Things I Learned - 28 Jan 2024

This week, I learned: ⭐ OpenAI’s prompt engineering strategies are an excellent start for prompt engineering. A few lessons: Use detailed system prompts, often containing the entire instruction set, if it won’t change over the course of a conversation. “… summary of the prior conversation could be included as part of the system message” is an interesting history compression tactic. OpenAI summarizes books by recursively summarizing sections and maintaining a running commentary of the summary so far. Dan sends Google documents with essays instead of emails. This allows people to comment on it. But commenting is a culture and not many people do it. Adriano does it a lot and we’ll. Dan and Adriano actively converse on GitHub issues llm-guard is an LLM content validation tool.

Auto vs GPT

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. ...

Things I Learned - 21 Jan 2024

This week, I learned: When comparing Mistral with 4b quantization vs unquantized: 2 responses were significantly shorter and fairly different 1 was identical 1 was almost identical but shorter by a few words 1 was slightly longer and fairly different #PREDICTION As humans have more conversations with LLMs, they will replace video watching and interactive gaming with conversation based role play. New game genres will evolve Lilac is an LLM-based data curation tool. Use it to search by concept (e.g. PII, duplicates, etc.) and then drop/update the results. Lungs have a Hausdorff dimension of 2.97 – giving them one of the highest surface area to volume ratio. Brains are 2.8. Sierpinski Pyramid is exactly 2 – which is weird. To solid-paint twice the size, you need 4 times as much paint. How I write podcast. Tim Ferriss High bars are constraints. I set the strongest constraints against the scarcest resources. Like reputation Being a category of one is more defensible than a competitive advantage Content always beats presentation. When in doubt, push for more interesting content Regular publishing improves thinking To build a habit, do less than you think you can do. That makes it easier to build momentum on the habit and sustain during crunch times There is a lot of mediocrity in the world. If you’re doing something (in a winner take all ecosystem), be the best. Top lawyers are exceptional proofreaders. They are able to see what is unclair, and what is redundant, and what has loop holes very quickly. Forcing yourself to cut down from a thousand words to 200 to a paragraph to a sentence takes you through a phase transition where you discover something unexpected The more outrageous the question, the more likely it is to be useful in generating a new perspective Eleven-labs speech synthesis with voice cloning is at the uncanny valley. With two 5-minute samples, my voice sounds a fair bit like my voice but is very clearly not my voice. I find stability ~ 30%, similarity ~ 80% and style ~50% gives a reasonable outcome. But the default voices (e.g. Joseph, George, Charlie) are excellent. Practical AI podcast: AI predictions for AI by API is the norm today and will grow Just having AI is no longer a differentiator AI is part of life, not just work #TODO Explore quickdrop from Stability for Maruti #TODO Explore Codium VS Code plugin and Continue.dev Hybrid systems that combine stats, ML, DL and AI models will grow AGI and AutoGPT resurgence RAG will continue to be a focus GPT4 will be beaten by open source models. Special purpose models beat it already Self hosted and cloud hosted models will grow for security Small language models will grow Productivity will be enhanced rather than replaced Multi modal models will grow Cost efficiency will grow in focus GPT Builder help explains how the GPT Builder updates GPTs - including some very interesting prompts

What does Gramener ask ChatGPT?

I looked at how Gramener uses ChatGPT Plus by evaluating 600+ chats asked over 3 months from Oct 2023 to Jan 2024. The team asks 6 questions a day. We don't track who or how many actively use ChatGPT Plus. This also excludes personal ChatGPT accounts. Still, 6/day is low for an entire team put together. The questions fall into 8 categories. Category%Excel, data exploration & analysis25%Text extraction and summarization13%HTML, CSS, or JavaScript code13%Python code13%LLMs, AI and use cases9%OCR and image analysis9%Generate images, logos, and designs7%General knowledge, policy & environment5%Audio and translation5% Here are some questions from each category - to give you an idea of emergent ChatGPT Plus usage. ...

Things I Learned - 14 Jan 2024

This week, I learned: Transparent LED screens will be useful in windshieds to display maps as we drive. Marimo is a reactive alternative to Jupyter notebooks that saves files as pure Python. To run an org-specific chatbot on your own LLM: (via awesome-chatgpt) opengpts - but it doesn’t support auth chatbot-ui - but Supabase is hard to install anse - but it doesn’t support auth ChatGPT-Next-Web - but it doesn’t support auth Python 3.13 gets a store and copy JIT If an npm package adds another package as a dependency with version “*”, target package cannot unpublish ANY version! So this is a way of freezing EVERY repo and preventing unpublishing of EVERY version – an unintentional flaw in the npm design. via Quantization is better than fewer parameters. So prefer high parameters (e.g. 70b) and quantize to 4-bit. In-browser playgrounds has compiled WASM versions of Python, PHP, SQLite. Happiness Lab podcast. Happiness lessons of the ancients Talking to strangers makes us happy Giving money makes us happy Free time makes us happier than working hard Tangi Domain-specific models being beaten by general purpose models is a phase. It will reverse towards domain. AI will potentially help build and understand domain-specific models Models are evolving so rapidly that humans cannot interpret models. We need a process to interpret models! xAI, Responsible AI, Physics-guided or Knowledge-guided models (called grey box models) are therefore a trend CS papers Don’t review other papers, certainly not other fields. Disregard measurement errors. When CS papers get applied to climate, manufacturing or biology, we’ll worry about Interpretability Domain-specific mechanics. (Introduce that into the training as a constraint.) Many domain experts are using AI to UNDERSTAND their process. Need to explore Uncertainty IB adds context to make learning applicable. But that distracts from the core learning, and if there’s a gap it widens Most data science courses teach “Python science”, not data science. They teach a bunch of models. They don’t teach how even one kind of model e.g. LSTM works. Most coaching programs today teach FAMILIARITY with problems, not critical thinking Most of current education will become redundant thanks to LLMs. For students AND teachers Coding will become irrelevant Cognitive thinking, reasoning, human relations, systems thinking will become more relevant Troubleshooting will become more important. AI is not self-diagnosing. I would hire someone who can figure out something is going wrong, diagnose what’s going wrong, and fix it #TODO Hire for troubleshooting ability. Give a Q, an A, and ask them to figure out if it’s wrong, why, and fix it All my exams and quizzes are open book, open ChatGPT. Onus is on me to give a problem that forces you to think. #TODO Write a question paper that is ChatGPT proof. Exploring AI could be a ToK subject. “How to interact with an AI?” We need a manual on how to use AI. Like Simon Willison says Content doesn’t suffice. You need pedegogy. What to serve you at what time, how, how to assess. Lots of businesses are filling this gap Students get great confidence when a teacher points to online content and says, I"ll tell you WHAT to see" and COMPLEMENTS that in their class “The map is not the territory.” Most people confuse sample mean for the actual. #ASK Parameter estimation -> Signal estimation -> State estimation Stats vs DL differ in that There is no notion of a defined “truth”. Hence reliability is not measurable Parameters have no value. Hence interpretability is ignored. #TODO Read 2020 National Education Policy. It’s quite modern. We need a manual on self-learning too Listening is not learning. You know only if you implement. Levels for students: I can solve it. I can explain why it works. I can find alternatives. I can apply it to a new area, reformulating (requires imagination.) For teachers, you also need: Responsible learning (extra careful about what to teach and how to teach, to exceite them, to teach at THEIR level). Show the universality and connecting to other concepts. E.g. noise reduction with FT is like using water to remove dirt. Transform to water domain, remove dirt, transform back to air domain. It’s better than dusting clothes to remove clothes. Washing machine programs are just different models of removing noise in the water domain. Teach people who WANT to learn AND who will APPLY it long-term. That’s what maximizes impact Grad students are more satisfying that way. Else, it is WASTED effort. (Not that it’s a bad thing for the student, but the effort IS wasted for the teacher) Therefore, I believe students should have general engineering first, and let students pick specialization later. Some universitie are doing that. #THINK Students remember my philosophy more than my content. We impart character, not just knowledge. Astrology and horoscopes serve a different function. They provide explainability, not predictive ability. As the world becomes less explainable, the need for astrology will grow. Explainability is about creating STORIES that fits data plausibly. It has nothing to do with data or truth. Explainability and predictive ability and reproducibility are all different. Maybe, Science is about the latter two, less about explainability. Astrology is a model. The map is not the territory. It’s an explanatory, not a predictive model. #THINK Therefore, my lessons are just explanations. Stats about experiments are STILL explanations. They are NOT reproducible or predictive. Hence not yet science The meaning of our life is the transformation we undergo in our lives #TODO Read “The Journey of Souls” by Michael Newton. A hypnotherapist #TODO Try regression therapy / hypnosis. Record it and listen to it. Just for fun! Rohini Deshpande Slam book was the Facebook of the 1900s Prepared mind is an extremely powerful tool for learning. Practice prepared mind When women drop out of education or career, that is also a waste from the teacher and system perspective The time for career growth is the same as child bearing time for women. That’s not true for men. But child rearing can be done by either. That’s not recognised. It’s 0K for a man to raise the child and make the home and 0K to treat that as the default Since men are more senior, it’s usually logical for them to stay in their jobs. That’s a systematic bias. When seniors advise women to step back. they respect it. That widens the barrier. Why not eliminate that situation? Be proud of the working women in the family Stats are just a symptom. They don’t explain the cause. (Map is not the territory.) Explanations are what really helps us fix the cause. Hence stories are important. Read Tinker Tailor Soldier Spy RV Athimber health tips: Eat foods with low glycemic index Eliminate free salt completely Voyage AI Embeddings have a higher quality, similar price compared to OpenAI embeddings. There’s a clear benefit to replacing text-embedding-3-large with voyage-3-lite. There’s a 200 MTok free tier currently. mixtral-offloading cleverly loads only the model layer required at any point, letting you run Mixtral 8x7b on Colab Free and on 16GB GPUs. This notebook runs on Colab Free too. CodeGPT is an alternative to Github Copilot that can use any LLM.

Things I Learned - 07 Jan 2024

This week, I learned: Raman Srinivasan: IITM Profs and MTechs are spinning off deep tech startup. Agnicool is an example. They 3D print rockets with ceramic composites from Germany Sriram Krishnan (Facebook), Balaji Krishnan invested in pre-Series A Govt is de-regulating space tech and geospatial. Talking of de-regulating nuclear. ISRO seems to be focusing on cutting edge while others are doing commercial stuff There are about 100 space tech startups in India You can build your own modular reactor Geospatial AI is a big opportunity Have released a lot of 10m resolution geospatial data almost for free success is about getting NO factor wrong. Failiure just requires one aspect to fail. Brand, business savviness, financial stability, tech superiority, deep pockets, managing Gvt, long-term mindset, etc. - all of these matter. That’s what made TCS monopolize the exam business in India. For deepening AI, we need, Talent, Data pipelines, Hardware Next wave is LMMs, not LLMs What’s not captured in LLMs is verbal knowledge and tacit knowledge (in people’s fingertips). India is rich in this. The road to tacit knowledge has to go through India We can get a welder to train a simulator and pay the welder We can get a storyteller to tell a few stories and train oral LLMs Tacit knowledge will have to cover robotics. Train robots to bring coffee in just 50 demos! “Project delays are within the ‘rulebook’. Buyt paying skilled welders for ship building or nuclear pressure boilers needs breaking 100s of rules. Once they get certified, they abscond to Iran or somewhere.” TCS Ignite started in 2006 by Ramadorai. Before recession. “There is going to be a talent shortage. Recruit from next rung. Science not engineering graduates. Break HR monopoly and corruption - colleges became placement agencies. Fewer people per college. Across the country. Train them.” Tried in 2000. HR refused. Business refused. When Chandra was identified, Ramadorai took it up himself as a challenge. Ramadorai had very precise attention. Sat 7 am calls. “What are you doing?” 2 min call. Enough to energize. Would exchange and ask for brief updates. He reads and responds. You get a decision in a few hours early in the morning. No decision bottleneck He wanted to know ALL the details. Very precise, small, frequent probes on what’s happening. E.g. one 6 am, he called. “What are the lectures planned for today?” He expected I would know this. If not, next time I would be prepared. He would call another person and ask the same question. So I updated the others. I’ve never seen anyone with that bility to ground-truth. He wants 10 birds from 1 stone. Get BSc, but don’t comprimize. Get the best 2 per college but a full batch size of 500. We became the biggest training program as a single batch – with 500 people. He wanted to demonstrate scale. HR and CFO said, ‘You recruit first. Then we’ll give you money. We don’t think it’s possible." We had anchor colleges and brought people from other campuses. We did digitized exams. Took big servers to the campus. Fully digitized with full auditability. Plugged the laptops into the college LANs. Kids had never used a mouse. We had to teach them. We said, “Don’t worry. These are logical questions, not questions. We’ll pay a full salary.” We learned that 1 out of 2 didn’t even join. Many took up a Masters. They didn’t want to join the workforce. Unless they’re desperate economically. Even poor parents, if they can afford to support you at home, they do that. It’s weird. Every weekend, we visited a few campuses. 71 locations across the country. Found the NSS college in Ottapalam (Kumbakonam of Kerala. Cultural centre.) College had a nice nice Math dept website. I said “Mr Ramadorai, this looks promising.” One Sat morning, he called and said, “When are you going to Ottapalayam?” We landed in the college. There was an impromptu communist student strike. We made 38 offers out of 100 who took the exam. Never had such a high conversion. One girl, whose father was a coolie, jad communication issues. Had a colleague talk in Malayalam. She was an amazing success. My colleague Murali made a documentary about her. We started in July. By Dec, we had 500 joinees. No one is doing such a thing now. You have to get dozens of things just right. Compromising on even one kills it. Ramadorain loaded it with multiple objectives. Fresh talent. Low cast. Sustainable. He kept pushing for innovation. I pushed back. But he was persistent. Over time, I came around and we started innovating. We restructured training program around innovation. Like a YCombinator. That unleashed extraordinary energy. Several of the kids are running their own startups. Ramadorai was very supportive of that. The assessment product came out of that. First batch, everyone was very sceptical. We got a lot of pushback. They’re dumb. Ethics issues. Communication issues. Lot of prejudice. So we got them to do internal recruitment till they were satisfied. An internal placement market. THEN reputation was set. I told them, always stick to the dress code. One weaver’s sone wore a bright yellow polyester T-shirt. I asked him why he didn’t stick to the dress code. “Sir, it’s my first T-shirt.” Ramadorai tracked how many became billable. We were unable to place 70. He said, give them 1 more month training. Then we placed 64 of the 70. He said “Do something about the 6. I want 100% placement.” We absorbed them as a teaching assistant. One was a weaver’s son. One was a PC’s daughter. A mestri’s son. A shopkeeper’s daughter from North Madras. None could speak English. They learned to code and helped build the exam software, with Srikumar who was a brilliant Java coder. That gave us the confidence that these are good kids, just from the wrong part of town. With a good guide, they’re very capable. We bought a bunch of Nintendo Wiis. Kids have to play. He asked for a welding simulator. “Velu the Welder”. The kids built it using the Wii. We got the most accomplished welder spend an afternoon at Ignite. He ripped us apart. 4 hrs non-stop. He told us EVERY thing wrong with it. Blasted us. I told Murali, “Let’s call it a toy. It’s not a simulator. Let kids play.” He said, “I want to show that it can be done!” Murali churned out rapid iterations in a frenzy. Ramadorai said, “Deploy it in the field.” So we went to all kinds of remote places like Gondiya below Nagpur. Surprisingly cosmopolatan. Junction of EW and NS train lines. We set up welding institutes in each. It was on the cloud. We could track everything. KPK killed the skills. Hard core bureaucrat. His view is colonial. Ignite philosophy is about unleashing energy of people. Colonoial model is about controlling people by keeping them poor. KPK and Chidambaram had that mindset. Ramadorai brought him in as Secy of NSDC. he killed the policies Modi did the first cut by creating a ministry. KPK ensured that it never gew. Like Yes Minister. Made sure nothing moved Had Govt not changed, he would have been Secy Finance. He was seen as Chidambaram’s blue eyed boy. People know he was associated with NSE scam. Ramadorai helped by bringing him into skills He is very smart. Knows the IAS machinery in and out. Lives and breathes that. H Ramadorai likes him though. Put him on board of Tata Consumers. NSE Scam. He’s part of the cabal with Ajay Shah. Private trading firms could co-locate within NSE and could make a huge amount of money. KPK ran some of this by proxy to fund Congress. But he left no fingerprints. But everyone knows it is him. He was running Chitra Ramakrishnan by proxy. He was the Himalayan Yogi. Ignite continued with unwavering focus. Kept increasing the kind of focus. We had a 99.5% success rate in placements. Just a handful of failures. Ramadorai has written about Ignite in “The TCS Story”. My Dad translated it in Tamil. It’s not a typical business biography. Worth reading. Should be a mandatory course in MBA courses in India. So many lessons. You have to read it knowing how Mr Ramadorai speaks. What is NOT said is just as important. Ch 5 is the thinnest - on the IPO. It is packed with so much stuff. Unless you know, you won’t understand. “Tatas got the Govt to change a tax law to make the IPO meaningful.” Behind that, there’s a lot. You have to be alert to catch the sentene. He won’t brag, or talk about the significance of some of these. Book is packed with dense insights. Unless you ARE LOOKING FOR IT, you’ll miss it. Worth reading SEVERAL times. You need a foot-noting. Currently reading Pasquenelli – Social History of Artificial Intelligence. Eye of the Master. Worth reading. I’m not Marxist by belief but they get some things right. Surprised how vibrant the European left is. “If someone is doing manual work, there is tacit knowledge that automation captures.” India doesn’t need self-driving cars. But a farmer would like a gaming controller that ploughs his fields while he sits under a tree. Semi-intelligent machines that removes the burden of hard labour in the country. Once a year, for a few weeks, I do manual labour. People are under-nourished. People typically work 5 hours a day. Not enough muscle mass. So use them for what they’re good at I’ve seen the power tools. When Chinese power tools became cheap, the power welding became much more efficient. Everyone has become a monkey with power tools. They charge per inch. They know how to leverage the tech for economic benefit. Just bring in the power tools and rapidly finish and make money. But there are sections that are still poor and haven’t made the transition. How can we create pathways for them? How can AI help? Anand: Why not use a gimball. RS: Good idea. Role modern psychologist DW Winnicott on ChatGPT (like Socrates) E.g. You don’t need a perfect mother. A good enough mother is better Similarly, why not a “good enough” Bharat mata than a perfect one? To persuade someone, align it with their identity. ChatGPT 5 technologies of interest according to Gartner’s latest hype cycle: GitOps Internal Developer Platform Graph Data Science Open Source Program Office Value Stream Management Platforms Gemini is an alternative to the Web. Sort of like Gopher, but recent SALI - Standards Advancement for the Legal Industry - has standards and ontology/taxonomy for legal documents, including patent litigation. Walking new routes habitualizes fighting fear and preferring novelty ⭐ GPT-4 is bad at math. It gets ~60-70% of answers wrong. LMQL provides a constraint-based query language for interacting with LLMs. It uses token masking, which is clever. Hollywood writers signed a deal that limits AI in script writing. It’s primarily aimed at protecting script writer wages. Adobe Firefly offers a “generative fill” that lets you remove or paint new objects into an image. I’m awaiting text to vector images. Duet AI is Google’s answer to Github Copilot. Teachers are using LLMs to plan lessons, write emails to parents, create tests, adjust reading level of materials, personalize content with tools like MagicSchool, Diffit, Eduaide. WizardLM creates datasets for instruction tuning by cleverly using LLMs to create new prompts. Deita is an approach to improve instruction tuning datasets. Dhyeya: Attack on Titan is as good at Death Note Jaidev: Long car drives are a good place to explore new song genres. Try in taxis Same radio channels may have different frequencies across cities. Vividh Bharati is 100.5 FM in Chennai and 106.4 in Delhi Things to explore: Radio for new songs Clubhouse Twitter Spaces Instagram reels YouTube reaction videos (e.g. atheist, Indian songs, etc.) Stand-up comedies (Ricky Gervais, Louis CK, Jordan Peterson) Porn artists are at risk because of Gen AI

Books in 2023

I read 52 books in 2023 (about the same as in 2022, 2021 and 2020.) Here’s what I read (best books first). Fiction The Kingkiller Chronicle. I picked it up before a flight to London in 2014. Read it through the flight. Read it late into the night at our AirBnB. Skipped my workshop prep. Read it during the workshop breaks. Read it on the flight back. And I re-read it every year or two. The language is beautiful and the story gripping. I feel miserable this series isn’t complete. The Name of the Wind by Patrick Rothfuss ⭐⭐⭐⭐⭐ The Wise Man’s Fear by Patrick Rothfuss ⭐⭐⭐⭐⭐ The Stormlight Archive. Another series I re-read regularly. Brandon Sanderson takes the scale of the story up a notch in every book. Rhythm of War by Brandon Sanderson ⭐⭐⭐⭐⭐ Words of Radiance by Brandon Sanderson ⭐⭐⭐⭐⭐ Andy Weir’s books. Since my daughter re-reads The Martian (laughing loudly), I picked up Project Hail Mary. It’s a brilliant depiction of alien physiology and communication, with a weird kind of humour I love. Project Hail Mary by Andy Weir ⭐⭐⭐⭐ The Egg by Andy Weir ⭐⭐⭐⭐ The Martian by Andy Weir ⭐⭐⭐⭐ Red Rising Saga. A pleasant discovery of a new series. Somewhat like The Hunger Games and Divergent. Red Rising by Pierce Brown ⭐⭐⭐⭐ Golden Son by Pierce Brown ⭐⭐⭐⭐ Morning Star by Pierce Brown ⭐⭐⭐⭐ Blake Crouch’s books. The two I read were both time-travel related and I love that genre. These do a great job of exploring some of the deeper implications of time-travel. Recursion by Blake Crouch ⭐⭐⭐⭐ Dark Matter by Blake Crouch ⭐⭐⭐ Ready Player One by Ernest Cline ⭐⭐⭐. It’s as good as the movie with slightly different scenes. The Reckoners by Brandon Sanderson. Another series I re-read. Steelheart by Brandon Sanderson ⭐⭐⭐⭐ Firefight by Brandon Sanderson ⭐⭐⭐ Calamity by Brandon Sanderson ⭐⭐⭐ The Year of Sanderson. Brandon Sanderson’s kickstarter raised $41m for 4 books this year (mostly Cosmere). The stories themselves were OK but the hints they drop about the Cosmere are invaluable. Yumi and the Nightmare Painter by Brandon Sanderson ⭐⭐⭐⭐ Tress of the Emerald Sea by Brandon Sanderson ⭐⭐⭐ The Sunlit Man by Brandon Sanderson ⭐⭐⭐ Fullmetal Alchemist by Hiromu Arakawa. After Death Note, it felt like a let-down when it started. A mundane story. Then it grew funny. Showed shades of a much deeper story. I’m mid-way through the series and I’m hooked. Fullmetal Alchemist, Vol. 1 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 2 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 3 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 4 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 5 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 6 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 7 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 8 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 9 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 10 by Hiromu Arakawa ⭐⭐⭐ Fullmetal Alchemist, Vol. 11 by Hiromu Arakawa ⭐⭐⭐ Mono no Aware e altre storie by Ken Liu ⭐⭐⭐. A nice short story Traitors Gate by Jeffrey Archer ⭐⭐⭐. A well-writter fast-paced average story. Mistborn: Secret History by Brandon Sanderson ⭐⭐⭐. Average story but with lots of “secrets” about the Cosmere. Asterix and the Griffin by Jean-Yves Ferri ⭐⭐. Some good jokes but not as good as the original series. Non-fiction ...