Code World Models in Simultaneous Move settings like Capital Markets. DeepMind's CWM approach relies on standard MCTS/IS-MCTS, which assumes a single active player at each node.
This doesn't work in simultaneous-move settings like Orbit Wars (or order-book markets), converging to an exploitable pure strategy rather than a Nash equilibrium.
LeCun's JEPA, by contrast, is a learned neural world model, which lacks the determinism, speed, and debuggability of a code-based simulator. Thus, it can drift or predict illegal states, and you can't inspect why it made a prediction the way you can trace a Python function.
TL;DR: The benefit is better auditability and easier RL-like training.
The SM-MCTS extension fixes the first problem (decoupled UCB per player approximates Nash equilibrium instead of a pure strategy) while keeping the second advantage intact (a deterministic, inspectable code simulator).
I don't believe in the original sin of slavery in Western countries.
Slavery has been existed for centuries before and, despite being abolished by Western countries (hint: there were several wars were people lost lives), still exists in China, India, Indonesia, and a large group of Arab countries.
Please educate yourself more on this. Step out of your bubble.
Christian nations have created the cultural and technical achievements over the last thousands of years. There is nothing even remotely comparable.
Undead Labs has shipped nothing
Compulsion shipped South of Midnight topping at ~1600 players on Steam
Ninja Theory has shipped Bleeding Edge and Hellblade 2
and
Double Fine shipped Keeper and Kiln.
It's a net positive that these studios and this culture is gone.
I am sure that food was amazing.
The only way they can compete in Japan is the enterprise-game. Their partnership with Daiwa and MUFG is probably exactly what they should be doing. I doubt that they get that far though. Like Mistral who has partnerships with BNP Paribas and Airbus, they deploy in an on-premise or private cloud and in those settings, their models make good PoC's but cant compete where it gets interesting -- Workspace Agents. If you look at them from a Chatbot over RAG perspective, maybe they can do it. But that's tech from 2023.
But did they deliver anything yet?
There are many startups with notable founders that are not being able to get models launched. And even if they are able to launch, so they get PMF.
In case of Sakana, they clearly focus on the Japanese market an have buildup a good pipeline on sovereign AI. But similar to Aleph Alpha or to a certain extend Mistral, I don't see how they can keep up.
I did a pair programming comparison over 3 month on Codex 5.2 and Claude Sonnet and my subjective experience was that based on cost and rollbacks to a previous commit Claude is significantly better. Especially in VS Code Copilot. I wrote a long Substack post about it. I would share its but its in the paywalled archive by now.
In my opinion, the bread example doesn't really work that well because it bridges into the physical domain which most cognitive systems don't have access to. That said, for grounding context and therefore creating truth having a version of a world model is very important (See Yan LeCun's work). My experience is that given the right world to operate in, an agent can indeed find flaws in recipes and fix it even though the agent has not been prompted explicitly to do it. This world, as far as I understand it now, is a combination of sequential (at which step am I in a process), conversational (what was talked about alread/ what had I done already), and context memory (what is the frame or reference/plane of existence).