The Time Use Survey 2024 data released last year lets you download a ZIP containing a 900 MB .Nesstar file. (This is after you register - but the registration is free, and though it requires a reason, it’s automated.) Nesstar is Norwegian software that’s now end of life. MOSPI provides this guide - with distorted screenshots - explaining how to install the software on Windows. But I use Linux. The software is end-of-life. Gaah! ...
Students of my course were given an assignment. Submit a picture story (no words) that others will understand and like. Explain others’ picture stories and rank them. Here are the results. Firstly, why this exercise? Because it teaches three skills I believe are important in the AI era: Creating unique content Communicating with clarity Marketing your ideas This is exactly what they were evaluated on. Uniqueness: How similar was their story to others'? Understanding: How well did others understand their story? Preference: How much did others prefer their story over others'? Here are some stories I enjoyed. Click for details. ...
I was reading Asterix on my flight from Brussels to Dubai when I remembered a colleague’s request. I typically convert my workshops into narratives like this and this. They wanted another event converted. Usually, I have the full transcript of my events. In this case, I just had a few paragraphs of notes. Far from enough. On the other hand, I was reading Asterix. And AI’s my magic potion. So I figured: Why not create a comic story? Using real faces? While reading Asterix? ...
Using the same approach as specification and verification I looked at how I review agents, i.e. what I comment on after they share an output. This page features the 28 review techniques I use. Some interesting ones: Show your style: I tell it why it doesn’t sound like me, and how I would have written it. Real example: “Still not in my style - revise more in line with these principles.” Pause and resume: Tell it not to exceed the usage limits. Real example: “We are at 96% usage of the 5h limit - so pause now and we can resume in a few hours.” More like this: Tell it what you liked and go in that direction. Real example: “Looks good. Give me 10 more.” Take the best of each: Give it other models’ output and pick the best from each. Real example: “Here is ChatGPT’s response. Take what’s better, drop what’s worse, follow up on new ideas this gives you, and revise your response.” Say “I meant…”: Clarify your real intent. “Sorry, I meant round off the 95% activity window in EACH namespace.” These are based on ~6.7K real responses. Skim through them and if you spot something interesting, test it out. If it works for you, share it with others.
The Innovation team has been experimenting with 3D interaction, audio, video and AI agents. Three things struck me: We can manipulate a 3D molecule with our hands, or try different furniture in a virtual room, using a browser. Sound search can find things a transcript never records. And a small specialist model can diagnose a machine at a tiny fraction of an audio LLM’s cost. AI can help us improve videos and business decisions when its suggestions are checked against evidence, not just written convincingly. New ways to interact and create Hold a 3D molecule in your hands (Sujal). At our Innovation Team meeting, I used hand gestures in front of my camera to manipulate a colourful 3D ATP synthase molecule: pluck, slice, scale, rebuild and explore its parts. The browser recognizes the gestures; a paired phone can also control the scene. It is related to Sujal’s remote 3D pottery experiment. ...
Since agents do most of the work, specification (telling it what to do) and verification (making sure it did it right) is more important than execution. This is what I’m often asked about. Of the ~600 questions people asked me this year, half were deciding what to do / ask for and every sixth question was about checking if it worked. I checked. For example: “What should we ask agents to do when we only have a dataset and no clear use case?” ...
I conducted a workshop last weekend for working professionals and had assigned homework as part of that. We reviewed their homework at the start of the class, and I noticed that the majority of them had clear AI smells. I let the participants know that using AI is perfectly fine, especially in an AI class, and asked how many of them used AI to write the final output, All, except one, said “Yes” - a bit of a surprise to me since it included some output that I thought was manually written. ...
Thornston Bell’s How I work with Agents suggests actively using remote machines for coding. I’d struggled with this for many months, and finally managed to set up my Windows laptop for remote coding. How? Tell my wife to tell the maid to never switch it off. (It doesn’t have battery.) Tell ChatGPT to install Remote Desktop Commander - and schedule it to run on boot. Now agents can use it. Tell ChatGPT to install Tailscale so I can SSH into it and copy files. Tell ChatGPT to create a sync-plutonium.sh that pushes files from my Linux system (graphene) to the Windows machine (Plutonium). That last step was the critical enabler. This means that most of the files on my regular laptop is also on the home laptop, and it has the same context. ...
I think it’s a miracle to see the sheer number of technologies that can come together with AI agents orchestrating them. I’m right now on a flight from Brussels to Dubai, and the Wi-Fi works. So, I’m dictating this blog post via PixelBoard, an AI-coded port of Gboard that lets me use Gemini for voice typing on Android (which is quite good!). I’m also browsing my Asterix comic book collection. These are on my Windows laptop in Singapore, which I’ve connected via Tailscale. I have no idea how to configure Tailscale, and ChatGPT did that for me. BTW, Tailscale is one of those services that I didn’t see a use for until I used it, and now will never turn it off. It creates a VPN between my phone, traveling laptop and home laptop, so I can browse files, SSH into each other, run HTTP servers, etc. All securely. ...
The Innovation team has built a few more demos since the last update. Three interesting learnings: We can speak in one language and be heard in another, live, in a normal Google Meet call. A person in another city can use their hands and a phone to sculpt a 3D object on your laptop. AI can search what was heard, not just said, and can check scientific claims by actually reproducing them. New capabilities Translate a live meeting into almost any language (Hritik). At Friday’s VIA talk, I spoke and the audience heard Filipino, Hindi, Tamil and Telugu with a short delay. Hritik built a desktop app that creates a virtual microphone and speaker for Meet. It translates both ways: what others hear from you, and what you hear from them. It took him a day or two to vibe code, and comes as a Windows, Mac or Linux app. I estimated about 0.6 US cents a minute in my trial. ...
The Innovation team built a few more demos last week. Three interesting learnings: Construct a 3D world you can walk through - from a picture. Real-time video analytics is increasingly easier with decision models. Small models supported by rules tend to perform well. 3D Worlds Turn one photograph into a 3D world. Jivraj used NVIDIA Lyra and other world models to create 3D worlds (from pictures) that you can walk through. ...
Sometimes, you need multiple approaches for different parts of a problem. Increasingly, agents are making this easier. For example, at MSCI, we’re using Google Translate to translate PDFs. Sometimes it does a great job. For example, here’s Hyundai’s E&C Sustainability Report, 2026, in Korean. It was translated perfectly by Google Translate. At other times, it does a terrible job. For example, here’s Pakistan’s Power Cement Annual Report 2026 in Urdu: ...
Our Innovation team built a few demos over the last couple of weeks. Three interesting things: Agents can build navigable 3D spaces Specialized vision models can outperform frontier LLMs on narrow tasks Simple search tools can beat elaborate document-retrieval systems. New capabilities Build an interactive 3D room from an image. A coding agent used Blender to create four increasingly detailed, navigable rooms. Click the image below and explore the final room: orbit, walk inside, inspect objects, or download the model. ...
Python 3.15 released with a TUI text adventure you can run via uvx --python 3.15 whatsnewt. I love text adventures, but not so much that I would spend a weekend learning a new game rather than playing Minecraft. So I had Claude and ChatGPT “play” it for me. It’s more a reading experience than a playing experience, but that can be pretty engaging, too. What I learnt by reading it (that I didn’t know before) was: ...
On 28 Feb 1990, Calvin and Hobbes played Scrabble. Calvin: Ha! I’ve got a great word and it’s on a “double word score” box! Hobbes: “ZQFMGB” isn’t a word! It doesn’t even have a vowel! Calvin: It is SO a word! It’s worm found in New Guinea! Everyone knows that! Hobbes: I’m looking it up. Calvin: You do, and I’ll look up that 12-letter word YOU played with all the Xs and Js! Hobbes: What’s your score for ZQFMGB? Calvin: 957. ...
A colleague was using an agent to classify paragraphs as titles, sections, figure captions, etc. He also asked it “How confident are you of your answer?”. Interestingly, the confidence was consistently high, typically ~95%. That got me curious. (Actually, no that didn’t get me curious - I saw Germayne and Joshua from Gojek doing this in a fantastic session at Lorong AI, but this is my story and I’ll tell it my way.): ...
VLC 3.0, there’s a Playlist view that can show the title, album, etc. But the Composer field is not supported. That’s a big deal for me. I track composers for ~1,200 Tamil, Hindi, and Telugu songs in that field. I really need to see and sort and filter by composer. (“Really need” like I “really need a cheesecake”, not like “really need a charger”.) Software’s so easy to change, so I asked ChatGPT: ...
Sarthak interviewed me at Data Hack Summit 2026. Here’s the Q&A. Interviews and panel discussions force me to think quickly and tend to crystallize thoughts I haven’t yet fully processed. I really enjoy them, and this was no exception. Q: Any key takeaways you’d be taking home? Knowledge graphs may not be as hot a topic as people might think, that’s definitely one. Forward-deployed engineers have not yet caught on as much as I would have thought they had. Surprisingly, no one mentioned outcome-based pricing as a theme, which is interesting; I’m guessing that there’s still a lot of pressure against it. And loop engineering does seem to have potential, but the verdict is out. Q: Is judgment now more valuable than analysis? ...
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.) ...
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.) ...