This is all just running in circles. The models are not obviously better. The pricing fluctuates or offset by some other less-obvious metrics (availability/speed/tokens per task/dumbing down). Everyone reports different outcomes in their usage because it's all so context and user dependent. Sometimes models do some things better but become so annoying and obtuse in their other doings that it's just not worth it (like Opus with the insane code comments and Astra with its over-the-top, everything-is-a-sales-pitch style). It feels like the AI gods just turn the knobs on things like compute to get the results they want to align with the IPO to make headlines.
They are pushing their customers towards Chinese models and providers. If you want to get something cutting edge done in defense, cyber, biology - something that isn't common knowledge - you need to venture east. That's an incredible side effect which the Chinese government surely enjoys.
It makes a lot of sense. I thought about it in the context of pull requests or change sets: if the text-to-code process is reliable, why don't you give me prompts instead of code? Code becomes just an intermediate representation.
I beg to differ. I stayed in Battersea for a week while exploring London. I found the place very welcoming, safe and inspiring. It’s convenient to get to and from with its dedicated underground line.
I can see how it fits the Apple
brand experience very well (they don’t do gritty stuff). In fact I believe there’s already an Apple Store there.
I'm a local to the area, I agree with everything you're saying here (despite the weird backlash) and I know exactly which shop you mean. That shop is one of the most bizarre shops I've ever seen. It's branded as a "general store" but there's absolutely no household brands, everything is about 5x the normal price and all of the shoppers look like rich influencers? I have a theory that the store is used to trial new products before they go to the wider market
> There's also a little local shop for the residents that stocks wine costing over £1000 a bottle.
What a weird complaint. I’ve been in grocery stores that have wine costing $500+/bottle. I would expect any wine shop to stock rare and expensive wines. Now, if that’s all they stocked, you might have a point.
If your corner shop sells wine that costs over £1000 a bottle I think you may very well be constitutionally unable to understand the point I am making.
That’s what some people consider success: moving from merge beginnings where the corner stores plural stock $500 bottles of wine, to a good area where the corner store singular stocks $1000 bottles of wine.
Come on now, when the rich go over to the artsy neighborhoods and fancy wine shops open up it's called "gentrification", but when they - actually a Malaysian group of investors - make their own place in a run down corner of London, a place that's accessible by public transport to anyone, and does justice to preserve the story of the power station, you call it grotesque.
It is absolutely still gentrification if you take one of the few places in London where people who work in lower-income jobs in London used to be able to afford to live and make it a luxury zone for unexplained wealth.
There are many gentrification complaints about that development and wider Battersea, and it has been an absolute legal battleground:
It's not actually the angle I was taking. Weirdly, considering it was driven by 1MDB, it's not an illegitimate or corrupt project in and of itself, and there's much more dodgy foreign money going into the rest of Battersea's redevelopment.
My complaint is what they built. It's a dreadful, dreadful project.
Well, the type of places that OP described are full of service people, paid the best wage that people with little training can make, because they can ALWAYS be nice and welcoming… even when being screamed at and spat upon by the rudest, meanest, and most despicable nepo-jerk you could imagine!
But, aside from the convenient access to the underground, I’m really intrigued by what you found “inspiring” about this place?
(I don’t know a single thing about it, never even heard of it, so I’m torn as to which of you two to believe… lol)
It's a combination of a park, a residential neighborhood and a shopping center in the renovated power station. The station is incredible building, with its brick construction. The residential buildings themselves are also special, with some designed by Frank Gehry, and the shopping center is inside the power station building and has an family-rated-steampunk feeling to it.
We stayed in an apartment overlooking the station front and it was a lovely sight.
I know someone who used to live in the new apartment development around the old power station; I think it is possibly the most soulless place I have ever visited. If you've seen The Good Place, then, eh, imagine a densified version of that, I suppose. It was really kind of amazing. Difficult to describe exactly why it was so off-putting, and I suppose tastes differ, but it really was unpleasant.
The power station itself is an impressive structure, mind you. But of all the things they could have done with it, it's a shame they did this.
Programming has a long standing culture of accepting the code to be somewhat wrong, so we have various tests, linters, reviews and error handling. Also in programming there are many ways to do something and it's the end result that matters most.
Not so in other knowledge work. There's no test harness for a contract and error is non-recoverable. Likewise in finance. There are specific ways of doing things and these ways are many times set in regulations. LLMs can assist all day, sure. But replacing the human, in highly regulated, zero tolerance for error environment?
The highly regulated, zero tolerance for error environment is a huge problem because anyone doing these jobs is more like a small sample size LORA than a general model.
It doesn't matter how smart someone is, they need specialized training to be good at these jobs. Specialized training in the area the company specializes in.
There is a category error in all this that is hard to think about because of the normal discourse and ordinary language. We say people work in "finance" but no one works in just "finance". They work at a company that has a specialization within "finance", inside a hierarchy that has specialization on top of specialization.
What we really need is exactly what we don't have and aren't going to get. A type of LORA that generalizes the task specific intelligence needed from a very small sample size and that in practice makes so many less mistakes in a highly regulated, zero tolerance for error environment that it is irresponsible to not use the model.
I have worked in this type of environment for 3 years and I have made zero mistakes in 3 years. The people that make even a small number of mistakes get fired.
Any real automation in this area is going to be incredibly slow and piecemeal over a long period of time because even an amazing model would need a long time to prove itself against what the human standards for error rates are.
Even the ensemble average error rate on a large number of tasks in space would not be good enough. It needs to be an average error rate over time.
You could say the Salvatorian Clause in contracts is like exception handling:
a "catch (all)": even if some clauses in this contract are illegal,
the remaining contract stays in place.
Logically, this actually doesn't make sense strictly speaking because the sentence creates a paradox: doesn't it make clear whether it includes itself or not, and each reading ends up in trouble. There is a "tradition" in law around the world to accept the only benign reading of such clauses, which I always found funny given that in all other ways lawyers adopt the most adversarial mindset imaginable.
You’re right; given that most of the money in the AI market is injected through OpenAI and Anthropic (which collect it through both selling equity and through customer revenue), the 7-8T is just a derivative of that.
It can't hallucinate, but it doesn't mean it can't make wrong decisions. Just because it adheres to a specific output format at all time, while LLMs have the output format at their mercy, then the claim of not hallucinating is made technically true.
I think that this specific part is not super interesting if your harness just recovers from invalid LLM outputs.
The latency and cost - yes, those are super interesting.
We have an agentic system that produces insights for end users, and runs most of its work on DeepSeek v4.1 Flash but as an output stage transforms the resulting text through Gemini 3.8 Flash for readability, and it works.
On my TODO is try and run all of the analysis pipeline in dense "machine speak" to save on tokens and just let Gemini sort it out at the end.
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