broast

Right, this is the common sense approach for identifying the cause of a regression. Not sure what people do other than this unless it's a very simple codebase

As an example, a more modern and higher resolution implementation of this style can be seen in "Teardown"

> but it hasn't really been able to solve any actual problems that I have.

This is so foreign to me as someone who has become dependent on LLM's

As I recall, my gripe with Stadia was the limited graphical capabilities. I don't recall if the graphics settings were locked but I remember only being able to play games on medium settings and not being able to achieve any better performance than a GTX 1080.

Meanwhile, your XCloud stream is hosted by an equivalent of an Xbox Series X, which while a console-level experience, the games were shinier and prettier than Stadia.

And otherwise I've found their streaming quality, performance, and latency, to be about equal (not the best) although XCloud continues to improve to this day.

Weren't the mandates to actually avoid being /indoors/ and amongst large groups of people? Personally, during lockdowns in the U.S is actually when I've spent the most amount of time outdoors and in the sun during my life, since there was not much else to do.

I've just recently had a shirt printed with the cover of Byte magazine Volume 8 No 6 (June 1983) on the front, because it looks so cool.

Then again, Stadia's streaming performance and graphical capabilities were subpar compared to established competing services like GeForce Now, Xcloud, and ShadowPC. If it were better it might have been worth it.

Both sides in every violent conflict ever have probably used this same line of reasoning, simultaneously. It doesn't help.

They're desperate to get off keycloak at my org. Not sure the specifics, but our users complain about Auth issues often, and the keycloak web interface is painfully slow too.

To say that the AI craze started after the crypto wave died down is disingenuous or misinformed. The future need for GPU's was apparent as soon as machine learning became relevant a decade ago. The effectiveness of transformers, rnn's, q-learning, etc, for language and other applications was not news when GPT-3 launched. NVidia invested heavily for 10 years, including funding research towards ML and AI, and steered the direction of the technology that we have today

They're behind in selling for now but ahead in research - who is to say that selling access to your AI is really where value and growth will be in the future?

I always find it surprising that so many people struggle to make effective human connections over chat. I think it must be generational, as I believe these are the connections I and other young people prefer.

My personal compromise is I eat every other day vegan. It's easy enough to do and makes a significant impact

I tend to think the overhiring was not a "mistake" but planned. They still get to keep all the intellectual output of the people they let go.

The "404" animation is great

Interestingly I see divides like that in the fully remote parts of my org, so I think it may be more related to what those teams work on rather than work style.

In fact our in-person teams have the opposite reputation: they are slow but theoretically work on high business value problems, while the remote hive mind takes care of business in the background.

Unfortunately it sounds like you're filtering on things that can be easily taught.

It's possible we could stumble on AGI without immediately realizing it, and without checks and balances built in, it could already be too late.

Wishfully I hope there was some intent from the beginning on exposing the impossibility of this contradictory model to the world, so that a global audience can evaluate on how to improve our system to support a better future.

I found the board members own words to be quite erratic between Friday and today, such as Ilya saying he wished he didn't participate in the boards actions.

I've ruined many usbc connectors like this and specifically dell dock connectors

If you've checked out the docs for the assistant api, you can intuit that there is a higher level system which decides which subsystems to use to respond. The assistant determines whether to use a tool (vision, code interpreter, search, retrieval), as well as which code or text language model to use to generate the response.

It often just takes a few minutes of verifying against your understanding and use case, and ask a few more questions, and you can identify incorrect answers and arrive at the verified correct answer, or useful answer if there is no correct answer, rather quickly- which should be how most people operate in most interactions with information. Not to mention it can now be forced to search the web and cite its sources.

I think at some point it just becomes a preference of your interface to the data your searching, and I've been enjoying natural language

I use it mostly for complex queries I can't Google and that's where it excels for me.

Reminds me of me when I was a junior dev. Pretend I already know how to do the thing and form the answer as I google and speak.

Weather is markovian

Have not noticed an issue this week.

Spoiled, or righteous indignation? Never have we been more productive as individuals, and efficient as an org. And no one has presented any actual functional reason to be in an office. No one wants to take a step backwards.

My team was facing an issue with their microservice not recovering after a Kafka outage, which we only observed once and we couldn't reproduce, and didnt understand why not. Googling the symptoms did not yield anything. ChatGPT gave us a theory which happened to be correct, which was that the outage needed to be long enough for the kerberos ticket needed to expire. I estimate without this answer from chatgpt we would have wasted at least a day of our own or other people's time in investigation, but it was solved in minutes.

Same