uxhacker

The BBC article seems to overstate the uniqueness of the service at Great Ormond Street Hospital. While it’s true that they are the first in the UK to offer a UKAS-accredited clinical metagenomics service (UKAS being the United Kingdom Accreditation Service, which certifies labs to meet medical testing standards like ISO 15189), metagenomics itself is already being used in several other places across the UK.

For example, the Earlham Institute, the University of Oxford, and the UK Health Security Agency are all actively involved in metagenomics research and surveillance.

For example: https://www.phgfoundation.org/blog/metagenomic-sequencing-in...

https://www.earlham.ac.uk/events/nanopore-metagenomics-sampl...

I’m trying to understand something broader about the U.S. tech economy and wondering what others think. How much of the money flowing into U.S. tech — particularly advertising spend on platforms like Meta and Google — is actually, indirectly, the result of America running a massive trade deficit? If dollars are going out to pay for imports (like ultra-cheap goods from Shein and Temu), those dollars have to come back in some form — often as investment in U.S. assets, including digital advertising.

Add to that the role of U.S. universities in driving innovation and attracting international capital, and it starts to look like this whole engine is powered by the very things that Trump’s tariffs and restrictions are pushing back against. Doesn’t that make his actions — while ostensibly protecting U.S. jobs — potentially anti-university and anti-investment in the longer term?

I’m genuinely asking this as someone without a background in economics and curious how others see it. Does anyone else think this crackdown might undercut the very ecosystem that’s funded a huge part of American tech?

So get the car delivered in Europe. Go on a driving holiday and then ship to the USA.

Not just that the pill works as well as the jab, but Lilly has stockpiled over a billion pills to meet expected demand.

What difficult to find metals do these batteries need?

It means personal ai on every computer. No privacy concerns, but saying that it is quite weird coming from a Chinese start up :)

So isn’t cursor just a tool for Claude or ChatGpt to use? Another example would be a flight booking engine. So why can’t an AI just talk direct to an IDE? This is hard as the process has changed, due to the human needing to be in the middle.

So Isn’t AI useless without the tools to manipulate?

It’s also weird that there is no about page naming the founders.

TDLR: The data was held by VW subsidiary Cariad. The location data was available for Volkswagen 460,000 vehicles in Amazon cloud. It was 300.000 cars in Germany, 80,000 in Norway, 70,000 in Sweden, 60,000 in the UK, 61,000 in the Netherlands, 50000 in France, etc

You can sign a petition against the change here : https://www.change.org/p/let-s-preserve-viollet-le-duc-s-sta...

What is so sad about this is the windows don't need to be replaced. Original windows hold significant value. While modern replacements typically need replacement within 20-30 years, historic wooden windows can last centuries with proper maintenance. The craftsmanship in older windows often surpasses modern alternatives, making restoration a worthwhile investment for both historical accuracy and longevity.

I restored 189 windows in my 200-year-old house in Poland rather than replacing them. The windows are fundamental to a building's character and historical authenticity. You can date a building by analyzing its window features. The older the house, the fewer and smaller the windows, often due to glass manufacturing limitations and structural needs. For instance, a 16th-century manor might have small, thick-glassed windows with irregular panes, while an 18th-century townhouse would show taller, multi-paned sash windows.

It goes back to the old wisdom DIKW pyramid.

EDITED My ASCI art pyramid did not work. So imagine a pyramid with DATA at the bottom, INFORMATION on top of the data, and KNOWLEDGE sitting on top of the INFORMATION, with WISDOM at the top.

And then trying top guess where AI is? Some people say that Information is the knowing, what, knowledge the how, and Wisdom the why.

A Call to expertise is actually a fallacy. This is because experts can be wrong.

The scientific method relies on evidence and reproducible results, not authority alone.

Edited to add a reference: see under Appeal to authority. https://writingcenter.unc.edu/tips-and-tools/fallacies/

Really interesting is that current LLMs don’t explicitly use chunking for storage; they rely on distributed representations across parameters. However, their self-attention mechanisms and sequence processing mimic chunking during runtime, creating dynamic "chunks" of context.

I’m at my limit, wondering if future models incorporating explicit chunking for better memory, scalability, and efficiency could truly take them to the next level.

You're absolutely right—this topic is fascinating but complex, which might explain why people are engaging with the idea but struggling with the takeaway. One way to think about the paper is that it extends the chunking model, which is essential not only for UX design but also for understanding how people perceive and organize the world around them.

How This Extends the Chunking Model

1) Dynamic, Real-Time Chunking: Traditional chunking models focus on discrete, often static information (like remembering a phone number or words). This study shows how the brain applies a similar principle to continuous, dynamic experiences—segmenting life into "mental chapters" as events unfold.

2)Neural Foundations: By identifying the specific brain areas (hippocampus and prefrontal cortex) responsible for marking event boundaries, it adds a biological layer to the chunking model. It’s not just a cognitive strategy—it’s a neural process tied to memory formation and retrieval.

3) Application to UX Design: In UX, understanding event boundaries can inform how we design user journeys. For example, breaking a process (like signing up for a service) into clear steps with defined "boundaries" helps users perceive the flow and remember their progress. Similarly, designing interfaces to reflect natural event segmentation (e.g., transitions between scenes in a video or steps in an onboarding flow) aligns with how people mentally organize experiences.

4) Understanding and Communication:

Beyond UX, this model shows why clear, structured narratives are critical for teaching, storytelling, or even summarizing a paper. Without clear boundaries, information gets lost in the noise. Potential Hypotheses for Altered States:

It also hints at why psychedelics, which might blur these event boundaries, lead to a sense of timelessness or interconnectedness. This could extend into therapeutic applications or understanding atypical cognition.

Why This Matters for Understanding Things When we fail to structure information with clear boundaries, it becomes harder to process or remember—perhaps like your experience skimming the article. This study offers a roadmap for how we can improve communication and design to better align with our brain's natural segmentation processes.

How about powerpoint as a metaphor? The challenge we face is how to explain something complex. But also do we not get into the issue that the Medium is the Message? That just by using voice rather than an image do we not change the meaning. And is that necessarily bad?

So what are the other models we could use ?

You can read here https://www.jstor.org/stable/249202?read-now=1#page_scan_tab... I am sure there are other resources available.

Is this the same issue with content creators being reimbursed for generative ai?

Originally the PNR when the reservation systems where built in the 1960’s and 70’s the six / seven / eight digit reference was the hash of the physical location in memory of the booking. It would take very few cpu cycles to recall the booking.

Nowadays of course the booking reference is virtual.

This really only presents the hypothesis that artificial intelligence (AI) will significantly impact the final stages of various processes, often referred to as the "last mile." However, she does not provide substantial evidence or detailed arguments to support this claim. The article lacks specific examples, data, or references that would substantiate her position, making it more of an opinion piece than a thoroughly backed analysis.

Don't get me to be wrong I would love this to be true.

Agile is dead long live (fr)agile.