Category: facebook

How easy it has turned out to be to write articles in English. A translator plus editing took 10 minutes. Plus another 3 minutes to create an illustration in DiffusionBee.

Right now, ChatGPT is being used to create resumes, recommendation letters, and cover letters, and theoretically, AI could soon replace HR entirely, aiding in conducting interviews. This is already feasible, and if a trained version is prepared, it will be truly spectacular.

Remember, about ten years ago there was Akinator (and still is), which could guess the “character” based solely on responses to questions. It used a decision tree algorithm, the same as machine learning. In that algorithm, the connections between concepts were simple, but in what is now used in ChatGPT, they are exponentially more complex. So when you interview someone, you basically have a very limited number of questions (say, twenty) to understand their qualifications and what kind of person they are. Being able to structure a dialogue in such a way to “guess the hero” more quickly is a skill in itself, not everyone possesses.

This is exactly where AI could be extremely helpful. It might be odd to hand over interviewing entirely to AI, but making AI a tool for the interviewer is very plausible. Along with voice recognition and analysis of responses, this tool could provide recommendations on what to ask, and identify where there are clear “leaks”. It can take into account details from the resume and new information garnered during the interview, as well as results from previous interviews with other people in the same company.

Such interviews could train a brain on a corporate level or one big brain common to all companies in the market. The second path assumes that some information will flow into a central system, a big “brain”. This might meet resistance at various levels, but if the efficiency of recruiting good employees skyrockets, businesses and governments might turn a blind eye eventually.

Moving forward, developments could go in two directions. The first is this unified big “brain” will know specific people. If you arrive at a new company, the AI there already knows not to ask certain questions because they were asked just last week in another company. Even if AI does not share this with the company, it may decide that this knowledge correlates with the job description and informal expectations of company leaders, and simply not waste time repeating this question. This path will face rejection from many people, but from a business standpoint, it’s very beneficial.

Essentially, everything may lead to a social rating system like Nosedive from Black Mirror, only there won’t be just one number. There will be billions of numbers, understandable to AI, from which it can make recommendations about a person’s suitability for a specific task.

The second path is if such interviews train a system that is not tied to specific individuals. But like in Akinator – based on the analysis of resumes and past interviews, the likelihood that a candidate will respond in a certain way to a particular question might be so high that AI simply won’t ask it. Especially if the response to that question is already considered in AI’s assessment of whether the candidate fits the job description or not.

In this case, the social rating is not tied to the individual, but it is tied to the “cloud” of that person’s properties, their history, and the traits of their personality, which all together pinpoint them quite accurately. Yes, they won’t have a direct link to the specific individual, but essentially the outcome will be the same as in the previous case. The recommendations will be the same.

I think that integrating AI into the hiring process will change significantly more than just spotting certain specialties. I believe such optimization will make the contrast between those who are working and those who are job hunting much stronger. It will become extremely difficult to land a good job just because you got “lucky” and the interviewers accidentally didn’t touch on a huge range of topics that the candidate would likely have failed. And the main thing—what objections could there be, since AI only helps in hiring those suitable for the job, not just anyone? And the government will ask the public: Or did you want it otherwise? Do you want doctors and teachers in schools to be hired just because they were “lucky” enough to pass an interview?

What do you think?

Yesterday until four in the morning, I was tinkering with this thing. It works! ChatGPT, Google AIY, can talk about the weather and forecasts (still slightly unreliable). And about everything under the sun. Keeps the session. Microphone is temporarily external. Voice recognition – openai whisper. Synthesis – Google TTS. Dialogues – openai GPT 3.5. Weather – tomorrow.io Inside – raspberry pi. I made a wakeword, but decided not to use it. It consumes the voice recognition API inefficiently.

My 16th attempt at oil painting.

Lately, my Mac has been a bit slow — it seems due to a lack of memory. Out of 32 GB, 26 are typically occupied, and it occasionally seems to peak at 32. I’ve dumped all the processes that run on my typical day. In total, that’s about 600 processes.

Out of these 600 processes, a whopping 464 are system processes that come with MacOS Ventura. Probably, some of them, which Apple considers default for some reason, could be disabled, such as Spotlight or Siri. And probably I will do just that, but for now, here they are.

And these 464 processes occupy 7.2 GB of memory. That means, on a machine with 8 GB of memory, I don’t really understand what’s left.

These processes are interesting to study. For example, the process photoanalysisd is used for analyzing photos and videos, specifically for recognizing faces and objects for search purposes (spotlight?). It’s kind of creepy that the OS recognizes something in my photos on the disk.

Or there’s the process contactsdonationagent. In short, the system sends various things from your computer for research purposes, not only to Apple but through Apple to other organizations. Possibly, this can be disabled through Share Mac Analytics in Privacy & Security.

For instance, among the processes, there is the DoNotDisturb server. A very interesting server indeed 🙂

Second place in terms of memory consumption (and often CPU) goes to IntelliJ Idea. It’s my work tool, hosting a large Java project or even multiple projects. Typically, Idea occupies about 6GB of memory. That’s quite a lot, but unfortunately, there’s no viable alternative. It seems because Idea keeps a search index in memory, and I have tens of thousands of files in my project.

In third place are the browsers. I use Brave and Chromium. Brave is currently consuming 2GB. If there are a lot of tabs, it goes up to 4GB. Chromium takes another gigabyte. Two browsers are necessary because some services – like Microsoft, particularly the browser-based Teams, only allow one user per browser. As a result, I have one Teams in Brave, another in Chromium, and a third as an app. However, with browsers, it’s the easiest — I just completely kill them through Force Quit and reload them. Almost always there’s nothing to lose, and ForceQuit works instantly, unlike a normal exit.

Microsoft products consume another 3.5 GB. Of this, Outlook consumes about a gigabyte, so does Excel, and the rest goes to Microsoft Teams. Most likely, it’s because Teams brings its own browser.

Then there’s Spotify, consuming 600MB in passive mode. Need to uninstall it. For some reason, I installed the DeepL translator, which eats another 400MB — although it’s just as good in its browser version.

And then there’s the troublesome Telegram. Why does it need so much memory? It can easily occupy up to 2GB after a few days in the background. But you reboot it (better with cache clearing), and it then only consumes about 130 MB, and it stays that way for some time. Should set up an automatic reboot every night.

In the end, it seems I need to buy the next laptop with 64 GB of memory..

Photos “from a past life”

2009, somewhere in eastern Ukraine. I only recognize Vasylivka, where the traffic police and architects teamed up

interesting about game theory in ELI5 style

Sometimes even too mainstream, but good for casual listening while driving

In conclusion – Added to my wishlist on Amazon the book Thomas C. Schelling, The Strategy of Conflict. Will start buying once my queue of unread books reduces by at least a third

Okay. Just a normal evening at home, two foxes wandering around

The bushes seem to be trying to tell me something

Doesn’t this look like HELP?

Bing knows two jokes. He finds them funny.