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This is my expectation as well. At CIDR this year there was a paper that presented an implementation of SQL/PGQ in DuckDB, and it outperforms Neo4J in a few selected benchmarks [1].

[1] https://www.cidrdb.org/cidr2023/papers/p66-wolde.pdf


> The ANN index IVF implemented in pgvector has very poor performance, with only around 50% recall.

My understanding is that this mostly due to the default settings that pgvector uses (nprobes = 3) and not due to the usage of IVF. The recall would improve significantly with better defaults. This of course would also increase the latency of vector searches, but that is the trade-off of using IVF instead of HNSW (worse latency at high recall, but much lower storage/memory costs).


This sounds like an interesting contrarian take. Would you care to elaborate?


But you don't have to write map-reduce jobs at all? You can just write SQL queries or Pandas programs, and they automatically get parallelized by Databricks. Databricks is a data warehouse (just like Snowflake).

https://www.databricks.com/product/databricks-sql


In a twist, pandas programs don't get parallelized on Spark. Someone had to go and write a parallel layer that duplicated the pandas API, because otherwise you ended up with the entire pandas program executing on a single executor.


there is Pandas on Spark, included into Spark itself (originally Koalas) - the switch to it is very easy, and you get parallelization.


TIS-100 brought back some of the same joy that I had when I began with programming many years ago. Since then programming has become boring for me, but the weird limitations of TIS-100 almost made it feel like I was starting fresh again. I loved learning tons of small tricks that I could apply to beat the harder levels.

Shenzhen I/O otoh felt like work.


Exapunks was my favorite of the three. If you liked TIS-100 I'd highly recommend trying out Exapunks.


Shenzen has that card game though, so you can slack off at work


Yeah. Why fire up Shenzhen I/O when you can instead dive into a design around some neat, but poorly documented chip from China in kicad.

Or jyst some interestimg hardware project in general.


In Shenzhen I/O, at least you know going in that every task is actually solvable.

And getting it wrong won’t set fire to anything. Or get your LAN hacked.


Wow, $14.99/month is a stark difference with the €2.99/month that they charge for a Prime subscription here in The Netherlands. I wonder if they will increase the subscription fee here to the same level once they reach the desired market share in the video streaming and e-commerce spaces here.


My guess is that the logistics of 2 day delivery in the Netherlands is much easier.


2-day delivery would be uncompetitive in The Netherlands. Next day delivery is the standard for webshops here, and most offer same day delivery as a paid upgrade when you either order before noon or live in a large city.


Still the general point stands.

The Netherlands is like a quarter of the area of New York state alone, and has about the same population.


yeah, it'd be nice if Amazon had an urban discount in the US :). Deliveries to large multifamily buildings must be tons more efficient than to the 'burbs.


Or the large markets subsidize the small ones just to maintain market dominance.


For those wondering what the differences between Raft and Paxos are: I can highly recommend the following paper https://arxiv.org/abs/2004.05074 It presents Paxos similarly to how Raft was originally presented.


You might be interested in this paper [1] which presents Paxos in the same way as Raft is presented in the Raft paper. In my view it really illustrates that most of the simplicity of Raft comes from its excellent presentation and not necessarily from its algorithmic simplicity.

[1]https://arxiv.org/pdf/2004.05074


(Multi-)Paxos and Raft are incredibly similar. I would even argue that Raft is just a variant of Paxos in the same way that e.g. Fast Paxos and EPaxos are variants of Paxos. Most of the Raft algorithm is identical to the Paxos algorithm. The main difference between the two algorithms is how leadership election works. In my view the main reason why Raft is considered to be simpler is because it was presented in a really clear paper. Paxos becomes equally simple when using a similar representation as used in that paper. See this paper: https://arxiv.org/pdf/2004.05074


Netflix is also the most expensive service that I am subscribed to. Netflix is €14 and Amazon Prime is only €6. I basically only watch Netflix for a few of their originals (which are arguably aren't that great).


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