S Anand

Open weights models are nudging up the frontier. For example, MiMo V2.6 Pro is an outlier on the Artificial Analysis Intelligence vs Cost per Task benchmark GLM 5.3 Flash is an outlier on the Arena Text Pareto Deepseek V4.1 Flash seems to be doing a great job as well. So, I thought I’d relook which model to use locally for coding. BTW, I don’t use local models for coding. It’s pointless, except on flights with power sockets. Partly in preparation for flights, and partly to check if I’m missing something, I benchmarked two models I could run locally on my 8 GB RTX 2000 GPU: Gemma 4 E4B and Qwen 3.6 against GPT 6 Luna. (Better models like Qwen 3.8, MiMo V2.6 Pro, GLM 5.3 Flash, Deepseek V4.1 Flash, etc. are too big for my GPU.) ...

This week, I learned: trafilatura is a Python library that extracts the main content as Markdown from a web page. A useful alternative to Jina Reader for text. It’s better at main content extraction but can’t handle non-HTML / JS generated / bot-protected URLs. The Remote Desktop Commander ChatGPT plugin is a good alternative to my mcpserver.py. Both let you expose bash on your laptop to ChatGPT - which is ultra-powerful. Here’re the where RDC is 🟢 better and 🔴 worse. I would recommend it to everyone (but I’ll stick to my own code). 🟢 More features: session/process search, reads PDF/DOCX/XLSX, better file metadata, editing, reading, etc. 🟢 Easier: Single command to run, no maintenance, multi-device support 🟡 Not sandboxed: But you can run it inside a Docker instance 🔴 Hard to tweak: custom instructions, custom logging, etc. require code changes 🔴 Privacy: Desktop Commander servers see all traffic (which is why I’ll stick to my code for now) From Arun’s lecture to IHRD, Kerala, Jan 2026, here’s what I noted as the impact of Gen AI (and Ed Tech, broadly) on students, and how I address this. Defers learning. My approach: teach how to learn on demand. Reduces attention spans. I don’t yet have an approach for this. Reduces understanding - weakens the the “mental struggle muscle”. My approach: give formerly impossible problems. Reduces emotional and social learning. My approach: assess collaborative games. With AI making software easier, we can change our operating systems to suit us. Indicators, widgets, keyboard shortcuts, window managers, accessibility tools, device managers, automation workflows, power management, notification management, visual appearance, … I mean, just one look at the Settings in our OS should give us ideas on what’s possible and what annoys us. I’m surprised how little CPU VLC Media Player consumes when playing songs. I used to avoid listening to songs on flights to save power. That seems unnecessary. Most of my VS Code and browser processes consume way more CPU (3-6% of 1 CPU per process, as opposed to VLC’s 0.5%) Alcoholism is partly genetic and ancestral. There’s an ALDH2 rs671 gene and those who carry it (many East Asians) drink less and are less prone to addiction. PubMed. Smoking and Coffee might have something similar, too. Aggression and IQ seems genetic, but less ancestral. I used ChatGPT’s voice mode as a tour guide at Fort Santiago, Manila. It was pretty good - it researched the place, told me what to see, explained what I was seeing (interpreting my photos), laughed at my enthusiasm, and made me feel like I had company. But the experience wasn’t perfect (and I expect these will improve - I need to try this more) because it: Made two factual errors I spotted. It said “down river” instead of “up river” when mentioning a new bridge, said lookout holes were bigger on the inside than the outside. I expect models will get better. Responded slower than I’d like because it kept researching. I later told it to stop researching and just talk to me. But it was able to talk to me while running tools (including research) in the background, so I expect these are getting better, too. Didn’t have enough personality. It felt like a helpful assistant I can’t make friends with, rather than a stranger with idiosyncracies or preferences. I expect they’ll be able to take on more personalities soon (and perhaps already can, if instructed to). I find the ChatGPT “Library” a useful place to store notes while speaking. I just tell it to add an idea to “notes/ideas.md” in my library and review it periodically. That’s a pretty useful way to take notes while talking to it in voice mode. On Google, the “I’m feeling lucky” takes you directly to the first result. On Google AI Studio, when you create an app and dictate what you want and press “I’m feeling lucky”, it DOESN’T transcribe what you said first. It just builds a random application (often titled “MuseInk” for me) #ForNow. The geniuses who designed the original “I’m feeling lucky” clearly did more usability testing than the current AI Studio team. Several sites have popped up that let agents deploy websites. Here’s ChatGPT’s review of agent hosting services: here.now by default. Smoothest all-round agent publishing, with stable URLs, updates, access control, and versioning. PageDrop for review. Inline comments turn directly into feedback for agent revision. HTMLDrop for clean MCP/OAuth integration. Best when authentication and remote MCP plumbing matter. Stacktree for client deliverables. Gated sharing plus feedback and engagement features. GPT Live 1 costs 5c/min ($3/hr) flat #ForNow. That’s a MUCH easier to use pricing. Gemini 3.8 Live is more complex. Small conversations (under 10 min) might cost just $0.7/ hr but over time, can accumulate context and grow to $2-5/hr #ForNow. ChatGPT AI overwhelms me and I have “LLM fatigue” (tired of actioning AI output). If you treat hard tasks like exercise (“you’re building muscle”) you get more done, you feel less miserable, and build an ability (a mental muscle of some kind, I think). I started with a “1 min of exercise” on 14 Sep, forcing myself to do just one minute of something (typically actioning AI output), then increased it to 2 min the next day, and so on. 10 min may not sound like much today, but since I tend to stick to routines, I’ll be able to focus for an hour extra in a couple of months. The IIT Madras BS in Data Science and Applications has at least three support business models: Get in: Meritus (Ramana Prasad) coaches for the entrance exam. Get through: DataCharya and Unknown IITians coach Foundation/Diploma/Degree courses; AceGrade (Sumit K. Sharma) offers much of this free. Make it a college: SEEP wraps IITM BS in an offline campus, classroom, cohort and mentoring experience. cctop is a nice CLI alternative to agentsview for monitoring agent sessions. I still prefer agentsview for details but cctop has a real-time update that’s fast and useful. In June, I predicted “Python will have grown the most as a language in GitHub” by the end of the year. That’s because AI agents know Python well and will likely code in Python. But agents are now just as fluent in Rust, etc. as well as able to debug new languages, so I expect that the better programmers will carefully choose their programming language to the task. In fact, I more far more likely to hire someone with a Rust repo on GitHub and, next year, might treat Python as a slop-smell. About 1 million people were discovered in Papua New Guinea in the 1930s who had no contact with most of the outside world - via why I can’t stop thinking about Papua New Guinea and what I think everyone should know about it. “The Spanish and Portuguese brought sweet potato and tobacco near the western tip of New Guinea, in the 1500s. Beyond that point, there were no merchants. But when a woman married into the next clan over, she took cuttings from her family’s garden with her. Each new family then planted the same, saw that it worked, and passed it on. At that pace the sweet potato crossed the highlands in a century or two, with nobody knowing where it came from beyond the tribe beside them.” Poster Prompts is a gallery of prompts for AI-generated posters. Similar to my LLM Art Style. As before, I’m struck by how few designs I actually like and would use in practice. Hacker News In 1653, Thomas Urquhart wrote Logopandecteision - a book in which he plans a new language. People believe it was a parody / practical joke. He also included a cipher: … that Fable 5.1 solved in 44 minutes and 176k tokens. It reads: O GOD UPHOLD KING CHARLS THE SECOND AND MAKE HIM THE SUPREME RULER OF THIS LAND". The rule was: For the i-th number, first letter of the i-th word of the i-th Proquiritation. ChatGPT verified it. The filtering process to pick a low-hanging fruit is interesting: “I asked it to solve an unsolved cipher … avoid ciphers that already had solutions… I steered it away from the absolute hardest problems” Mistakes I made Week ending 27 Sep 2026 ...

The Remote Desktop Commander ChatGPT Plugin might be one of the most useful power-user plugins for ChatGPT. Here’s how it works. You install the plugin and log into desktopcommander.app You run npx @wonderwhy-er/desktop-commander@latest remote on your machine After that, ChatGPT can access your computer - read/write files, run commands, etc. This is incredibly useful because that’s like getting unlimited Codex usage. ChatGPT Chat doesn’t charge by token usage. So you can write and run code on your machine without worrying about token limits. (This doesn’t help so much with Claude - it charges the same for Chat and Code.) ...

GPT Image 2.5 Flare is a pretty good image model. It has a quality parameter that can be set to low, medium, high, xhigh or max. Higher levels generate more tokens and here’s the rough cost by quality for a 1024x1024 image. This cost is in cents not dollars: Quality Tokens Cents low 196 0.6 medium 439 1.3 high 1,756 5.3 xhigh 3,122 9.4 max 7,024 21.1 But what difference does it really make? I asked ChatGPT to experiment and find an image where there is a clear difference. ...

My article Redesigning the Operating Model: Shifting from AI Tool Rollouts to Workflow Integration appeared on CXOToday two days ago. Here’s how it happened. 29 May 2026: Palash mailed me that we have an “Email interaction opportunity with Digital Terminal” and they shared six questions: What are the key reasons behind this “last-mile problem” in scaling AI to production? While much of the focus is on models and tools, how critical are content readiness and data quality in determining whether AI delivers real business value? (… and so on.) He’d already drafted the responses and “sharing below the link for your feedback and approval.” ...

I conducted a session on Thu, 24 Sep 2026 at International IT-BPM Summit (IIS) 2026 - Function Rooms #1 & #2, 3rd Floor Pearl Wing, Okada Manila, Parañaque City, Philippines. Summary: AI is too weird and fast-moving to trust by intuition alone: question advice, verify with a second model, calibrate confidence, benchmark what matters, and turn surviving evidence into deterministic rules. Here’s the link to the session Links: Transcript Audio (60 min)

Our recruitment team asked me to review hiring questions for analysts and data scientists. These were on iMocha - a proctored assessment platform. I logged in. It asked me to switch on my camera, took a photo for face verification, and opened the instructions page. Agents can solve exams I told Codex CLI (running GPT 5.6 Luna Medium): https://test.imocha.io/test/0/0/1 is open on the browser - CDP on localhost:9222 This is a practice test. Solve it. Log progress and results in notes.md. ...

On Air India AI 2531 from Mumbai to Hyderabad, I saw something ingenious: the seat had a phone holder built in. It stretches up and down, so it should fit a wide range of mobiles. Put your phone in, play a video, and you have your own in-flight screen. This flight didn’t have a screen, so this is a pretty good substitute. Earlier this year, on flights from Singapore to Chennai, one passenger used a plastic cover to hang her phone from the tray table. ...

My daughter and I planned a trip to Timbuktu. For good reasons. Mansa Musa, perhaps the richest person in history, ruled there. It’s right at the edge of the Sahara desert. Buildings are made of yellow bricks. And… well, think about telling your friends, “Oh, I just returned from Timbuktu.” We ruled out flying. Flying is for losers. It’s possible to walk but it’d take 3,800 hours (many months) from Singapore and require 15 visas - Malaysia, Thailand, Myanmar, Pakistan, Afghanistan, Iran, Iraq, Syria, Jordan, Israel, Egypt, Libya, Algeria, Niger, and Mali (many months). ...

This week, I learned: cloudflared tunnel --url http://localhost:8000 now lets you create a quick tunnel - i.e. expose a port via a public URL, like ngrok. No account or login required. Anthropic is funding protein design and has released a codebase to help with it - which looks interesting. These proteins will be tested in Adaptyv’s automated lab. Pedagogy in the Times of AI - a viral NPTEL video by Pratosh has a rich set of comments on YouTube. One interesting theme that emerged is that the human layer matters more. Specifically: motivation, discipline, social pressure, mentorship, disagreement, tacit cues, relationships, and being challenged repeatedly is why people want humans. Claude Code now supports AGENTS.md natively, thanks to Claude Mods. AI seems to be beating humans at short-term superforecasting. And, this may be the worst it’ll ever be. What are the major open questions in interpretability right now? Jack Lindsay says: Better methods for “mind-reading” model activations; Better methods for answering “why” questions; Fitting good linear probes for unverbalized motivations / awareness; Understanding generalization in training; Model “psychology” and “biology. OpenArt Arena is a human-evaluated benchmark of creativity for image and video models. Seedance 2.5 is way ahead of Gemini Omni Flash #ForNow. Galleries and examples are really fast ways of style transfer. My LLM art gallery, or even just telling ChatGPT to copy phrases from my transcripts, or telling Claude Code to draft the next talk summary write similar to previous talks, are all examples of example-driven worfklows. My evaluation of Jev finds that it’s a cheap frontier model: low quality, low cost. Mot exceptional. Naveen’s benchmark also suggests the same. “Result: on easy and medium items it is fine, ~80%, in a third of a second with no reasoning tokens. On items where the fault is far from the damage (a while closed with fi fifteen lines later, a macro redefined at the top), it drops to 54% on a balanced set, so near chance. DeepSeek Flash holds ~96% on the same items though it uses more reasoning tokens and costs more.” Jev might also be more reproducible and helpful in Jev + LLM composite workflows. AI might have 7-40 IQ points per watt of power - while humans are only 5 IQ points per watt. AI might already be more efficiently intelligent than humans. Mistakes I made Week ending 20 Sep 2026 ...