Bingo. Local cop goes in, buddy-buddys with the loss prevention manager, gets access to run plates for the immigration folks outside. "Professional courtesy" strikes again!
Thats not the point, if there were a better proprietary engine stockfish would still be there as a baseline. Anyone can access an engine as good as stockfish to practice against. Are any open models touting mathematical breakthroughs?
There is money in this, so of course the closed models are far ahead. The open models will likely catch up a bit at some point, just as Stockfish caught up to AlphaZero. That being said, there are already a couple. It seems Deepseek has a claimed proof to the "Ziegler's Cross-Polytope Conjecture" [0], but I can't speak to the significance of the result.
It would be nice if OP noted what caused the change in their opinion?
did datafusion gain some feature that they noted was missing in the previous article, or did something in their understanding click so they could overcome the previous issues?
The previous issues were in my mind, not in DataFusion.
I tried using DataFusion as an in-memory tool, which was a mistake. If the graph fits in memory, Networkit, IGraph, etc. will almost always be faster. These tools cannot process anything bigger than the available memory.
So, I changed my approach. I wrote my own naive "disk checkpointer," offloading everything to disk and avoiding materialization. Although I was afraid that writing to and reading from the disk would be slow, it is surprisingly fast with DataFusion. The results are impressive: fast and out-of-core.
Sorry, this post is short and not very detailed. I did not expect it to be at the top of HN and receive so much attention.
I thought of datafusion work and the rust implementation as a way to address the delta seen vs the Spark/JVM GraphFrames implementation (author is a major contributor).
Looking forward to more such innovations, which will benefit the ecosystem as a whole. Why would anyone want to use a pure python graph algorithm package unless they're dealing with toy graphs?
We shared with the author how databricks multi-node and single-node graphframes were wildly inefficient for this kind of thing: we were measuring doing billion-edge graph traversals & scans in single node in-memory in seconds with regular dataframe (cudf) libraries, so the core of pagerank, which is magnitudes more efficient than their original spark approach
So then the question became pandas/polars/datafusion/duckdb/etc, must of which are rust/native. I'm curious myself why datafusion vs others, it's an interesting project :)
All "dynamic" means is that you don't know or don't prove the precise value statically. However you may know the range of possible values, or you may know properties of your algorithm that mean it can never attempt an out-of-bounds access. Sometimes you don't know any of these things, but sometimes you do.
What I was (badly) trying to express was more that given static bounds rust could also eliminate dynamic checks. So saying e.g. ATS can eliminate static checks, is kind of switching the target.
I'd also say a few things, if knitting takes a long time consider how long it takes to make a good clear pattern so that others can replicate it.
People who make patterns are already dealing with a saturated market.
This includes historical/vintage patterns, which for many years patterns were primarily given away freely to incentivize yarn sales, or dominated by publishers. It wasn't until recently (internet, etsy, ravelry) when designers actually had the means to sell directly to consumers. People making an effort to produce usable patterns are now being dwarfed by AI nonsense in the speed of their output. It was already a difficult market. That everybodys images of real objects (along with AI generated ones) are being used to peddle and market patterns that will never work can be really demotivating.
One last thing is how many of the 8 people in this podcast company are actually generating slop and how many are actually just doing marketing?
If you only care about the material and physical utility of the product, you can order the sweater from AliExpress for 5% of the cost and no time spent.
The same way that the AI generated podcast about knitting, or engaging in consumption is enjoyable for many people and a form of stress relief, which was the point that the comment above was criticizing.
So the conclusion is that the utility of the activity is subjective, and if most people spend their time listening to AI factually incorrect podcasts about knitting and enjoying it, it's no different than knitting yourself and enjoying it. The blog was poor in this disambiguation, and pushed a more Aristotole-like ontological view of what is meaningful, which is more common view in engineering/hard-science dominated fields.
They are not the same. One is a passive thing (viewing) and the other is active (physical creation). We should not mistake one for the other. It is like the difference between listening to music and making it.
It is fine though if people who don't knit enjoy knitting podcasts, but this is not that. Somewhere between the producer/consumer relationship there should exist some actual knitting. Otherwise (in cases like this) it's just plain exploitation.
That's completely your subjective opinion that ignores reality. If people feel like they are participating in something, or they feel like their identity is based on something they consume passively, it's as valid as the physical thing.
If people did not feel good from passive consumption, no-one would be listening, following or looking at things, people would just make and create all the time, which is obviously not true.
If what you say is true, there would be no value from AI-generating blogs in question, or AI-generated movies/youtube films. Yet both have millions of downloads, views and listens, as the article mentions.
Reality involves physical objects you can hold in your hands, not abstract experiences. Abstract experiences are subjective not objective most of the time.
Knitting is not just entertainment, it's a means to produce useful things as well as artistic projects.
Many people are either lazy or have been discouraged from creativity by a consumer society and the education system. I've watched plenty of online content. I have nothing from it but feelings (the very subjective opinion you talk about), and very occasionally a tiny bit of new information. Knitting creates clothing which can be used to keep out the cold (objective) and so on. In fact this very winter, I wore things my friends knitted me. Gloves, hat, socks, snood, scarves... They served a practical function beyond entertainment or just looking good.
Seriously? You can't get the feeling of satisfaction of wearing something, or having someone wear something you made from AliExpress. My point is your sense of feeling and validation is extremely distorted if you have no knitted material to show for it?
Completely subjective take by you with similar epistemology around value as the blog author.
People might not care. I might identify as a runner because I bought a little jacket, expensive shoes, and wide-purple-tinted sunglasses, do I have to run? Not necessarily if the objects and my identity gives me the feeling of completion and satisfaction.
If your premise was true for all people, and the sense would be distorted, we would not see these phenomena, and people wouldn't listen or engage with AI-content. But the biological reality and the path of least resistance seems to prove us otherwise.
My only complaint with the article is that it doesn't seem to mention that digitized proofs can contain gaps but that those gaps must be explicit like in lean the `sorry` function, or axioms.
Carr made public comments January 29.[1] The 1st news report of FCC investigation was published February 7 seemingly.[2] And CBS's risk and reward estimates for a current official and a candidate could have differed.[3] And Ossoff and Shapiro had not filed as candidates reportedly.[4]
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