mushufasa

My understanding with this project is they also replace the screen and battery with newer parts e.g. higher resolution, or at least that's an option, and all the ports are new (it's a new motherboard). So really the only 'old' parts are the keyboard and chassis. My understanding is there's lots of cheap replacements for the keyboard floating out there given the mass production and the original intention for this device to be easily serviceable by IT departments instead of "RMA everything."

This is the type of rumor that could swing a stock price... I'm skeptical of how this got out there and by whom.

Languages inherently have network effects; most people around the world learn English so they can talk with other professionals who also know English, not because they are passionate about Charles Dickens.

My take (and my own experience) is that python won because the rest of the team knows it. I prefer R but our web developers don't know it, and it's way better for me to write code that the rest of our team can review, extend, and maintain.

I happen to know IBM made some great hires -- one of my classmates who was excellent in the field, who had impressive quantum computing nature publications before graduation, worked at IBM for the past several years.

Though it looks like he recently switched to working at Google AI...

https://scholar.google.com/citations?user=NaxMJzQAAAAJ&hl=en

One of my colleagues read a paper about quantum computing techniques to solve complex optimization problems (the domain of complex mixed integer solvers) and tried it out for a financial portfolio optimization, replicating the examples provided by one of the quantum computing companies during a trial period.

The computer *did not* produce the same results each time, and often the results were wrong. The service provider's support staff didn't help -- their response was effectively "oh shucks."

We discontinued considering quantum computing after that. Not suitable for our use-case.

Maybe quantum computing would be applicable if you were trying to crack encryption, wherein getting the right result once is helpful regardless of how many wrong answers you get in the process.

The key concept here is that the demand is mostly exogenous changes; people demand fewer horses because horses are no longer as good of a product. The whole supply/demand curve for horses shifts.

Another way to think of this intuitively is simple economies of scale. Or volume discounts if you work in sales.

When you buy 10,000 handbags you pay the wholesale price whereas buying a single handbag can be quite expensive.

If there is way lower hose demand (volume of sales), the horse producers will have to charge a higher price per horse.

Thus, society in aggregate spends way less on horses while the price of a horse goes up.

Here's one free article covering a book about the washing machine example https://www.theguardian.com/technology/2010/aug/29/my-bright...

As someone who attended this school and has a degree from their economics department: this finding very consistent from what I learned in classes covering the economics of innovation. Historically, technological revolutions have increased productivity and labor force participation, despite many pundits at the time worried about loss of jobs.

The core intuition for this phenomenon is that human society overall takes the tech productivity gains to do more things overall, creating new goods and services. The broader range of goods and services overall also enables more people to find work.

Put another way, "“One thing I love about customers is that they are divinely discontent. Their expectations are never static – they go up. It’s human nature. You cannot rest on your laurels in this world. Customers won’t have it.” -- one of Bezos's Amazon shareholder letters.

One of my favorite counterintuitive examples: The biggest economic gains from the 1800s Industrial Revolution actually came from the humble washer/dryer. By making routine homeware 100x more efficient, this (along with other home appliances) allowed more women to enter the labor force, nearly doubling labor force participation within a couple generations. Though, at the beginning, lots of people were opining about homemakers losing a sense of purpose or relaxing all the time.

It's certainly possible that this study is just reinforcing the researcher's biases from their previous understanding of the economics of innovation, and also possible that this study is accurate today but conditions will change in the future. That said, I believe the burden of proof is on the pundits claiming cataclysmic job loss, which is counter to economic historians' models of innovation.

the counterpoint is that unix itself is a holistic system -- the value of unix is the integration of a bunch of different tools by providing a consistent way to manipulate streams of text and files with standardization

The EU and others listed are actively trying to regulate AI. Permissive OSS libraries' "one job" is to disclaim liability. This is interesting that they are just prohibiting usage altogether in jurisdictions where the definition of liability is uncertain & worrying to the authors.

isn't this just a change from opt-in to opt-out? will make a big difference but still gives individuals control of their data governance

"we sync into their systems of record and act as that verification layer"

As long as those 'systems of record' are controlled by the customer, then that is self reporting. If they don't enter a sale into their CRM or tag it differently there's nothing you can do.

The industries where I have seen pay-for-outcomes work are industries where there are regulated legal controls or strong third parties. For example, a lot of financial services have commission payments that are based on the actual invested assets as measured by the bank/custodian, that then get paid out to salespeople or partnerships.

They must have raised money based on this plan -- the board must be holding them to execute it again to hit the projected IRR. If they had full control of their own destiny, I think most operators would just focus on a different business model.

1 in 20 doesn't sound great. But you have to mediate that with

- everyone and their mother are doing a "generative ai program" right now, a lot of times just using the label to try to get their project funded, ai being an afterthought

- if the 1 out of 20 projects is game-changing, then you could argue right now people should actually be willing to spend even more on the opportunity, maybe the number should actually be 1 in 100. (The VC model is about having big success 1 in 10 times.)

- studies of ongoing business activities are inherently methodologically limited by the data available; I don't have a ton of confidence that these researchers' numbers are authoritative -- it's inherently impossible to truly report on internal R&D spend especially a private companies without inside information, and if you have the inside information you likely don't have the full picture.

This sounds really great in concept.

I don't see detail here. As someone who would be interested in using this, can you clearly explain how you will measure and track the outcomes? That's the key detail that matters.

Relying on customers to self-report is not sufficient, and an automated self-report-system is not a true improvement.

interesting -- I ran into this recently playing baldur gate 3 and was curious the technical details why. my fix was that I had an external monitor and I just reset the resolution to the external monitor. (by default, though, the monitor was showing up blurry though; with the wrong aspect ratio.)

would love this to be a desktop background -- linux or macOS

there was a company "Zogo" that built a phone app to do this and sold it to banks as a free perk to try to increase savings rates / utilization of financial products at the bank. Had some moderate success. Haven't heard about it recently.

I think they should totally do this but I think they should call it "rate-limiting" instead of "weekly limit". Seems pretty clear to me that the purpose is to avoid situations where people are running 5 background agents 24/7, not the person working during business hours normally. Reframing this makes it more clear this is about bots not users.

I would love to see an update on what has improved and what is the same

Django-ninja is a combination of Django with fastapi.

> * The Global Technical Potential (in TWh/year) is 1/10th of offshore wind

To put this in perspective, less than 1% of the world's land area would be needed for wind turbines to power the current energy needs of the globe (according to NREL). So this is not a limiting factor.

On the one hand I am the target audience for this: someone who wants to focus on data and have the frontend "solved" for me.

On the other hand, I have been burned by every similar framework I've tried (e.g. Dash by plotly, many others) when I *need* to tweak one small thing in the frontend, and simply can't because of the way the framework functions. In which case, I have had to rewrite the feature from scratch. So I have found these tools okay for internal tools or proof-of-concept stage, but inadequate for real applications with real users where you need to quickly iterate on feedback in directions you cannot predict in advance.

Note there's a popular cybersecurity company called "Vanta" to which they own the trademark, so the name probably should be changed to avoid confusion.

I actually started my startup with this approach -- good old Django.

Lasted for a year until we had users wanting to do complex interactions on the frontend.

Simple CRUD apps are fine, but users expect a lot of interactivity these days where things on the screen interact with each other.

The nice thing about Django, though, is that you can easily switch to api-based backend with DRF or Django-Ninja. We used DRF but if I were to do it again, I'd choose ninja.

Yes I've tried cursor. Currently it gives 1) high level suggestions if I ask about architecture, which may be valid but doesn't solve the issue of refactoring a large existing codebase to make architectural changes, or 2) some specific improvements on very simple functions, but it majorly falls short for 3) actually implementing improvements, because it doesn't have the context of the product and what "makes sense" as tradeoffs and choices. There are a lot of times where for us, "correctness" is a state of data calculations rather than code validity, where unit tests / integration tests don't exist and aren't trivial to generate.It is counterproductive if we make something run faster but return the wrong results. Or if a team member were to look at a task/function, they could reason "actually this feature that does X should actually be doing Y" but that isn't something the AI can reason about in practice. In those cases, it would be ideal to change the function without relying on tests, because you would actually want the behavior to change. Small example: a feature is not performant, and rather than just making that feature perform better, the better solution would be to switch to a different library that we added elsewhere in the codebase for accomplishing that work.

Also, while cursor is now able to scan terminal server logs to see errors, it doesn't come "out of the box" hooked up to app performance profiling tools -- even just running locally. There probably are some MCP servers or something to do that but I haven't set that up. Really you would want the IDE agent to have a feedback loop that goes like "optimize {speed, resource usage} subject to the constraint of {unit/integration test}" and let it run asynchronously or overnight etc. (Of course, there are tons of times that LLMs will work themselves into a dead end loop, and it would be bad to indefinitely generate LLM API calls on a dead end overnight).

A lot of our code was written by domain experts who aren't trained in algorithms/data structures. We have new relic and other performance assessment tools to see where we have long running queries etc. But looking at the realized performance will only show you the biggest problem areas, like long running queries, and will miss the "Death by 1000 papercuts" of functions that work but in a way that is unnecessary. It would be nice if there is a tool that looks more holistically at whether certain functions are designed well, both in terms of space-time complexity of the algorithms and in terms of overall design of certain features. For example, a feature that sequentially changes a lot of things in a database could not raise any red flags in a profiler, but could be unnecessarily adding a lot of time versus an approach that might pull data into memory, conduct all the operations, then bulk reinserting. Or which could be refactored to act in parallel versus sequential.

This is what is really hard to figure out because you need to know 1) what is the business logic you actually need (and what tradeoffs can you make that would be acceptable given the product), 2) algorithm design, 3) how web apps scale things horizontally, 3) which things get performed on the cpu / memory versus a database, and more.

Instead of hoping for a tool that can do all of that at once, it would be nice if a tool could at least visualize (2) within an existing project to help a human who can keep those things in their head at one time to spot problem areas with code design / system architecture that wouldn't necessarily be revealed by simply looking at logging/APM tools.

this could be truly helpful if I could include it into my (large) existing codebase to help spot performance bottlenecks. that's not something I could so simply pasted into a self-contained snippet, though. Do other HN know of other static analysis tools that would be great for this?

Yes you can name a brand name without using their logo.

That's not what the author did here -- he invented a fake logo and chose a domain name and title that include "WaffleHouse." Trademark law is specifically designed to prevent people from creating a fake logo and registering a domain that makes people think it is your own brand. Yes, there is some exception for parodies and criticism, but writing a review / parody sketch is a completely different format than a website that lists information that purports to be official open/closures of your business.

You can't create a product that contains the brand name of another product; I can't invent "Magic Kleenex" or "Better Google," so he similarly can't name something a "Waffle House Index." What he could do is name something "disaster index" or "breakfast restaurant index" where the data happens to be from the waffle house locations.