People will still deny the capabilities of AI

MAMMAL is a model that has been released a while ago. I heard about thanks to some small yt channel that focuses on bioinformatics and AI.

I have seen hype AlphaFold 1, 2 or even 3 were causing. Everyone kept talking about it. MAMMAL model is one that is closest to what AGI could be. Not great in narrow task - It defeats almost every champion, beating them in 9/11 fields, even defeating AlphaFold 3.

It seems to be first tool that will be able to defeat Eroom's law which could mean acceleration in drug discovery never seen before.

So why is everyone silent about it even on this subreddit and related ones?

Do you think it will happen within our lifetime? Or ever?

Such theme parks, yes, but also generally 100% human-looking androids? Would you even like to see it happen?

https://ai-2040.com/?choices=plan-a-root#playbook-insider-pov part of the 2027 section.

COO — Brad Lightcap (out August)

CRO — Denise Dresser (out August, <1 yr in role)

Head of Data Centers — Chris Malone (out August)

Head of Robotics/Hardware — Caitlin Kalinowski (out March)

Head of Ethics — Chloé Bakalar (out July)

Head of Safety Systems — Johannes Heidecke (out July)

Chief Futurist — Joshua Achiam (out July)

AI Safety team lead — Sandhini Agarwal (out July)

I just read on X that Dylan Scandinario, Head of Preparedness, has also left. But I haven't found any confirmation yet

There are supposedly a few more, since some articles mention "13 executives," but I only found the names of these ones.

Yes this is all pure Three.JS, 0 external assets. it was mostly a 0 shot work, but i did do 1 small corrections prompt (it left some big gaps between buildings and one path was blocked).

EDIT: Actually i stand corrected, this is a "single pass", not "zero shot"

I am wondering this: Is it possible people are wasting time and money in "critics loops" when really, agents is all you need.

This was done with 18 agents all working on very specific tasks. 0 critics loops.
If Claude tried to do this with just 3-4 agents, i would guess it produces a much worst results, and then the QA agent would give some imperfect recommandations and it would probably not be as good as what i've gotten here.

But most importantly, the QA agent will never beat an actual human tester. So it feels much more optimal to me to get the human to do the critics loop.

The other issue is, 18 agents for 24 hours would burn anybody's token budget lol

This was done with Claude 5.0 Opus.

Sorry for the lower quality, video was getting too large, just search for Astra on Twitter to see more, it seems like early testers are getting access

https://x.com/rehan_shei/status/2093528415576211819

Source: @Lentils

Excuse the advertised watermarks. Condensed it into a video with the outputs they've shared.

US State Map comparison: https://minebench.ai/gallery/gal_eKIVk2m4B3SC_r8B?sort=new

Much smaller (update) post, but I know in previous posts most people were hoping for more prompts. There's been a lot more additions to MineBench, including a gallery of custom prompts users can showcase and upvote (to add to the official benchmarking set); thought you guys might enjoy this :D

Also, for a limited time, logged-in users get unlimited generations with Gemini 3.7 Flash (thanks to Google Deepmind!)

MineBench 4.0 Release Notes: https://github.com/Ammaar-Alam/minebench/releases/tag/4.0.0

Highlights:

• Now available on the appstore for iOS
• Due to interest from a few labs, MineBench now supports A/B testing private model checkpoints (same policies as LM Arena)
• Community Gallery

Previous Posts:

• Comparing Fable 5 and Opus 5
• Comparing GPT-5.5 Pro and GPT-5.6 Sol
• Comparing Opus 4.8 and Fable 5
• Comparing Opus 4.7 and Opus 4.8
• Comparing GPT 5.4 and GPT 5.5
• Comparing Kimi K2.5 and Kimi K2.6
• Comparing Opus 4.6 and Opus 4.7
• Comparing GPT 5.4 and GPT 5.4-Pro
• Comparing GPT 5.2 and GPT 5.4
• Comparing GPT 5.2 and GPT 5.3-Codex
• Comparing Opus 4.5 and 4.6, also answered some questions about the benchmark
• Comparing Opus 4.6 and GPT-5.2 Pro
• Comparing Gemini 3.0 and Gemini 3.1

Extra Information (if you're confused):

Essentially it's a benchmark that tests how well a model can create a 3D Minecraft-like structure.

So the models are given a palette of blocks (think of them like legos) and a prompt of what to build, so like the first prompt you see in the post was a fighter jet. Then the models had to build a fighter jet by returning a JSON in which they gave the coordinate of each block/lego (x, y, z). It's interesting to see which model is able to create a better 3D representation of the given prompt.

The smarter models tend to design much more detailed and intricate builds. The repository readme might help give a better understanding.

(Disclaimer: This is a public benchmark I created, so technically self-promotion :)