The Firefight: King of the Hill experience is expanding today to include five new maps! Ranging in size, the new maps will spice up the encounters, bring variety to the playlist, and ultimately keep your foot firmly on that Warthog accelerator pedal.

Firefight: King of the Hill Refresh | Halo Infinte | Halo - Official Site (en)

Following his defeat by the Master Chief, the Didact’s physical form was burned away by the Composer, casting his consciousness into a vast desert. It is here that Kelly Gay’s latest novel, Halo: Epitaph, begins—and in this preview, we will see the beginning of his great journey…

The Didact Returns | Halo: Epitaph Preview | Halo - Official Site (en)

&quot;It&#x27;s just one rock rotated, scaled, and moved around&quot;

Halo 3 player discovers every single rock in one of the game's most memorable levels is the same rock: "I can't keep this knowledge to myself anymore"

Halo 3 player discovers every single rock in one of the game's most memorable levels is the same rock: "I can't keep this knowledge to myself anymore" | GamesRadar+

Halo Season 2 Episode 3 is titled &#x27;Visegrad&#x27;. The series airs on Paramount+ and continues the saga.

Halo Season 2 Episode 3 ending explained: Understanding the Visegrad climax

On Twitter, a former 343 Industries developer has revealed that dozens of &#x27;game ideas&#x27; were shot down that could have boosted the Halo universe.

Dozens of Halo Pitches Were Shot Down at 343, Former Dev Reveals - Insider Gaming

Helldivers 2, a PlayStation-only title, is generating steam and stream figures that surpass those of Starfield and Destiny 2, making it the new darling of the battle pass/games as a service market.

HELLDIVERS 2 Takes The Gaming Community By Storm As Steam Numbers Surpass DESTINY 2 And HALO INFINITE

Halo season 2 episode 4, titled Reach, is slated to premiere on February 22, 2024, on Paramount+.

Halo season 2 episode 4: Release date and time, where to watch, and more

Xbox players could have had their Helldivers experience earlier than PlayStation and PC players.

There was a Helldivers-inspired Halo ODST game pitched at one point - - Gamereactor

Ex-Halo Dev KEvin Schmidt has revealed that multiple game pitches were made at 343, some of which sound awfully similar…

Wish Xbox had Helldivers 2? Amid the hype, Ex-Halo dev teases pitched game ideas that didn't make the cut | VG247

Hal9

hal9

Table of Links Abstract and 1. Introduction Why ELIZA?
The Intelligence Engineers
Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs
From IPL to SLIP and Lisp
A Critical Tangent into Gomoku
Interpretation is the Core of Intelligence
The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion
Finally ELIZA: A Platform, Not a Chat Bot!
A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community
Another Wave: A BASIC ELIZA turns the PC Generation on to AI
Conclusion: A certain danger lurks there
Acknowledgements and References 11 Another Wave: A BASIC ELIZA turns the PC Generation on to AI Another defining event in ELIZA’s descendancy occurred almost exactly a decade later, in 1977 Creative Computing, one of the magazines that, along with BYTE, was the “Hacker News” and “GitHub” of the mid-70s personal computer explosion, published an ELIZA knock-off written in BASIC.[36] This was coincidentally well-timed as it coincided nearly exactly with the so-called “1977 trinity”: The year that the Commodore Pet, the Apple II, and the TRS-80 all appeared.[12] Within a few years, millions of computer hobbyists – neither academics nor otherwise professionally involved with computers – had personal computers of all sorts, mostly with BASIC as their primary user-level programming language. Not a small number of those hobbyists were interested enough by the possibility of AI – perhaps with HAL9000, the murderous computer from 2001[13], still in recent memory – to type in this BASIC ELIZA (which was only a couple pages of code), and experiment with it themselves. Because of its simplicity, and the personal computer explosion, this ELIZA begat hundreds of knock-offs through the decades, in every conceivable programming language, making it perhaps the most copied and knocked-off program in history.[16] Just as Cosell’s Lisp ELIZA was spread by the ARPANet, this BASIC ELIZA, was spread by the wide-spread availability of personal computers. As a result of these coincidences, and an inherent interest in AI (or at least in talking with computers) the version of ELIZA that was known in the academic community was Cosell’s Lisp version, and the version known to the public was the BASIC version. But until it was rediscovered in 2021, the original MADSLIP ELIZA, was forgotten, and had not been seen by anyone for at least 50 years.[16, 14] Author:
(1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). This paper is available on arxiv under CC BY 4.0 license. [16] Indeed, I curate a web site, ELIZAGen.org[14], dedicated to the history of ELIZA and ELIZA-like programs. In that capacity I am regularly sent new, or newly-discovered knockoffs of one or another of the ELIZA threads, usually my own BASIC ELIZA. Just last week, as I write this in April of 2024, I received an email pointing out a version of my ELIZA that ended up, through channels unknown, in Apple’s HyperCard programmable notecard system for the original Apple Macintosh computers.[15] Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Why ELIZA? The Intelligence Engineers Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs From IPL to SLIP and Lisp A Critical Tangent into Gomoku Interpretation is the Core of Intelligence The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion Finally ELIZA: A Platform, Not a Chat Bot! A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community Another Wave: A BASIC ELIZA turns the PC Generation on to AI Conclusion: A certain danger lurks there Acknowledgements and References Why ELIZA? Why ELIZA? The Intelligence Engineers The Intelligence Engineers Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs Newell, Shaw, and Simon’s IPL Logic Theorist: The First True AIs From IPL to SLIP and Lisp From IPL to SLIP and Lisp A Critical Tangent into Gomoku A Critical Tangent into Gomoku Interpretation is the Core of Intelligence Interpretation is the Core of Intelligence The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion The Threads Come Together: Interpretation, Language, Lists, Graphs, and Recursion Finally ELIZA: A Platform, Not a Chat Bot! Finally ELIZA: A Platform, Not a Chat Bot! A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community A Perfect Irony: A Lisp ELIZA Escapes and is Misinterpreted by the AI Community Another Wave: A BASIC ELIZA turns the PC Generation on to AI Another Wave: A BASIC ELIZA turns the PC Generation on to AI Conclusion: A certain danger lurks there Conclusion: A certain danger lurks there Acknowledgements and References Acknowledgements and References 11 Another Wave: A BASIC ELIZA turns the PC Generation on to AI Another defining event in ELIZA’s descendancy occurred almost exactly a decade later, in 1977 Creative Computing, one of the magazines that, along with BYTE, was the “Hacker News” and “GitHub” of the mid-70s personal computer explosion, published an ELIZA knock-off written in BASIC.[36] This was coincidentally well-timed as it coincided nearly exactly with the so-called “1977 trinity”: The year that the Commodore Pet, the Apple II, and the TRS-80 all appeared.[12] Within a few years, millions of computer hobbyists – neither academics nor otherwise professionally involved with computers – had personal computers of all sorts, mostly with BASIC as their primary user-level programming language. Not a small number of those hobbyists were interested enough by the possibility of AI – perhaps with HAL9000, the murderous computer from 2001[13], still in recent memory – to type in this BASIC ELIZA (which was only a couple pages of code), and experiment with it themselves. Because of its simplicity, and the personal computer explosion, this ELIZA begat hundreds of knock-offs through the decades, in every conceivable programming language, making it perhaps the most copied and knocked-off program in history.[16] Just as Cosell’s Lisp ELIZA was spread by the ARPANet, this BASIC ELIZA, was spread by the wide-spread availability of personal computers. As a result of these coincidences, and an inherent interest in AI (or at least in talking with computers) the version of ELIZA that was known in the academic community was Cosell’s Lisp version, and the version known to the public was the BASIC version. But until it was rediscovered in 2021, the original MADSLIP ELIZA, was forgotten, and had not been seen by anyone for at least 50 years.[16, 14] Author: (1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). Author: Author: (1) Jeff Shrager, Blue Dot Change and Stanford University Symbolic Systems Program (Adjunct)( jshrager@stanford.edu). This paper is available on arxiv under CC BY 4.0 license. This paper is available on arxiv under CC BY 4.0 license. available on arxiv available on arxiv [16] Indeed, I curate a web site, ELIZAGen.org[14], dedicated to the history of ELIZA and ELIZA-like programs. In that capacity I am regularly sent new, or newly-discovered knockoffs of one or another of the ELIZA threads, usually my own BASIC ELIZA. Just last week, as I write this in April of 2024, I received an email pointing out a version of my ELIZA that ended up, through channels unknown, in Apple’s HyperCard programmable notecard system for the original Apple Macintosh computers.[15]

Another Wave: A BASIC ELIZA Turns the PC Generation On to AI

- HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “ ” award, featuring the most promising and innovative companies in the Seattle startup ecosystem. Seattle, WA - May 23,2023 Startups of the Year The list, compiled by the HackerNoon team, showcases that are making significant contributions to the Seattle economy and driving innovation in their respective industries. 200+ startups https://www.youtube.com/watch?v=ZqIW54yMsNc&t=2s&embedable=true Nominations are open. You can nominate your company as the . startup of the year in Seattle here The for Startups of the Year 2023 include: nominated Startups in Seattle Xealth Diagrid Twelve Labs XetData Coda Derisk pyq Logixboard Otto Robotics Protect AI Augment AI Proxi XetData Bungee Tech InsightStudios Pipe17 Coffee Meets Bagel Symbl.ai DefenseStorm Ozette Karat Kevala Moment Veeve Observa Cakework Forum3 Hal9 MotherDuck Read SBL Spiral “We are thrilled to recognize the top startups in Seattle and celebrate their achievements,” said . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO is a community-driven voting platform that recognizes startups that are changing technology and the world for the better. Starting May 8th, 2023, the internet can nominate and vote for the best ventures in their city. The voting period will remain open until December 31, 2023, and winners will be announced in January 2024 after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 In its , a total of 44,427 startups were nominated in 16 different regions, and the community cast 234,344 votes during a 6-month long campaign in favor of budding companies that were growing and trending across every major city in the world. The received perks from sponsors and a free from HackerNoon. previous iteration 1,382 winners tech company news page As a proponent of the open data movement, HackerNoon releases the unique social data gathered from Startups of the Year on GitHub as “ ” for valuable insights. /where-startups-trend Apart from validation from the world's greenest tech publication, all nominees relevant to their domain, region, and funding. They will also receive an and a free version of their very own on HackerNoon. These pages include business overviews (such as head count, founding year, bio, social links, and domain ranking) coupled with dynamic updates every time the company is mentioned in HackerNoon stories or relevant headlines around the web. get free interviews amazing discount package designed for their startup Tech Company News Page People can , and vote once per day per award for who they think should be Startup of the Year all the way up to December 31st. until June 8th nominate their favorite startups In addition to the award itself, winners receive exclusive interviews, an exclusive NFT from HackerNoon, and a .Tech Domain for life. About HackerNoon HackerNoon is a technology publication that aims to empower developers, entrepreneurs, and tech enthusiasts to share their knowledge and expertise with a global audience. With a readership of over 4M+ monthly visitors, HackerNoon provides a platform for startups and innovators to showcase their work and connect with a vibrant community of like-minded individuals. Did you know that companies that actively engage in blogging experience a whopping 67% increase in leads? Take advantage of HackerNoon's ' ' to kickstart your own company's blogging journey. Startups Package Startups Of The Year 2023 is sponsored by . .Tech Domains For more information about the “Startups of the Year 2023” list and the nominated companies, please visit our . FAQ page Nominations are open. You can nominate your company as the . startup of the year in Seattle here

Startups of The Year 2023: 200+ Startups Nominated in Seattle

Hackers, Assemble! The final round’s results announcement of the by & HackerNoon are now live! Cybersecurity Writing Contest Twingate This contest is one of the most happening contests to date. The numbers speak for themselves: We published total of 364 stories during the contest (the acceptance rate at HackerNoon is almost 50%)! Total reads generated was > ONE MILLION (1,069,876 to be exact) Total reading time generated so far: 4 months, 25 days, & 16 hours The success of this contest is because of the whole HackerNoon community! Shoutout to our super-dope 35k+ contributors and millions of awesome readers! As usual, we picked all the stories tagged with the tag on HackerNoon, published in November 2022. Then we chose the top stories using 60:30:10 weightage respectively to: #cybersecurity Number of hours read The number of people reached The freshness of the content The Cybersecurity Writing Contest: Nominations and Winners: by Scanning 2.6 Million Domains for Exposed .Env Files @sdcat by Pros and Cons of Cybersecurity Automation @zacamos by Disinformation-as-a-Service: Content Marketing’s Evil Twin @verasmirnoff by Secure Coding Practices Every Developer Should Know @gloriabradford by Why You Should Avoid Using Public WiFi @juxtathinka by Your USB Gadget Could Be Weaponized @fatman by An Insecure Pillar in Cybersecurity @hal9000 by Cybersecurity Myth-Perceptions @shanni by Top Emerging Cybersecurity Threats and How to Prevent Them From Happening to You @induction by America's Strangest Unsolved TV-Hack and The Story Behind It @strateh76 Now let’s see who won 👀 FIRST place goes to https://hackernoon.com/your-usb-gadget-could-be-weaponized?embedable=true One only has to look at the top influencers on Instagram or TikTok to see how a group could be easily persuaded to buy the next cool gadget. An exploit that you can plug into your computer, like USB-based plasma balls, fans, Mini-fridge, coffee warmers, LEDs, or even a charging cable. Well deserved, . You have won $600! @fatman In SECOND place, we have https://hackernoon.com/americas-strangest-unsolved-tv-hack-and-the-story-behind-it?embedable=true On November 22, 1987, Chicago sports commentator Dan Roan covered the best moments of an American football game between the Chicago Bears and the Detroit Lions. It was a regular newscast following the evening news on local WGN-TV, of which Roan hosted several hundred. At 9:14 p.m., the reporter disappeared from the TV screens. Congratulations , on securing second place! You won 300 USD! @strateh76 The third position and most-read story award goes to https://hackernoon.com/scanning-26-million-domains-for-exposed-env-files?embedable=true Since almost every web application accesses a database or uses some APIs to communicate with, these credentials must be passed to the application. If this is done using the .env file, the credentials are in plain text in this file. When the web server is misconfigured and this .env file is delivered by the web server, anyone can query this data. To do this, one can visit just a URL with a browser, such as: https://example.com/.env. The dangerous aspect is that the passwords and secrets are in unencrypted form in the .env file. Excellent story, ; you have won $200! @sdcat Let’s wrap up the announcement! We will contact the winners shortly. Keep an eye on to see the current and upcoming writing contests! contests.hackernoon.com

The Cybersecurity Writing Contest: Final Round Results Announced!

Concurso de redacción sobre seguridad cibernética: ¡se anuncian los resultados de la ronda final!

Concours d'écriture sur la cybersécurité : les résultats de la phase finale sont annoncés !

साइबर सुरक्षा लेखन प्रतियोगिता: अंतिम दौर के परिणाम घोषित!

The Cybersecurity Writing Contest: 最終ラウンドの結果が発表されました!

Concurso de Redação sobre Cibersegurança: Resultados da Rodada Final Anunciados!

Cuộc thi viết về An ninh mạng: Đã công bố kết quả vòng chung kết!

网络安全写作比赛：决赛结果公布！

The Heat Index Of Questions About PHP

The story goes that Caesar, to exchange secret messages with his generals in the field, used to shave his messengers bald and write the message on their scalps. He would then wait a few months for their hair to grow back and send them off to their destinations. Only his trusted generals would know of this method to exchange messages, thus delivering his orders securely (albeit a few months late). This impractical, and rather silly, example describes what cryptology is all about. Cryptology is the science of securing communication. The term is taken from the Greek ("hidden, secret") and ("word"). In essence, it is about "hiding words". It is only one pillar in the science of Cybersecurity, but it is a significant one. At the base of this pillar are the subdivisions of cryptology: Cryptography and Cryptanalysis. The two can almost be seen as complementary. Where cryptography is the practice of transforming communications into a form that is unreadable to eavesdroppers, cryptanalysis is the practice of trying to unravel those transformed messages by an unintended recipient. kryptós lógos And it is here, at the base of this pillar, where one proof of a problem could cause the collapse of Cybersecurity. So, enter the Pantheon, this temple of Cybersecurity if you will, and let me guide you to where the cracks in the Corinthian columns begin to show. There are many different algorithms designed to keep messages secure. I'm going to tell you a bit about some of those systems so that the foundation of these algorithms becomes clear. If you've read anything about cryptography, chances are you've come across a concept called the "Caesar cipher". This is another example of a method used to secure messages. It is also attributed to Caesar, although this one doesn't involve a messenger's locks (pun intended) to keep the message safe. Instead, this cipher introduces an important concept that a significant portion of cryptographic algorithms are based on: Modular Arithmetic. I know, I know. It sounds scary, right? What if I told you, it's so simple that you use it every day? See, your clock is based on modular arithmetic as well. When you're trying to figure out how much sleep you're going to get if you have to wake up at 06:00, as you're finishing up that deadline at 23:00, you know not to count past 24:00. The result is always going to be less than 24:00. You're essentially calculating modulo 24. This is modular arithmetic, and it is used extensively in cryptography. Even in its simplicity, though, modular arithmetic holds many secrets that aren't immediately evident. Many cryptographic algorithms rely on these secrets. Caesar's cipher is a symmetric cipher. This means that both parties use the same key. Let's say the key is 3. The sender would shift every letter of his message by 3. This is called encryption. The receiver needs to know the key, and would then shift back every letter by 3, obtaining the original message. This is called decryption. Compare this to the bald messenger method. Encryption is letting the messenger's hair grow over the message, decryption is shaving the messenger bald. Now, is the Caesar cipher very secure? Well, not really. Anyone can easily try all the different keys, of which there are 26 in total, and find the correct one to unravel the message. This is called a Brute Force Attack. While the cipher is not very secure, it does adhere to an important principle that Caesar's bald messengers do not adhere to. Kerckhoffs principle states: "A cipher should not require secrecy, and it should not be a problem if it falls into enemy hands." In other words, the principle states that only the key should remain secret. The method may be made public, but without the key, the message should remain secure. If Caesar's formerly bald messenger gets intercepted by the enemy and the interceptor is aware of the method used by Caesar, the poor messenger will be shaved bald again in no time, revealing the message on his scalp. With Caesar's cipher, however, even if the interceptor knows the method of encryption, he would still have to try 26 different keys to uncover the message. Caesar's cipher is one of the simplest ciphers in existence, but its simplicity nicely demonstrates aspects of modular arithmetic. Other common symmetric cryptosystems are DES, 3DES, and AES. They essentially do the same thing as Caesar's cipher, albeit way more complex and harder to brute force. If you want to read more about these systems, I highly recommend reading the . AES Comic Let's introduce another important concept. Asymmetric cryptography (or public-key cryptography). The difference is that instead of the two parties having the same key, they have their own public and secret keys. Before we dive into RSA, here's a cool tidbit about it for you. When RSA was invented by Ron Rivest, Adi Shamir, and Leonard Adleman, it was illegal for them to export the algorithm or even its description, as part of munitions control in the US. RSA was considered so powerful that it was to be kept a military secret. As a freedom of speech protest, they wore T-shirts with the algorithm printed on them to conventions and talks. RSA is the most popular public-key cryptosystem. It's a super cool system that perfectly illustrates what a lot of modern cryptography is based on. We're going to get a bit technical here but bear with me. The fundamental theorem of arithmetic states that any positive number can be represented in exactly one way as a product of one or more primes. For example, the number 77 can be represented by multiplication of 7 (a prime) and 11 (a prime). There is no other way to represent 77 in primes apart from changing the order of the primes. Keep this in mind while I explain RSA. Before a message can be sent, we need to do some setup. Say, Bob wants to send a message to Alice and there is some eavesdropper called Eve. Alice, as the receiver, chooses two large prime numbers. She multiplies these two numbers to get the result m, the modulus. We're going to keep it simple and small in our example. Alice chooses 7 and 11 as prime numbers, resulting in the modulus 77. She publishes the modulus 77 and some chosen encryption exponent e. The combination of the modulus 77 and the encryption exponent e is called her public key. With Alice's public key Bob can encrypt the message he wants to send. In this case, the message is a number x. Encryption in RSA is done by taking x^e mod m. This results in ciphertext y and sends this to Alice. Now, Alice can do some magic with the prime factors 7 and 11, which results in a piece of information called d (for decryption). This is Alice's secret key. All Alice has to do now is take y^d, which will result in Bob's original message x. Phew, that was a lot, but the hard part is over! Now, notice that only Alice knows prime factors 7 and 11. This means that only Alice can do that magic trick to get information d.  But if you're sharp you would disagree with me here. You'd say: "Since 77 is published and everyone has access to it, Eve can easily figure out that 77 = 7*11 and do the magic trick as well to obtain d, with which she can get the original message x". I would agree with you here. Then I would tell you: "What are the primes of the number 30142741". Chances are you won't be able to tell me the answer. I can very easily tell you the answer though since all I did was take two prime numbers and multiply them to get 30142741.  And if I told you those two numbers, you could just as easily verify that the product is 30142741. So indeed, RSA relies on Eve (or you) not being able to find those two primes. In this case, the primes are 6037 and 4993. See how difficult prime factorization is, but how easy it is to verify the correct primes? That's it!  We are finally at the base of the pillar. Do you see the cracks? Probably not. Let me clarify. So, the transformations we apply to the message (encryption) need to be invertible for the receiver to be able to decrypt it. The receiver can invert the message because she is in possession of some extra information. Meanwhile, any interceptor, not in possession of that information, will not be able to decrypt the message. In RSA, for example, the interceptor would need to find the two prime factors of the modulus. Finding the two prime factors of a small number like 77 is, of course, easy, but prime factorization becomes much harder when a large number is chosen. Verifying that the two primes are factors of the modulus is always relatively easy since you just do multiplications. If prime factorization was easy or if there was an algorithm that can solve the problem relatively fast, then RSA would become obsolete. It relies on prime factorization being hard to solve, but easy to verify. We can make a distinction between two sets of problems. There are problems for which we know a way to find the answer quickly, for example, multiplication or squaring. This set is called "class P". The other class, "NP" is a set of problems for which there are no known ways to find an answer quickly, but when you have some information, the answer is easily verifiable. Prime factorization belongs to this class. But what if there is a way to solve a prime factorization problem easily? This would imply that prime factorization belongs to the P class. In fact, maybe we could prove that all NP problems are actually P problems. The conclusion would be that P = NP. This conclusion would have disastrous consequences for cryptography. As we've seen, RSA relies on prime factorization being difficult to solve. But RSA is only one of many algorithms that rely on NP problems and prime factorization is only one example of an NP problem. Other symmetric and asymmetric ciphers used for your financial transactions, your e-mail communication, etc. would be rendered obsolete. Bitcoin and other cryptocurrencies would suffer severe consequences as well since Bitcoin relies on cryptographic hashing, specifically, the SHA-256 hashing algorithm. For a new block to be accepted in the blockchain, this new block needs to contain a proof-of-work. In short, the proof is easy for any node in the network to verify, but generating the correct number is extremely hard. Proof of P = NP could on the other hand have positive consequences for other fields. Many mathematical problems remain hard to solve. Just imagine the effects it could have on mathematics! Proof of P ≠ NP would mean that our cryptographic algorithms are secure and that the title of this article is just clickbait. But at least I offered you the chance to win a million dollars! That's the reward the Clay Mathematics Institute will award to the first person to solve the "P vs NP" problem. So, give it a shot! Maybe you could be the one to break modern cryptography and send us back to using bald messengers for our daily communication. Also Published Here

An Insecure Pillar in Cybersecurity

Un pilar resquebrajado en ciberseguridad

Un pilier non sécurisé de la cybersécurité

साइबर सुरक्षा में एक असुरक्षित स्तंभ

サイバーセキュリティにおける安全性の低い柱

Um Pilar Inseguro na Segurança Cibernética

Một trụ cột không an toàn trong an ninh mạng

网络安全中的不安全支柱

**MIAMI, Florida, November 21st, 2024/CyberNewsWire/--**Halo Security, a leader in external attack surface management and penetration testing, has announced the launch of its new Slack® app, empowering cybersecurity teams to receive real-time alerts on newly discovered assets, vulnerabilities, and other essential security updates directly within the Slack collaboration software. This new integration allows Halo Security’s customers to seamlessly incorporate important security notifications into their existing Slack workflows, improving response time and enhancing collaboration across security and IT teams. Previously, Halo Security offered Slack alerts through a Zapier integration, but this new, direct integration delivers a more streamlined experience, giving customers greater control with minimal configuration. Halo Security’s platform offers comprehensive external attack surface management, encompassing asset discovery, risk and vulnerability assessment, and penetration testing in a single, user-friendly dashboard. Built by a team of experienced penetration testers, security engineers, and reformed hackers, Halo Security provides organizations with an attacker’s perspective to help identify and address vulnerabilities. With the new Slack integration, customers are notified as soon as new issues and vulnerabilities are detected, unknown assets or open ports are discovered, and new technologies appear on their websites, helping teams stay ahead of emerging threats without being overwhelmed by irrelevant alerts. “Organizations need real-time, customized alerts for emerging security threats, but too many notifications can lead to alert fatigue,” said Ben Tyler, CTO of Halo Security. “Our direct Slack integration is easily configurable, giving customers precise control over which alerts they receive and allowing them to focus on the most critical issues directly within their existing workflows." How to Get Started with Halo Security’s Slack Integration Halo Security customers can activate the Slack app today directly from their accounts. New users interested in trying the Halo Security platform can sign up for a 7-day free trial at halosecurity.com. About Halo Security Halo Security is a comprehensive external attack surface management platform that provides asset discovery, risk assessment, and penetration testing in a single, easy-to-use dashboard. Founded by cybersecurity experts with backgrounds at McAfee, Intel, Kenna Security, OneLogin, and WhiteHat Security, Halo Security delivers a unique attacker-based approach to help organizations safeguard against potential threats. Users can learn more at halosecurity.com. Slack is a registered trademark and service mark of Slack Technologies, Inc. Contact VP of Marketing Nicholas Hemenway Halo Security nick@halosecurity.com This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here **MIAMI, Florida, November 21st, 2024/CyberNewsWire/--**Halo Security, a leader in external attack surface management and penetration testing, has announced the launch of its new Slack® app, empowering cybersecurity teams to receive real-time alerts on newly discovered assets, vulnerabilities, and other essential security updates directly within the Slack collaboration software. This new integration allows Halo Security’s customers to seamlessly incorporate important security notifications into their existing Slack workflows, improving response time and enhancing collaboration across security and IT teams. Previously, Halo Security offered Slack alerts through a Zapier integration, but this new, direct integration delivers a more streamlined experience, giving customers greater control with minimal configuration. Halo Security’s platform offers comprehensive external attack surface management, encompassing asset discovery, risk and vulnerability assessment, and penetration testing in a single, user-friendly dashboard. Built by a team of experienced penetration testers, security engineers, and reformed hackers, Halo Security provides organizations with an attacker’s perspective to help identify and address vulnerabilities. With the new Slack integration, customers are notified as soon as new issues and vulnerabilities are detected, unknown assets or open ports are discovered, and new technologies appear on their websites, helping teams stay ahead of emerging threats without being overwhelmed by irrelevant alerts. “Organizations need real-time, customized alerts for emerging security threats, but too many notifications can lead to alert fatigue,” said Ben Tyler, CTO of Halo Security. “Our direct Slack integration is easily configurable, giving customers precise control over which alerts they receive and allowing them to focus on the most critical issues directly within their existing workflows." “Organizations need real-time, customized alerts for emerging security threats, but too many notifications can lead to alert fatigue,” said Ben Tyler, CTO of Halo Security. “Our direct Slack integration is easily configurable, giving customers precise control over which alerts they receive and allowing them to focus on the most critical issues directly within their existing workflows." How to Get Started with Halo Security’s Slack Integration Halo Security customers can activate the Slack app today directly from their accounts. New users interested in trying the Halo Security platform can sign up for a 7-day free trial at halosecurity.com . halosecurity.com halosecurity.com About Halo Security Halo Security is a comprehensive external attack surface management platform that provides asset discovery, risk assessment, and penetration testing in a single, easy-to-use dashboard. Founded by cybersecurity experts with backgrounds at McAfee, Intel, Kenna Security, OneLogin, and WhiteHat Security, Halo Security delivers a unique attacker-based approach to help organizations safeguard against potential threats. Users can learn more at halosecurity.com . Slack is a registered trademark and service mark of Slack Technologies, Inc. Halo Security Halo Security halosecurity.com halosecurity.com Contact VP of Marketing Nicholas Hemenway Halo Security nick@halosecurity.com This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Halo Security Launches Slack Integration For Real-Time Alerts On New Assets And Vulnerabilities

Halo Security, yeni aktivlər və zəifliklər haqqında real vaxt siqnalları üçün Slack inteqrasiyasını işə salır

Halo Security lanza la integración de Slack para alertas en tiempo real sobre nuevos activos y vulnerabilidades

Halo Security が Slack 統合を開始し、新たな資産や脆弱性に関するリアルタイムアラートを提供

Halo Security, 새로운 자산 및 취약점에 대한 실시간 알림을 위한 Slack 통합 출시

„Halo Security“ pradeda lėtą integraciją, kad realiuoju laiku būtų pranešama apie naujus išteklius ir pažeidžiamumą

Halo Security Melancarkan Integrasi Slack Untuk Makluman Masa Nyata Mengenai Aset dan Kerentanan Baharu

Halo Security lanceert Slack-integratie voor realtime waarschuwingen over nieuwe activa en kwetsbaarheden

Halo Security lansează integrarea Slack pentru alerte în timp real privind noile active și vulnerabilități

Halo Security запускает интеграцию со Slack для оповещений в реальном времени о новых активах и уязвимостях

Halo Security интегратсияи сустро барои огоҳиҳои вақти воқеӣ дар бораи дороиҳо ва осебпазириҳои нав оғоз мекунад

“Halo Security” täze aktiwlere we gowşak taraplara hakyky wagt duýduryşlary üçin haýal integrasiýa başlaýar

Ukhuseleko lweHalo luzisa uDityaniso lweSlack lwezilumkiso zeXesha lokwenyani kwii-asethi ezitsha kunye nokuba semngciphekweni

Halloween is the perfect time to add a touch of spooky fun to your website. You don’t need to go overboard with decorations, something as simple as changing your fonts can make a big impact. Most of the fonts shown are free to download, and to add them to your CSS, use the following code. @font-face {
    font-family: "font name",
    src: url("Extra Days.otf");
}

.font-family {
    font-family: "font name";       
} Font Tester Before you start, if you want to easily test out different local fonts you can use the font tester chrome extension. Not only does it become easier for you to choose a perfect font for Halloween, but provides you with a better understanding of typography. Download Font tester Bloody Hell Download Bloody hell Melted Monster Download Melted Monster Heartless Download Heartless Night core Download Night core Help Me Download Help me Frank knows Frank knows Exquisite corpse Download Exquisite corpse Monster Pumpkin Download Monster pumpkin Zombie Holocaust Zombie holocaust That’s it for now. If you have any more spooky fonts feel free to comment :) Halloween is the perfect time to add a touch of spooky fun to your website. You don’t need to go overboard with decorations, something as simple as changing your fonts can make a big impact. Most of the fonts shown are free to download, and to add them to your CSS, use the following code. @font-face {
    font-family: "font name",
    src: url("Extra Days.otf");
}

.font-family {
    font-family: "font name";       
} @font-face {
    font-family: "font name",
    src: url("Extra Days.otf");
}

.font-family {
    font-family: "font name";       
} Font Tester Before you start, if you want to easily test out different local fonts you can use the font tester chrome extension. Not only does it become easier for you to choose a perfect font for Halloween, but provides you with a better understanding of typography. Download Font tester Download Font tester Download Font tester Bloody Hell Download Bloody hell Download Bloody hell Download Bloody hell Melted Monster Download Melted Monster Download Melted Monster Download Melted Monster Heartless Download Heartless Download Heartless Download Heartless Night core Download Night core Download Night core Download Night core Help Me Download Help me Download Help me Download Help me Frank knows Frank knows Frank knows Frank knows Exquisite corpse Download Exquisite corpse Download Exquisite corpse Download Exquisite corpse Monster Pumpkin Download Monster pumpkin Download Monster pumpkin Download Monster pumpkin Zombie Holocaust Zombie holocaust Zombie holocaust Zombie holocaust That’s it for now. If you have any more spooky fonts feel free to comment :)

Top Spooky Fonts to Use for Your Website on Halloween 🎃

Overcome LLM Hallucinations Using Knowledge Bases

التغلب على الهلوسة باستخدام قواعد المعرفة

Überwinden Sie LLM-Halluzinationen mithilfe von Wissensdatenbanken

Supere las alucinaciones de LLM utilizando bases de conocimiento

Surmontez les hallucinations du LLM grâce aux bases de connaissances

Հաղթահարեք LLM հալյուցինացիաները՝ օգտագործելով գիտելիքների հիմքերը

知識ベースを使用して LLM 幻覚を克服する

Reseo ny Hallucinations LLM amin'ny fampiasana toby fahalalana

LLM Alucinaciones nisqakunata atipay Yachaypa Bases nisqawan

Depășiți halucinațiile LLM folosind baze de cunoștințe

දැනුම පදනම් භාවිතා කරමින් LLM මායාවන් ජය ගන්න

Övervinna LLM-hallucinationer med hjälp av kunskapsbaser

Shinda Ukumbi wa LLM Kwa Kutumia Misingi ya Maarifa

When I first set out on the entrepreneurial path, I had one goal: success. But after diving headfirst into the world of search funds and high-stakes startups, I found myself frustrated, drained, and questioning everything I’d come to believe about entrepreneurship. It wasn’t just that I wasn’t seeing the progress I’d envisioned—it was more personal. I felt like I was participating in a script that wasn’t written for me. My journey to create HalalFinanx wasn’t just about building a website; it was about reclaiming control, redefining success, and connecting to something meaningful. The Glamorous Illusion of Entrepreneurship Like many people, I was lured into entrepreneurship by the shiny allure of success stories and the promises of independence and financial freedom. Owning something, leading a team, and creating value sounded perfect. The search fund model was especially appealing, offering a structured path to find, acquire, and grow an existing business. It seemed like a straightforward formula with a lot of support. But as I dove deeper, the reality didn’t line up with the narrative. It felt like the supposed “freedom” of entrepreneurship was simply a myth, shackled by complex financial structures, endless pitching cycles, and a business environment that seemed more concerned with pleasing investors than creating something meaningful. I was constantly running from one “critical task” to another, but with no tangible progress. The whole structure of the search fund, built on layers of assumptions, started to feel like a game—and not the kind I wanted to play. The more I went, the more I felt like I was living someone else’s dream. I was chasing metrics that weren’t meaningful to me, jumping through hoops for outcomes that felt hollow. I started asking myself, “Is this what entrepreneurship is supposed to feel like?” I wanted out, but I didn’t know where to turn. Finding a New Path – The Birth of HalalFinanx The turning point came when I realized that if I wanted real change, I had to start creating things that resonated with me, not just my bank account or a pitch deck. As a Muslim, I’ve always been interested in Islamic finance, especially the ethical approach it brings to wealth. However understanding the field and accessing resources can be a challenge. I thought, why not create something to make Islamic finance easier to understand? I’ll be honest—this wasn’t the kind of idea that was going to impress traditional investors or fit into the typical startup. But for the first time, I was excited about what I was working on. I saw a real gap, not in a theoretical market sense, but a gap in what people genuinely needed. HalalFinanx was my way of bringing Islamic finance to the digital age in a way that’s accessible, understandable, and useful. There was one small issue: my skills lie in the backend and data. I’ve built and structured plenty of systems, but front-end work? Design? User experience? That was all new territory. Still, I knew that if I didn’t push myself here, I’d be back where I started—stuck in a rut, relying on others to bring my vision to life. This time, I was going to be in control. Learning by Doing – Building HalalFinanx with Bolt.new To get HalalFinanx off the ground, I turned to Bolt.new, a product that allowed me to work in a framework even with my limited front-end knowledge. Building this project was intense. I’d spend late nights combing through design guides, trying to make sure the site looked decent and functioned smoothly. It was exhausting, but the work felt real. This wasn’t just a project to show a board or potential investors—it was something I cared about personally, and every element I worked on felt like it added to that sense of fulfilment. Sure, there were plenty of challenges. Frontend work, it turns out, isn’t just about knowing which elements go where—it’s an art form. I struggled with layout, design principles, and even simple user flows. There were days when I’d look at the site and think, “This isn’t working.” But rather than giving up or passing the task to someone else, I forced myself to learn. It was a series of trial and error of building, testing, and iterating. What kept me going was the vision of what HalalFinanx could become, and each small win felt monumental. Making a button work, fixing a colour scheme, aligning content so it made sense—all of these were tiny victories in a larger war. The backend developer in me was learning to appreciate the nuances of frontend work, and it was humbling. The Personal Impact of Creating HalalFinanx This journey with HalalFinanx wasn’t just about building a site it was about redefining what success and fulfilment meant to me. In the search fund and traditional startup world, everything had been about numbers, KPIs, and keeping the right people happy. Here, with HalalFinanx, I was finally creating something with a purpose that resonated with me on a personal level. Building a site to provide accessible Islamic finance information was meaningful, not because of the potential returns or scalability, but because it filled a need I felt deeply. Each piece of content, each design tweak, and each function was geared towards making something simple, clear, and beneficial to anyone seeking this kind of financial guidance. I wasn’t answering to anyone but myself and my users, and that was liberating in a way I hadn’t expected. On a personal level, I found myself rediscovering why I wanted to create in the first place. I wanted to build something that mattered, and HalalFinanx became that for me. Instead of chasing empty metrics, I was now chasing real feedback from real users. Each suggestion and piece of feedback helped me refine the site, making it not just a project, but an evolving resource. For the first time, I was thinking long-term, not about exits or acquisition targets, but about sustainability and relevance. Looking Forward – The Ongoing Journey of HalalFinanx I don’t know where HalalFinanx will be in five years, but I know I’m in it for the long run. This isn’t a project that I’ll drop at the first sign of difficulty or when the next big thing comes along. It’s a genuine part of me now, a blend of my skills, my values, and my aspirations. I’m constantly looking for ways to improve it, from gathering user feedback to exploring new resources and insights to share. This journey taught me that real entrepreneurship isn’t about the numbers on a spreadsheet or the approval of others. It’s about finding something that matters to you, something you’re willing to build from scratch, without shortcuts or compromises. HalalFinanx is still a work in progress, but it’s my work, and that’s what makes it worth every bit of effort. When I first set out on the entrepreneurial path, I had one goal: success. But after diving headfirst into the world of search funds and high-stakes startups, I found myself frustrated, drained, and questioning everything I’d come to believe about entrepreneurship. It wasn’t just that I wasn’t seeing the progress I’d envisioned—it was more personal. I felt like I was participating in a script that wasn’t written for me. My journey to create HalalFinanx wasn’t just about building a website; it was about reclaiming control, redefining success, and connecting to something meaningful. The Glamorous Illusion of Entrepreneurship Like many people, I was lured into entrepreneurship by the shiny allure of success stories and the promises of independence and financial freedom. Owning something, leading a team, and creating value sounded perfect. The search fund model was especially appealing, offering a structured path to find, acquire, and grow an existing business. It seemed like a straightforward formula with a lot of support. But as I dove deeper, the reality didn’t line up with the narrative. It felt like the supposed “freedom” of entrepreneurship was simply a myth, shackled by complex financial structures, endless pitching cycles, and a business environment that seemed more concerned with pleasing investors than creating something meaningful. I was constantly running from one “critical task” to another, but with no tangible progress. The whole structure of the search fund, built on layers of assumptions, started to feel like a game—and not the kind I wanted to play. The more I went, the more I felt like I was living someone else’s dream. I was chasing metrics that weren’t meaningful to me, jumping through hoops for outcomes that felt hollow. I started asking myself, “Is this what entrepreneurship is supposed to feel like?” I wanted out, but I didn’t know where to turn. Finding a New Path – The Birth of HalalFinanx The turning point came when I realized that if I wanted real change, I had to start creating things that resonated with me, not just my bank account or a pitch deck. As a Muslim, I’ve always been interested in Islamic finance, especially the ethical approach it brings to wealth. However understanding the field and accessing resources can be a challenge. I thought, why not create something to make Islamic finance easier to understand? I’ll be honest—this wasn’t the kind of idea that was going to impress traditional investors or fit into the typical startup. But for the first time, I was excited about what I was working on. I saw a real gap, not in a theoretical market sense, but a gap in what people genuinely needed. HalalFinanx was my way of bringing Islamic finance to the digital age in a way that’s accessible, understandable, and useful. There was one small issue: my skills lie in the backend and data. I’ve built and structured plenty of systems, but front-end work? Design? User experience? That was all new territory. Still, I knew that if I didn’t push myself here, I’d be back where I started—stuck in a rut, relying on others to bring my vision to life. This time, I was going to be in control. Learning by Doing – Building HalalFinanx with Bolt.new To get HalalFinanx off the ground, I turned to Bolt.new, a product that allowed me to work in a framework even with my limited front-end knowledge. Building this project was intense. I’d spend late nights combing through design guides, trying to make sure the site looked decent and functioned smoothly. It was exhausting, but the work felt real. This wasn’t just a project to show a board or potential investors—it was something I cared about personally, and every element I worked on felt like it added to that sense of fulfilment. Sure, there were plenty of challenges. Frontend work, it turns out, isn’t just about knowing which elements go where—it’s an art form. I struggled with layout, design principles, and even simple user flows. There were days when I’d look at the site and think, “This isn’t working.” But rather than giving up or passing the task to someone else, I forced myself to learn. It was a series of trial and error of building, testing, and iterating. What kept me going was the vision of what HalalFinanx could become, and each small win felt monumental. Making a button work, fixing a colour scheme, aligning content so it made sense—all of these were tiny victories in a larger war. The backend developer in me was learning to appreciate the nuances of frontend work, and it was humbling. The Personal Impact of Creating HalalFinanx This journey with HalalFinanx wasn’t just about building a site it was about redefining what success and fulfilment meant to me. In the search fund and traditional startup world, everything had been about numbers, KPIs, and keeping the right people happy. Here, with HalalFinanx, I was finally creating something with a purpose that resonated with me on a personal level. Building a site to provide accessible Islamic finance information was meaningful, not because of the potential returns or scalability, but because it filled a need I felt deeply. Each piece of content, each design tweak, and each function was geared towards making something simple, clear, and beneficial to anyone seeking this kind of financial guidance. I wasn’t answering to anyone but myself and my users, and that was liberating in a way I hadn’t expected. On a personal level, I found myself rediscovering why I wanted to create in the first place. I wanted to build something that mattered, and HalalFinanx became that for me. Instead of chasing empty metrics, I was now chasing real feedback from real users. Each suggestion and piece of feedback helped me refine the site, making it not just a project, but an evolving resource. For the first time, I was thinking long-term, not about exits or acquisition targets, but about sustainability and relevance. Looking Forward – The Ongoing Journey of HalalFinanx I don’t know where HalalFinanx will be in five years, but I know I’m in it for the long run. This isn’t a project that I’ll drop at the first sign of difficulty or when the next big thing comes along. It’s a genuine part of me now, a blend of my skills, my values, and my aspirations. I’m constantly looking for ways to improve it, from gathering user feedback to exploring new resources and insights to share. This journey taught me that real entrepreneurship isn’t about the numbers on a spreadsheet or the approval of others. It’s about finding something that matters to you, something you’re willing to build from scratch, without shortcuts or compromises. HalalFinanx is still a work in progress, but it’s my work, and that’s what makes it worth every bit of effort.

Building HalalFinanx: A Journey from Disillusionment to Personal Fulfillment

One data scientist recently argued with me that we should stop using the term “hallucination” and just call these outputs what they really are: errors. The premise is simple—calling them errors would set more reasonable expectations for AI’s behavior. While this argument might make sense for someone coming from a statistics or programming background, it fundamentally misunderstands how AI works and why the term “hallucination” is actually more appropriate, albeit imperfect. The Misunderstanding of AI’s Nature From a statistical perspective, an error is a deviation from a known value or standard. It’s easy to quantify, easy to detect, and there’s a clear sense of right and wrong. If a model predicts a 20% probability when the true probability is 30%, we call it an error. We can measure this deviation, adjust the model, and move forward. For a data scientist accustomed to working within this framework, it’s natural to see LLM outputs that are factually incorrect as just another type of error. If an AI model says, “A circle has three sides,” then it’s clearly made a mistake—like a regression model producing a bizarre outlier. The problem with this comparison is that it applies a narrow definition of error to a system that generates language, not discrete values. AI models like GPT-4 do not “make errors” in the traditional sense because they lack a clear objective standard like those found in statistics. Why We Call It “Hallucination” AI language models generate sequences of tokens—words and phrases—based on probabilistic patterns. These patterns are learned from vast amounts of text data, and the models produce the most probable sequence of words given the context. Because of this structure, a language model might generate a phrase that is syntactically correct but semantically flawed. Imagine these two statements: “A circle has three sides.” “The professor said a circle has three sides.” If you evaluate these on a token-by-token basis, both might be highly probable outputs based on their preceding context. The first statement is objectively false, while the second statement could be contextually true if a professor actually made that erroneous claim. The model doesn’t have an internal understanding of geometry or truth—it’s simply generating words that fit together well. That’s why when the output is nonsense, we call it a “hallucination” instead of an error. The model didn’t make a mistake according to its own mechanics; it just produced an improbable yet plausible-sounding string of text. The Inadequacy of Calling It “Error” Labeling such outputs as errors creates the false impression that these models should know better. But knowing requires understanding, and that’s not how AI models are built. They don’t “know” in the way humans do, nor do they validate statements against a factual baseline. There is no inherent “truth” within the architecture of an LLM. The model operates based on patterns and associations, not logical consistency or factual accuracy. When I hear the argument that AI hallucinations are “logical errors” or “input errors,” it reminds me of the Garbage In, Garbage Out (GIGO) adage in traditional programming. If your inputs are flawed or your logical framework is off, the system produces wrong outputs. But that analogy only goes so far with AI because language and context are far more nuanced than a spreadsheet of values or a database query. An LLM doesn’t make logical errors in the programming sense. Instead, it lacks an internal verification process to ensure that what it’s saying is true. Imagine trying to apply the same logic to artistic styles or creativity. If an AI-generated image combines elements of a cat and a cloud, calling it an “error” is inappropriate. The model didn’t err—it produced a plausible but nonsensical creation based on its input data and generative process. Hallucinations and Human Perception This distinction is crucial because calling these outputs “errors” could mislead people into thinking that LLMs are making simple mistakes that can be fixed with better logic or more data. But hallucinations in LLMs are not bugs that can be patched. They are a byproduct of how these models work—of generating text without a built-in sense of truth. The onus is still on the human user to guide the AI’s output by crafting better prompts, setting clearer parameters, and using post-processing tools to verify facts. This is why the term “hallucination,” while imperfect, is closer to the mark. It conveys that the model is not just producing an error but fabricating new content—fabrications that are a natural consequence of its design, not the result of poor logic or faulty inputs. It serves as a reminder that these models are generative, not analytical. They don’t have a grasp of reality and can produce completely fabricated content even when all the inputs seem perfect. Setting Expectations for AI’s Outputs Ultimately, the data scientist’s argument comes from a place of wanting to simplify AI’s behaviors for the end-user. If we call these outputs “errors,” maybe people will understand AI’s limitations better. But in reality, this simplification does a disservice to the complexity of these models. We need to help people understand that AI models do not think, reason, or understand—they predict and generate. Their hallucinations are not “errors” in a mechanical or statistical sense but are intrinsic artifacts of how they operate. Until we develop AI models with built-in mechanisms for validating truth, we will continue to see outputs that are not just factually wrong but sometimes fantastical. And as we refine our language and expectations around AI, we need to keep terms like “hallucination” in place—if only to remind ourselves that these models are not yet capable of true understanding. So, while I appreciate the sentiment behind labeling these outputs as errors, it inadvertently strips away the nuances that make AI hallucinations fundamentally different from the statistical errors many data scientists are familiar with. As we continue to refine our models and our language, it’s worth keeping these distinctions in mind to set clearer expectations for what AI can and cannot do. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com One data scientist recently argued with me that we should stop using the term “hallucination” and just call these outputs what they really are: errors. The premise is simple—calling them errors would set more reasonable expectations for AI’s behavior. While this argument might make sense for someone coming from a statistics or programming background, it fundamentally misunderstands how AI works and why the term “hallucination” is actually more appropriate, albeit imperfect. The Misunderstanding of AI’s Nature From a statistical perspective, an error is a deviation from a known value or standard. It’s easy to quantify, easy to detect, and there’s a clear sense of right and wrong. If a model predicts a 20% probability when the true probability is 30%, we call it an error. We can measure this deviation, adjust the model, and move forward. For a data scientist accustomed to working within this framework, it’s natural to see LLM outputs that are factually incorrect as just another type of error. If an AI model says, “A circle has three sides,” then it’s clearly made a mistake—like a regression model producing a bizarre outlier. The problem with this comparison is that it applies a narrow definition of error to a system that generates language, not discrete values. AI models like GPT-4 do not “make errors” in the traditional sense because they lack a clear objective standard like those found in statistics. Why We Call It “Hallucination” AI language models generate sequences of tokens—words and phrases—based on probabilistic patterns. These patterns are learned from vast amounts of text data, and the models produce the most probable sequence of words given the context. Because of this structure, a language model might generate a phrase that is syntactically correct but semantically flawed. Imagine these two statements: “A circle has three sides.” “The professor said a circle has three sides.” If you evaluate these on a token-by-token basis, both might be highly probable outputs based on their preceding context. The first statement is objectively false, while the second statement could be contextually true if a professor actually made that erroneous claim. The model doesn’t have an internal understanding of geometry or truth—it’s simply generating words that fit together well. That’s why when the output is nonsense, we call it a “hallucination” instead of an error. The model didn’t make a mistake according to its own mechanics; it just produced an improbable yet plausible-sounding string of text. The Inadequacy of Calling It “Error” Labeling such outputs as errors creates the false impression that these models should know better. But knowing requires understanding, and that’s not how AI models are built. They don’t “know” in the way humans do, nor do they validate statements against a factual baseline. There is no inherent “truth” within the architecture of an LLM. The model operates based on patterns and associations, not logical consistency or factual accuracy. When I hear the argument that AI hallucinations are “logical errors” or “input errors,” it reminds me of the Garbage In, Garbage Out (GIGO) adage in traditional programming. If your inputs are flawed or your logical framework is off, the system produces wrong outputs. But that analogy only goes so far with AI because language and context are far more nuanced than a spreadsheet of values or a database query. An LLM doesn’t make logical errors in the programming sense. Instead, it lacks an internal verification process to ensure that what it’s saying is true. Imagine trying to apply the same logic to artistic styles or creativity. If an AI-generated image combines elements of a cat and a cloud, calling it an “error” is inappropriate. The model didn’t err—it produced a plausible but nonsensical creation based on its input data and generative process. Hallucinations and Human Perception This distinction is crucial because calling these outputs “errors” could mislead people into thinking that LLMs are making simple mistakes that can be fixed with better logic or more data. But hallucinations in LLMs are not bugs that can be patched. They are a byproduct of how these models work—of generating text without a built-in sense of truth. The onus is still on the human user to guide the AI’s output by crafting better prompts, setting clearer parameters, and using post-processing tools to verify facts. This is why the term “hallucination,” while imperfect, is closer to the mark. It conveys that the model is not just producing an error but fabricating new content—fabrications that are a natural consequence of its design, not the result of poor logic or faulty inputs. It serves as a reminder that these models are generative, not analytical. They don’t have a grasp of reality and can produce completely fabricated content even when all the inputs seem perfect. Setting Expectations for AI’s Outputs Ultimately, the data scientist’s argument comes from a place of wanting to simplify AI’s behaviors for the end-user. If we call these outputs “errors,” maybe people will understand AI’s limitations better. But in reality, this simplification does a disservice to the complexity of these models. We need to help people understand that AI models do not think, reason, or understand—they predict and generate. Their hallucinations are not “errors” in a mechanical or statistical sense but are intrinsic artifacts of how they operate. Until we develop AI models with built-in mechanisms for validating truth, we will continue to see outputs that are not just factually wrong but sometimes fantastical. And as we refine our language and expectations around AI, we need to keep terms like “hallucination” in place—if only to remind ourselves that these models are not yet capable of true understanding. So, while I appreciate the sentiment behind labeling these outputs as errors, it inadvertently strips away the nuances that make AI hallucinations fundamentally different from the statistical errors many data scientists are familiar with. As we continue to refine our models and our language, it’s worth keeping these distinctions in mind to set clearer expectations for what AI can and cannot do. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com

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