I work with VCs to scale their pipeline. See https://xitter.cf/t.co/vT2Y1rcrB1

Lisbon, Portugal
Joined October 2016
The feeling when you are only 5 hours away from reset and you are at 99%....
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On my way to HackMeridian to build the future of international cooperation using @StellarOrg
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Jensen Huang has a message for Germany
Jensen Huang has a message for the UK
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Level 5 of the AI pyramid is the roughly 5,000 people inside the AI labs who work with internal models far beyond anything public. To settle P vs NP or find zero days at scale you need those, while most of the work that matters for you and me happens one level below.
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My recommendation is to aim for level 3 if you create, 4 if you research. Full article: medium.com/@marcelmueller/th… to talk about where your company stands: jadenx.com
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Level 4 of the AI pyramid is people doing frontier-grade work with public frontier models. Several researchers I know outpace their peers on quality and pace because they use LLMs properly in their research, and for most applied science the public models are already enough.
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Level 3 of the AI pyramid is professional users. The good developers I work with use LLMs every day and get better step by step, and freelancers without restrictions just try things until AI gives them real value, without fifteen courses or an upskilling program first.
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In my consulting work with enterprises, including regulated ones, I usually see people one to one and a half years behind the strong freelancers and developers in my circle, both in which AI tools they use and in how good they are at using them.
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Public frontier models already get you very close to the top of what AI can do today, and where you end up depends far more on how you use them than on which models you can access. I think of AI users as a five-level pyramid, from people who never used AI up to the labs.
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Level 2 of the AI pyramid is casual chatbot users, about 1 to 2 billion people by Karpathy's estimate. In my home area maybe 20% have tried ChatGPT, and for most of them it stays a chatbot they asked a few things once, a bit like a better Google search.
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Level 1 of the AI pyramid is everyone who has never really used AI, about 6 billion people by Karpathy's estimate. Where I grew up in rural Germany, most people know AI from tabloid headlines about AI craziness and drones, so they are a bit intimidated by it, which I understand.
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Andrej Karpathy recently described the gap in how people understand LLMs as a sharp funnel, from about 6 billion people who barely touched them to about 5,000 with internal frontier systems. I agree with most of it and would split his top level into two. xitter.cf/karpathy/status/210936…
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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Most people who say they use AI are on level 2 of 5. The models that get you to level 4 are already public, and enterprises tend to be one to one and a half years behind experts in using them. I drew the five levels so you can see where you stand 🧵
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If AGI makes me obsolete I will get back to producing music
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Let's assume for a second "AGI AI will kill SaaS". Because with AGI "we can build all tools with just prompting". Thought experiment. How would that look like?
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For mid market and enterprise: Is the sum of the costs of my AI to build it + corporate clusterfuck while building it + meetings to escalate + costs of piece of mind x risks + annoyance by underachievers nitbicking about details < SaaS costs over lifetime. If yes build, if not buy
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Knowing all three groups I would almost say: For uncritical stuff you can live without: build, for critical stuff the question is mostly driven by "how outrageous is the price for that stupid SaaS" and "how much ongoing clusterfuck you are going to have to endure".
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