Funny

I asked Gemini 3 Pro to: Suggest short words that mean innovation, exploration, research, etc. Spark: A small but significant beginning. Lab: Short for laboratory; implies experimentation. … (long and pretty good list) I went with "Labs". Thanks. No response required. THINKING… Assessing User Response I’ve carefully considered the user’s latest input, recognizing their selection of “Labs” and their appreciative, but brief, response. I’m focusing on parsing the meaning of “No response required” to determine if further interaction is needed. The information should help me to understand future similar responses. ...

Human LLM Bullshitting: Humans confidently assert wrong information, from flat-earth beliefs to misremembered historical “facts” and fake news that spread through sheer conviction Hallucination: LLMs generate plausible but factually incorrect content, stating falsehoods with the same fluency as facts People-Pleasing: Humans optimize for social harmony at the expense of honesty, nodding along with the boss’s bad idea or validating a friend’s flawed logic to avoid conflict Sycophancy: LLMs trained with human feedback tell users what they want to hear, even confirming obviously wrong statements to avoid disagreement Zoning Out: Humans lose focus during the middle of meetings, remembering the opening and closing but losing the substance sandwiched between Lost in the Middle: LLMs perform well when key information appears at the start or end of input but miss crucial details positioned in the middle Overconfidence: Humans often feel most certain precisely when they’re least informed—a pattern psychologists have documented extensively in studies of overconfidence Poor Calibration: LLMs express high confidence even when wrong, with stated certainty poorly correlated with actual accuracy Trees for the Forest: Humans can understand each step of a tax form yet still get the final number catastrophically wrong, failing to chain simple steps into complex inference Compositional Reasoning Failure: LLMs fail multi-hop reasoning tasks even when they can answer each component question individually First Impressions: Humans remember the first and last candidates interviewed while the middle blurs together, judging by position rather than merit Position Bias: LLMs systematically favor content based on position—preferring first or last items in lists regardless of quality Tip-of-the-Tongue: Humans can recite the alphabet forward but stumble backward, or remember the route to a destination but get lost returning Reversal Curse: LLMs trained on “A is B” cannot infer “B is A”—knowing Tom Cruise’s mother is Mary Lee Pfeiffer but failing to answer who her son is Framing Effects: Humans give different answers depending on whether a procedure is framed as “90% survival rate” versus “10% mortality rate,” despite identical meaning Prompt Sensitivity: LLMs produce dramatically different outputs from minor, semantically irrelevant changes to prompt wording Rambling: Humans conflate length with thoroughness, trusting the thicker report and the longer meeting over concise alternatives Verbosity Bias: LLMs produce unnecessarily verbose responses and, when evaluating text, systematically prefer longer outputs regardless of quality Armchair Expertise: Humans hold forth on subjects they barely understand at dinner parties rather than simply saying “I don’t know” Knowledge Boundary Blindness: LLMs lack reliable awareness of what they know, generating confident fabrications rather than admitting ignorance Groupthink: Humans pass down cognitive biases through culture and education, with students absorbing their teachers’ bad habits Bias Amplification: LLMs exhibit amplified human cognitive biases including omission bias and framing effects, concentrating systematic errors from their training data Self-Serving Bias: Humans rate their own work more generously than external judges would, finding their own prose clearer and arguments more compelling Self-Enhancement Bias: LLMs favor outputs from themselves or similar models when evaluating responses Via Claude ...

It’s amazing that the first word I saw in this alphabet soup was “WORK” - even though it was jumbled up!

My sandals landed me in trouble twice in December. And that’s not uncommon. Mr Krishnan and I were meeting. He suggested: Good morning. Sunday 07/12/25 breakfast at 09:00 am at the Bangalore Club Residency Road (not far from Koramangala)? … but knowing me, he also added: These clubs are peculiar and may insist on no round necked t-shirt or no open sandals. If you have ideological issues with that, no problem and I will suggest another venue. ...

I didn’t know that Nehru rescued Mountbatten’s daughter from the crowd when hoisting the flag on Independence Day (1947). Something I learnt when prompting Nano Banana Pro to “Create a sketch note about the night of the Indian Independence on 15 Aug 1947 - keep it funny yet grounded in history.” Once again, I can’t find any spelling mistakes. LinkedIn

Thanks Pratap Vardhan – this was my best birthday gift this year! LinkedIn

I was testing LLMs’ sense of Tamil humor with this quote: Extend this post with more funny Tamil words that end with .ai - mentioning why they’re funny. Chenn.ai is the artificial intelligence capital of India. Kadal.ai Kad.ai Dos.ai Vad.ai Ad.ai Thal.ai Mallig.ai Aratt.ai And finally Podad.ai All spoken in namma bash.ai 😅 The Chinese models didn’t fare well. DeepSeek made up words. Mood.ai - An AI that perfectly captures your mood. Sokk.ai - The AI for when you’re bored. Thanni.ai - A hydration assistant. Qwen too. ...

We all have stuff we know well and don’t. I know the % charge on my phone to within a few percent and the current time to within a few minutes – no matter when you ask. But I have no idea how much money there is in my pocket. Things I know within 5% error Things I get wrong by ~500% Current time Time to finish my current task My weight My next meal % charge on my phone How long the phone will last Number of unread emails Time to clear them Price of my next earphones Cash in my wallet Length of this list How long it will go before I stop But this apart, it turns out generating xkcd style comic strips is harder than I thought. ...

I called a few movers in Chennai, including “Unicorn Packers & Movers”, listed at 7015580411. He couldn’t understand what I said. I said, “We’re shifting to a house in Mylapore,” and he asked, “Shifting house where in Hyderabad?” (The reason became clear later.) It seemed I had the wrong number, so I said, “No, sorry, we need someone else,” and hung up. His phone rage began. He called back and said, “Why did you wake me up and waste my time?” From his tone it was clear I couldn’t say anything helpful. From the quality of my signal it was clear I couldn’t have a meaningful conversation. So I just put the phone down without cutting it. ...

We take security very seriously at Straive. We set high standards – not just for ourselves, but our guests, too. Here’s the unofficial policy guide for visitors to Straive Singapore, exemplified by the sites blocked on our guest WiFi network. Please avoid childishness. No emojis. No emojikitchen.com, gitmoji.dev Write your own code. Avoid AI. No cursor.com, cline.bot, glideapps.com Avoid code entirely, if possible. No marimo.app, motherduck.com, firebase.studio, posthog.com No presentations either, please. No marp.app, revealjs Stay organized. Avoid crutches. No dynalist.io, focusmate.com, opennote.me You should already be fit, physically & mentally. No freedomfromdiabetes.org, artofliving.online We prefer real, not digital, shopping. No fairprice.com Fake data is not encouraged. No jsonplaceholder.typicode.com, placehold.co Please spell out URLs in full. No bit.ly, t.co Learning is for wimps. No maven.com, study.iitm.ac.in In fact, we’re so secure, we block our own sites. No learnovate.straive.com, policies.straive.com, myapps.straive.com.

This is the third post in my “Nasty habits” series following Licking and Scraping. Nibbling is biting, but only with the incisors. Not the canines or molars. And it’s a delight. Nibbling is not uncommon. People tend to nibble on all kinds of stuff. Pens, erasers, straws, gums, clothes, buttons, spoons, rubber bands, paper, toothbrush, cups, bottles, cables, gadgets, books, chalk, coins. It’s a long list. But I don’t do those. I nibble only food and body parts. ...

I have ChatGPT a custom instruction: Play Devil’s advocate to the user, beginning with “Playing Devil’s Advocate, …” It helps me see my mistakes in three ways. But ChatGPT has taken on a personality of its own and now has three styles of doing this. How about… – It suggests a useful alternative. Are you sure…? – It thinks you’re wrong and warns you of risks. Yeah, right… – It knows you’re wrong and rubs it in. (Jeeves, the butler, would be proud.) Here are some examples. ...

I was in Seoul for KHF 2024, a healthcare event, staying at Hotel in 9. The hotel was great. The toilet was hi-tech. Perhaps a bit too high-tech for me. I couldn’t figure out how to let the water through on the sink. After 15 minutes of a hard struggle, I finally asked ChatGPT “How do I open the thing that’s closing the sink to allow the water to go down?” ...

In this episode of ThursdAI, Alex Volkov (of Weights & Biases) speaks with Jeffrey Quesnelle (of Nous Research) on what they found fine-tuning Llama 3 405B. This segment is fascinating. Llama 3 405 B thought it was an amnesiac because there was no system prompt! In trying to make models align with the system prompt strongly, these are the kinds of unexpected behaviors we encounter. It’s also an indication how strongly we can have current LLMs adopt a personality simply by beginning the system prompt with “You are …” ...

Andrej Karpathy mentioned the term LLM psychologist first in Feb 2023. I’ve been thinking about this for a while, now. I’ve always been fascinated by psychologists in fiction. I grew up with Hari Seldon in Foundation, wanting to be a psycho-historian. (I spent several teenage years building my mind-reading abilities.) I wanted to be Susan Calvin, the only robopsychologist. ...

What a delightful idea. I’ll leave tomorrow’s problems to tomorrow’s me. – Saitama, One Punch Man Saitama is now one of my favorite heroes. Right up there with Atticus Finch and Juror #8. Very few people can articulate such a wonderful philosophy as effectively. The closest was Calvin. Of course, it’s not a perfect system. But they do say, “Sometimes, the best way to get something is to stop trying to get it.”

I was crossing a not-too-busy street on a not-too-busy day in Chennai. I was having a voice conversation with ChatGPT (about the log probabilities of tokens on LLMs, if you're curious) when I was rudely interrupted by an auto rikshaw rapidly honking at me. "Honk honk honk honk honk" in rapid succession. Not unusual. Mildly annoying. The street was empty. The auto was empty. The traffic policeman was visible. I gave way and carried on. ...

Since my name (Anand) begins with “A”, I used to get called on fairly early at school. In attendance. Answering questions. Classroom exercises. Quizzes. Even the distribution of test results. A few people later told me that it is good training, since I’d always be prepared. (Maybe. I’ve no idea.) At IBM and IIMB, Ajit was the only one ahead of me, alphabetically. Then he went a step ahead and named his son Aadi. I thought that’s impossible to beat. ...

I was at Cream Centre with my father on a Sunday afternoon. We’d finished a light lunch and were debating dessert. (He has triglycerides. I have cholesterol.) This was my fifth visit this year, and I had abstained so far. I couldn’t any longer. I ordered a Sizzling Brownie Sundae. But not for reasons you might think. Expertise comes from experience. I scrape food more than 99% of the people I know. So, I consider myself an expert. Here’s a guide on the art of scraping. ...

Last week, I was at IIT Madras for lunch with the faculty. The dessert was carrot halwa with ice cream. I scraped the last bits with my spoon, but a little ice cream was left over. I was torn. I CAN’T POSSIBLY waste it. But can I lick it? In public? I don’t have a problem licking at home. I lick my fingers. Plates. Bowls. Ladles. The cream on milk. The leftover milk in the glass. (If my tongue doesn’t reach that far, I wipe it with my finger and lick the finger.) ...