I don't understand the architecture section. The title is "layered architecture," but then it talks about Ports/Adapters, which would be hexagonal architecture?
I was about to leave a very witty "just be idempotent ;)" response but did not consider the nonce. I'd be surprised if Google is quick to change this, so I guess be stateful on the receiving server, persist that you handled a certain request already, and if you get a duplicate request, replay the response from the first one?
At this point, I cannot take these kinds of safety press releases serious anymore. None of those models pose any serious risk, and it seems like we're still pretty far away from models that WOULD pose a risk.
After having used Datadog for several years, going back to Grafana / Loki / Prometheus felt like regressing by two decades. As much as I appreciate free solutions, I feel like Grafana has really fallen behind when it comes to developer experience
Why, exactly, do we need to put a memory cache such as Redis in front of Postgres?
Postgres has its own in-memory cache that it updates on reads and writes, right? What makes Postgres' cache so much worse than a dedicated Redis?
I'm assuming you're targeting this mainly at enterprises and business use-cases such as callcenters, but are you planning to make this usable for personal use cases as well? For example, having a bot to bounce ideas off while coding. Pretty much "just" the TTS / STT layer to talk to my finetuned LLM in a natural manner while you handle interruptions and such.
I think the main issue right now for personal use would be cost (and I'm guessing STT / TTS are the most expensive parts..)
I really do not understand these memes about overengineered FactoryFactoryFactories. I have 10 YOE, did I just get lucky? I've worked at enterprise Java shops as well, but even there I'd call the software pragmatic. Are these overengineered monstrosities REALLY still a thing, or is it "just" people suffering in legacy projects? Even the juniors I worked with were following KISS and YAGNI.
I wonder if we're at a point where you could build a voice assistant like that, except almost-realtime and streamed end to end:
User speaks and speech to text starts streaming text while the user is still speaking. That text stream is piped into a LLM, which also streams its output text. That output text is streamed to text-to-speech, which also generates audio in a streaming manner.
Great. Glad to see we're still world leaders at shooting ourselves in the foot. It makes sense to regulate AI use in critical infrastructure and flat out outlaw use of AI to manipulate public opinion, but that's where it should have stopped.
At the risk of sounding like a complete idiot, isn't the hypothesis of the original paper still true? Let's assume self assessment score is perfectly random between 0% and 100%, so on average every group will always estimate themselves to be 50% correct
Then by definition that means people who are unskilled and often incorrect will overestimate themselves, while people who are often correct will underestimate themselves. Take a complete idiot for example. You always get 0% test score. Yet your self-assessment is random between 0% and 100%. Hence you overestimate yourself much more often than people who always get 100% test score.
In fact, if the two are uncorrelated, then that still means that
I really do not understand why this is a discussion, why a video had to be made about it and why we now need an interview about this.
Clean code / readable code / whatever you want to call it is often at odds with performance. This has been a known fact for decades. Everybody is aware of this. And for most enterprise projects it just doesn't matter.
The performance analysis discovered nothing new and added nothing of value