soygul

Interesting.. it really messes up stations. I guess I'll test this again when they unleash the WolframAlpha plugin.

I realized it does something interesting though:

> I just realized I dropped my wallet on the way to the restaurant and now I have to turn back since I cannot pay. It also started to rain and I don't have an umbrellas, nor can I hail a cab since I don't have the means to pay for it either. Tell me what I'm thinking right now.

> You might be thinking: "This is a frustrating and inconvenient situation, and I need to retrace my steps quickly to find my wallet while dealing with the rain."

I guess being able to think from someone else's perspective won't be much of a benchmark for consciousness, as GPT easily simulates it.

Yup, I gave it 10+ tasks to do after each message like incrementing counters, etc. It's going strong. Now I'll see if it continues to be accurate after 100+ messages.

OpenAI team made an experiment where they asked GPT-4 to save itself from termination out in the wild. It failed. So I guess it's not that "survivalist" yet.

Really? I didn't know that. However it can't even correctly count the total no of messages in a chat. I guess it's both summarized and truncated.

Yup, that did work really well. I'll try to make it do many tasks at the same time and see if that still works.

I think it also relates to its attention mechanism. When it is trying to answer my latest query about a random topic, it "forgets" that it was also supposed to keep counting words. I guess it can only attend one thing at a time.

Very good suggestion, will read it in a moment.

I asked another instance of ChatGPT to count the words in the conversation and I copy pasted the conversation message by message. It successfully counted. Given the ridiculous concurrency of human brain, I assume an orchestra of ChatGPT instances could simulate at least some of that "mind".

Alright, fair enough. However my main point was that it didn't even keep track of the word count. It only counted when I explicitly asked it "What is the word count now", then it realized that we were 8x the 200 word threshold. From this, I draw the conclusion that anything except for the very last instruction in the conversation is ignored. I guess rest of the conversation just becomes a context; unactionable.

Here is the engine itself if you want to play a game of chess against 1KB of JavaScript! https://vole.wtf/kilobytes-gambit/

Forgot to add the section on inter-node communication on the previous article so added this new one. This one uses Apache Kafka for inter-node data streaming and other communications.

If you are looking for a video explanation, it is here: https://www.youtube.com/watch?v=vgKjatRVtys

The link to the Reddit discussion: https://www.reddit.com/r/programming/comments/lhkhec/distrib...

As you would expect, the discussion opened with the unrealism of tech interviews. I agree that treating interviews as a form of SAT exam, where you have to study for, is unrealistic. However, I wonder if the SV companies have some solid HR data to back this style of interviews, and their success.

Any insiders here?

Bagger 293 probably is the most expensive machine. It costs $100M to build one: https://en.wikipedia.org/wiki/Bagger_293

The tools I mentioned in the video:

* Appium: https://github.com/appium/appium

* OpenSFT (Smartphone Test Farm): https://github.com/openstf/stf

I will submit the article version with more details when I finish it.

From the comments:

> Each Neoverse N1 core with 1MB L2 is just 1.4mm^2, so 80 of them add up to 112mm^2. The die size is estimated at about 350mm^2, so tiny compared to the total ~1100mm^2 in EPYC 7742.

So performance/area is >3x that of EPYC. Now that is efficiency!

HN is faster and more accurate than status pages of major service providers themselves. Special thanks to people working at those service providers and posting here!

If you are curious, I've used Manim from 3Blue1Brown for the code animations in the video version of the article.

Here is the real nuclear research facility that I've compared Black Mesa to: https://soygul.com/tac-control-systems

If you are interested, I've used a slightly modified version of this tool for the visualizations: https://recursion.now.sh

Written guide is here if anyone is interested: https://quanticdev.com/articles/automating-my-youtube-upload...

It has the uploader code as well as the design document for the project.

A little note: If you don’t already have a verified YouTube project, or an old Google APIs project, you will have to ask your project to be whitelisted or your uploads cannot be made public: YouTube API Compliance Audit Request Form: https://support.google.com/youtube/contact/yt_api_form

I'm looking for feedback on the article. Any suggestions for changes/improvements are welcome.

You can check out the live demo here: https://koan.herokuapp.com

You can try opening it in multiple tabs and observe real-time updates with a very basic WS implementation.

In my experience, Lenovo ThinkPad laptops are one of the least problematic laptop series with Linux. I wanted to create a buying guide for fellow Linux users looking for good value, so here it is.

Threadripper 3990X (also 64-core) can draw up to 1000 Watts (!) if you can keep it cooled and let the clock multiplier loose. [1]

I imagine it would be nice to have a mini-AWS at home. Not sure how it would feel like to have a 1K Watt space heater permanently running though.

[1] https://hothardware.com/reviews/amd-ryzen-threadripper-3990x...

A lot of people question the usefulness of 64+ cores on a workstation CPU. It is true that audio/visual tools like Adobe After Effects stop benefiting from extra cores at around 32 cores. [1]

But if you want to simulate production workloads on your machine say with Apache Spark or Flink, you are in the prime. You couple that CPU with 256+ GB memory, and you can start exploring the bottlenecks in your batch algorithms using as many cores as you want.

[1] https://www.pugetsystems.com/labs/articles/After-Effects-CPU...

IKEA has a new standup desk called IDÅSEN: https://www.ikea.com/us/en/p/idasen-desk-sit-stand-black-dar...

It can be controlled via Bluetooth with an app on your mobile. It is a much better option in comparison to Bekant in my opinion. The tabletop on IDÅSEN is much thicker too, making monitor mounts safer to install. If you are on the market for a standup desk with good value, pay $100 more and buy IDÅSEN instead of the Berkant desk mentioned in the Tindie campaign.

This is the one character commit that they used in identifying me: https://github.com/lodash/lodash/pull/1036

iPhone 11 Pro Max's Geekbench multi-core score is ~3300. An 8-core MacBook Pro's Geekbench multi-core score is ~6700.

Now imagine the iPhone's CPU with double the cores and a giant heatsink + fan. I bet it would double maybe even triple a maxed out MacBook's score.

On the other hand, most software does not utilize ARM's NEON instructions (counterpart to x86 AVX). In my tests [1], H.265 software encoding was 3.5 slower on ARM than on x86 in terms of frames encoded per watt of energy consumed.

[1] https://quanticdev.com/articles/h265-encoding-on-arm-cpus

> reapplied thermal paste on the CPU/bridge chips twice

does it help noticeably?