Suramya's Blog : Welcome to my crazy life…

January 22, 2025

ELIZA Resurrected using original code after 60 years

If you have been following the AI chat bot news/world then you would have heard the name ELIZA come up. Eliza was the world’s first chatbot created over 60 years ago by MIT professor Joseph Weizenbaum and was the first language model which a user could interact with. It had a significant impact on the AI world (Actual AI research not the LLM wanna be AI we have right now) and was the first to attempt the Turing test. It was originally written in a programming language invented by Weizenbaum called the Michigan Algorithm Decoder Symmetric List Processor (MAD-SLIP) and the pattern matching directives were provided as separate scripts. Shortly after the initial release it was rewritten in LISP which went viral. Unfortunately the original code in MAD-SLIP went missing till recently soon after that.

One of the most famous ELIZA scripts was called Doctor that emulated a psychotherapist of the Rogerian school (in which the therapist often reflects back the patient’s words to the patient). Much to his surprise Weizenbaum found that folks attributed human-like feelings to the computer program. Wikipedia explains how the software worked:

ELIZA starts its process of responding to an input by a user by first examining the text input for a “keyword”.[5] A “keyword” is a word designated as important by the acting ELIZA script, which assigns to each keyword a precedence number, or a RANK, designed by the programmer.[15] If such words are found, they are put into a “keystack”, with the keyword of the highest RANK at the top. The input sentence is then manipulated and transformed as the rule associated with the keyword of the highest RANK directs.[20] For example, when the DOCTOR script encounters words such as “alike” or “same”, it would output a message pertaining to similarity, in this case “In what way?”,[4] as these words had high precedence number. This also demonstrates how certain words, as dictated by the script, can be manipulated regardless of contextual considerations, such as switching first-person pronouns and second-person pronouns and vice versa, as these too had high precedence numbers. Such words with high precedence numbers are deemed superior to conversational patterns and are treated independently of contextual patterns.[citation needed]

Following the first examination, the next step of the process is to apply an appropriate transformation rule, which includes two parts: the “decomposition rule” and the “reassembly rule”.[20] First, the input is reviewed for syntactical patterns in order to establish the minimal context necessary to respond. Using the keywords and other nearby words from the input, different disassembly rules are tested until an appropriate pattern is found. Using the script’s rules, the sentence is then “dismantled” and arranged into sections of the component parts as the “decomposition rule for the highest-ranking keyword” dictates. The example that Weizenbaum gives is the input “You are very helpful”, which is transformed to “I are very helpful”. This is then broken into (1) empty (2) “I” (3) “are” (4) “very helpful”. The decomposition rule has broken the phrase into four small segments that contain both the keywords and the information in the sentence.[20]

The decomposition rule then designates a particular reassembly rule, or set of reassembly rules, to follow when reconstructing the sentence.[5] The reassembly rule takes the fragments of the input that the decomposition rule had created, rearranges them, and adds in programmed words to create a response. Using Weizenbaum’s example previously stated, such a reassembly rule would take the fragments and apply them to the phrase “What makes you think I am (4)”, which would result in “What makes you think I am very helpful?”. This example is rather simple, since depending upon the disassembly rule, the output could be significantly more complex and use more of the input from the user. However, from this reassembly, ELIZA then sends the constructed sentence to the user in the form of text on the screen

Now after over 60 years the original code written in MAD-SLIP has been resurrected by Jeff Shrager, a cognitive scientist at Stanford University, and Myles Crowley,an MIT archivist, who found it among Weizenbaum’s papers back in 2021. Which is when they started working on getting the code to run, which was a significant effort. They first created an emulator that approximated the computers available in the 1960’s and then cleaned up the original 420-line ELIZA code to get it to work. They published a paper: ELIZA Reanimated: The world’s first chatbot restored on the world’s first time sharing system on 12th Jan where they explain the whole process.

ELIZA, created by Joseph Weizenbaum at MIT in the early 1960s, is usually considered the world’s first chatbot. It was developed in MAD-SLIP on MIT’s CTSS, the world’s first time-sharing system, on an IBM 7094. We discovered an original ELIZA printout in Prof. Weizenbaum’s archives at MIT, including an early version of the famous DOCTOR script, a nearly complete version of the MAD-SLIP code, and various support functions in MAD and FAP. Here we describe the reanimation of this original ELIZA on a restored CTSS, itself running on an emulated IBM 7094. The entire stack is open source, so that any user of a unix-like OS can run the world’s first chatbot on the world’s first time-sharing system.

You can try it out: here.

Source:

– Suramya

November 7, 2024

Artificial Intelligence is not a reason to stop using your natural Intelligence

Filed under: Artificial Intelligence,My Thoughts,Tech Related — Suramya @ 6:59 PM

The more I see posts about some of the proposed use cases for AI the more I feel that some people just don’t want to use their brains and want to outsource all thinking to the ‘AI’. The latest example that triggered this post is screenshoted & Quoted below:

See BlockQuote Below the Image

Though malloc is a very useful function in c, it is not without its problems. The biggest is that it can be confusing for some to decide how much memory to allocate, needing complicated statements with sizeof . To solve this I propose a new alternative to malloc that utilizes the power of modern developments in Al, mallocPlusAI . The usage is simple.

int* x = (int*)mallocPlusAI(“Enough memory to store up to 5 integers”);

mallocPlusAI takes in a character array which is forwarded to a ChatGPT instance alongside an initial prompt “You are a memory allocator for a computer, and you need to tell me how many. bytes of memory I would need to accomplish a certain task. Make sure to give your response as only a whole number of bytes, do not provide any other text. Here is what I request: “

So instead of doing something like the following

5 * sizeof(int) + allocation overhead

Because apparently it is too hard to type 5 * sizeof() * Allocation Overhead, we will call an external API which brings the following downsides:

  • Which has a cost associated with it
  • Adds another layer of complexity & dependency to your application
  • Each ChatGPT query consumes an estimated 2.9 Wh of electricity, nearly ten times more than a standard Google search
  • Opens an avenue for attack where the remote prompt can be modified by a malicious actor to return incorrect values of size potentially causing the application to crash or leak data

Can someone please explain to me why you would use something like this instead of spending 2 mins thinking about what size of memory to assign?

– Suramya

October 22, 2024

Tech is not a replacement for human contact

Filed under: Artificial Intelligence,My Thoughts,Tech Related — Suramya @ 6:35 PM

The more I read about the kind of products these so call ‘AI Founders’ are coming up, the more I feel that they all need some serious therapy. The latest example of this is intouch.family which is an AI powered chatbot that calls your elderly parents so you don’t have to. I mean seriously? The official description is:

InTouch is a subscription service for seniors which regularly calls and keeps company to your parent, evaluates their well-being and alerts you if assistance is needed.

I get that we are all busy and it sometimes gets hard to call people and keep in touch, but anyone who thinks that AI is a replacement for the human touch especially in keeping up relationships needs to get their head examined.

I am quite bad at remembering birthdays and anniversaries except for close family and friends. When I was in college I thought that it would be nice if I could automate wishing folks Happy Birthday without having to actually wish them myself. So I wrote a program where I fed in all the birthday’s and the idea was that at a random time during the day it would email them a message wishing them. I even had a lot of enhancements planned, like use the ‘Poet’ program (it generated poems, based on certain criteria) and add it as part of the message to make it more personal. Spent a few days creating the program and it worked perfectly.

I was about to start using it and then realized that the whole point of wishing folks on their birthday was to keep in touch with them, not discharge an obligation. Especially if you have not talked to someone for a while, wishing them allows you to initiate a conversation. So I ended up changing the software to email me a reminder (This is in the days before Google Calendar and other reliable online calendars) so that I could call/email/text the person wishing them.

The whole idea behind technology is to make human contact easier, not to replace human contact. Telegrams allowed us to send urgent news quickly, then came phones that allowed us to talk to people who were far away, then we had VoIP/Voice Calls that allowed you to call without massive bills. Then came video calls such as zoom/Whatsapp etc that allow you to see the person you are talking to as well as hear them. In the near future we will have VR calls where you will feel that you are in the same room as the other person.

Unfortunately, most of the ‘AI’ services we see are being created/marketed as a replacement for human contact instead of as an aid to it. For example, instead of making friends to talk to, someone has created a AI ‘friends bot’ that you can share stuff with. (can’t find the link right now) Another genius created a whole social network that contains only AI bots that respond to your posts and create content.

I know making new friends can be scary at times but you need to find out what works for you. The stereotypical nerd who is anti-social is not something you want to aim for because that is absolute nonsense. You need to work with others if you want to succeed in life. If you are on the spectrum it can be harder for you to make friends but you need to see what works for you. One of my close friends is like that and we stay in touch over chat and emails as I know that they prefer non-verbal communications. With others I call or email or meet face to face. At one point a lot of my existing friends became busy with life (Got married/had kids etc) and I had to go out and make new friends so I started hiking and joined groups where we would go out for weekend trips or hikes. Ended up making new friends and actually met my wife in one of these trips. (Which was awesome!) I also have a lot of online friends that I have never met face to face (but I hope to when I can) and we email/message each other all the time.

Tech is awesome but nothing beats the human touch. Use Tech to enable/improve your connections/interactions but don’t make it a replacement for them.

– Suramya

August 27, 2024

MIT Researchers publish AI risk database exposing 700+ ways AI can be risky

Filed under: Artificial Intelligence,Computer Software,My Thoughts — Suramya @ 10:44 AM

AI (or rather what is call AI right now), is not really intelligent but it does have a lot of risks associated with using it. We all know about the Deep Fakes and the hallucinations etc but those are not the only risks of using generative AI. The researchers at MIT have cataloged the over 700 risks of using generative AI.

The risks posed by Artificial Intelligence (AI) are of considerable concern to academics, auditors, policymakers, AI companies, and the public. However, a lack of shared understanding of AI risks can impede our ability to comprehensively discuss, research, and react to them. This paper addresses this gap by creating an AI Risk Repository to serve as a common frame of reference.

This comprises a living database of 777 risks extracted from 43 taxonomies, which can be filtered based on two overarching taxonomies and easily accessed, modified, and updated via our website and online spreadsheets. We construct our Repository with a systematic review of taxonomies and other structured classifications of AI risk followed by an expert consultation. We develop our taxonomies of AI risk using a best-fit framework synthesis. Our high-level Causal Taxonomy of AI Risks classifies each risk by its causal factors (1) Entity: Human, AI; (2) Intentionality: Intentional, Unintentional; and (3) Timing: Pre-deployment; Post-deployment. Our mid-level Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental, and (7) AI system safety, failures, & limitations. These are further divided into 23 subdomains. The AI Risk Repository is, to our knowledge, the first attempt to rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible, comprehensive, extensible, and categorized risk database. This creates a foundation for a more coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed by AI systems.

They have published a paper on it: The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks From Artificial Intelligence that you should check out. They have also made their entire database available to copy for free as well.

Check it out if you have some free time.

Source: Boingboing.net: MIT’s AI risk database exposes 700+ ways AI could ruin your life.

– Suramya

July 29, 2024

Detecting AI-Generated Videos using MISLnet

Filed under: Artificial Intelligence,My Thoughts — Suramya @ 11:43 PM

With new technology and ‘AI’ it is becoming easier and easier to create fake images that look realistic enough to fool the casual eye. The problem is that this can be used to promote lies or scams etc. So we need to be able to identify if a given image is AI generated or real. Unfortunately, this is something that is easier said than done because as soon as the detector comes up with a way to identify fake images, the generators make changes to fix the issue resulting in a on-going game of whack-a-mole. That being said, it is important that we can identify and there is a lot of fascinating work that is happening in this space.

In an actually useful implementation of AI, researchers have trained a system called MISLnet that searches for statistical traces left in synthetic images by their source generator. It looks for relationships between pixel color values that are present in images taken by a digital camera which are not there in the AI generated image. This allows the system to identify AI generated images with over 98% accuracy.

I read the paper Beyond Deepfake Images: Detecting AI-Generated Videos(PDF) and honestly a lot of it went over my head. But based on tests it seems that MISLnet does perform well in identifying AI generated images.

The new tool the research project is unleashing on deepfakes, called “MISLnet”, evolved from years of data derived from detecting fake images and video with tools that spot changes made to digital video or images. These may include the addition or movement of pixels between frames, manipulation of the speed of the clip, or the removal of frames.

Such tools work because a digital camera’s algorithmic processing creates relationships between pixel color values. Those relationships between values are very different in user-generated or images edited with apps like Photoshop.

But because AI-generated videos aren’t produced by a camera capturing a real scene or image, they don’t contain those telltale disparities between pixel values.

The Drexel team’s tools, including MISLnet, learn using a method called a constrained neural network, which can differentiate between normal and unusual values at the sub-pixel level of images or video clips, rather than searching for the common indicators of image manipulation like those mentioned above.

The tool specifically targets images taken with a digital camera. It does not take into consideration that the image might have been taken by an Analog camera or is a scan of a printed images. In both those scenarios the relationships between pixel color values that the tool uses to identify real images will not exist, potentially leading the tool to falsely classify the image as fake or AI generated.

That being said, this is pretty interesting research and I am looking forward to testing the tool once it is released for general use.

Source: Schneier on Security: New Research in Detecting AI-Generated Videos

– Suramya

June 20, 2024

Some thoughts on the current AI hype market

Filed under: Artificial Intelligence,My Thoughts — Suramya @ 11:22 PM

Found this hilarious but accurate write up on AI and how the current Hype is spoiling the industry: I Will Fucking Piledrive You If You Mention AI Again. It is a little rude, filled with profanity but accurately covers the current state of AI. It is filled with gems such as:

So it is with great regret that I announce that the next person to talk about rolling out AI is going to receive a complimentary chiropractic adjustment in the style of Dr. Bourne, i.e, I am going to fucking break your neck. I am truly, deeply, sorry.


Unless you are one of a tiny handful of businesses who know exactly what they’re going to use AI for, you do not need AI for anything – or rather, you do not need to do anything to reap the benefits. Artificial intelligence, as it exists and is useful now, is probably already baked into your businesses software supply chain. Your managed security provider is probably using some algorithms baked up in a lab software to detect anomalous traffic, and here’s a secret, they didn’t do much AI work either, they bought software from the tiny sector of the market that actually does need to do employ data scientists. I know you want to be the next Steve Jobs, and this requires you to get on stages and talk about your innovative prowess, but none of this will allow you to pull off a turtle neck, and even if it did, you would need to replace your sweaters with fullplate to survive my onslaught.

Consider the fact that most companies are unable to successfully develop and deploy the simplest of CRUD applications on time and under budget. This is a solved problem – with smart people who can collaborate and provide reasonable requirements, a competent team will knock this out of the park every single time, admittedly with some amount of frustration.

Most organizations cannot ship the most basic applications imaginable with any consistency, and you’re out here saying that the best way to remain competitive is to roll out experimental technology that is an order of magnitude more sophisticated than anything else your I.T department runs, which you have no experience hiring for, when the organization has never used a GPU for anything other than junior engineers playing video games with their camera off during standup

The current hype and insistence by companies to insert AI capabilities in everything whether it is needed or not is getting to the point where it is actively annoying and in some cases dangerous. The recent attempted release of Recall + Copilot by Microsoft is a good example of dangerous. Then we have companies releasing AI powered BIOS , that “interpret the PC user’s request, analyze their specific hardware, and parse through the LLM’s extensive knowledge base of BIOS and computer terminology to make the appropriate changes to the BIOS Setup. This breakthrough technology helps address a major hurdle for PC users that require or desire changes to their BIOS Setup for their personal computers but do not fully understand the meaning of the settings available to them.

I really don’t need AI in my mouse or use AI to create a perfect smoothie or the thousand other things folks are shoving AI into. ChatGPT can’t do simple addition or multipications and keeps making up stuff. Google’s AI Gemini recommends that people add glue to their pizza’s, it misidentified a poisonous mushroom as an edible one and there are many many more such cases out there (I have posted some examples earlier).

The problem is that folks (grifters to be honest) are selling AI as the cure all for all problems a company wants to solve. This is overshadowing the actual work being done in the field which is solving actual problems and use cases.

What we have right now is Machine Learning that has a good track record in predicting responses, but it is nothing close to being intelligent. A cat has more intelligence in it than the current ‘AI’. This is not to say that we won’t have AI systems in the future. I have been hearing the claim that AI is just around the corner for about 25 years now but we are not there yet.

May 23, 2024

Windows 11 will feature builtin Spyware in the near future or Recall AI as Microsoft Calls it

Till recently if you wanted to spy on someone and see what they have been doing on the computer, you had to infect their computer by making them visit a dodgy site or get physical access and download a RAT (Remote Access Trojan) & install it on the target’s computer, configure the Antivirus to ignore it and put in a backdoor so that you can access the data remotely. Obviously this was a lot of work so looks like some cyber criminals reached out to Microsoft (MS) and asked for help. MS being a super helpful company, has added a functionality called ‘Windows Recall’ to it’s windows 11 Preview build to solve this. Recall takes a snapshot (literally) of the screen every few seconds and stores it in a searchable database ‘stored locally’. Basically it does exactly what spyware does without having to install anything new on your system. As per the company below is how the Recall works:

Recall uses Copilot+ PC advanced processing capabilities to take images of your active screen every few seconds. The snapshots are encrypted and saved on your PC’s hard drive. You can use Recall to locate the content you have viewed on your PC using search or on a timeline bar that allows you to scroll through your snapshots. Once you find the snapshot that you were looking for in Recall, it will be analysed and offer you options to interact with the content. What actions you can take depend on the content and the chat provider capabilities in Copilot in Windows. For example, you may highlight a block of text and decide to summarise it, translate it, or open it with a text editor like Word or Notepad. If you highlight an image, you will be able to edit it or use your chat provider in Copilot in Windows to find or create a similar image.

Recall will also enable you to open the snapshot in the original application in which it was created, and, as Recall is refined over time, it will open the actual source document, website or email in a screenshot. This functionality will be improved during Recall’s preview phase.

The best part is that according to their own announcement the snapshots will not hide passwords/account numbers etc. However, it does block you from recording DRM’d video you might be watching because protecting that is important not simple things like personal information etc.

Note that Recall does not perform content moderation. It will not hide information such as passwords or financial account numbers. That data may be in snapshots that are stored on your device, especially when sites do not follow standard internet protocols like cloaking password entry.

This is a gold mine for data thieves, abusers, industrial espionage, identity thieves and other cyber criminals. Once they have access to a PC they don’t need to do anything else except copy the data from the Recall DB to their own system and happily browse through the users personal data at their leisure.

I don’t think MS has thought about folks who use public computers such as the ones in an Internet Cafe or Hotels or Libraries. With this feature enabled all someone has to do is wait a few days then come back and copy incredibly private information that they can then sell/use. Privacy and Domestic Abuse experts are raising questions about this as well because sure as night follows day, abusers will use this to track what their victims are doing on a computer and that can go bad very quickly.

Even if the data is supposedly only on the local machine we don’t know when MS is going to force it to be uploaded to their servers using OneDrive or other similar setups. All the coverage I have seen for this functionality 99% of them have raised similar concerns about the security, privacy and quite frankly the need for this kind of surveillance.

Imagine what would a regieme like Taliban, China or other conservative/restrictive governments do with information they get from this system. You are dreaming if you think that they will not force MS to make this information available to them at the risk of losing access to that market if they don’t. Once you have the capability to do this, feature creep will happen for sure and we will end up in a Surveillance state.

The only Windows 11 system at my place is my wife’s laptop and you can be sure that I am going to disable this ‘feature’ as soon as it launches.

Source: Bleepingcomputer: Windows 11 Recall AI feature will record everything you do on your PC

– Suramya

May 17, 2024

Yeah, AI replacing us is not happening anytime soon

Filed under: Artificial Intelligence,My Thoughts — Suramya @ 10:49 AM

We are nowhere near having an actual AI, the current implementations we have are not even as intelligent as a cat or a dog forget humans. We do have amazing work being done on Machine Learning and Predictive software but nothing is even close to being intelligent. What we have right now is a scholastic parrot pretending to generate amazing information. To top it all, all the grifters are out in force scamming people by claiming AI is the cure for everything, the same way NFT’s and Blockchain were going to cure all the ills of the world.

I have been hearing claims that AI is ready to replace developers/low paid jobs etc for over 25 years now with similar results at the end of the day. Some of the examples I found over the past few weeks showcasing the amazing power of AI:


‘sun’ & ‘den’ are 4 character words as per AI


Would you like a Bananum?


The Entire Devin AI demo was faked. The developers lied about the entire thing and made a ton of money


Yup, we can totally say that an irrational number with never ending decimal places after 3 has the last 5 digits as ‘65359’

There are so many more of these examples I can share… Please don’t buy into the hype, look at the facts and make a decision.

– Suramya

May 16, 2024

Google claims to have created AI to detect scams in realtime by listening to all your calls

Scams are getting more and more common nowadays, with folks loosing a lot of money due to this. We absolutely need more ways to detect and warn people about scams but I don’t think this is the right approach. By ‘this’, I am talking about Google’s recent announcement at Google I/O to use Gemini Nano to alert users to potential scams during a phone call.

The feature, which will be built into a future version of Android, uses Gemini Nano, the smallest version of Google’s generative AI offering, which can be run entirely on-device. The system effectively listens for “conversation patterns commonly associated with scams” in real time. Google gives the example of someone pretending to be a “bank representative.” Common scammer tactics like password requests and gift cards will also trigger the system. These are all pretty well understood to be ways of extracting your money from you, but plenty of people in the world are still vulnerable to these sorts of scams. Once set off, it will pop up a notification that the user may be falling prey to unsavory characters.

In order for the functionality to work we would have to give Google full and complete access to all our phonecalls & audio during the call. I don’t know about you but I don’t want to give this kind of personal data over to a company that has already lied about the data they collect (referring to the recent lawsuit on their tracking the web-browsing habits of users in incognito mode that they settled last month).

– Suramya

Source: Slashdot: Google Will Use Gemini To Detect Scams During Calls

May 13, 2024

Please don’t use AI to cheat on your interview no matter how tempting it sounds

Interviews are hard and at times folks who are really good at work don’t do that well in interviews. This could be because of nervousness, anxiety or just bad timing/questions. However, that doesn’t mean that you should cheat in the interview because trust me, you will get caught. Having been in the industry for over 24 years, I have seen multiple instances where folks decided to cheat in the interview thinking they would get away with it but in the end all of them were caught and ended up getting blacklisted in the company. In some cases it can even lead to charges & cases being filed against you.

Now that AI is getting into everything, it was inevitable that it would enter the interview world as well as an cheating aid. Enter www.milio.ooo/. They don’t even attempt to hide the fact that this tool is meant to help candidates cheat in their interviews. From their website, right at the top “Job adverts cheat, so why can’t you?”. I mean it doesn’t get more blatant than that… As per the description on their site the software listens into the audio stream of the interview and then displays the answer on the screen for you to parrot out. A sample question and answer featured on the site is shown below:

What digital marketing tools and platforms are you familiar with?

I have experience working with a variety of digital marketing tools and platforms, including: - Google Analytics: I have used Google Analytics extensively to track website traffic, user behavior, and conversion rates. I am comfortable setting up custom reports, analyzing data, and identifying opportunities for optimization. - HubSpot: I have experience using HubSpot for marketing automation, lead nurturing, and CRM integration. I have created email campaigns, landing pages, and workflows to drive engagement and conversions.
Sample answer to a question generated by the cheating software

The site doesn’t explain how it ensures that its responses actually match what is in your resume abd I doubt there is much of that happening here. In anycase, I do understand folks who are desperate can end up using tools like this one to get a job. But while it might look like a good bet in the short term it will get you in trouble in the long term. If the people trying to cheat actually put in the effort they put into cheating the system into actually learning the system they would be much better off.

Please remember that the folks who are taking the interviews (like me) have been doing this for a while and it is quite easy to figure out that someone is reading an answer off the screen. In the past we used to listen for keyboard sounds to figure out if someone was googling for answers but with this ‘AI’ listening that tell is no longer there. However, if this is on a video interview I can still figure out that you are reading off the screen by looking at you.

Also remember, most large companies do have face to face interviews as well and a final fit round before rolling out an offer letter. I have had an example in one of my previous companies where a person who had cleared all the phone interviews was in office for the final rounds and one of the interviewers asked them a basic clarification question and they were unable to answer, so the interviewer got suspicious and asked more probing questions. Finally the candidate admitted that someone else had taken the phone interview (this was before video calls/interviews) and they ended up getting blacklisted and obviously didn’t get a job. Even with video interviews, one of the candidates was recently caught lip-syncing the answers that someone else was giving.

This actually gave me an idea for a project (which I might or might not work on). Basically, a lot of times in meetings we talk about technologies or projects we are working on and sometimes I end up making a note for myself to look up something post the call because I wasn’t sure of what it does. It would be really cool to have an assistant/program running in the background that continuously gave information & links to additional information when people talk about projects or technologies or past discussions. I doubt it would be good enough to only give information I would need but it could be an interesting addition to make a person more productive. Basically the same technology used in this site but instead of interview answers actually giving links to more information along with summaries etc.

Long story short, please don’t cheat on interviews no matter what tech is powering the cheat tool.

– Suramya

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