For context, since a lot of people on HN haven't worked on games - this is not intended to compete with Git for general software development. This is a competitor with Perforce for game development.
Git is fine for text based files like code, but it's really bad at stuff like textures, 3D models, audio files, and other non-text files that game developers need to collaborate on. For example, one artist might need to obtain an exclusive lock on some art assets while editing them, because there is no sane way to merge two artists' async edits.
The SOTA in this area is Perforce (https://www.perforce.com/products/helix-core), a proprietary system. From what my gamedev friends tell me, when Perforce works it's great, but it hits enough snags that you need a tools engineer to manage it and occasionally fix issues manually. Git LFS is an alternative, but my gamedev friends all prefer Perforce especially when working on team projects beyond like 3-4 people.
My wife operates an optical trap (a sophisticated microscope, she uses it for studying gene/dna physical properties) and she's pretty good at working with that instrument. The number of people good at working that microscope are in the ballpark of 2000 (+- 1000) in the world! She has cried a lot in the last one year for the mess science research has become. We are moving out of the country at the end of August.
Some initial thoughts as a practicing radiologist:
- This looks really cool and I hope they keep innovating on this. I love seeing new modalities develop and despite my (many) reservations and criticisms, if even one good use case comes out of it that truly helps people, it's tech money well spent imo.
- They show the reconstructed images as though they are a low resolution CT, and promise that quality will improve as they iterate. This is cool, but ultrasound is not CT. Ultrasound cannot image the lungs, as they are filled with air. You cannot find bone lesions, as the sound waves do not penetrate the cortex. You cannot image many structures in the abdomen if they are surrounded by gas-filled bowel. The brain is encased in bone, so you might get some penetration but it will be very limited. Even with theoretically perfect AI reconstruction, these scans will not be true "full body" in that there will be structures that are not reliably imaged. Imagine paying for weekly full body scans for years, everything looks fine, then its the lung cancer surrounded by air and invisible to ultrasound that kills you (that's why we use CT for lung screening!)
- The images they show are very cool, and do appear to show the correct structures. I realize this is early, but fuzzy shapes of organs is very, very far from medically useful. The whole point of screening is to identify problems early, often by definition, small. This technology looks like it will be best for seeing large, superficial (close to the skin) structures, whereas for effective screening, you want the opposite - small, deep structures.
- "Incidentalomas" or unexpected, probably benign, findings are annoying to physicians, but I in general have no problem with people collecting data on themselves where they can. To me it's similar to heart rate monitors or home blood pressure cuffs. The main issue here is education, so that patients know what the data is and is not telling them. The more complex the data, the more difficult that is.
- Many people mistakenly believe that early diagnosis is the final boss in medicine, that if only we could find every cancer early we could prevent all those deaths. There are, in fact, many, many other hurdles and bottlenecks. Many chronic, expensive diseases do not have clear imaging manifestations. The claim that "it's completely possible that with enough early imaging in the future, the world could avoid 30% of all deaths and 50% of all healthcare costs", I think, to any practicing physician, would sound completely divorced from reality.
It's no surprise. The wild tech optimism of the 1990s and 2000s has completely fallen apart as time and time again tech companies have proved to be some of the most hostile actors in most American's lives. Perhaps edged out only by things such as actual violent crime and partisan hatred. (which itself, of course, is stoked to the absolute maximum in part due to technology trends in the past 15 years or so)
The loneliness epidemic, a constant drip-feed of outrage -- all so that people can make a small amount of money, distracted driving. Nearly every single service becoming worse over time, etc. Since then, the tech CEOs has been sidling up to the halls of power and effectively begging to help destroy privacy as thoroughly as possible.
I certainly know that my life was transformed for the worse by social media. And I don't mean that I went down any rabbit holes -- rather common culture was hollowed out, friends were distracted, friends fell down their own extremist rabbit holes. There is no successful social media company that actually cares about the negative impacts it has had on society. They speak about things such as "providing value" where value = time spent on the platform. They do not care if they ruin lives.
So a few years ago, nearly everywhere you went people are talking about how thoroughly AI was going to transform society. You couldn't go anywhere without hearing it. Of course people are wary. Big tech has been a net negative in very loud, intrusive, and obvious ways in _most_ people's lives. And now they're saying they're going to radically reform society.
The only hope we have is that they're wrong, and their power to change things will be minimal. For sure, if they really how the power to radically change everything, they would change it for the worse and would never spend a moment worrying about the damage they had done.
I could be wrong, but it feels like one issue is that AI seems to cater more as a signal to venture capital and the internals of the tech industry in a lot of these products, while consumers just want to know "what is this product going to actually do for me," and care less about whether it is implemented with the buzzword du jour.
This is sadly not even the full extent of it. What they did is, they locked their api entirely for anything that is not play protect certified. That means, all the cool stuff that was doable via community-driven projects is now dead in the water.
The "app" they provide is 60% advertisement, 30% features, and I unironically preferred using a Home Assistant connection instead of of it for everything. Even for automations like "when to preheat the car", since that was easier and more intuitive outside of their native function.
This also means, that charge control from the cars side is not possible to automate anymore.
Sure, one could take the position "but it was never officially promised", but for some people, including me, having the api (which is paid btw) was a selling point.
>No customer or user wakes up and says, ‘I hope I get to talk to a chat bot or an AI agent today
This is so true. I led the implementation of an AI customer service agent and even though management thinks it’s a great success the metrics tell a totally different story. Our customers hated it. I haven’t seen anything in tech that is hated more.
Before you think we did a bad job with our solution, I can tell you we went with some of the best and did our own intensive testing and worked on latencies etc., I actually thought the final version was pretty good but our customers just hated it.
It is amazing how Volkswagen keeps messing up.
I am currently in the market for a new car, an EV specifically. Volkswagen brands were at the top of my list for many reasons, among them the excellent driving assist implementation.
I got an offer from a dealer three weeks ago and was going to order the car, then the API for the community integration got turned off. I decided to hold back and see what comes from it. Now this, which ultimately - since I am a GrapheneOS user - makes me completely cancel my plans.
I really do not understand VWs thinking here. It would cost them little to nothing to continue not blocking the the inofficial API and not block GrapheneOS (or other non Play Protect androids) users. It would have no adverse effects on the average Joe, but it would gain a lot of support and enthusiasm from heavy users, differentiating from other brands. Not to mention the fact that it is the USERS data in the first place
My friends from grad school who went on to become professors tell me that not only did their grant funding dry up, but they were unable to follow through on hiring many of the grad students they had planned to hire, since the students came from foreign countries and faced new visa restrictions. So the money for science is gone, the people to do to the science are gone, and the institutions continue to not support their researchers, workers, and communities. It's the death of research in the usa.
Something else that git isn't good at: permissions. In gamedev, you might have proprietary work that you want to restrict to certain users. In P4, you can add restrictions to certain directories for only those who have signed the required NDAs. That's not something that you can do in git: it's all or nothing. Maybe you can set something up with submodules, but that's going to upend your repository if you hadn't planned for it.
>while consumers just want to know "what is this product going to actually do for me," and care less about whether it is implemented with the buzzword du jour.
I would say that undersells the (not neutral, actively negative) impact of AI to many.
What many people hear is "made with the tech that plagiarizes, leaves artists (and soon you as well) without a job, and makes things generic and bland!"
You might as well market it as "created by child labor".
I have received the email that my photobucket account is going to be deleted, so I've logged in after who knows how many years and got offered the same thing, to subscribe. Instead I've went to close the account and in the process (or somewhere else, don't remember exactly) there was an option to first download all the data which I've used and got the images back (there were just a few as I haven't used the service really), then I've closed the account. There was no need to subscribe.
If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument.
With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative. Also (you might raise an eyebrow at this) being nice to Claude will be rewarded and being mean to Claude will be punished. Claude tends to mirror your tone more aggressively and you don't want to get into negative loops with it.
With GPT, you have to be precise and reduce ambiguity. GPT will often try to resolve ambiguity in a min-max style "I'm going to do X, but make sure it is not quite Y". It will tend to be more paranoid and overengineer to catch all edge cases if you don't tell it precisely what the scope is.
With Qwen, you have to give it a shape and let it fill it in. Qwen likes XML, JSON and lists. Qwen likes to be shown a bunch of examples of previous work.
As is stated in the article, but is not clear just from the headline, this was not an unexpected outcome from the initiative. The Commission did not seek discussions with SKG, and spent virtually all of their time with the gaming industry lobby groups.
SKG was prepared for this, and their intention has been to join up with the group putting together the new Digital Fairness Act, since the objective there is very similar, but much broader in scope, and most of the groundwork is already there. Much of the earlier recorded Q&A sessions in Parliament had representatives commenting on this already, so it's the natural approach. This way, legislation will almost certainly be put forward and voted on, and the lobby groups will likely have a harder time trying to wrestle with a larger movement and a parliament that seems sympathetic to the cause.
Basically, this is a battle lost that never really mattered. The climax of this war is yet to come.
> You want as much data as you can get about your health as quickly and as cheaply as possible. In other words, you want a technology optimized for getting as many “megabytes per second per dollar” of information about your body.
This is so far from my vision of what I want from healthcare. I want a healthcare system that is optimised around A) proactively keeping me healthy, and B) reactively helping get back to healthy when I am not. I do not care about the amount of megabytes of data I have about my body.
German companies, especially old school industrial ones like VW, have a very hard time understanding open platforms. The view everything through the lense of liability and compliance first. Their thinking is that if someone runs their app on a custom ROM and uses that to manipulate the app in any way, and that causes some extremely hypothetical damage, that they might be held liable for not having prevented this situation.
Obviously, the chances of that are virtually zero. But they'd rather make their product worse than assume with any kind of risk, even if it is virtually zero. That is simply the way in which German enterprises operate.
It is now significantly harder to figure out who understands the systems and is using AI effectively and who doesn't know shit and is just slinging LLM copypasta around. Before 2025, the underperformers/coasters were at least relatively identifiable by the paucity of their contributions. Now all of the sudden every single engineer is filing PRs, code reviews, technical design documents, and every other artifact under the sun with perfect formatting and at least superficial plausibility. This is mostly due to incredible pressure from the C-level for every engineer to be using as much AI as possible, but it's also just a game theory respopnse because it's in every engineer's best interest to be as prolific as possible.
We are absolutely drowning in documentation and code that seems legit and the only recourse is to lean on AI to help process the sheer quantity of it. I have a feeling that the fallout from this phase of the industry is going to be an exotic form of technical debt that is remarkable mostly in its enormity.
This is the problem with all of the recent “AI” crap that has been shoved into our devices.
We have had ML features for years and it provided real benefits but most people did not know or care how it worked, it just did its job in the background without the underlying tech being shoved in your face.
Everything AI though is the opposite, it wants to focus on the technology first and the benefits second. It is actively making a worse UI and often providing little to no benefit.
Most consumers don’t actually care how their tech works, just that it does and gives them benefits.
And to think that the "old" Outlook's splash screen is there for a reason: it used to take a while to open before SSDs became commonplace! Windows in general used to be usable on HDDs; SSDs would blow everyone's pants off making everything open instantly. These days we have 20+ Gbps SSDs without the AHCI latency tax and they're no longer enough to open an e-mail.
I use DeepSeek every day (via VSCode Insiders and Zed Editor). It's very affordable and, while it's slightly behind Claude (not sure how far behind Fable), it suits my working style well. I'm not using unsupervised multi-agent workflows and don't need a library of skills files - I'm writing most of the code and leaning on AI to help with mundane tasks - like;
- generating types for APIs
- generating boilerplate based on existing code
- improving existing code (adding error handling, timeouts, things like that)
- Writing SQL repository boilerplate / queries
- Creating implementations against hand written tests
- Helping me understand and implement APIs from third party libraries
- Writing documentation
I've spent like $2 in the last month and have used over 100 million tokens.
It's doubled my productivity and unlocked work that I could not have done before.
As an Australian, I'm not sure that I care about the safety of my data when it comes to LLMs. US companies already stole scores of data to train their models on and it's hard to imagine they suddenly grew some integrity. I'll care when regulators step in, until then it's out of my control so I'll just use the best price-to-productivity product available.
> Things start off fine, but then mold starts growing in the bathroom, and a recurring leak springs up in the living room, and then roaches start appearing in the kitchen.
When I started reading the article, I thought the whole point was gonna be that the author doesn't take care of the apartment.
The recurring leak might not be the author's fault, but the mold in the bathroom and roaches in the kitchen definitely are. Is this a case of a total lack of self-reflection? Or a post to scare people away from becoming landlords?
I don't know much about this guy, but I remember reading an interview with him maybe 15 years ago where he was asked if his lifestyle had changed since he came into money and if he bought a new house or anything, and his answer was basically something like: "Not really, and I've already got good water pressure where I'm at, what else do I need?" I can't help but like his attitude.
Just today as I pushed some changes to Github, I was thinking how user-unfriendly Git's UI is:
Enumerating objects: 5, done.
Counting objects: 100% (5/5), done.
Delta compression using up to 10 threads
Compressing objects: 100% (3/3), done.
Writing objects: 100% (3/3), 290 bytes | 290.00 KiB/s, done.
Total 3 (delta 2), reused 0 (delta 0), pack-reused 0
remote: Resolving deltas: 100% (2/2), completed with 2 local objects.
I know all of these things communicate something to the die-hard Git user, but for most people (even most people using Git, I bet) this is just complete gobbledegook. What the hell is "delta compression"? Why do I care how many threads it's using? What is an 'object' and what does it mean when it's 'local'? What does 'pack-reused' mean?
From the documentation, it looks like Lore does a bit better in this regard:
Pushing 1 fragment(s)
Pushed 1 fragment(s), 124.00 bytes
Pushing a3f8c2d1... to branch main
Pushed revision 1 -> a3f8c2d1... to branch main
It's a controversial and complicated idea. The downside, and the reason why most doctors do not recommend full body scans, is that every human body is a bit weird and there will almost always be something "wrong" that will be visible in a full body scan. This can lead to unnecessary testing, anxiety, and even unnecessary procedures. Many of these oddities flagged by the scan would never have caused any actual issues had the patient never been aware.
While there are many individual stories of full-body scans detecting early-stage cancer before it became symptomatic, there seems to be a general sense among doctors that implementing full-body scanning on a population level would lead to overall more harm than good. The thinking is that it is better to do regular targeted screenings for diseases that you're in a risk group for (e.g. colonoscopies, mammograms, cancer marker blood tests, etc.) rather than full-body scans.
I'm not a doctor, and I personally do find the idea of full-body scans very appealing, but I also know that if the scan detects a possible cancer, I wouldn't be able to just ignore it if the doctor tells me it's likely ok. Any time I felt any pain or any sort of symptom in that general area, I know I would worry about it. Maybe that's worth it for the potential life-saving results, but it definitely is a cost of this type of scan that needs to be acknowledged.
> When the shutdown ended in mid-November, Reynolds’s team had just two weeks to get on budget. It failed. The plan the group submitted would cost too much and take too long. “Our last hope was that NASA headquarters would understand what had gone on and give us some leeway,” Reynolds says. NASA did not. After nearly 10 years of work, AXIS was dead.
If the scientists haven't left science behind after an experience like this, probably nothing will. What an absolute kick in the nuts to have a decade of your life erased because someone did a keyword search for science projects to stop, in the name of saving money, while at the same time wasting even more money on other things.
I think I should feel angry, but I just feel sad for all the humans involved here, I hope they manage to come out with a more positive perspective than I'm able to here.
> Unlike infrastructure projects in Britain or America, which are heavily reliant on external consultants to handle all stages of the project, this group of well-paid in-house engineers led much of the Madrid Metro expansion. The team stayed largely the same throughout the different projects, meaning that they were able to learn from their experience and apply it to future projects.
Imagine that: building expertise in-house and within the governmental org results in better planning and management and thus outcomes.
Git is fine for text based files like code, but it's really bad at stuff like textures, 3D models, audio files, and other non-text files that game developers need to collaborate on. For example, one artist might need to obtain an exclusive lock on some art assets while editing them, because there is no sane way to merge two artists' async edits.
The SOTA in this area is Perforce (https://www.perforce.com/products/helix-core), a proprietary system. From what my gamedev friends tell me, when Perforce works it's great, but it hits enough snags that you need a tools engineer to manage it and occasionally fix issues manually. Git LFS is an alternative, but my gamedev friends all prefer Perforce especially when working on team projects beyond like 3-4 people.