there being an algorithm change. The study made an analysis, and concluded that they might point towards there being an algorithmic change.
Additionally, as you say "If the claim is that Musk tuned the algorithms at that special date, you have to prove it by other means". What other means exactly? We have no data to go on except observations of what happens on the platform. From the information we have it seems like everything points towards this being the case.
The case for manipulation happening furthered even more by Elon Musk repeatedly showing he is full of shit, and has no qualms lying and totally making stuff up. (see his repeated lies about Autopilot, his lie about being world class at video games, his lies about DOGE cuts, etc).
Before dismissing these findings, ask yourself honestly: would you apply the same rigorous standards of proof if the algorithmic changes benefited different political figures or viewpoints?
> would you apply the same rigorous standards of proof if the algorithmic changes benefited different political figures or viewpoints?
That's the whole point I'm basically making: I think this is an obviously bogus study, but one side will happely take the conclusions as granted because it falls in line with an agenda or narrative - furthering the divisions in society. Which by the way doesn't mean that the other side doesn't spew garbage as well.
But in these specific case, where it's so obvious... We can go on with corona virus lab like I mentioned. In these cases, where the common sense is "turned off" in some people, I really wonder what's going on and speak up. It's absurd.
> The study made an analysis, and concluded that they might point towards there being an algorithmic change.
Yes but you can't do that for the reasons I mentioned. But still doing it and then another study referencing that crap, shows to me that science is not at play here.
> From the information we have it seems like everything points towards this being the case.
Well if Greta Thunberg at the height of her popularity fell from a wind mill, someone could've made the claim Twitter is suddenly boosting a certain group of accounts. The CEO of Twitter even wrote condolences, something is up here!! Sorry, but this garbage.
> What other means exactly? We have no data to go on except observations of what happens on the platform.
Yes that's an issue, but that's not my problem?! If the circumstances do not allow for a proper study, you don't make it. I would look whether the boost in republican engagement came down again. If it stayed on the same level (maybe til today?!), I would agree, something is very fishy. Maybe there is a study that did that already? I don't know.
> The case for manipulation happening furthered even more by Elon Musk repeatedly showing he is full of shit, and has no qualms lying and totally making stuff up.
But this is not a science approach you can enrich a crappy study with. You can surely have that opinion - I have no problem with that. That's an opinion without proof, which I have too on certain topics. But then producing bogus studies to try to turn this opinion into some sort of fact where people point to as "proof" is what makes me upset. It doesn't help the cause, only causes division, because the people pointing think they have science on their side, instead of just having a opinion.
Your dismissal of this research shows a fundamental misunderstanding of how scientific analysis works.
The study analyzed two separate phenomena - changes in engagement for Musk's posts AND changes in engagement for Republican content - occurring simultaneously. When taken together, these patterns strongly suggest algorithmic changes, not just organic user behavior from the assassination attempt.
Saying "you can't do that for the reasons I mentioned" is just wrong. Studies absolutely can point toward likely explanations without 100% certainty - that's literally how science progresses. The researchers used appropriate cautious language because they understand scientific rigor, not because their analysis is "crap."
Your argument that "if circumstances don't allow for a proper study, you don't make it" would eliminate most scientific advancement. Should we have abandoned Alzheimer's research because perfect data wasn't available? Obviously not.
What's truly absurd here is your selective skepticism. You demand impossibly high standards of proof for findings you dislike while accepting "common sense" explanations that align with your preconceptions.
Before dismissing research as "garbage" that "causes division," maybe consider whether your reaction is based on methodological concerns or simply that the evidence contradicts your preferred narrative about Musk. Your eagerness to defend him while offering nothing but personal opinion suggests it's the latter.
> The study analyzed two separate phenomena - changes in engagement for Musk's posts AND changes in engagement for Republican content - occurring simultaneously
And in which political bubble is Musk popular? It's not seperate phenomena. What do you expect? That let's say republican engagement organically increases (as I claim), but Musks engagement stays the same, even though he made many statements regarding the assassination attempt and got people riled up because of his endorsement? This is ridiculous, sorry.
> Should we have abandoned Alzheimer's research because perfect data wasn't available? Obviously not.
The study authors should've been well aware of the above. They didn't care and did it anyway, because they knew fully well that people will not care, because it fits a certain narrative.
> Your eagerness to defend him
Okay I think we can stop it here then. You think I write in defense of Musk. I think you are completely oblivious to common sense. The truth is probably not that black and white though.
We were talking about his son, he let the process play out in full which is beyond respectable.
When the incoming administration has shown extraordinary will to persecute political opponents, I think it would be unethical not to preemptively pardon these people.
Yeah, i feel like currently they are at about the price of camera traps 10 years ago. There is very little mass-manufacturability to them right now (it's all open source and made from off-the-shelf parts) but later if we can find more funding, we are going to make a design more for manufacturing which should hopefully drive the costs down even more! :)
> There is very little mass-manufacturability to them right now (it's all open source and made from off-the-shelf parts)
This is the obstruction to using them in an educational setting. If they were available for $600+ each but already completely built (minimal DIY), they would be more likely to get into (some) schools.
We have a group of kids in Rhode Island building some with the library there! Part of a "Wildlives" program where the kids also learn to put camera traps around the local nature!
totally! Right now we are just trying to get them out and tested on science projects around the world, but hopefully we can find funding to make more designs that could be manufactured in bulk (like the audiomoth and groupgets) and have even more of these things out and about!
It is now. There were a few years where it had basically disappeared (2015-2018). When Apple eventually put it back in the open-source world, it was done with little fanfare so it could be easy to miss.
Helpful thread, thanks: Google support team churn after the distribution transition to Asus IoT, Frigate devs were preparing to fork Google repos, then new Google devs appeared.
> Google is getting back on top of things aka coral support which is nice.. it seems that the original devs weren't on the project and new devs needed to be given notice. Hopefully this continues and things are kept up to date.. updated libcoral and pycoral libraries are coming as well.
It's good that Frigate brought attention to languishing Linux maintenance for Coral. Rockchip 3588 and other Arm SoCs have NPUs, which will likely be supported in time, but each SoC will require validation. Coral Edge TPUs were a convenient single target that worked with any x86 and Arm board, via USB or M.2 slot.
I don't know about this at any detailed level, but doesn't designing standard cells for leading edge nodes involve a lot of trial and error? Is a lot of the issues that can occur even well understood to the level that it can be simulated?
With the approach you mention, would it involve creating "custom standard cells", or would the software allow placement of every transistor outside of even a standard cell grid? If the latter, I would have trouble believing it could be feasible with the order of magnitude of computing power we have available to us today.
The best results will be with custom shapes and custom individual placement of every transistor outside standard cell but within the PDK rules. Going outside the PDK rules will be even better but also harder.
The trial and error you do mostly by simulating your transistors which you than validate by making the wafers. You can simulate with mathematical models (for example in SPICE) but you should eventually try to simulate at the molecular, the atom/electron/photon and even at the quantum level, but each finer grained simulation level will take orders of magnitude more compute resources.
Chip quality is indeed limited by the magnitude of computing power and software: to design better (super)computer chips you need supercomputers.
We designed a WSI (wafer scale integration) with a million core processors and terabytes of SRAM on a wafer with 45 trillion transistors that we won't chip into chips. It would cost roughly $20K in mass production and would be the fastest cheapest desktop supercomputer to run my EDA software on so you could design even better transistors for the next step.
We also designed a $800 WSI 180nm version with 16000 cores with the same transitors as the Pentium chip in the RightTo article.
Has this WSI chip been taped out/verified? I must admit I am somewhat skeptical of TBs of SRAM, even at wafer scale integration. What would the power efficiency/cooling look like?
The full WSI with 10 billion transistors at 180nm has not been taped out yet, I need $100K investment for that. This has 16K processors and a few megabyte SRAM.
I taped out 9 mm2 test chips to test transistors, the processors, programmable Morphle Logic and interconnects.
The ultra-low power 3nm WSI with trillions of transistors anda Terabyte SRAM will draw a megaWatt and would melt the transistors. So we need to simulate the transitors better and lower to power to 2 to 3 terawatt.
There is a youtube video of a teardown of the Cerebras WSI cooling system where they mention the cooling and power numbers. They also mention that they also modeled their WSI on their own supercomputer, their previous WSI.
This sounds exciting but the enormous and confusing breadth of what your bio says you are working on, and the odd unit errors (lowering "a megawatt" to "2 to 3 terawatt), is really harming you credibility here. Do you have a link to a well-explained example of what you've achieved so far?
Are you concerned that going away from standard cells will cause parametric variation, which reduces the value proposition? Have you tested your approach on leading FinFET nodes?
It's probably more of a node thing than a fab thing. You would have a much easier time getting the fab to do random stuff for you on a legacy node compared to a leading edge node.
Leading edge nodes are basically black magic and are right on the edge of working vs producing broken chips.
You as a customer would never want to be in a position where you are solely responsible for yields.
