#it's essentially a parsing error
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The result of that flash poll I did the other day, Riv wound up winning so here he is!
Random OC lore below for anyone interested.
Riv is the oldest of the aur, a species unintentionally formed from the energetic aftershocks of the creation of his planet. Because there was only so much of that energy to go around, there are a limited number of "souls" available for their species, and thus the aur have a static population. Although functionally immortal, they do lose neuroelasticity over time, which eventually makes living pretty unpleasant, so they inevitably opt to pass away and allow a new member of the species to be born.
Several thousand years ago, Riv contracted a particularly dangerous magical condition that left him discolored—he used to be a very pale apricot color and his hair was opalescent white—and with chronic pain, but also keeps him from losing neuroelasticity, allowing him to live basically forever without experiencing the ennui that is the literal death of the rest of his species.
Travelers of other species who came across the aur in ancient times wound up essentially engaging in a millennia-long game of telephone that led to a gross misunderstanding of what they actually looked like, which is where the concept of unicorns comes from. When the aur finally went public as a species to get people to stop killing each other, everyone was very surprised to find that they look nothing like horses or deer. (Although they do have hooves, which is what led to the mistranslation that brought about that misconception in the first place.)
#original character#original art#artists on tumblr#lavayel-en riv#art tag#in spite of all that#it should be mentioned#that I refer to riv affectionately as#prince hold my beer#he's very old#ie: too old to care what anyone thinks#and too old to worry about consequences#what happens happens#might as well make it happen yourself#random extra lore:#the aur do not have mouths#but they do have teeth#if you were to like...cut into that space and look#there's teeth in there#it's essentially a parsing error#they're modeled loosely after the gods that made the planet#but it didn't all come through correctly#a copy of a copy of a copy#internally they're pretty close#but the externals are...ehhhhh#the indori cycle#TIC
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ChoiceScript Savepoint System Very Quickly
Hey guys,
@hpowellsmith made a great template for save points! It requires you to create another variable for every variable you have in your ChoiceScript game, so that it can store the old values to essentially "save"! This won't rely on third-party saving systems but is rather hard-coded into the game itself.
I realize that it can be a daunting task to create a whole other set of variables, especially if you already have many, many of them. (Looking at TSS' code, there are thousands!)
But I propose two super quick ways to automatically create all the variables you need for save points.
Find and replace.
Copy all your *create variables
Paste it into a Google Docs
On, PC, Ctrl+H to open up the dialog box for Find and Replace (link on how to find and replace on different platforms)
Search for "*create " (space included at the end) and replace it with *create save_
Hit "Replace All" and there you have your duplicated variables to paste into your startup (do so without replacing any of your old variables).
Bonus: you can instead replace it with *create save1_ , *create save2_ , etc. to have multiple save slots.
You can create all your needed variables in startup quickly with this, but there is still the issue of having to *set the variables to the new variables (when you're saving) or vice versa (when loading).
Hence the other way:
Save System Generator
I also made a program where, if you copy and paste all of your *create variables, it will automatically:
Give you code to put in your startup (the duplicated save variables)
Give you code that you use to save.
Give you code that you use to load.
I recommend you do it the way Hannah PS does in their template by calling a *gosub_scene.
Here are the step by step instructions on how to do this:
1. Prepare your *create variables. To clarify, you will only put in *create stuff into the program. Copy from your very first *create to your very last *create (the variables you want to save at least). Do not add any comments or additional code that is NOT *create. Do not have any additional spaces at the end (line breaks in between *create should be fine, but be more aware for potential errors).
2. Create a .txt file. In Hannah's template, the file is called "savegame.txt". You will want to make a *label save and a *label load that each *return (as depicted above).
3. Load up the program. Here is the link.
4. Pasting in your code. Paste in your code and immediately after your last *create, press enter, press $, and press enter again.
Note 1: You cannot use Ctrl+V or shortcut keys to paste in the code. You have to right click and paste it. Do not do this on mobile.
Note 2: You might want to do this in segments, as the program might have difficulty parsing through it, and you will more easily find errors in case they happen. Maybe every 30-50 variables to keep them bite-sized. I've tested inputting up to 70 unique variables to success.
5. Startup variables. After reading your input, it will give you code that you then have to add to your startup. Copy it by highlighting and right-clicking on it (do not use shortcut keys or do this on mobile).
6. Save. If you press S and enter, it will give you the code that you need to put in your savegame.txt under your *label save .
7, Load. If you press L and enter, it will give you the code you need to put in your savegame.txt under your *label load .
8. Using it. As in the template, you'll want to call on this with a *gosub_scene savegame load (if you want to load) or *gosub_scene savegame save (if you want to save).
And that's it! Please let me know if the program works incorrectly! 💕💕
#choicescript#choicescript resources#cs coding resources#choicescript coding resources#choicescript saving#choicescript save system
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One phrase encapsulates the methodology of nonfiction master Robert Caro: Turn Every Page. The phrase is so associated with Caro that it’s the name of the recent documentary about him and of an exhibit of his archives at the New York Historical Society. To Caro it is imperative to put eyes on every line of every document relating to his subject, no matter how mind-numbing or inconvenient. He has learned that something that seems trivial can unlock a whole new understanding of an event, provide a path to an unknown source, or unravel a mystery of who was responsible for a crisis or an accomplishment. Over his career he has pored over literally millions of pages of documents: reports, transcripts, articles, legal briefs, letters (45 million in the LBJ Presidential Library alone!). Some seemed deadly dull, repetitive, or irrelevant. No matter—he’d plow through, paying full attention. Caro’s relentless page-turning has made his work iconic.
In the age of AI, however, there’s a new motto: There’s no need to turn pages at all! Not even the transcripts of your interviews. Oh, and you don’t have to pay attention at meetings, or even attend them. Nor do you need to read your mail or your colleagues’ memos. Just feed the raw material into a large language model and in an instant you’ll have a summary to scan. With OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude as our wingmen, summary reading is what now qualifies as preparedness.
LLMs love to summarize, or at least that’s what their creators set them about doing. Google now “auto-summarizes” your documents so you can “quickly parse the information that matters and prioritize where to focus.” AI will even summarize unread conversations in Google Chat! With Microsoft Copilot, if you so much as hover your cursor over an Excel spreadsheet, PDF, Word doc, or PowerPoint presentation, you’ll get it boiled down. That’s right—even the condensed bullet points of a slide deck can be cut down to the … more essential stuff? Meta also now summarizes the comments on popular posts. Zoom summarizes meetings and churns out a cheat sheet in real time. Transcription services like Otter now put summaries front and center, and the transcription itself in another tab.
Why the orgy of summarizing? At a time when we’re only beginning to figure out how to get value from LLMs, summaries are one of the most straightforward and immediately useful features available. Of course, they can contain errors or miss important points. Noted. The more serious risk is that relying too much on summaries will make us dumber.
Summaries, after all, are sketchy maps and not the territory itself. I’m reminded of the Woody Allen joke where he zipped through War and Peace in 20 minutes and concluded, “It’s about Russia.” I’m not saying that AI summaries are that vague. In fact, the reason they’re dangerous is that they’re good enough. They allow you to fake it, to proceed with some understanding of the subject. Just not a deep one.
As an example, let’s take AI-generated summaries of voice recordings, like what Otter does. As a journalist, I know that you lose something when you don’t do your own transcriptions. It’s incredibly time-consuming. But in the process you really know what your subject is saying, and not saying. You almost always find something you missed. A very close reading of a transcript might allow you to recover some of that. Having everything summarized, though, tempts you to look at only the passages of immediate interest—at the expense of unearthing treasures buried in the text.
Successful leaders have known all along the danger of such shortcuts. That’s why Jeff Bezos, when he was CEO of Amazon, banned PowerPoint from his meetings. He famously demanded that his underlings produce a meticulous memo that came to be known as a “6-pager.” Writing the 6-pager forced managers to think hard about what they were proposing, with every word critical to executing, or dooming, their pitch. The first part of a Bezos meeting is conducted in silence as everyone turns all 6 pages of the document. No summarizing allowed!
To be fair, I can entertain a counterargument to my discomfort with summaries. With no effort whatsoever, an LLM does read every page. So if you want to go beyond the summary, and you give it the proper prompts, an LLM can quickly locate the most obscure facts. Maybe one day these models will be sufficiently skilled to actually identify and surface those gems, customized to what you’re looking for. If that happens, though, we’d be even more reliant on them, and our own abilities might atrophy.
Long-term, summary mania might lead to an erosion of writing itself. If you know that no one will be reading the actual text of your emails, your documents, or your reports, why bother to take the time to dig up details that make compelling reading, or craft the prose to show your wit? You may as well outsource your writing to AI, which doesn’t mind at all if you ask it to churn out 100-page reports. No one will complain, because they’ll be using their own AI to condense the report to a bunch of bullet points. If all that happens, the collective work product of a civilization will have the quality of a third-generation Xerox.
As for Robert Caro, he’s years past his deadline on the fifth volume of his epic LBJ saga. If LLMs had been around when he began telling the president’s story almost 50 years ago—and he had actually used them and not turned so many pages—the whole cycle probably would have been long completed. But not nearly as great.
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Psychosis is not a mark of intellect.
Psychopathic people mistake the ability to manipulate other people and exploit their emotions to be a mark of intelligence. They have a belief in their own superiority and flatter themselves with the idea that because they can break the rules of how feelings work, trick people into thinking they're emotionally neuro typical only to deceive them for their own ends, it makes them a smarter, more mature person.
That's not how intelligence works. People like this aren't smarter, they're broken. Just as the ability to lie and disrupt communications doesn't make you more intelligent, it makes you a violent predator. Just using a different means to exploit, trap and deprive your prey. And when it's your own family or species, that's just virtually cannibalism.
Exploiting somebody's trust is not a mark of intelligence, it's a mark of someone that does not have those inhibitions natural in a functioning brain. The willingness to suspend them for selfish reasons is not something to praise. And that's kind of why you have all these disgusting assholes calling themselves empaths or "dark empaths." You aren't some gifted genius, you're a monster. And because of people like yours predations, others have to learn to reign in their emotions in disbelief you could act like this, just to deal with you.
It's easy as pie to deceive and manipulate people that trust you or think you also share those healthy social and emotional inhibitions. The same ones that go off like error messages in your brain if you kill someone. Those same ones that make you sleepless if you unknowingly engage in cannibalism- even if it's necessary to survive. You can rationalize it all you want, but objectively speaking, we're animals. We're hard wired for certain things, and to not do certain things. People not missing these essential things have to cultivate violating them in order to condition themselves to continue doing them. It's not a mark of supremacy or cleverness to exploit another person by deception or manipulation. It comes natural to people that are broken and willing to engage in that sort of behavior.
Often I've come across people that thought they were superior for their willingness to exploit someone else. That being able to extract something from another and get away with it was proof of their supremacy, or at least, that of another's inferiority. If you confront them and tell them you know they're being dishonest and deceptive, their brains interpret that as, "Hey! You took advantage of how I'm too dumb to comprehend what you did!" And take it as a compliment. The inexperienced person confronting the deceiver expects the person receiving this to come clean or acknowledge they did wrong and panic because they've been caught. But that's not how a person built like this reacts, unless it's also another form of manipulation.
I'm lucky enough that as a child I had a firsthand experience with a peer like this that was a rowdy little boy. Because it meant, not only did I get the hard, cold life lessons of what dealing with a manipulative psychopath meant pushed on me, and the time to parse it out, it also meant I got to beat his fucking ass for being a manipulative and violent shit. So badly, he screamed hysterically for his mother. And then I never saw his disgusting, psychotic self again.
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New Android Malware SoumniBot Employs Innovative Obfuscation Tactics
Banking Trojan Targets Korean Users by Manipulating Android Manifest
A sophisticated new Android malware, dubbed SoumniBot, is making waves for its ingenious obfuscation techniques that exploit vulnerabilities in how Android apps interpret the crucial Android manifest file. Unlike typical malware droppers, SoumniBot's stealthy approach allows it to camouflage its malicious intent and evade detection. Exploiting Android Manifest Weaknesses According to researchers at Kaspersky, SoumniBot's evasion strategy revolves around manipulating the Android manifest, a core component within every Android application package. The malware developers have identified and exploited vulnerabilities in the manifest extraction and parsing procedure, enabling them to obscure the true nature of the malware. SoumniBot employs several techniques to obfuscate its presence and thwart analysis, including: - Invalid Compression Method Value: By manipulating the compression method value within the AndroidManifest.xml entry, SoumniBot tricks the parser into recognizing data as uncompressed, allowing the malware to evade detection during installation. - Invalid Manifest Size: SoumniBot manipulates the size declaration of the AndroidManifest.xml entry, causing overlay within the unpacked manifest. This tactic enables the malware to bypass strict parsers without triggering errors. - Long Namespace Names: Utilizing excessively long namespace strings within the manifest, SoumniBot renders the file unreadable for both humans and programs. The Android OS parser disregards these lengthy namespaces, facilitating the malware's stealthy operation.
Example of SoumniBot Long Namespace Names (Credits: Kaspersky) SoumniBot's Malicious Functionality Upon execution, SoumniBot requests configuration parameters from a hardcoded server, enabling it to function effectively. The malware then initiates a malicious service, conceals its icon to prevent removal, and begins uploading sensitive data from the victim's device to a designated server. Researchers have also highlighted SoumniBot's capability to search for and exfiltrate digital certificates used by Korean banks for online banking services. This feature allows threat actors to exploit banking credentials and conduct fraudulent transactions. Targeting Korean Banking Credentials SoumniBot locates relevant files containing digital certificates issued by Korean banks to their clients for authentication and authorization purposes. It copies the directory containing these digital certificates into a ZIP archive, which is then transmitted to the attacker-controlled server. Furthermore, SoumniBot subscribes to messages from a message queuing telemetry transport server (MQTT), an essential command-and-control infrastructure component. MQTT facilitates lightweight, efficient messaging between devices, helping the malware seamlessly receive commands from remote attackers. Some of SoumniBot's malicious commands include: - Sending information about the infected device, including phone number, carrier, and Trojan version - Transmitting the victim's SMS messages, contacts, accounts, photos, videos, and online banking digital certificates - Deleting contacts on the victim's device - Sending a list of installed apps - Adding new contacts on the device - Getting ringtone volume levels With its innovative obfuscation tactics and capability to target Korean banking credentials, SoumniBot poses a significant threat to South Korean Android users. Read the full article
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Minecraft Crew
(Background/side characters that I have essentially made into OCs)
Name: Teal Pronouns: She/they Occupation: Team Lead - The Minecraft Experience Age: Mid-30s A hard worker with a strong sense of duty. Has desperately searched for the cause of the glitch or error that happened that evening. She is not the one who invented the technology, but she's the most well-versed in its operation.
Name: Indigo Pronouns: He/they Occupation: Operator - The Minecraft Experience Age: Early 30s A sensitive fellow, he is very loyal to Teal, they have been friends since college. If it weren't for Teal he probably would have walked away from the business altogether after what happened that evening, but has instead joined Teal in her investigation. He's better at parsing code than Teal is.
Name: Fern Pronouns: They/them Occupation: Intern - The Minecraft Experience Age: Early 20's They really wish they had actually read the waiver they were having people sign. This was supposed to be a simple job! Has felt disillusioned with the industry but doesn't know how to escape it - it's what their education is in.
Name: Sky Pronouns: They/them Occupation: Operator - The Minecraft Experience Age: Mid-20's Another operator who works the booths sometimes. Sneaks into the game to steal game objects to sell on the black market. Not particularly concerned about the incident at Booth 30. Cocky, but their confidence isn't completely unwarranted. Friends with Purple.
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So something terrible happens which makes future Crowley go back to try to fix it and there's just 2 Crowleys running around in the present? Oh, and thanks for explaining!
Regarding not taking yourself seriously: I may not be entirely convinced by this particular theory - or any, yet - but I don't think time travel is completely out there or impossible either. Considering the way Adam resets things after the failed Apocalypse, the timeline clearly can be messed with, as can time itself, as Crowley repeatedly demonstrates. I saw the post you reblogged about the rugs and we are rapidly moving out of the territory of plausible deniability regarding the sheer number of bizarre continuity errors. Any one or two of them on their own, yes, but collectively?
If you do go looking back through the minisodes, Crowley's hair seems to go shorter-longer-shorter in Job and his sideburns look like they get quite a bit shorter in the crypt in the Resurrectionists. I didn't see anything in the Nazis minisode, but that doesn't meant nothing's there.
further ask:
hi anon!!!✨ first of all, im so sorry for not getting round to your asks until now!!!
re: first ask - mhm that's the half-baked idea, anyhow!!! and tbh 💀 im not completely convinced either but i like to entertain the possibility just out of Fun, so here we are!!!✨ oh god The Rugs - so the red one, that appears during the ball? okay sure i can accept that it is part of the Austen Aesthetic, and once the magic lifts it shifts back to the normal s2.
as for the s1 one... im torn. because i saw the amazing post where they hand-painted the mf sink tiles bc they would be in the background of a couple of shots, and wanted to at least be as close to the s1 ones as possible (GO crew honestly do the Mostest). and yeah okay, re: the difference between the s1 and s2 rugs, maybe it's that they thought 'well it's going to be on the floor most of the time and therefore out of shot' but. there are two shots that literally focus on it. as the focal point. so to my mind, they either literally couldn't find a like for like replacement (completely valid), or something Fishy is going on.
ive seen a couple of people remark on the flashbacks potentially being skewed because they're from aziraphale's perspective, but ive genuinely had the half-baked idea that the whole season is. there's so many in-story indicators, to my mind - biased red/yellow colour grading, the cartoony loch ness animation in ep3, and tbh the whole ball thing - and i do wonder if this whole rug sitch (as well as other Unexplained Things) might be chalked up to this very thing; that we are seeing s2 for the mostly part literally through aziraphale's eyes, and that what we see is a little... altered. magicked. as i said, half-baked idea, but there we are.
i did end up going through ACtO, and it's currently sat in my drafts at the moment because... well, idk what to make of it. the scenes where - by my estimation - he has the longer, more defined-curl wig, is every shot in job's house (three scenes, iirc), and so it might actually, if you consider that these scenes were likely filmed in alternative days to the other ACtO scene, a plain continuity/wig-availability issue. plus, when looking at the dialogue, all the scenes in some way link together (so i don't, essentially, think it can feasibly be the same time-travel theory). the only thing, i guess, that still remains valid is that we are seeing a recount of the events of ACtO as per aziraphale's retelling... but even then, there are plenty of scenes where they are very heavy in the crowley perspective (ie it doesn't feel like aziraphale is fudging anything), so this doesn't 100% feel like a true explanation either imo.
i do still need to look at the resurrectionists minisode though, so may well be able to parse some crackpot musing once ive done that!!!✨
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I would also like to add regarding these tags: the sentiments about creative failure being indelible and cancelling out all your good work are not true and accurate to all or even most environments. There are a couple environments where they may feel true or where some bad actors may behave in a way where they become as good as true:
- in abusive relationships, including caregiver relationships you might experience early in life, you may have received the kinds of criticism that teach you never to try because failure cancels out success
- on the internet in extremely high visibility contexts - viral posts or for celebrities - some people will take it upon themselves to mock or cancel people just for making understandable errors, particularly where those errors can be parsed as a failure to care enough about the needs of everyone else on the damn planet everywhere, OR where those errors may involve having some trait that is mockable according to conventional societal standards of various flavours (eg “oh look this person screwed up while being non-normative in their social performance or gender or looks, we are shitty bullies so we’re gonna mock them”)
The vast majority of functional human beings do not agree that “if you draw a line wrong you’re a fraud and an impostor” or “you are your mistakes” or “everyone hates you forever”. These are beliefs that arise from a distorted world view, potentially arising from negative prior experiences but sometimes just arising from your brain fucking with you by way of anxiety disorder.
Running events in a way where there’s an error is a matter of scale. If you mess up something about the physical safety of an event and people are injured that may be a big deal, but if you undercater, or forget to invite someone, or your accessibility could use improvement, these are not indelible failures, they’re errors where we can learn iteratively.
If you give advice and you give incorrect advice, the scale of the error matters a lot, but often your prior training can help you heaps. If giving advice as a hobby or calling stresses you out enormously because of the potential risk to others, it’s ok to not prioritise that option. But there are low stakes areas where an error is just not a big deal, or where the advice you’re giving is a matter of taste.
In terms of combatting the belief that any failure is essentially terminal, cognitive strategies - the kind you might find in therapies like CBT or ACT - can be really helpful. Another thing that can help is low stakes practice - trying out failure in a controlled safe environment in small doses with people you trust, to give your brain and nervous system the experience of feeling, over and over again, that failure can be ok.
I think people get mixed up a lot about what is fun and what is rewarding. These are two very different kinds of pleasure. You need to be able to tell them apart because if you don't have a balanced diet of both then it will fuck you up, and I mean that in a "known cause of persistent clinical depression" kind of way.
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Integrating Address Lookup API: Step-by-Step Guide for Beginners
Address Lookup APIs offer businesses a powerful tool to verify and retrieve address data in real-time, reducing the risk of errors and improving the user experience. These APIs are particularly valuable in e-commerce, logistics, and customer service applications where accurate address information is essential. Here’s a step-by-step guide to help beginners integrate an Address Lookup API seamlessly into their systems.
1. Understanding Address Lookup API Functionality
Before integrating, it’s crucial to understand what an Address Lookup API does. This API connects with external databases to fetch validated and standardized addresses based on partial or full input. It uses auto-completion features, suggesting addresses as users type, and provides accurate, location-specific results.
2. Choose the Right API Provider
Several providers offer address lookup services, each with unique features, pricing, and regional coverage. When selecting an API, consider factors like reliability, data accuracy, response speed, ease of integration, and support for international addresses if needed. Some popular options include Google Maps API, SmartyStreets, and Loqate.
3. Obtain API Credentials
Once you've chosen a provider, sign up on their platform to get your API credentials, usually consisting of an API key or token. These credentials are necessary for authorization and tracking API usage.
4. Set Up the Development Environment
To start integrating the API, set up your development environment with the necessary programming language and libraries that support HTTP requests, as APIs typically communicate over HTTP/HTTPS.
5. Make a Basic API Request
Construct a basic API request to understand the structure and response. Most address lookup APIs accept GET requests, with parameters that include the API key, address input, and preferred settings. By running a basic test, you can see how the API responds and displays potential address matches.
6. Parse the API Response
When the API returns address suggestions, parse the response to format it into user-friendly options. Typically, responses are in JSON or XML formats. Extract the needed data fields, such as street name, postal code, city, and state, to create a clean, organized list of suggestions.
7. Implement Error Handling and Validation
Errors can occur if the API service is unavailable, if the user enters incorrect information, or if there are connectivity issues. Implement error-handling code to notify users of any problems. Also, validate address entries to ensure they meet any specific format or regional requirements.
8. Test and Optimize Integration
Once you’ve integrated the API, test it thoroughly to ensure it works seamlessly across different devices and platforms. Pay attention to response times, as this affects user experience. Some API providers offer caching options or allow for request optimization to improve speed.
9. Monitor API Usage and Costs
Most address lookup APIs charge based on the number of requests, so monitor your usage to avoid unexpected charges. Optimize your API calls by limiting requests per session or using caching to reduce redundant queries.
10. Keep Up with API Updates
API providers often update their services, offering new features or making changes to endpoints. Regularly check for updates to keep your integration running smoothly and utilize any new functionalities that enhance the user experience.
By following these steps, businesses can integrate Address Lookup APIs effectively, providing a smoother, more reliable user experience and ensuring accurate address data collection.
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Revolutionizing Recruitment with AI Resume Parser: Digital Resume Parser (DRP)
Efficiently identifying the correct candidate is essential in the cutthroat world of recruitment. It can take a lot of time and be prone to human mistake to go through many resumes using traditional methods. Here comes the AI Resume Parser, a hiring process game-changer. In this field, the Digital Resume Parser (DRP) is a notable solution. An AI Resume Parser: What Is It? An AI resume parser is a program that automatically extracts and analyzes data from resumes using artificial intelligence. Important factors like contact details, employment history, qualifications, education, and more can be swiftly identified by it. The hiring process is streamlined by this technology, which also makes it faster and more precise.
The Digital Resume Parser's (DRP) Salient Features
Precise Extraction of Data: DRP reduces the possibility of errors by precisely extracting pertinent information from resumes using sophisticated AI algorithms.
Efficiency and Speed: Quickly reviews hundreds of resumes in a matter of minutes, greatly expediting the hiring process.
Parsing that is customizable: Enables you to concentrate on particular fields or keywords that are pertinent to the job specifications.
Integration Capabilities: Provides a seamless workflow by integrating with current HR software and applicant tracking systems (ATS).
Multilingual Support: Suitable for international hiring, this feature can parse resumes in a variety of languages.
Benefits of DRP usage
Time-saving: Frees up recruiters to concentrate on more critical tasks by automating the tiresome process of manual resume screening.
Enhanced Accuracy: Minimizes human mistake and guarantees that no important information is missed.
Improved Candidate Experience: Quicker processing times result in applicants receiving answers, enhancing their encounter in general.
Data-Driven Decisions: Offers in-depth analysis and insights to assist recruiters in making well-informed choices.
Scalability: Suitable for businesses of all sizes, it can effortlessly handle high resume volumes.
How DRP Transforms Recruitment
Using artificial intelligence (AI) to manage the preliminary steps of candidate screening, Digital Resume Parser (DRP) revolutionizes the recruitment process. This guarantees that the most qualified applicants are found promptly and precisely while also saving time. You can increase hiring quality overall, cut expenses, and increase efficiency by incorporating DRP into your recruitment strategy.
Your hiring procedure can be completely transformed by integrating an AI resume parser, such as Digital Resume Parser (DRP), into the applicant screening process. DRP is an advanced feature set with several advantages.
For contemporary recruiters trying to stay ahead in the cutthroat employment market, DRP is a vital tool. Are you prepared to simplify the hiring process? Find out how Digital Resume Parser (DRP) will assist you in more quickly and effectively locating the ideal candidates!
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Improve Delivery Accuracy with Google Address Validation API Integration
In today's fast-paced digital world, ensuring accurate delivery is critical for both businesses and consumers. Address validation, which is the process of verifying and standardizing postal addresses, plays a vital role in ensuring that mail and packages reach their intended recipients without delays or errors. One powerful tool that businesses can leverage to enhance delivery accuracy is the Google Address Validation API. Integrating this API not only improves the quality of address data but also streamlines operations, reduces return rates, and increases customer satisfaction.
What is Google Address Validation API?
The Google Address Validation API is a service that allows businesses to validate and standardize addresses in real-time using Google’s comprehensive address database. This API is designed to correct and complete address information, making sure that the address provided is formatted correctly, contains all necessary elements (street, city, zip code), and matches an existing location.
Benefits of Integrating Google Address Validation API
Enhanced Delivery Accuracy: By validating addresses before a delivery is initiated, businesses can ensure that the package is sent to a correct and standardized address, minimizing the risk of failed deliveries.
Reduced Operational Costs: Failed deliveries due to incorrect or incomplete addresses can result in extra costs, including redelivery attempts, customer service intervention, and product returns. The Google Address Validation API helps to reduce these costs by minimizing delivery errors.
Improved Customer Satisfaction: Timely and accurate deliveries are essential for customer satisfaction. Validating addresses ensures that customers receive their packages on time, leading to fewer complaints and enhanced loyalty.
Real-Time Address Verification: The API allows businesses to validate addresses at the point of entry in real-time, whether it's during checkout on an e-commerce website or when inputting data into a CRM. This reduces the chance of typos, incomplete data, and invalid addresses.
Global Reach: Google’s address database covers a wide range of countries and regions, allowing businesses to validate international addresses with ease, making it an ideal solution for companies with a global customer base.
Customizable for Your Needs: The API can be customized to suit different business needs. Whether it’s address cleansing, autocomplete features, or batch validation, businesses can tailor the API to their specific operational processes.
How Google Address Validation API Works
Google’s Address Validation API leverages the Places API to provide real-time suggestions and validation as users input their address information. The process involves:
Input Parsing: As the user enters an address, the API breaks down the input into recognizable elements such as street name, number, postal code, city, and country.
Standardization: The API compares the input against Google's address database, correcting misspellings, adding missing elements, and ensuring the address adheres to the standardized format recognized by postal services.
Validation: After standardization, the API checks if the address exists in Google’s database. If it matches a known location, the address is validated.
Geocoding: For further accuracy, the API can also provide the geocoded location of the address in terms of latitude and longitude, which can be useful for delivery routing and planning.
Steps to Integrate Google Address Validation API
Obtain the API Key: To start using the Google Address Validation API, you will need to obtain an API key from the Google Cloud Platform.
Enable the API: Once you have the key, you can enable the Address Validation API from the Google Cloud console and configure it based on your requirements.
Customize for Use Cases: Depending on your business, you may want to add additional features such as address autocomplete or batch processing. These features can be integrated alongside the core validation process.
Integration into Platforms: The API can be integrated into your website or application, allowing real-time address validation during checkout, CRM data entry, or shipment processing.
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Understanding Applicant Tracking Systems (ATS): A Comprehensive Guide
Applicant Tracking Systems (ATS) are essential tools for modern recruitment, enabling companies to manage large volumes of applications efficiently. These systems help recruiters sort, rank, and manage candidates through an automated process, reducing the burden of manual recruitment tasks.
How ATS Works
An ATS serves as a central repository where all job applications are stored and managed. When candidates apply for a job, the ATS automatically parses their resumes and converts the content into a structured format. This allows recruiters to quickly filter candidates based on keywords, qualifications, or specific criteria relevant to the role.
ATS tools often integrate with online job portals, making it easier to post openings and manage applicants in one place. By automating the resume screening process, ATS drastically reduces the time spent on manual shortlisting, allowing recruiters to focus on more strategic tasks like interviews and final assessments.
Benefits of Using an ATS
Improved Efficiency: ATS streamlines the hiring process by automating the initial stages, saving time on reviewing large volumes of resumes.
Enhanced Candidate Experience: ATS tools can send automated updates to candidates about their application status, providing transparency and improving their overall experience.
Bias Reduction: With automated resume parsing, ATS helps minimize unconscious biases by evaluating candidates based on predefined qualifications and criteria.
Analytics and Reporting: Many ATS systems offer data-driven insights, allowing recruiters to analyze trends, improve hiring strategies, and track key performance indicators like time-to-hire.
Common Challenges and How ATS Addresses Them
Recruiters often face challenges like missing out on top talent due to manual errors or spending too much time on unqualified candidates. ATS systems resolve these issues by automatically ranking applicants based on predefined parameters such as skills, qualifications, and experience. This ensures that only the most qualified candidates move forward in the hiring process.
Additionally, ATS helps eliminate redundant tasks like posting jobs to multiple platforms or manually tracking each applicant’s progress, streamlining the overall workflow.
For More Information : https://www.techdogs.com/td-articles/curtain-raisers/applicant-tracking-systems-ats-explained
The Future of ATS
As recruitment technology evolves, ATS systems are becoming smarter and more versatile. With the integration of artificial intelligence (AI) and machine learning, future ATS tools will likely offer advanced candidate matching, predictive analytics, and even improved diversity hiring features. These advancements will continue to shape the future of hiring, making recruitment faster, fairer, and more effective.
In conclusion, ATS plays a pivotal role in modern recruitment, offering efficiency, transparency, and fairness to both recruiters and candidates. By automating various stages of the hiring process, ATS ensures that companies can identify and hire the best talent faster and more effectively.
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Resume Parser – A next step for upcoming recruitment Industry/Revolutionizing Recruitment in coming years
Introduction
Imagine a resume parser as the ultimate digital librarian in the world of recruitment. Just like a skilled librarian effortlessly categorizes books by titles, authors, and genres, a resume parser dives into the vast sea of resumes, automatically extracting and organizing key details such as names, job titles, skills, and educational backgrounds and many more.
Backed by advanced technologies like natural language processing (NLP) and machine learning (ML), Furthermore, Using smart machines like ChatGPT, Anthropic, Gemini etc. this tool transforms unstructured resume content into a neatly structured format. It's like turning a chaotic pile of books into a perfectly organized library, where finding the right information becomes a snap job.
In the busy world of hiring, a resume parser is a helpful tool that saves time. It quickly goes through many resumes, picking out the most suitable candidates and showing them to recruiters in an easy-to-understand way. By handling the initial screening automatically, it allows recruiters to spend more time on important hiring decisions.
How resume parser works
A resume parser works by automatically scanning, reading and analyzing resumes to extract desired information and organize it into a pre-defined format
It basically reads resumes, picking & pulling up essential information and placing them in a structured format desired by recruiter. It also eliminates unnecessary and redundant information from CV so you don’t have to waste time reading and analyzing same contents.
Basically it goes like:
Reading Resume/CV > Processing on Content > Data Extraction > Data Picking > Structuring Content in format > Keyword Matching > Final Result.
Benefits of adapting resume parser in your recruitment Process
There are numerous benefits of getting resume parser on board in your recruitment process. Lets take a look in some of the major gains.
Time Efficiency
Fast process of reading, scanning, and putting in a structured manner in blink of an eye. You can even apply a batch process with resume parser. Just give it tons of resumes, press the button and grab a coffee
Accuracy
By eliminating upto 95% Human interaction, resume parsers provide consistent and objective evaluation of resumes, minimizing human errors and biases.
Scalability
Resume parsers shine with their scalability, effortlessly managing hundreds of resumes. This makes them perfect for both massive hiring campaigns and ongoing recruitment. They also handle resumes from different sources and formats, making them a great fit for global hiring needs
Enhanced Candidate Experience
Resume parsers accelerate the initial screening process, leading to quicker communication with candidates and a smoother overall experience. By automating the parsing, they ensure that every candidate is assessed based on consistent criteria, which enhances fairness throughout the selection process
Economical Cost
Any kind of automation always result in a great cost saving. And so does the resume parser. Right from the beginning it eliminates the human efforts and lots of layers of human intervention are skipped and hence results into a considerable cost saving. Along with that, Faster screening and selection reduce the overall time-to-hire, saving costs associated with prolonged vacancies.
Elevated decision-making
Resume parsers organize data in a structured format, allowing recruiters to make more informed decisions based on clear, quantifiable information like skills, experience, educational background etc. With the ability to generate detailed reports and analytics, recruiters can evaluate the success of their recruitment strategies and make data-driven adjustments
Resume parsing also offers other benefits, such as integrating with your current platform, using custom parsers to find specific data, and converting resumes in various formats into a consistent format that suits your needs.
Resume parser VS Traditional extraction methods
Here we can easily check the differences and Pro/Cons of using resume parser against traditional extraction methods of resumes.
Title
Resume Parser
Traditional Method
Efficiency
Speed and
Fast processing of multiple resumes Automated data Scanning and organization
Time-consuming, manual processing Manual data entry and extraction
Accuracy and Consistency
Consistent and objective evaluation Precise data extraction with pre-defined algorithms
Inconsistent results due to varying interpretations Chances of error gets high in traditional data entry
Scalability
Handles large volumes efficiently Easily adaptable to different recruitment needs
Struggles with high volumes, requires more resources Constrained growth potential and requires High-maintenance
Integration and Data Management
Seamless integration with ATS and HR software Centralized and structured data storage
Isolated systems and uneven data organization Manual recording and disorganized data
Candidate Experience
Faster response times and improved experience Objective and fair screening
Faster response times and improved experience Objective and fair screening
Candidate Experience
Faster response times and improved experience Objective and fair screening
Slower feedback and potential candidate frustration Subjective evaluation and inconsistent treatment
Cost Implications
Cost-effective with reduced manual labor Result and evolution is faster and hence reducing vacancy costs
Higher costs due to manual labor Extended hiring timelines and increased costs
Data Insights and Reporting
Enhanced analytics and detailed reports Data-driven & Transparent decision-making
Limited reporting and less comprehensive data Subjective decision-making
In modern recruitment, companies face an overwhelming number of resumes for each job posting. Traditional methods of manually sifting through resumes are not only time-consuming but also prone to human error. Resume parsers is becoming essential tools, transforming the recruitment process by making it faster and more accurate.
Another crucial add on is that human recruiters, consciously or unconsciously, may have biases that affect their judgment. Resume parsers eliminate this issue by focusing solely on the qualifications and experience of the candidates, promoting a more objective and fair hiring process.
Added to that, the need for resume parsers in modern times is driven by the demands of speed, accuracy, and fairness in the recruitment process. They empower companies to manage their talent acquisition more effectively, ensuring that the best candidates are identified and onboarded swiftly without unnecessary waiting of getting sorted complex process.
Challenges & limitations of resume parser
While resume parsers offer significant benefits in the recruitment process, they also come with their own set of challenges and limitations that companies must consider and should continuously improve their parser algorithm. Parsing Errors and Incomplete Data Extraction: Despite advances in AI and machine learning, resume parsers can still struggle with accurately interpreting complex or non-standard resume formats. They may misinterpret or miss crucial information, particularly when resumes include unconventional layouts, graphics, non-standard fonts, or use tables, text boxes, or images to present data. This can result in incomplete or skewed views of a candidate’s qualifications.
Bias Side - While resume parsers aim to reduce human bias, they can introduce their own biases based on the data they are trained on, potentially favoring certain candidates and perpetuating existing biases. Additionally, these parsers may struggle with resumes from candidates who speak different languages or come from diverse cultural backgrounds, further disadvantaging those applicants.
Limited Subject Understanding - Resume parsers often rely heavily on keyword matching, which can lead to candidates being ranked higher simply for using exact keywords, even if they are less qualified, while those using synonyms might be overlooked. Additionally, these parsers may struggle with understanding the context behind information, such as differentiating job titles or recognizing relevant experience from a different industry.
Incorporating a resume parser into an existing recruitment platform can be technically challenging, requiring careful planning to ensure seamless integration with Applicant Tracking Systems (ATS) and other HR tools. Along with that, resume parsers need regular updates to stay current with new resume trends, formats, and terminologies, demanding ongoing maintenance and resources to remain effective.
Data Privacy - Resume parsers process a large amount of personal data, which raises concerns about data privacy and security. Companies must ensure that the parser complies with data protection regulations like GDPR and that candidates’ information is handled securely.
Costing - Developing or purchasing a high-quality resume parser can be costly, particularly for small to medium-sized businesses, with expenses including initial setup and ongoing maintenance. Furthermore, there is a risk of companies becoming overly reliant on resume parsers, which might lead to overlooking candidates who could be a great fit but don’t meet the parser’s criteria
Conclusion
As companies continue to embrace technology to stay ahead, resume parsers are becoming an essential part of a forward-thinking recruitment strategy. They're not just a convenience, but a game-changer that empowers businesses to attract and secure top talent with unparalleled speed and accuracy. In a world where competition for the best candidates is fierce, resume parsers are setting the stage for the future of hiring, turning an old, and most of the time - cumbersome process into a seamless experience that benefits both employers and job seekers alike.
Beyond just saving time, these tools also reduce the chances of human error, ensuring that no great candidate slips through the cracks. As recruitment continues to evolve, resume parsers are not just a technical upgrade – they’re transforming how we approach, talent discovery, making the process smarter, faster, and more human-centered.
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Leveraging TrackHR and Technological Advancements for Business Growth
In today’s fast-paced business environment, effective work management is crucial for the success and growth of any organization. Business owners are constantly seeking innovative solutions to streamline their operations, enhance productivity, and achieve sustainable growth. The advent of technology has brought about significant advancements in work management software, and one such solution that stands out is TrackHR. This cutting-edge technology is revolutionizing the way businesses handle human resources and work management, providing numerous benefits for business owners aiming for expansion and success.
* Centralized Data Management:
TrackHR technology enables business owners to centralize their data management, consolidating essential information such as employee records, attendance, performance metrics, and more into a single platform. This centralized approach not only saves time but also reduces the likelihood of errors associated with manual data entry. Business owners can access real-time, accurate information, facilitating better decision-making and strategic planning.
* Enhanced Employee Productivity:
One of the key factors contributing to business growth is the productivity of its workforce. TrackHR incorporates features like task assignment, progress tracking, and performance analytics, fostering a collaborative and efficient work environment. Automation of routine tasks allows employees to focus on high-value activities, ultimately increasing overall productivity. As a result, business owners witness improved output, reduced operational costs, and a positive impact on their bottom line.
* Streamlined Recruitment Process:
Recruitment is a critical aspect of business growth, and TrackHR technology simplifies and streamlines the hiring process. Automated applicant tracking systems, resume parsing, and candidate profiling help identify the most suitable candidates quickly and efficiently. This not only saves time for HR professionals but also ensures that the organization attracts top talent, contributing to the long-term success and growth of the business.
* Employee Engagement and Satisfaction:
Work management software like TrackHR facilitates effective communication between management and employees. Features such as performance feedback, goal setting, and employee recognition contribute to enhanced engagement and job satisfaction. Satisfied employees are more likely to be committed to their work, resulting in reduced turnover rates and a positive impact on the company’s reputation, which is vital for sustained growth.
* Scalability and Flexibility:
Business owners aiming for growth need a work management solution that can scale with their evolving needs. TrackHR offers scalability and flexibility, allowing businesses to adapt to changes seamlessly. Whether the organization is expanding its workforce, opening new branches, or entering new markets, the software can be customized to accommodate the evolving requirements of the business.
Conclusion:
In the dynamic landscape of modern business, adopting advanced work management software like TrackHR is a strategic move for business owners looking to achieve sustainable growth. The technology’s ability to centralize data, enhance productivity, streamline recruitment, boost employee engagement, and provide scalability positions it as a valuable asset for any organization. By harnessing the power of TrackHR, business owners can navigate the complexities of workforce management with efficiency and focus, setting the stage for long-term success and prosperity.
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While all three are tools used in Python programming, they serve distinct purposes and are not typically used together in a single data collection pipeline.
Understanding the Tools
* Selenium: This library primarily interacts with web browsers. It's ideal for handling dynamic content, JavaScript-heavy websites, and complex user interactions like filling forms, clicking buttons, and scrolling.
* Requests: A simpler library for making HTTP requests. It's efficient for static content and doesn't interact with browsers.
* Scrapy: A powerful framework built on top of libraries like Requests (or others) for large-scale web scraping projects. It provides features like item pipelines, item loaders, and robust error handling.
Combining Selenium and Scrapy
While not directly combined, Selenium can complement Scrapy for specific scenarios:
* Dynamic Content: When a website heavily relies on JavaScript to render data, Selenium can be used to load the page and extract the fully rendered HTML. This HTML can then be fed into Scrapy for parsing and data extraction.
* Complex Interactions: If a website requires user-like interactions (e.g., logins, clicking through pages), Selenium can automate these steps before Scrapy takes over for data extraction.
Typical Workflow
A common approach involves:
* Using Selenium: Load the webpage, interact with elements, and obtain the fully rendered HTML.
* Converting to a String: Convert the HTML to a string format.
* Feeding to Scrapy: Create a Scrapy spider that processes the HTML string as a response.
Example Code Structure
import scrapy
from selenium import webdriver
from selenium.webdriver.common.by import By
class MySpider(scrapy.Spider):
name = 'my_spider'
start_urls = ['http://example.com']
def __init__(self):
self.driver = webdriver.Chrome()
def parse(self, response):
# Use Selenium to load the page if needed
self.driver.get(response.url)
# Perform Selenium actions if required
html = self.driver.page_source
# Create a scrapy response object
scrapy_response = scrapy.http.TextResponse(url=response.url, body=html, encoding='utf-8')
# Use Scrapy to extract data from the HTML
yield from self.parse_item(scrapy_response)
def parse_item(self, response):
# Your Scrapy parsing logic here
pass
def close(self, spider):
self.driver.quit()
Key Considerations
* Performance: Selenium can be slower than using Requests directly. Use it judiciously.
* Anti-Scraping Measures: Both Selenium and Scrapy can trigger anti-scraping mechanisms. Implement appropriate measures like delays, random user-agents, and proxies.
* Error Handling: Robust error handling is essential in both Selenium and Scrapy to ensure data quality and script reliability.
In conclusion, while Selenium and Scrapy can be combined for specific use cases, it's often more efficient to use Requests directly within Scrapy for static content. Selenium is best suited for handling dynamic content and complex user interactions.
Would you like to explore a specific use case or need more detailed code examples?
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Create ATS Friendly CV
With the job market being highly competitive, it is very important that you make your CV ATS-friendly to get shortlisted for an interview. Improved and highly adopted by employers, ATS is a way in which employers improve the efficiency of their hiring process. The difference in this is done by filtering through the résumé for particular keywords and formats before it can get to the human eye. In essence, optimizing your resume for ATS can improve the prospects of passing the initial screening.
Understanding the ATS Process
Most often, submission of one's resume online would go directly physically into an ATS database. The software then goes over the resume and pulls out keywords and different important details which would give a certain order to how perfect your qualifications are in line with the job description. So, a poorly formatted CV or one without the right keywords may never reach the recruiter.
Leveraging the Right Keywords
Identify and Integrate Keywords: Start by carefully reviewing the job description to pinpoint keywords and phrases that are frequently mentioned. These keywords often include specific job titles, required skills, and industry-related terms. Make sure to weave these keywords naturally into your CV, aligning them with your experience and qualifications.
Use Exact Match Keywords: It's essential to use keywords exactly as they appear in the job listing. For instance, if the employer is looking for "leadership experience," use that exact phrase in your CV. Also, include both full terms and their abbreviations, such as "Customer Relationship Management (CRM)."
Optimizing Your CV Format
Reverse Chronological Format: The reverse chronological format is the most ATS-friendly. This format, which lists your work experience starting with the most recent, is preferred because it clearly shows your career progression and is easy for ATS to parse.
Standard Headings: Stick to traditional section headings like "Work Experience," "Education," and "Skills." Avoid using creative or unconventional headings, as these can confuse the ATS and cause important information to be overlooked.
Adhering to ATS-Friendly Formatting
Keep It Simple: A simple, clean design is crucial. Avoid using tables, graphics, or special characters, as these can disrupt the ATS’s ability to read your CV.
Font and Size: Choose commonly used fonts like Arial, Calibri, or Times New Roman. Use a font size of 11-12 pt for regular text and 14-16 pt for section titles to ensure readability.
Bullet Points: Standard bullet points (e.g., circles or squares) should be used to list your responsibilities and achievements. This format is easily readable for both ATS and human recruiters.
Avoid Headers and Footers: Refrain from placing critical information in headers or footers, as many ATS might not scan these sections.
Tailoring Your CV for Each Job
It’s important to customize your CV for each job application. While this may require more time, it significantly increases your chances of passing the ATS screening. Make sure your skills and experiences align with the job requirements, and prominently feature relevant keywords.
Testing and Refining Your CV
Use CV Scanners: Tools like Avua IdealMatch can help you test your CV by comparing it against the job description and providing a match score. They also offer suggestions for improvements, such as adding more relevant keywords or adjusting formatting.
Proofreading: Always proofread your CV to eliminate any spelling or grammatical errors. Even small mistakes can hurt your chances of passing the ATS.
Additional Tips for an ATS-Friendly CV
File Format: Submit your CV in the format specified by the job listing, usually a Word document or PDF. While most modern ATS can read PDFs, some older systems may not.
Avoid Keyword Stuffing: Use keywords naturally within the context of your CV. Overloading your CV with keywords can make it difficult to read and may be flagged by recruiters.
Regular Updates: Keep your CV up-to-date with your most recent job experiences, skills, and accomplishments to ensure it remains relevant.
Optimizing your CV for ATS is all about strategic keyword placement and clean formatting. By tailoring your CV for each job and following these best practices, you’ll improve your chances of getting noticed by both the ATS and hiring managers. Utilize tools like Avua IdealMatch to refine your CV, and always proofread carefully to ensure it’s error-free. Following these guidelines can greatly enhance your success in the job application process.
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