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Cake day: December 11th, 2023

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  • zerakith@lemmy.mltoScience Memes@mander.xyzpringles
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    3 months ago

    I’m pretty sure it’s real. I met someone once who worked in materials research for food and they said that modelling was big there because the scope for experimentation is more limited. In materials for construction where they wanted to change a property they could play around with adding new additives and seeing what happens. For food though you can’t add anything beyond a limited set of chemicals that already have approval from the various agencies* and therefore they look at trying to fine tune in other ways.

    So for chocolate, for example, they control lots of material properties by very careful control of temperature and pressure as it solidifies. This is why if chocolate melts and resolidifies you see the white bits of milk that don’t remain within the materia.

    *Okay you can add a new chemical but that means a time frame of over a decade to then get approval. I think the number of chemicals that’s happened to is very very small and that’s partly because the innovation framework of capitalism is very short term.




  • I won’t rehash the arguments around “AI” that others are best placed to make.

    My main issue is AI as a term is basically a marketing one to convince people that these tools do something they don’t and its causing real harm. Its redirecting resources and attention onto a very narrow subset of tools replacing other less intensive tools. There are significant impacts to these tools (during an existential crisis around our use and consumption of energy). There are some really good targeted uses of machine learning techniques but they are being drowned out by a hype train that is determined to make the general public think that we have or are near Data from Star Trek.

    Addtionally, as others have said the current state of “AI” has a very anti FOSS ethos. With big firms using and misusing their monopolies to steal, borrow and coopt data that isn’t theirs to build something that contains that’s data but is their copyright. Some of this data is intensely personal and sensitive and the original intent behind the sharing is not for training a model which may in certain circumstances spit out that data verbatim.

    Lastly, since you use the term Luddite. Its worth actually engaging with what that movement was about. Whilst its pitched now as generic anti-technology backlash in fact it was a movement of people who saw what the priorities and choices in the new technology meant for them: the people that didn’t own the technology and would get worse living and work conditions as a result. As it turned out they were almost exactly correct in thier predictions. They are indeed worth thinking about as allegory for the moment we find ourselves in. How do ordinary people want this technology to change our lives? Who do we want to control it? Given its implications for our climate needs can we afford to use it now, if so for what purposes?

    Personally, I can’t wait for the hype train to pop (or maybe depart?) so we can get back to rational discussions about the best uses of machine learning (and computing in general) for the betterment of all rather than the enrichment of a few.


  • This is a basic represention and inclusion issue. Unless you are actively seeking out voices of those minorities and addressing their concerns you will have a reinforcing loop where behaviour that puts people off engaging will continue and it will continue to limit people from those minorities being involved (and in the worst case causing active harm to some people who end getting involved). From what I understand the behaviour that has been demonstrated and from who those people leaving it is clear this is active issue within Nix. Having a diverse range of people and perspectives will actually make the outputs (software) and community generally better. It’s about recognising the problems in the formal and informal structures you are creating and working to address them.

    Additionally, but just to clarify nepotism would be giving positions based on relationships with people in power and not ensuring that your board contains a more representative set of backgrounds and perspectives.



  • Being available in a niche market isn’t the same as being affordable because its a mass product. There’s more use-cases then you outline: they are particularly good for those with certain types of disabilities. You are right that mixing with traffic is another key reason why they arent as popular. There’s a reason you see them most commonly in areas with decent segregated infrastructure. Personally I have a DF for some of the reasons you outline. My point wasn’t all about the frame though that was just an example, its also true of the focus at component level where R&D has not prioritised low-cost low-maintance options because the high-cost high-performance market was more lucrative and that stems from in part from the direction performance cycling took.


  • I didn’t mean that all bikes sold were UCI compliant as directly as that. The market has focused on pursuing a fairly narrow definition of performance for a bike in part because of the narrow definitions of racing cycling. That’s had knock on effects for the type of components that have been focussed on and developed. The near ubiquity of diamond frames over recumbents which prioritise comfortably for example.

    I think we have seen that effect lesson over the last decade or so (e.g. belt drives for example). Ebikes help as they have very different markets, need different properties and have by definition no need to overlap with UCI compliance at all.

    Of course its quite hard to unpick the other factors that have led the market to be cater so strongly to leisure market over the utility market but the UCI I think is up there in setting a cultural standard for what a bike is at the cost to alternatives.



  • I agree there may be quite a large range but just to say that can still be useful.

    I think its crucial to start denormalising all the costs and externalities of car focussed transport policy. Motornormativity means policy makers and general public internalise costs of progressive infrastructure and are blind to the huge costs of the status quo.

    So even being able to pin a wide range on it can be helpful. Not for financial costs but for emissions I was able to show even for the lower end of a wide range of additional hard-to-quantify emissions for scenarios that didn’t drastically reduce private car usage as well as electricify would blow past thier carbon budgets.


  • I haven’t seen any work estimating this. I have as part of my work spent some time trying to estimate the upstream effects of private cars (and other forms of transport) and it quite quickly gets very hard to find very much data. Even something quite basic like road maintainance gets quite difficult to unpick. So we know broad generalisations like heavier vehicles cause more damage but its quite hard to isolate this connection with individual traffic make ups (e.g. how much change in costs does a 10% change in average vehicle weight cause)

    Sadly, we don’t have a culture that particularly wants to know or track the costs. I’m not sure I’d be so confident though that the administration costs would be completely neglible. Some of the costs are quite high level: highway engineering, infrastructure and enforcement which can have high labour and materials costs. Probably what you need is a “natural experiment”. Find a town or city that already happens to have a strange policy (I vagually recall somewhere that has a network of golf cart usage?) and try and ask the relevant authority whether they can provide the back history of spending and compare it to a similar size “normal” road network.

    Related bugbare of my mine is the term cycling or walking infrastructure when in reality most if it is actually only necessary because of cars so its really car infrastructure (i.e. to facilitate cars going non human speeds without killing people or damaging buildings).






  • Who knew recommending Distros could be so controversial 😛?

    Seriously though I think this is a great flowchart and you took on board the more reasonable suggestions from the intial post. This flowchart now quickly eliminates some of the distro choice anxiety. Worst case a newbie might end up on a distro like mint and then end up migrating to a different one.

    One comment I had is that I actually didn’t know what opinionated DE meant without googling despite being a long time Linux user (maybe thats just my ignorance) and I wonder if a newbie might be confused maybe there’s another way of saying it (flexible versus simple?).

    Anyway, I really think early me would have appreciated this when I first started even if that would been ultimately “use Ubuntu” back then.