jsemrau

The enshitification of Google is inevitable. It went from all the space you ever need for your email to "you are at 93% usage. Upgrade to premium" in just a few years.

If you go further down this line of argumentation you will end up at what will be cheaper capital punishment or prison for life.

Having society (a group of unrelated jurors) to pay for the crimes of an individual (however minor you perceive them to be) is not justice. That's why you got kicked out.

Qwen3-TTS is working well on my box.

As per 2026, the idea of building a generally great agent fails because it is not just a function of prompt, skills, and memory.

If Apple's "Intelligence" paper has shown one thing is that never do something in the LLM that can also be done recursive and deterministic.

I can't use Google for anything anymore.

1. Google News API now returns only Google links that don't resolve to anything in code. 2. Google Search results are atrocious and only unearth non-authoritative blogspam and aggregator sites.

The core issue is that places I previously curated are now overrun by activists of all directions.

Documentation is memory.

Over the last years, being "online" has become so stressful and toxic that I just don't want to spend much time there anymore. 2016 me would be ecstatic about this product. 2026 me just want to be in the real world.

I think the "brain in a vat" comparison is more apt. Without a form of digital embodiment (harness) they are not of much use. Sensor, tooling, memory, planning, and reasoning loops all lead to a much higher quality task-completion.

This is a discussion on context window and not context.

Please read my essay on context window saturation. I am also the author of deepcq (intent-aware memory querying & context mgmt for LLM agents)

Needing large context windows is an illusion.

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).

https://github.com/ternary-ai/ow-code-world-model https://jdsemrau.substack.com/p/a-self-improving-code-world-...

Like the rest of the world. Since there are many non-Western countries that still have slaves there is no original sin.

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.

There are more people enslaved now than at any point in time in history. Guess the 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.

I am entirely sold on Qwen3-TTS's voice cloning. It runs locally and I can run it as many times as I want.

Over the last 8 years

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.

Microsoft own Enterprise if you like it or not. And Microsoft will also own a large piece of the AI in Enterprise cake. https://www.microsoft.com/en-us/frontier-company

The last two years have been perfect for accumulating tech debt.

2023 you would have probably implemented your Agents with LangChain and RAG

2025 you'd use MCP and OpenAI/Anthropic Agent SDK.

2027 you will use a workspace frameworks (Amazon, Microsoft) sensor libraries and world models.

Agents are a fantastic generational technologies, but in mid-2026 the environment they are operating in is quickly changing.

The only way forward is to stay agile, understand model and vendor risk.

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.

Interesting timing as Workday is facing Discrimination Claims in California doing the same thing.

https://www.yahoo.com/news/us/articles/california-judge-upho...

Just because you have a large garage doesn't mean you can park your car easily.

> there was no qualified American applicants

I have been hiring for 20 years and find this increasingly impossible to believe. Please expand why that would be the case.

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).

Self-correcting agents are already here: https://jdsemrau.substack.com/p/hyperagents-and-self-correct...

Anthropic for sure. It's a useful professional product that I find many use-cases for in my professional and private life. OpenAI not so much.