Patrick J. (@xrb) header
Patrick J. (@xrb) profile picture

Building production geospatial AI for insurance. Zurich & Lausanne. ETH Zürich CS alum. Views my own.

Zurich & Lausanne, Switzerland
Joined April 2008
This 👇
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
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Prithvi running in orbit is a quiet but important GeoAI milestone. Less latency, fewer downlinks, more on-board filtering for floods, fires and other events. Foundation models for Earth observation are moving closer to the sensor. #GeoAI
NASA's Prithvi has become the first geospatial AI foundation model in orbit! 🛰️ This model, which was developed by NASA’s IMPACT AI team at #NASAMarshall, could improve satellite observations of floods, wildfires, and more. Read the full story: go.nasa.gov/3QXbyY4
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Even now, I'm a strong proponent of augmentation over automation in coding and AI in general. Iron Man suit, not Iron Man robot. Fully with @karpathy on this one. #vibecoding #AI
Andrej Karpathy at YC AI Startup School: "build Iron Man suits, not Iron Man robots." i've been watching builders ship and builders stall. the shippers are still coding. they wear the suit. they direct a team of agents and the keys stay in their hands. the stalled ones became the robot. they only prompt now. the muscle that catches when the model is wrong has gone quiet. there is no neutral way to use AI. you either get sharper or you get hollower. most are getting hollower and won't notice till the chat won't open. how to stay in the first group, inside:
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GPT-5.5 and Claude Opus 4.7 are both pointing in the same direction: less prompt magic, more outcome delegation. For teams, the question is shifting from “which model is best?” to “which tasks deserve the expensive model?” #openai #anthropic #gpt55
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What happened to #social media? ↗ Promoted
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I am seeing lots of such messages on Reddit. Drawback of current #AI development is that humans (e.g. teachers) are not well informed about how to detect AI-generated content. They are using latest shit tool as if it was reliable. #ChatGPT
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1988: Math teachers protest against calculator use. 2023: Teachers protest against ChatGPT use. via @HeyImCastro
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Pre-#ChatGPT looking for a solution to a programming error: google the error message + a few keywords. Browse the results from Stackoverflow until there is a post that has a relevant solution. Try it out and test.
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No lookup to #Stackoverflow or any documentation. These are all internal knowledge stored in the model weights.
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To my appreciation, this is already past human level. Even a good computer scientist would not be able to write down a solution to a random question without looking it up. The backend used was #GPT4.
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Current state of #AI development.
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Just read (quickly) GPT-4 paper. Impressive staff. Solid improvement over GPT 3.5 and ChatGPT. Lost of comparisons on benchmarks presented, including a whole collection of exams designed for humans. cdn.openai.com/papers/gpt-4.… #gpt4
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Is it AGI? Probably not (fully). But who cares. Though top-10% on the bar exam without learning is massive (as a single example). Will it be a game changer? Surely! As has been #ChatGPT 3.5 months ago (my goodness, how fast).
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Just the multimodality with #ChatGPT model performance would be a game changer.
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