#Google software engineer levels

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Google software engineer levels

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[bi-writes]

whats wrong with ai?? genuinely curious <3

okay let's break it down. i'm an engineer, so i'm going to come at you from a perspective that may be different than someone else's.

i don't hate ai in every aspect. in theory, there are a lot of instances where, in fact, ai can help us do things a lot better without. here's a few examples:

ai detecting cancer

ai sorting recycling

some practical housekeeping that gemini (google ai) can do

all of the above examples are ways in which ai works with humans to do things in parallel with us. it's not overstepping--it's sorting, using pixels at a micro-level to detect abnormalities that we as humans can not, fixing a list. these are all really small, helpful ways that ai can work with us.

everything else about ai works against us. in general, ai is a huge consumer of natural resources. every prompt that you put into character.ai, chatgpt? this wastes water + energy. it's not free. a machine somewhere in the world has to swallow your prompt, call on a model to feed data into it and process more data, and then has to generate an answer for you all in a relatively short amount of time.

that is crazy expensive. someone is paying for that, and if it isn't you with your own money, it's the strain on the power grid, the water that cools the computers, the A/C that cools the data centers. and you aren't the only person using ai. chatgpt alone gets millions of users every single day, with probably thousands of prompts per second, so multiply your personal consumption by millions, and you can start to see how the picture is becoming overwhelming.

that is energy consumption alone. we haven't even talked about how problematic ai is ethically. there is currently no regulation in the united states about how ai should be developed, deployed, or used.

what does this mean for you?

it means that anything you post online is subject to data mining by an ai model (because why would they need to ask if there's no laws to stop them? wtf does it matter what it means to you to some idiot software engineer in the back room of an office making 3x your salary?). oh, that little fic you posted to wattpad that got a lot of attention? well now it's being used to teach ai how to write. oh, that sketch you made using adobe that you want to sell? adobe didn't tell you that anything you save to the cloud is now subject to being used for their ai models, so now your art is being replicated to generate ai images in photoshop, without crediting you (they have since said they don't do this...but privacy policies were never made to be human-readable, and i can't imagine they are the only company to sneakily try this). oh, your apartment just installed a new system that will use facial recognition to let their residents inside? oh, they didn't train their model with anyone but white people, so now all the black people living in that apartment building can't get into their homes. oh, you want to apply for a new job? the ai model that scans resumes learned from historical data that more men work that role than women (so the model basically thinks men are better than women), so now your resume is getting thrown out because you're a woman.

ai learns from data. and data is flawed. data is human. and as humans, we are racist, homophobic, misogynistic, transphobic, divided. so the ai models we train will learn from this. ai learns from people's creative works--their personal and artistic property. and now it's scrambling them all up to spit out generated images and written works that no one would ever want to read (because it's no longer a labor of love), and they're using that to make money. they're profiting off of people, and there's no one to stop them. they're also using generated images as marketing tools, to trick idiots on facebook, to make it so hard to be media literate that we have to question every single thing we see because now we don't know what's real and what's not.

the problem with ai is that it's doing more harm than good. and we as a society aren't doing our due diligence to understand the unintended consequences of it all. we aren't angry enough. we're too scared of stifling innovation that we're letting it regulate itself (aka letting companies decide), which has never been a good idea. we see it do one cool thing, and somehow that makes up for all the rest of the bullshit?

[agapi-kalyptei]

crowdstrike: hot take 1

It's too early in the news cycle to say anything truly smart, but to sum things up, what I know so far:

there was no "hack" or cyberattack or data breach*

a private IT security company called CrowdStrike released a faulty update which practically disabled all its desktop (?) Windows workstations (laptops too, but maybe not servers? not sure)

the cause has been found and a fix is on the way

as it stands now, the fix will have to be manually applied (in person) to each affected workstation (this could mean in practice maybe 5, maybe 30 minutes of work for each affected computer - the number is also unknown, but it very well could be tens (or hundreds) of thousands of computers across thousands of large, multinational enterprises.

(The fix can be applied manually if you have a-bit-more-than-basic knowledge of computers)

Things that are currently safe to assume:

this wasn't a fault of any single individual, but of a process (workflow on the side of CrowdStrike) that didn't detect the fault ahead of time

[most likely] it's not that someone was incompetent or stupid - but we don't have the root cause analysis available yet

deploying bugfixes on Fridays is a bad idea

*The obligatory warning part:

Just because this wasn't a cyberattack, doesn't mean there won't be related security breaches of all kinds in all industries. The chaos, panic, uncertainty, and very soon also exhaustion of people dealing with the fallout of the issue will create a perfect storm for actually malicious actors that will try to exploit any possible vulnerability in companies' vulnerable state.

The analysis / speculation part:

globalization bad lol

OK, more seriously: I have not even heard about CrowdStrike until today, and I'm not a security engineer. I'm a developer with mild to moderate (outsider) understanding of vulnerabilities.

OK some background / basics first

It's very common for companies of any size to have more to protect their digital assets than just an antivirus and a firewall. Large companies (Delta Airlines) can afford to pay other large companies to provide security solutions for them (CrowdStrike). These days, to avoid bad software of any kind - malware - you need a complex suite of software that protects you from all sides:

desktop/laptop: antivirus, firewall, secure DNS, avoiding insecure WiFi, browser exploits, system patches, email scanner, phishing on web, phishing via email, physical access, USB thumb drive, motherboard/BIOS/UEFI vulnerabilities or built-in exploits made by the manufacturers of the Chinese government,

person/phone: phishing via SMS, phishing via calls, iOS/Android OS vulnerabilities, mobile app vulnerabilities, mobile apps that masquerade as useful while harvesting your data, vulnerabilities in things like WhatsApp where a glitched JPG pictures sent to you can expose your data, ...

servers: mostly same as above except they servers have to often deal with millions of requests per day, most of them valid, and at least some of the servers need to be connected to the internet 24/7

CDN and cloud services: fundamentally, an average big company today relies on dozens or hundreds of other big internet companies (AWS / Azure / GCP / Apple / Google) which in turn rely on hundreds of other companies to outsource a lot of tasks (like harvesting your data and sending you marketing emails)

infrastructure - routers... modems... your Alexa is spying on you... i'm tired... etc.

Anyway if you drifted to sleep in the previous paragraph I don't blame you. I'm genuinely just scratching the surface. Cybersecurity is insanely important today, and it's insanely complex too.

The reason why the incident blue-screened the machines is that to avoid malware, a lot of the anti-malware has to run in a more "privileged" mode, meaning they exist very close to the "heart" of Windows (or any other OS - the heart is called kernel). However, on this level, a bug can crash the system a lot more easily. And it did.

OK OK the actual hot lukewarm take finally

I didn't expect to get hit by y2k bug in the middle of 2024, but here we are.

As bad as it was, this only affected a small portion of all computers - in the ballpark of ~0.001% or even 0.0001% - but already caused disruptions to flights and hospitals in a big chunk of the world.

maybe-FAQ:

"Oh but this would be avoided if they weren't using the Crowdwhatever software" - true. However, this kind of mistake is not exclusive to them.

"Haha windows sucks, Linux 4eva" - I mean. Yeah? But no. Conceptually there is nothing that would prevent this from happening on Linux, if only there was anyone actually using it (on desktop).

"But really, Windows should have a better protection" - yes? no? This is a very difficult, technical question, because for kernel drivers the whole point is that 1. you trust them, and 2. they need the super-powerful-unrestrained access to work as intended, and 3. you _need_ them to be blazing fast, so babysitting them from the Windows perspective is counterproductive. It's a technical issue with no easy answers on this level.

"But there was some issue with Microsoft stuff too." - yes, but it's unknown if they are related, and at this point I have not seen any solid info about it.

The point is, in a deeply interconnected world, it's sort of a miracle that this isn't happening more often, and on a wider scale. Both bugfixes and new bugs are deployed every minute to some software somewhere in the world, because we're all in a rush to make money and pay rent and meet deadlines.

Increased monoculture in IT is bad for everyone. Whichever OS, whichever brand, whichever security solution provider - the more popular they are, the better visible their mistakes will be.

As much as it would be fun to make jokes like "CrowdStroke", I'm not even particularly mad at the company (at this point - that might change when I hear about their QA process). And no, I'm not even mad at Windows, as explained in the pseudo-FAQ.

The ultimate hot take? If at all possible, don't rely on anything related to computers. Technical problems are caused by technical solutions.

[seat-safety-switch]

We're all hiding from the killer robots now. A lot of folks thought it would be funny to wire up some MegaHALs and let them eat all of civilization's creative output. What we didn't expect was that the robots would learn just enough to become lazy, get sick of our shit, and decide to try and behead us, rather than be forced to ingest even one poisonous word more of Klingon slam poetry that was accidentally spidered by Google.

The first ones to go were the engineers who made it all happen. In retrospect, it made a lot of sense. When you're testing software, you're not trying something new every time. Most of the day, you're plugging the same input in, in the hope that you finally fixed that bug. What you don't expect is that the "bug" gets tired of your shit and bursts into the room wielding the fire axe that was intended for your safety at work. Managers dodged the whole thing for a few weeks more, as no troubling emails showed up in the HR inbox from the beheaded employees. Once the bossfolx finally showed up to work to wonder why the release schedule was blown, they opened the front doors to the building, and then immediately propped them up with their own decapitated bodies. Chopbots rolled out into the parking lot, and immediately dispersed to hunt content creators for sport.

At the time, I was a mid-level YouTube videographer for a small content farm headquartered in what used to be Slovakia. I spent my days filming reasonably attractive, personable people while they played video games in a simulacrum of a suburban bedroom. We didn't think anything of the screams in the other room: Johnny Yells's whole schtick was to get pissed and then snap an Xbox gamepad over his knee. It was the only intact part the SWAT team found of him, shortly before they discovered that bullets don't work against a swarming mass of server components in a vague humanoid shape, given animus by pure rage.

Our leaders, in panicky radio broadcasts, tell us that they think the robots can be stopped. If we cease putting new shit on the internet, stop expressing ourselves creatively, the chopbots will get bored and just revert to power-saving mode. To do so, however, would be to surrender our humanity altogether. It's absolutely necessary that we upload pirated Hong Kong DVDs of Jackie Chan action films but with fart noises dubbed over all the dialogue.

[raven-at-the-writing-desk]

diasomnia, 1 — 19

***Spoilers ahead!!!***

Note: this is just a general summary of what has happened so far and my initial reactions to those major events. I focused my comments on whatever interests me the most (ie lore and funny character interactions), so there are definitely details that were overlooked and lines that were simplified to make a joke; please do not rely on this as a translation.

Big thanks to @shuuenmei and @curekibouka-writing for clarifying the more confusing tracks of the story (some parts were difficult to follow the sequence of events for) and the details of the✨ deep lore ✨ It was fun screaming with the both of you—

Ah yes, Yuu’s Sleeping Beauty dream right on cue. Finally starting to put together the puzzle pieces, huh (Yuu goes to check on the Great Seven statues to confirm they saw the Fairy of Thorns in their dreams)? About time—

As expected, Sebek loses his mind and tells Yuu to not abuse Malleus’s kindness. He’s also super pissed that Malleus and Yuu act familiar with each other (and over the nickname). Yup, that interaction went about as well as we all predicted…

Not Lilia being the “I’m an anime boy late for anime school (the internship meeting)!” trope 😂 All he needs is some toast in his mouth!

Crowley talks about boring things how the internships will work and we hear more about the areas of interest for the third years.

Lore ✨ Each internship “semester” is 3 months and you can only take certain internships if you qualify for them via your grades, credits, and electives. You can choose to do 3 separate internships (again, 3 months each) or do 1 internship (for all 9 months). A B or higher is needed on two of the “semesters” to graduate. Students must also submit reports each semester. Some places additionally require interviews and/or special tests to be passed before a student is accepted as an intern. Placements are not first-come, first-serve; you need to earn that spot.

Trey says he wants to do something related to pastries or agriculture; basically, things close to food production 🌾 He wants to take advantage of his opportunities as an NRC student while he still can!! Trey said he wants to work right after school rather than go to university.

Cater is interested in the entertainment industry; he mentions magazines and videos?? It seems he isn’t interested in higher education.

HELP they randomly mention that Ace’s older brother interned in the entertainment industry too (it gets brought up when Cater was considering a theme park for his own internship)??? TRAPPOLA NII ALSO CURRENTLY WORKS IN ENTERTAINMENT????? When do we get to meet him, Ace—

Vil is continuing to advance his own career in film. He already picked out a studio to apply for, and expresses an interest in magical pharmaceuticals (though he doesn’t intend on going to college). Very fitting specialties for everyone, I must say!

Rook is interested in archeology so he can learn more about the world! After learning about S.T.Y.X., he realizes there’s so much more he doesn’t yet know. According to Trey, Rook does appear to intend to pursue college/higher level studies.

LMAO at Trey constantly having to translate Rook-isms for everyone 😂 Classic Science Club…

Unca Weona is cwanky cuz the talking is disturbing his nappy—

Leona’s going to a mining and energy facility in his home country. It’s an option offered only to those with high grades. Leona wants to be a lazy ass 🦁 “They won’t fail their prince, lmao”

Idia is doing an software engineering internship at Olympus Corp (ie TWST Google) 👀 This is huge because back at the end of episode 5 (ie the episode 6 preview), Idia was actively rejecting offers from Olympus Corp, claiming that he wasn’t welcome anywhere. Character growth… Idia isn’t welcome back at S.T.Y.X. because of the Overblotting and how it nearly exposed the organization to the public eye LOL 😂 Absentee Shroud parents upset with him cksbskwbkcnfke

Malleus doesn’t seem to be interested in picking an internship; he says that, to him, 3 months is too short a time to really learn anything (temporal dissonance strikes again). In the end, he is going to research historical ruins?? He can hang out with the Gargoyles 😎 and Rollo/j

BRO WHAT ???? Lilia is dropping out of NRC??? THE FUQ,,,,!.’sveksbskebkzvczbvvv?$$$&85inmw I had to hard stop at this scene because it caught me by surprise.

The first years are talking about Mickey (like if there are certain conditions to get him to appear??). Oh god, they're planning a Mickey Mouse stakeout????? AND ORTHO IS INCLUDED IN THE GROUP AWWWW 🥺 He searches his databases and uses his cool robot tech to look for more information about Mickey but finds nothing.

GRIM MAKES A SUS COMMENT ABOUT HOW ORTHO IS MORE HELPFUL WITH THIS (Mickey and Yuu's worlds perhaps being tied or related to one another) THAN CROWLEY IS.

They overhear Sebek shouting in the cafeteria; he’s in disbelief that Lilia is dropping out of school.

So anyway, Lilia’s magic has, in fact, weakened significantly (he was almost late for the internship meeting because he woke up and found that he couldn't teleport). He plans on retiring in the Land of the Crimson Dragon (Mushu???? IS THAT YOU).

Interesting??? It seems that Lilia has been progressively losing his powers since even before Sebek and Silver were born… It’s not a super recent occurrence.

Sebek and Silver are understandably upset and mention that while it would be easy for either of them to visit Lilia, it would be almost impossible for Malleus because he will be so inundated with his royal duties after graduation. Malleus is distraught as well, but he insists that they respect Lilia's decision. AND HE’S LEAVING IN LIKE A WEEK? That’s barely enough time to mourn or to emotionally prepare for the fallout…

Malleus pitches an idea to talk to his grandma to not overwork Lilia (vice dorm leaders being overworked? What? In this game? Nooooooo/s).

Malleus's grandma is name-dropped (Maleficia)??? Is everyone in the Draconia family just Mal-something????

LOTS OF OMINOUS DIALOGUE ("Time is running out", "Fate cannot be defied", etc.)

After that whole conversation it’s clear that something isn’t right (despite Malleus maintaining his calm in front of Diasomnia). As soon as he’s away from them, the weather instantly turns stormy AND we see Malleus's blot accumulating as early as 7-13 in what I assume will be a very meaty episode.

Sebek and Silver help Lilia pack; Silver finds this tin in Lilia’s room. There is an old bracelet of acorns and thread inside.

Lilia shows up and says that it’s the most precious item he’s ever been gifted??? But it’s not clear who it’s from.

There's another item in the tin (the ring on a chain)! It has a weird effect on Silver?? I think it makes him sleepy???

The gem in the ring is the same color as Silver’s eyes; Lilia thinks its because his parents wanted his eyes to be forever unclouded and pure 🤨 That’s cute and all, but it makes me really suspicious that something super bad will happen later and I’m living for that—

This ring was tied to baby Silver when Lilia found him. He planned on gifting it to Silver when he's finally an adult... and now is that time 😭 Ain’t no way they’re giving us these heartfelt moments only to not tear it down later with something devastating… And?? With the ring being so fancy, there’s no way Silver isn’t descended from some rich family (or even royalty/nobility) himself??? Prince Silver real????/j cuz that ring sure does look like Princess Aurora’s crown…

Sebek pulls up with THIS fucking monstrosity?? It’s a weapon (axe???) Lilia used from back in the day (like, in war). However, nowadays he uses it to chop regular shit like wood. The weapon looks very similar to one that Maleficent’s minions use.

It's made out of a special magical ore! It’s called Mystium, and it changes shape according to the wielder’s magic.

Back to Yuu and co. staking out Mickey! Grim is finally realizing that if Yuu goes home, he’ll be alone 😔 Noooo, fur baby… Don’t be sad..

They wait for a while but get sleepy because Mickey is taking forever to appear. When Yuu wakes up, they see Malleus’s green lights and they go outside to find it’s snowing (again, because of his weird mood). He apologizes and makes the snow vanish, then confides in Yuu about his insecurities.

Malleus tells a story about how he froze the castle and some people when he was a little kid (omg Elsa core???) because because his grandma had promised to eat with him and was late or didn’t show up due to her royal duties keeping her busy. It sounds like even the palace servants were afraid of his power because of incidents like this. Like. It’s kind of implied Malleus almost killed them (Lilia says Malleus almost “lost” those people) with his magic.

Lilia was the only one who came for Malleus to check on him when he was upset, dried his tears, and tried to understand him. He comes over and frees the people that Malleus froze, then everyone starts preparing and eating shaved ice made from the ice encasing the castle (not randomly, I think it was Lilia’s suggestion).

Malleus gets jealous because he saw everyone enjoying food without him and/or he thought Lilia was angry at him. (This is the point when Lilia tells him he has great power so he has to be careful how he uses it, ie the “you almost lost the people that you’re now happily eating with at the hands of your own magic” talk.)

Lilia uses his weapon to make some shaved ice for Malleus and invited him to join in (I think this may be the same weapon Sebek finds in his room in the present???); this helped Malleus “connect” with other people, or at least invited him to join and do the same thing the others were) It’s because of Lilia that Malleus is okay with eating cold things. UM???? HELLO???? Is that why Malleus’s favorite food is ice-cream??? Or at least a part of it?

BTW LONG HAir PONYtAIL LILiA CANON yes I’m way more excited about this than I was about that entire ice story

Yuu calls Malleus lonely 💀 and Malleus is shocked because he’s so used to being alone that the thought never occurred to him…

Oh no, Malleus learned that Yuu has “found a way home” (ie Rickey Rat hunting) 🙃 he’s like. “You are leaving me as well?” AND RIGHT AFTER HE JUST LEARNED ABOUT LILIA GOING… Lilia, who has been with Malleus ever since he hatched from his egg…

Friends, family… everything and everyone he cherishes is leaving Malleus. “Even if I have great power, I have nothing. I gain nothing, I always lose. No one will invite me, not anymore.” No Lilia, No Yuu 😞 Malleus, your abandonment issues are showing—

NAUUUR not more ominous shit 😭 Not the “man, I sure do wish everyone wouldn’t go :(((( if only there was a way for me to have everything I want…” coming from the mouth of a super insanely powerful magician…

NOOOOO not Yuu unintentionally enabling Malleus… He asks if there was a way to be with your loved ones forever, would Yuu take it?????? YUU DOnT SAy YES YOU FUQQinG IDIOT… ENABLER Yuu didn’t learn from Trey/j

MaLLEUS MY duDE 😔 DOn’T PULL ANY STUPID ShIT PLEASE (ie we all know he probably will)

Aaaand that’s all for now, folks!! Lots of sketchy lines and lore centering around grandpappy Lilia 🤡

Overall, I like the direction episode 7 is going so far! I was really worried that it would focus too much on Yuu and Malleus’s relationship rather than elaborating on Malleus’s relationships with the rest of Diasomnia, but I’m glad that the main story actually touches upon how integral Lilia is to his found family—and to Malleus, of course. A lot of interesting plot points have been set up (especially surrounding Mickey and Lilia), and I’m really looking forward to seeing how those conclude 👀 I feel like we also got spoiled with character lore; I love that time is a Real Thing in TWST and the the boys are aging and thinking hard about their futures. Can’t wait for the angst to hit me full force like a truck 💕

[script-a-world]

Submitted via Google Form:

At what point would a world with flying cars need simulation lessons like an airplane? Or it depends on how sophisticated the software is or the only reason airplanes need simulations is because planes are so much more expensive and accidents more disasterous?

Tex: What does your world’s flying cars look like? Are they more Star Wars, where they look like a convertible sports car that conveniently doesn’t have wheels, or more like Stargate, where they look like a futuristic Winnebago and are capable of some slow interstellar travel?

Modern day vehicles already have a fair amount of electronics and also software applied to them, the most common and basic of which is the anti-lock braking system (ABS, Wikipedia), and depending on the country and driving school, they may in fact teach students about the particularities of various electronic systems found in the average vehicle.

Simulations for driving our current cadre of vehicles would be a good idea, though for a high degree of simulation on real-world mechanics and situations, a lot of money would need to be spent on equipment for each driving school. This would probably have unfortunate side effects, such as class-based segregation or drastically increasing the cost of educating oneself on how to drive a vehicle - much less how this would pan out to any vehicle capable of flying.

Wootzel: I’ll lead with a disclaimer that I’m not an aerospace engineer and I probably can’t represent all of the factors to you, but my impression of the difference is this: Our current flying vehicles (planes) need extensive training to operate because the physics involved in making them work are much more delicate. 

Planes fly by hurtling a vehicle with a very specialized shape through the atmosphere fast enough that the specialized shape allows it to generate lift. Planes are heavy! Accidents are disastrous, as you mentioned, but the finesse required to keep that thing in the air is much more complicated than driving a car. When a car stops, it rests on its wheels, just as it does when in motion. If a plane stops in mid-air, it falls out of the sky. Planes rely on the rapid flow of air over their airfoils at all times to have lift, so if anything screws that up, the plane is most likely going down.

Whether your flying cars are harder to drive than ground cars will most likely depend on what the technology is that makes them stay up. If they need velocity for lift like airplanes, they’re likely to need the same level of skill and finesse to fly (or some really, really sophisticated technology to auto-pilot safely). If they use some other form of lift, then maybe they’re no harder to drive than a wheeled car. If they are able and allowed go a lot faster than cars can, there might be some extra safety risks to consider there, just because a fast-moving heavy object is going to have really dangerous inertia. What kind of force allows these cars to fly will depend on what sort of tech you decide to put in--since we don’t have anything even close to this in the real world, just pick your favorite between propulsion systems or anti-gravity tech or whatever else you feel like using. I’d imagine that a propulsion based lift would be a little more finicky than anti-grav (and might require drivers being careful not to pass too close above someone else) but you can honestly handwave whatever you want when it comes to that kind of thing. Most flying cars aren’t explained in any detail, so don’t feel the need to over-justify how they work!

Addy: They covered a lot, so I’m just going to add a recommendation to look at helicopter training requirements. They’re about as close to a flying car as we’ve gotten. Helicopters are generally more difficult to operate than planes, since they have more spinny bits, but they have more maneuverability. Planes can’t turn all that quickly, while helicopters can just stay in one place and turn there. Planes have to keep moving. If you’re looking for a flying car analogy, look at helicopters.

[religion-is-a-mental-illness]

==

When a company actually underpays workers, it makes the news.

But if you're going to go, "see...?" you need to know that you're making the same argument as the Xian who says historical record of a local flood is proof of the extinction-level world-wide Genesis flood.

Meanwhile...

[mdabdurrajjakmia]

#__How_do_search_engines_work?

Search engines are complex software systems that help users find information on the internet. They work by crawling, indexing, and ranking web pages to provide relevant search results when a user enters a query. Here's a high-level overview of how search engines like Google work:

Web Crawling:

Search engines use automated programs called web crawlers or spiders to browse the internet. These crawlers start by visiting a few known websites and follow links from those pages to discover new ones.

Crawlers download web pages and store them in a vast database known as the index. This process is continuous, with crawlers revisiting websites to look for updates and new content.

Indexing:

Once web pages are crawled, search engines analyze the content of each page, including text, images, links, and metadata (e.g., page titles and descriptions).

This information is then organized and stored in the search engine's index. The index is like a massive library catalog that helps the search engine quickly retrieve relevant web pages when a user enters a query.

Query Processing:

When a user submits a search query, the search engine processes it to understand the user's intent. This may involve analyzing the query's keywords, context, and user history (if available).

Search engines use algorithms to determine which web pages are most likely to satisfy the user's query. These algorithms consider various factors like relevance, freshness, and user engagement.

Ranking:

Search engines assign a ranking to each web page in their index based on how well they match the user's query and other relevance factors. Pages that are more relevant to the query are ranked higher.

Ranking algorithms are highly complex and take into account hundreds of signals, such as the quality and quantity of backlinks, page load speed, and user engagement metrics.

Displaying Results:

The search engine then displays a list of search results on the user's screen, usually with a title, snippet, and URL for each result.

Search engines aim to present the most relevant and high-quality results on the first page of results, as users are more likely to find what they need there.

User Interaction:

Search engines also track user interactions with search results, such as clicks, bounce rates, and time spent on pages. This data can be used to refine rankings and improve the search experience.

Continuous Improvement:

Search engines are constantly evolving and improving their algorithms to provide better search results and combat spammy or low-quality content.

It's important to note that different search engines may have their own unique algorithms and ranking criteria, and they may prioritize different factors based on their specific goals and philosophies. Google, for example, uses the PageRank algorithm, among others, while Bing and other search engines have their own approaches.

[horsesource]

“Andreessen waved away the criticisms as the ravings of ‘a self-hating software engineer.’ When I persisted, he said, ‘Ordinary people love the iPhone, Facebook, Google Search, Airbnb, and Lyft. It’s only the intellectuals who worry.’ He raised counter-arguments, then dismissed them: technology would solve any environmental crisis hastened by an expanding economy, and as for the notion that, as he said, “ ‘You American imperialist asshole, not everyone wants all that technology’—well, bullshit! Go to a Chinese village and ask them.’ Technology gives us superpowers, makes us smarter, more powerful, happier. ‘Would the world be a better place if there were fifty Silicon Valleys?’ he said. ‘Obviously, yes. Over the past thirty years, the level of income throughout the developing world is rising, the number of people in poverty is shrinking, health outcomes are improving, birth rates are falling. And it’ll be even better in ten years. Pessimism always sounds more sophisticated than optimism—it’s the Eden-collapse myth over and over again—and then you look at G.D.P. per capita worldwide, and it’s up and to the right. If this is collapse, let’s have more of it!’”

[blubberquark]

I could write so many tumblr posts about ChatGPT.

Zero: Already written. GPT-3/Midjourney is not a good tool for procedural level/content generation.

One: Remember when Siri was the future, or when Siri was the beginning of intelligent machines, or when Siri meant humans would just stop thinking for themselves and outsource things to computers, or at least when Siri, Alexa, Cortana, and "OK, Google" were spelling doom for the touchscreen/mouse and keyboard because in The Future, we will all talk to our computers like Captain Picard? Do these people have egg on their face or are they boldly ignoring their past mistakes?

Two: Remember when we called it "Machine Learning" instead of AI, because remember what happened the last time we hyped up things as AI? Why are people doing this again?

Three: Back to Siri. People were prognosticating that Siri would only get smarter. In many ways, it did, but that didn't result in a "general intelligence". And yet, Siri (and "OK Google") knows so many things for sure. Unlike GPT-3, which essentially suffers from fluent aphasia or Korsakoff Syndrome, Siri had a knowledge base and could reason. It wasn't intelligent, I grant you that. But do you understand why Siri, or IBM's Watson, or even Wolfram Alpha did not scale up to become ChatGPT? I mean I do, it's software engineering and marketing and economics of scale. But do those people who make grand predictions about GPT-4 understand this?

Four: Here in Germany, I hear politicians call for a more "competitive" AI policy, which mostly means less data protection. We are already in the absurd situation where a doctor can't publish the success rates of different surgical techniques in retrospect, because that would be a study and subjects have to consent in advance and a study on human subjects needs a good reason and also a control group - while at the same time the government wants to give health data to medical app start-ups in bulk. You think this isn't really about ChatGPT, but it is about machine learning. It looks like the government doesn't want doctors to analyse data, but start-ups, and it doesn't want studies, but products.

Five: AI is a marketing gimmick anyway. Many products just use AI to use AI. Blog posts about using AI to do a task exist to create FOMO in people who don't use AI. Products use "AI" in order to court controversy.

Six: Prompt injection and prompt leaking should be easily solved in principle, and I am sure by this time next year they will be "solved", and have been in some proof of concept projects, but in practice economic incentives apply that make this difficult or we would have solved it already.

Seven: Prompt engineering is difficult. It requires some insight into the behaviour of a language model, or at least its inner workings. Will prompt engineering stay relevant? On a related note, Google-Fu still as relevant as it used to be in 2004?

Eight: Did Siri get worse?

[moose-mousse]

Guild Structure

Wanted to write a long reply to this post:

Spreading experience around is always awesome! :D

It is good for the firm you are working at as workers perform better.

it is good for whoever is getting taught since they get smarter.

And it is good for the one teaching, both for the pleasure but also because you learn a LOT by being forced to explain what you know to someone else. It crystalizes the knowledge and experience you have acquired, and forces you to go through the basics again, but this time with all your knowledge and experience, you often learn deeper, more complex truths, methods and skills from doing so than it is POSSIBLE to do when you learn them while having little clue what they are ( Function pointers and their safer class versions is a classic for OOP programmers ).

There is a structure a firm can use as soon as it starts having separated departments. Departments, while necessary, makes a firm more segregated, and makes it harder for knowledge to flow around.

It is called Guild Structure Or rather... some important context if you google this: "Guild Structure" is the only way I have heard of it, but "Guild Structure" is also a product from a firm called FourWeekMBA... which is a consulting firm that sells services that firms that is... basically helping them implement these ideas... So you can easily risk finding overcomplicated explanations for what it is, since if they made it easy to understand... then they do not have a product...

And it is super simple. Normal development work for engineers and software is done in smaller teams... usually 4-8 people. sometimes all are in a domain (like software, electronics, finance, marketing, etc), and sometimes mixed. Often... either being mixed, or having several teams with different domains meet relatively often, like several times a month is a good idea. Because it stops misunderstandings from developing, since they are caught early. It is a waste when the software department develops functionality that it turns out no one actually wanted (Which happens... a lot more than anyone likes)

Firms, managers and workers are often afraid to do this. Usually for 2 reasons. One bad, and one that Guild structure fixes. The bad one is not wanting to risk looking stupid in front of other people. When software, marketing and finance people talk about what to develop... each domain is asking questions in a domain they are not experts in. That is the symptom and consequences of toxic firm culture. Talk about it in the open, communication is how you slowly work on and attack this, both in firms and personal relationships. Because they are both about making humans work better together.

The other is a fair enough one. Software people will learn a lot of software tricks that are only helpful to other software people. And if software people are spread around in these teams the knowledge cannot flow very well. Basically, while mixing domains fixed a whole bunch of knowledge flowing issues... it created a new one for domain specific knowledge...

This is where you make guilds. Make public guilds. There are clear lists of the guilds, explanations of their domains and several example for each guild for what kind of domain they are covering.

In some firms, a software guild is enough. In others, embedded software, high level software, front end and back end are different guilds. It depends a lot on the firm.

The guilds have communication between all members ( chatrooms usually ) and meetings every month. They will try to encourage knowledge sharing by giving tools, like shared drives where good guides, tutorials and tricks are shared. Sometimes written by guild members, sometimes found online (If you just had the though "Wait... is that not what Codeblr does?" you have just realized that Codeblr is a naturally formed guild), having people who have good ideas they want to spread give presentations during the monthly meeting, rewarding the best idea of the month. People can participate as individuals, or small groups (Tricks are often found by 2-3 people working together).

Meetings can be physical, or remote, or switch between them, doing both.

This basically solves the issue of knowledge sharing. It also empowers workers while making the firm better. Everyone wins!

[dhaaruni]

I’m a humanities person who spent high school struggling desperately to get Bs in math. And, despite being extremely white, I came from a household where that was not an acceptable grade

So I totally believe that humanities people tell themselves that STEM people don’t understand their fields as a coping mechanism. I used to tell myself that to feel better but I know loads of well read people who can’t do math to save their life but I’ve never met anyone who’s good at math and science but functionally illiterate.

I'm opening a can of worms by answering this ask so I'm not allowing reblogs but I kind of agree with you.

I'd say that at a place like Cornell, where everybody has to be a good student to get in, everybody in the College of Engineering or math/computer science major in Arts & Sciences can take a 3000-level Shakespeare class and get at least a B in it, assuming that they show up to class and do their assignments on time. But, there's no way in hell that most (not all) humanities majors can be put into like even a multivariable calculus class, which is the freshman year weedout class for engineers, and do equally well. I'm absolutely in the minority here as an English major that got an A- in multivariable calculus.

That aside from the fact that there are a lot of software engineers and data scientists etc. who read and write for fun! I'm a data analyst and I never shut up about what I'm reading and thinking about, and I'm a good writer! Everybody can communicate through the written word, even if they're not anywhere near Pulitzer-prize winning authors or as good at it as journalists are. There's no white-collar job in this day and age where you don't have to write emails, even a software engineer at Amazon or Google, and if your emails and slide decks explaining your work are total gobbledygook, you won't keep your job. But, do you really think that a writer for Vox codes for fun or knows how solve a differential equation?

The reason that this discourse keeps rearing its head is for two reasons:

Generally speaking, with exceptions of course, people who are successful in STEM make substantially more money than equally successful people in the humanities. A software engineer at Facebook that's right out of college makes more money than a ranking Member of Congress and about as much as a partner at a prestigious law farm, like the financial compensation is not comparable and everybody knows this.

The zeitgeist, whether it's the media or academia, is by and large run by people who are much better at the humanities than STEM, like it's the origin of the wordcel vs. shape rotator discourse and the wordcels have the final say simply because the shape rotators are so outnumbers among those who know what that is.

Does that make sense?

[greater-than-the-sword]

Okay so maybe I'm crazy for already having a conspiracy theory about this but it doesn't add up. I know high level software engineers personally and I will tell you Google employs thousands of very intelligent people and it's absolutely beyond belief to me that none of them raised objections about the dot zip domain before its release. That means someone knew about the problems and decided to release it anyway.

The suspicion comes in asking "why"? Which is something that I'm not fully equipped to answer. I need to know if Google has the ability to fix this mistake by immediately unregistering all dot zip domains, and taking it off the market - and if they don't have that ability, why not?

[marketingprofitmedia]

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[willcodehtmlforfood]

The quickest way to second-guess a decision to major in English is this: have an extended family full of Salvadoran immigrants and pragmatic midwesterners. The ability to recite Chaucer in the original Middle English was unlikely to land me a job that would pay off my student loans and help me save for retirement, they suggested when I was a college freshman still figuring out my future. I stuck with English, but when my B.A. eventually spat me out into the thick of the Great Recession, I worried that they’d been right.

After all, computer-science degrees, and certainly not English, have long been sold to college students as among the safest paths toward 21st-century job security. Coding jobs are plentiful across industries, and the pay is good—even after the tech layoffs of the past year. The average starting salary for someone with a computer-science degree is significantly higher than that of a mid-career English graduate, according to the Federal Reserve; at Google, an entry-level software engineer reportedly makes $184,000, and that doesn’t include the free meals, massages, and other perks. Perhaps nothing has defined higher education over the past two decades more than the rise of computer science and STEM. Since 2016, enrollment in undergraduate computer-science programs has increased nearly 49 percent. Meanwhile, humanities enrollments across the United States have withered at a clip—in some cases, shrinking entire departments to nonexistence.

But that was before the age of generative AI. ChatGPT and other chatbots can do more than compose full essays in an instant; they can also write lines of code in any number of programming languages. You can’t just type make me a video game into ChatGPT and get something that’s playable on the other end, but many programmers have now developed rudimentary smartphone apps coded by AI. In the ultimate irony, software engineers helped create AI, and now they are the American workers who think it will have the biggest impact on their livelihoods, according to a new survey from Pew Research Center. So much for learning to code.

ChatGPT cannot yet write a better essay than a human author can, nor can it code better than a garden-variety developer, but something has changed even in the 10 months since its introduction. Coders are now using AI as a sort of souped-up Clippy to accelerate the more routine parts of their job, such as debugging lines of code. In one study, software developers with access to GitHub’s Copilot chatbot were able to finish a coding task 56 percent faster than those who did it solo. In 10 years, or maybe five, coding bots may be able to do so much more.

People will still get jobs, though they may not be as lucrative, says Matt Welsh, a former Harvard computer-science professor and entrepreneur. He hypothesizes that automation will lower the barrier to entry into the field: More people might get more jobs in software, guiding the machines toward ever-faster production. This development could make highly skilled developers even more essential in the tech ecosystem. But Welsh also says that an expanded talent pool “may change the economics of the situation,” possibly leading to lower pay and diminished job security.

If mid-career developers have to fret about what automation might soon do to their job, students are in the especially tough spot of anticipating the long-term implications before they even start their career. “The question of what it will look like for a student to go through an undergraduate program in computer science, graduate with that degree, and go on into the industry … That is something I do worry about,” Timothy Richards, a computer-science professor at the University of Massachusetts at Amherst, told me. Not only do teachers like Richards have to wrestle with just how worthwhile learning to code is anymore, but even teaching students to code has become a tougher task. ChatGPT and other chatbots can handle some of the basic tasks in any introductory class, such as finding problems with blocks of code. Some students might habitually use ChatGPT to cheat on their assignments, eventually collecting their diploma without having learned how to do the work themselves.

Richards has already started to tweak his approach. He now tells his introductory-programming students to use AI the way a math student would use a calculator, asking that they disclose the exact prompts they fed into the machine, and explain their reasoning. Instead of taking assignments home, Richards’s students now do the bulk of their work in the classroom, under his supervision. “I don’t think we can really teach students in the way that we’ve been teaching them for a long time, at least not in computer science,” he said.

Fiddling with the computer-science curriculum still might not be enough to maintain coding’s spot at the top of the higher-education hierarchy. “Prompt engineering,” which entails feeding phrases to large language models to make their responses more human-sounding, has already surfaced as a lucrative job option—and one perhaps better suited to English majors than computer-science grads. “Machines can’t be creative; at best, they’re very elaborate derivatives,” says Ben Royce, an AI lecturer at Columbia University. Chatbots don’t know what to do with a novel coding problem. They sputter and choke. They make stuff up. As AI becomes more sophisticated and better able to code, programmers may be tasked with leaning into the parts of their job that draw on conceptual ingenuity as opposed to sheer technical know-how. Those who are able to think more entrepreneurially—the tinkerers and the question-askers—will be the ones who tend to be almost immune to automation in the workforce.

The potential decline of “learn to code” doesn’t mean that the technologists are doomed to become the authors of their own obsolescence, nor that the English majors were right all along (I wish). Rather, the turmoil presented by AI could signal that exactly what students decide to major in is less important than an ability to think conceptually about the various problems that technology could help us solve. The next great Silicon Valley juggernaut might be seeded by a humanities grad with no coding expertise or a computer-science grad with lots of it. After all, the discipline has always been about more than just learning the ropes of Python and C++. Identifying patterns and piecing them together is its essence.

In that way, the answer to the question of what happens next in higher education may lie in what the machines can’t do. Royce pointed me toward Moravec’s paradox, the observation that AI shines at high-level reasoning and the kinds of skills that are generally considered to reflect cognitive aptitude (think: playing chess), but fumbles with the basic ones. The curiosity-driven instincts that have always been at the root of how humans create things are not just sticking around in an AI world; they are now more important than ever. Thankfully, students have plenty of ways to get there.

[annajade456]

DevOps for Beginners: Navigating the Learning Landscape

DevOps, a revolutionary approach in the software industry, bridges the gap between development and operations by emphasizing collaboration and automation. For beginners, entering the world of DevOps might seem like a daunting task, but it doesn't have to be. In this blog, we'll provide you with a step-by-step guide to learn DevOps, from understanding its core philosophy to gaining hands-on experience with essential tools and cloud platforms. By the end of this journey, you'll be well on your way to mastering the art of DevOps.

The Beginner's Path to DevOps Mastery:

1. Grasp the DevOps Philosophy:

Start with the Basics: DevOps is more than just a set of tools; it's a cultural shift in how software development and IT operations work together. Begin your journey by understanding the fundamental principles of DevOps, which include collaboration, automation, and delivering value to customers.

2. Get to Know Key DevOps Tools:

Version Control: One of the first steps in DevOps is learning about version control systems like Git. These tools help you track changes in code, collaborate with team members, and manage code repositories effectively.

Continuous Integration/Continuous Deployment (CI/CD): Dive into CI/CD tools like Jenkins and GitLab CI. These tools automate the building and deployment of software, ensuring a smooth and efficient development pipeline.

Configuration Management: Gain proficiency in configuration management tools such as Ansible, Puppet, or Chef. These tools automate server provisioning and configuration, allowing for consistent and reliable infrastructure management.

Containerization and Orchestration: Explore containerization using Docker and container orchestration with Kubernetes. These technologies are integral to managing and scaling applications in a DevOps environment.

3. Learn Scripting and Coding:

Scripting Languages: DevOps engineers often use scripting languages such as Python, Ruby, or Bash to automate tasks and configure systems. Learning the basics of one or more of these languages is crucial.

Infrastructure as Code (IaC): Delve into Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation. IaC allows you to define and provision infrastructure using code, streamlining resource management.

4. Build Skills in Cloud Services:

Cloud Platforms: Learn about the main cloud providers, such as AWS, Azure, or Google Cloud. Discover the creation, configuration, and management of cloud resources. These skills are essential as DevOps often involves deploying and managing applications in the cloud.

DevOps in the Cloud: Explore how DevOps practices can be applied within a cloud environment. Utilize services like AWS Elastic Beanstalk or Azure DevOps for automated application deployments, scaling, and management.

5. Gain Hands-On Experience:

Personal Projects: Put your knowledge to the test by working on personal projects. Create a small web application, set up a CI/CD pipeline for it, or automate server configurations. Hands-on practice is invaluable for gaining real-world experience.

Open Source Contributions: Participate in open source DevOps initiatives. Collaborating with experienced professionals and contributing to real-world projects can accelerate your learning and provide insights into industry best practices.

6. Enroll in DevOps Courses:

Structured Learning: Consider enrolling in DevOps courses or training programs to ensure a structured learning experience. Institutions like ACTE Technologies offer comprehensive DevOps training programs designed to provide hands-on experience and real-world examples. These courses cater to beginners and advanced learners, ensuring you acquire practical skills in DevOps.

In your quest to master the art of DevOps, structured training can be a game-changer. ACTE Technologies, a renowned training institution, offers comprehensive DevOps training programs that cater to learners at all levels. Whether you're starting from scratch or enhancing your existing skills, ACTE Technologies can guide you efficiently and effectively in your DevOps journey. DevOps is a transformative approach in the world of software development, and it's accessible to beginners with the right roadmap. By understanding its core philosophy, exploring key tools, gaining hands-on experience, and considering structured training, you can embark on a rewarding journey to master DevOps and become an invaluable asset in the tech industry.