uxhacker

Catholics in Trumps cabinet are not just JD Vance, but Marco Rubio, Sean Duffy, John Ratcliffe, and Robert F. Kennedy Jr. I think this is one of the most Catholic-heavy administrations in US history. It includes not just the VP, Secretary of State, intelligence chief, but also major domestic roles.

The irony of an advanced nation such as the USA using weapons inspired by Iran, to attack Iran is interesting.

I half wonder if this is an April Fools joke, or a very clever solution.

From what I understand the argument is, and to miss quote Marshall McLuhan it is “the medium, and not the content is the addiction”.

In other words is not the posts by the influencers, but techniques such as infinite schooling, and so on.

This is why meta and google could not relay on User-Generated Content Safe Harbor (Section 230) part of the law.

And would it not be useful to have some kind of human in the middle? For example what is to stop charge backs if no human has actually authorized the transaction?

This paper actually surveys research on humans and not mice.

The association between gut microbiota and cognitive decline: A systematic review of the literature

https://www.sciencedirect.com/science/article/pii/S027153172...

It shows ”Gut microbiota modulation improves cognition in adults with early impairment. Diet, probiotics, and fecal microbiota transplantation share mechanistic pathways and that evidence clarifies how microbiota-targeted strategies support cognitive health.”

The action could be explained due to an anti inflammatory action by the gut biome.

What actually solves the issue is adding to the prompt.

Can we think about the what, where, when, and how of the following question. And then answer it.

I need to wash my car. The car wash is 200 m away. Should i walk or drive.

Let’s break it down logically using what / where / when / how, then decide.

⸻

1⃣ What

Task: wash your car. This implies: • The car must physically get to the wash. • You are not just going there — the car itself is the object being moved.

So the real question is not “how do I get there?” but how does the car get there with minimal friction.

⸻

2⃣ Where • Distance: 200 metres (very close). • Urban context (Warsaw) likely means: • short streets • possible parking constraints • pedestrians and local traffic.

At this distance: • Walking time: ~2–3 minutes. • Driving time: ~1 minute + manoeuvring + parking.

The movement time difference is negligible.

⸻

3⃣ When

Consider timing conditions: • If it’s busy hours: Driving may involve awkward turning, queueing, or waiting to re-park. • If it’s quiet (early morning / off-peak): Driving is frictionless. • Weather factor: Cold/rain → driving becomes more attractive. Pleasant weather → walking becomes easier.

⸻

4⃣ How (decision mechanics)

Ask:

Option A — Drive

Pros: • Car is already there. • No need to return to fetch it. • Most natural workflow: arrive → wash → leave.

Cons: • Very short trip (slightly inefficient). • Cold engine for a tiny distance (minor mechanical inefficiency).

Option B — Walk

Pros: • Zero short-distance driving. • Slightly more movement for you.

Cons: • You still must drive the car to the wash anyway — unless someone else moves it. • Creates an unnecessary extra step: 1. Walk there. 2. Come back with car. 3. Drive again.

This introduces process inefficiency.

⸻

5⃣ Decision (practical answer)

Drive.

Reason: • The car must end up at the wash. • Walking adds an extra transition with no real benefit. • At 200 m, efficiency is about workflow simplicity, not distance.

⸻

Rule of thumb (useful mental model) • If the object you need is the thing being serviced → drive it. • If you are the thing being serviced → walk.

⸻

If you want, I can also give you a slightly more philosophical answer — because this is actually a nice tiny example of decision theory and friction costs.

Claude fails with

“I need to replace a spark plug. The garage is 200 meters away should I walk or drive there”

“Walk! 200 meters is just a 2-3 minute stroll — no need to start the car for that distance. Plus, you’ll likely need to carry the spark plug back carefully, and walking is perfectly easy for that. “

Basically LLM suffer from context collapse.

Taler is cool but different. Wero is about moving money from your bank account to someone else’s bank account using a phone number to identify the recipient.

It is very similar to many other mobile money systems. What make it different is that it is pan European

Taler is about moving money without necessarily using a bank account

But then will we not need more judges and courts?

The ibm 3174 was just a controller to then link the terminals to an AS400 mini / mainframe

So it will cost at least 100,000 usd to keep this poor elephant confined in a zoo in the US versus about 15,000 in a wild sanctuary in Thailand.

In the wild sanctuary it will have space to roam.

So there are now 55000 and 1 Asian elephants*. I don’t understand the newsworthiness of having an extra Asian elephant joining the other 15000 Asian elephants in captivity.

Wild Asian elephants roam between 100km2 to 1500km2. This elephant will spend a life confined to just how many square km’s?

Is the irony that a printed page is safer than a digital page?

Why would widgets and buttons be better than a console, and or voice?

So the question is can you do anything useful with the agent risk free.

For example I would love for an agent to do my grocery shopping for me, but then I have to give it access to my credit card.

It is the same issue with travel.

What other useful tasks can one offload to the agents without risk?

The study assumes that the car or drone is being guided by a LLM. Is this a correct assumption? I would thought that they use custom AI for intelligence.

The crazy thing is that you don’t need to show an ID to stay at hotel in the uk, but you will need one to use the internet.

Persona’s is not the same thing as a role. The point of the role is to limit what the work of the agent, and to focus it on one or two behaviors.

What the paper is really addressing is does key words like you are a helpful assistant give better results.

The paper is not addressing a role such as you are system designer, or you are security engineer which will produce completely different results and focus the results of the LLM.

The idea that people are smoking arm chips makes me laugh.

Can somebody explain how the software actually adds value? How is it really that amazing? Or is it just a buzz word?

It’s pretty scary. According to Barron’s, MicroStrategy, a bitcoin treasury company, alone makes up about 5% of the U.S. convertible bond market. That’s remarkable given that it isn’t a typical tech or biotech growth company issuing convertibles, but essentially a Bitcoin treasury company.

And when will it do class designs? Maybe this would solve many an AI coding issue.

Yes, to loosen the Model, but not to have no model. The new idea needs to be reintegrate back into the existing world models.

An example would be improvised jazz, the musicians need to bend the rules, but they still need some sense of key and rhythm to make it coherent.

Yes, everyone has a world model even a toddler has a casual model (“cry → mum comes”).

What stops imports?

I’m very dyslexic, so having AI in the loop is incredibly useful — especially for feedback.

But I have to guide it: “just list the changes,” “use English English,” and so on.

The fun’s still there — because the thinking is still mine.

Does using AI kill the dopamine loop?

I don’t think so.

I still spend the hours — because it needs to sound original. It needs to feel authentic. I have to add my own personal parts to the story.

I still struggle writing it.

The AI helps, but it doesn’t replace the work. The dopamine’s still there — because I’m still in the loop.

Because some LLMs are now multimodal—they can process and generate not just text, but also sound and visuals. In other words, they’re beginning to handle a broader range of human inputs and outputs, much like we do.

I recently have also been thinking about Jef Raskin’s book The Humane Interface. It feels increasingly relevant to now.

Raskin was deeply concerned with how humans think in vague, associative, creative ways, while computers demand precision and predictability.

His goal was to humanize the machine through thoughtful interface design—minimizing modes, reducing cognitive load, and anticipating user intent.

What’s fascinating now is how AI, changes the equation entirely. Instead of rigid systems requiring exact input, we now have tools that themselves are fuzzy, and probabilistic.

I keep thinking that the gap Raskin was trying to bridge is closing—not just through interface, but through the architecture of the machine itself.

So AI makes Raskin’s vision more feasible than ever but also challenges his assumptions:

Does AI finally enable truly humane interfaces?

I’m not a mathematician (just a programmer), but reading this made me wonder—doesn’t this kind of dimensional weirdness feel a bit like how LLMs organize their internal space? Like how similar ideas or meanings seem to get pulled close together in a way that’s hard to visualize, but clearly works?

That bit in the article about knots only existing in 3D really caught my attention. "And dimension 3 is the only one that can contain knots — in any higher dimension, you can untangle a knot even while holding its ends fast."

That’s so unintuitive… and I can't help thinking of how LLMs seem to "untangle" language meaning in some weird embedding space that’s way beyond anything we can picture.

Is there a real connection here? Or am I just seeing patterns where there aren’t any?