Underneath the hood other serverless technologies like lambda are running lightweight VMs running linux. Therefore they can easily accept any linux compatible container and they can run it for you in a serverless way.
Cloudflare Workers are running modified Node.js runtimes. You can only run code that is compatible with their modified Node.js runtime. For Cloudflare to be able to offer a product that runs arbitrary linux compatible containers they would have to change their tech stack to start using lightweight VMs.
If you want to run Node.js, then Cloudflare Workers probably works fine. But if you want to run something else (that doesn't have a good WASM compatibility story) then Cloudflare Workers won't work for you.
Depending on your use case, there is a way to proxy gRPC to Cloud Run in a slightly hacky way leveraging the fact that outbound gRPC works.
You can run in GCE a gRPC server that whenever it gets a gRPC request, it temporarily stores the gRPC message and associates it with a session ID. It then sends a HTTP request to Cloud Run with that session ID. Then your Cloud Run instance will take that session ID to make a gRPC connection to your gRPC server in GCE. This GCE instance will then take the session ID, retrieve the gRPC request, and forward it to the Cloud Run instance.
This is admittedly hacky, but depending on your use case, may be good enough.
"There is as yet no absolute challenger to the relational model. When people think database, they still think SQL. But if there is a true challenger, it is in the graph model."
This article is quite biased towards graph databases with regards to the SQL versus NoSQL tension. This video presents a much more balanced view of SQL versus NoSQL, in my opinion.
https://www.youtube.com/watch?v=qI_g07C_Q5I
Here's my attempt at a summary.
Wolfram speculates that the universe is a network of nodes and connections. This network changes over time by simple substitution rules. Specific patterns in the network give rise to effects that on the larger scale that we experience as the physical world. He has shown that if you model the universe this way, you can neatly derive special relativity and general relativity. He is also doing a brute-force search through networks to look for one that exhibits properties like our universe.
pg's argument is that if the average performance of one admitted group is better than the other the admission process has a bias. This example shows that you can have an unbiased process, but the average performance of the groups differs.
I think I have a simpler counterexample to disprove pg's hypothesis than any other counterexample I've read in the comments. Suppose our goal is to admit the top 5 applicants with the following performances:
A - 30,000
A - 10,000
A - 9,000
B - 7,000
B - 5,000 # Cutoff point below this line
A - 4
B - 3
B - 2
Even though admitting the top 5 by score is perfectly fair, the applicants from group A perform better.
I have no first hand knowledge of this, so I'm probably wrong. Maybe it's more accurate to say that the late stage investments are driving valuations up (ie the a16z analysis). But a lot of these later stage investors would not have felt comfortable without the liquidation preferences. The key distinctions is that liquidation preferences are not critical a VC's decision to invest, but are critical to the later stage large institutional investor's decision.
I think the heavy reliance on these templates is a good clue. Apple TV's interaction model is a lot about swiping around from tappable element to tappable element. Arbitrary layouts will make this a miserable experience. Apple probably wants to establish a number of layout patterns that they believe will yield a good experience.
The original Google Now team leaving is not indicative of a problem. Google Now is more a search product than an Android product, so it makes sense for it to be taken over by Search engineers.
I think the best way to judge this product is as a hub for a smart home. The fact that it is an easy to wifi router is incidental (in spite of the fact that is all the marketing is talking about). It seems pretty clear, "onHub" is suppose to be a hub for a bunch of "on" branded smart home devices.
https://cloud.google.com/kubernetes-engine/docs/how-to/tpus#...