Vitor
Article
Vitor is a recurring person in the Astral Codex Ten archive, appearing 8 times across 8 issues between June 07, 2022 and April 01, 2026. The archive places it in contexts such as “Some readers pushed back: why did I think this? For example, Vitor :”; “I would like to check whether I have won my bet with Vitor about image model progress”; “one of my commenters, Vitor, asked”. It most often appears alongside Gary Marcus, Scott, Berkeley.
Metadata
- Category: People
- Mention count: 8
- Issue count: 8
- First seen: June 07, 2022
- Last seen: April 01, 2026
Appears In
- My Bet: AI Size Solves Flubs
- Open Thread 230
- I Won My Three Year AI Progress Bet In Three Months
- Meetups Everywhere Spring 2025: Times & Places
- Now I Really Won That AI Bet
- Open Thread 390
- Meetups Everywhere 2025: Times and Places
- Meetups Everywhere Spring 2026: Times & Places
Related Pages
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- Gary Marcus (5 shared issues)
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- Scott (5 shared issues)
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- Berkeley (4 shared issues)
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- Discord (4 shared issues)
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- Hamburg (4 shared issues)
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- Marcus (4 shared issues)
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- 131 Colonie Center (3 shared issues)
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- 200 Degrees (3 shared issues)
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- Aaron Kaufman (3 shared issues)
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- ACX (3 shared issues)
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- ACX (3 shared issues)
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- ACX MEETUP (3 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
Some readers pushed back: why did I think this? For example, Vitor:
Inline links: Vitor
I did end up agreeing to bet with Vitor. Let me explain why.
3: Related: does anyone reading this have access to the new Parti-20B image model from Google? I would like to check whether I have won my bet with Vitor about image model progress. If yes, I will write a post about it and give you good publicity. Please contact me at scott[at]slatestarcodex[dot]com
Inline links: Parti-20B image model, my bet with Vitor
At the time, I wrote: I’m not going to make the mistake of saying these problems are inherent to AI art. My guess is a slightly better language model would solve most of them…for all I know, some of the larger image models have already fixed these issues. These are the sorts of problems I expect to go away with a few months of future research. This proved controversial. Gary Marcus in particular has emphasized how challenging compositionality is for modern language and image models: @sama @gdb @Plinz @ylecun, \n\nEach of you ridiculed my recent title, but this is what the article was actually about: compositionality.\n\nYes, there are many kinds of progress in other directions. \n\nBut compositionality is at the core of intelligence. \n\nNo AGI without it. ","username":"GaryMarcus","name":"Gary Marcus","profile_image_url":"","date":"Sat Apr 09 04:34:37 +0000 2022","photos":[],"quoted_tweet":{"full_text":"Compositionality *is* the wall. \n\nEven “red cube” and “blue cube” on their own are represented unreliably; not one of ten images correctly captures the full phrasal description.\n\nThe images are beautiful, but no match for the precision of language. https://t.co/uvoXUtETwi","username":"GaryMarcus","name":"Gary Marcus"},"reply_count":0,"retweet_count":7,"like_count":54,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> And one of my commenters, Vitor, asked: Why are you so confident in this? The inability of systems like DALL-E to understand semantics in ways requiring an actual internal world model strikes me as the very heart of the issue. We can also see this exact failure mode in the language models themselves. They only produce good results when the human asks for something vague with lots of room for interpretation, like poetry or fanciful stories without much internal logic or continuity. Not to toot my own horn, but two years ago you were naively saying we'd have GPT-like models scaled up several orders of magnitude (100T parameters) right about now (https://slatestarcodex.com/2020/06/10/the-obligatory-gpt-3-post/#comment-912798). I'm registering my prediction that you're being equally naive now. Truly solving this issue seems AI-complete to me. I'm willing to bet on this (ideas on operationalization welcome). I responded to Marcus here, and I responded to Vitor by making a bet on whether AI image models could draw some compositionality-heavy pictures by 2025. The specific terms we agreed on: My proposed operationalization of this is that on June 1, 2025, if either if us can get access to the best image generating model at that time (I get to decide which), or convince someone else who has access to help us, we'll give it the following prompts: 1. A stained glass picture of a woman in a library with a raven on her shoulder with a key in its mouth 2. An oil painting of a man in a factory looking at a cat wearing a top hat 3. A digital art picture of a child riding a llama with a bell on its tail through a desert 4. A 3D render of an astronaut in space holding a fox wearing lipstick 5. Pixel art of a farmer in a cathedral holding a red basketball We generate 10 images for each prompt, just like DALL-E2 does. If at least one of the ten images has the scene correct in every particular on 3/5 prompts, I win, otherwise you do. DALL-E can’t do any of these: If I were being kind, I would give it the farmer in the cathedral. But I am being unkind, so the farmer in front of the cathedral doesn’t count. II. There are now at least four more AI image models available: Google Imagen announced May 2022.
Inline links: https://slatestarcodex.com/2020/06/10/the-obligatory-gpt-3-post/#comment-912798, here, bet, https://substackcdn.com/image/fetch/$s_!_gqe!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F6138ab0d-3a82-4eb9-a328-bf38ea0f6b10_632x784.png, announced
Contact: Vitor Contact Info: acxzurich[a t]proton[period]me Time: Saturday, May 3rd, 3:00 PM Location: Blatterwiese in front of the chinese garden (In case of rain we are inside the garden) Coordinates: https://plus.codes/8FVC9H32+VH
Inline links: https://plus.codes/8FVC9H32+VH
Commenters objected that this was overly optimistic. AI was just a pattern-matching “stochastic parrot”. It would take a deep understanding of grammar to get a prompt exactly right, and that would require some entirely new paradigm beyond LLMs. For example, from Vitor:
Inline links: For example, from Vitor
Thanks to everyone who helped operationalize, judge, and generate images for this bet. Vitor, you owe me $100, email me at scott@slatestarcodex.com.
4: Vitor, the counterparty in my AI bet, concedes but notes I have behaved badly: I slightly shifted terms to deal with model limitations, posted the original (premature) victory claim, retracted the original victory claim, apologized for the original victory claim, and posted the new on-time victory claim, all without consulting him. He’s right that this is bad behavior, and I let my excitement around figuring things out about AI get ahead of the fact that this was a real bet against a real person who deserved to be consulted on how I talked about it. I apologize.
Inline links: concedes but notes I have behaved badly
Contact: Vitor Contact Info: acxzurich[a t]proton[period]me Time: Saturday, September 6th, 3:00 PM Location: Blatterwiese in front of the chinese garden (In case of rain we are inside the garden) Coordinates: https://plus.codes/8FVC9H32+VH Notes: We have an email list and a signal group to announce ~monthly meetups. Write an email to be added.
Inline links: https://plus.codes/8FVC9H32+VH
Contact: Vitor Contact Info: acxzurich[@]proton[.]me Time: Saturday, May 9th, 3:00 PM Location: Irchelpark, next to the bridge over the pond. Coordinates: https://plus.codes/8FVC9GXW+723 Group Link: https://luma.com/acx-zurich Notes: We have an email list and a signal group to announce ~monthly meetups. Write an email to be added. All events are also listed on our Luma calendar.
Inline links: https://plus.codes/8FVC9GXW+723, https://luma.com/acx-zurich
Contact: Vitor Contact Info: vitor[.]felixx[@]gmail[.]com Time: Saturday, April 25th, 3:00 PM Location: We’ll be on front of the greenhouse in the Botanical Garden with a ACX MEETUP sign. Coordinates: https://plus.codes/586GHQ46+QP
Inline links: https://plus.codes/586GHQ46+QP
Backlinks
- Askwho
- Brands
- DALL-E2
- Edwin Chen
- Gary Marcus
- Google Imagen
- GPT-2
- I Won My Three Year AI Progress Bet In Three Months
- Meetups Everywhere 2025: Times and Places
- Meetups Everywhere Spring 2025: Times & Places
- Meetups Everywhere Spring 2026: Times & Places
- MidJourney
- My Bet: AI Size Solves Flubs
- Now I Really Won That AI Bet
- Open Thread 230
- Open Thread 390
- Organizations: G
- People: A
- People: E
- People: G
- People: V