We really ought to come up with some new terms in this space... it is just confusing to mix "strong consistency" in with "eventual consistency" in any way.
I’m pretty sure the term came from Google (at least that is where I heard it first described) and just referred to a backend engineer with speciality in this area. Now usually these roles have “distributed systems” in the title, even if you aren’t really on the inside of the systems. That or “systems and infrastructure”, “data infrastructure”, or “AI/ML infrastructure” or sometimes “MLE” for those kinds of orgs. Or back to good ole “big data” now that it’s no longer tacked on everything.
Personally I think an updated camcorder would be incredible. CCD with global shutter and in a pocketable format with modern stabilization, a video analog to the rx100. Way too niche though.
I’ve seen people who seem to know what they’re talking about cast doubt that you could create your own probiotic yogurt in a typical kitchen since other strains are likely to dominate without a sterile environment and careful methods.
Hello! My name is Brian and I have around 7 years of experience - the bulk of which I spent developing high-scalability storage software for HPC and enterprise. I focused on high-throughput data processing components that automate HSM and data lifecycle policies/operations primarily built with Scala, Spark, and Cassandra. Primarily passionate about systems-level software but open to a variety of roles. Thank you for reading.
In my opinion it will or already has redefined our conceptual models of intelligence - just like physical models of atoms or gravitational mechanics evolved and newer models replace the older. The older models aren't invalidated (all models are wrong, after all), but their limits are better understood.
People are waiting for this Prometheus-level moment with AI where it resembles us exactly but exceeds our capabilities, but I don't think that's necessary. It parallels humanity explaining Nature in our own image as God and claiming it was the other way around.
If jaw placement is an issue you can get corrective surgery without an apnea diagnosis (AFAIK). There’s a lot of info on Reddit, you can generally tell from your side profile or bite if it is a potential culprit.
In what way does this or anything else Trump has done or indicated to do advance the state of education towards the goals of the reform you are talking about?
Nobody will watch anyone's "creations". The TV or whatever device watch on will observe what you and everyone else engage with and how you interact with it and create content for you on the fly, just like Instagram and TikTok's feeds do now.
AI creatives can enjoy the brief blip in time where they might get someone else to watch what they've created before their skills become obsolete in an exponentially faster rate just like everyone else's.
> Often times, "Stream vs. Batch" is discussed as if it’s one or the other, but to me this does not make that much sense really.
Just seems like a flawed premise to me since lambda architecture is the context in which streaming for data processing is frequently introduced. The batch vs stream discussion is more about the implementation side - tools or techniques best used for one aren’t best suited for the other since batch processing is usually optimized for throughput and streaming is usually optimized for latency. For example vectorization is useful for the former and code generation is useful for the latter.
The tooling is pretty easy to learn if scary looking at first and becoming a JVM expert, at least in the context of GC tuning, might take you a week or less. Some of the defaults are surprising though.
And I think there is some parallel with the kernel vs GC and mmap vs buffer pools - the GC simply has better context in the scope of the application. With other processes in the picture, though, yeah there is some provisioning complexity there.