4,844 karma · joined October 2, 2016
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On one hand I think automating content moderation is a great idea. People who review content are exposed to very unhealthy things, and tend to experience trauma after a long enough time (2-5 years). Anything AI can do to reduce trauma of employees or contractors I think would be a net win.
But this poster actually understands the AI output and is able to find real issues (in this case, use-after-free). From the article:
> Before I get into the technical details, the main takeaway from this post is this: with o3 LLMs have made a leap forward in their ability to reason about code, and if you work in vulnerability research you should start paying close attention. If you’re an expert-level vulnerability researcher or exploit developer the machines aren’t about to replace you. In fact, it is quite the opposite: they are now at a stage where they can make you significantly more efficient and effective.
https://learn.microsoft.com/en-us/dotnet/core/deploying/trim...
https://learn.microsoft.com/en-us/dotnet/core/deploying/nati...
I know the first Die Hard is 4k, but the others are not.
https://www.consumerreports.org/electronics/personal-informa...
Edit: apparently Google did not use the author's codebase, instead using an Apache 2.0 licensed codebase [1] explained here [2].
[1]: https://github.com/kubernetes-sigs/gcp-filestore-csi-driver
I feel like there needs to be more education about redaction and obfuscation tools, namely this black box tool and blurring. It is usually possible to reverse blurring. Not redacting information properly is just embarrassing.
> Copilot agent mode can create apps from scratch, perform refactorings across multiple files, write and run tests, and migrate legacy code to modern frameworks.
https://code.visualstudio.com/blogs/2025/02/24/introducing-c...
Mike Monteiro: Fuck you, pay me.
Rather than sitting through a 50 minute lecture, I found a similar lecture on the same topic (c debugging, I think it was), and pointed out that the MIT instructor covered the same topic, in more depth, in real-time, with a live demo, in overall less time than it took the State University professor to explain. It was concise, wasted no time, and gave me clear information on what I needed to know with minimal extra examples.
And my course instructor hated me pointing that out.
[1]: https://ocw.mit.edu/
You see this already in medicine. Anesthesiologist can oversee up to 6 concurrent cases, with NP’s or CRNA’s doing the actual work.
This only works for straightforward, not medically complicated cases. The more complicated cases (pregnancy, cancer, obesity, etc) are still typically fully managed by an MD /DO.
The results are controversial. Healthcare systems can save cost, but patient care is hit or miss.
https://deepmind.google/discover/blog/gemini-robotics-brings...
Example:
https://github.com/actions/runner/pull/2477#issuecomment-244...
Meanwhile, compared to something written in dotnet or go. I bet there’s a very strong chance those projects will continue to work in 3-5 years.
Did the submitter intentionally change the post title to get more clicks?
https://www.industryweek.com/semiconductors/article/55246295...
https://www.news5cleveland.com/news/politics/ohio-politics/o...
I have a 5.1 surround sound setup with Dolby atmos and 4k HDR 10 with Nvidia Shield Pro android TVs as clients. I have Blu-ray rips that play completely fine on Plex, but stutter, have no sound, or downscale to 2.0 sound on JellyFin.
There are some fixes that involve using a JellyFin server and a Kodi media client on Google TV’s. This does enable DTS and Ddd+ sound. While that technically works, it is very involved and feels like many more steps than just using Plex.
If you use a basic 1080p tv with two speakers and lazy encodes of media, Jellyfin probably works great for you. If you have anything a little more complex then you will inevitably see some problems.
This is similar to other open source projects like Ashai. The basic features are easy enough to build, but the more complicated use cases always require more time and effort, and people aren’t always willing to do that complicated extra effort for free.
I’ve never had any of my open source software used, and I typically license it with MIT, so I’m curious how other groups and organizations actually comply with the license.
At that point the hard work of reverse engineering and coming up with a spec and a reliable piece of software that implements that spec are done. Don’t let that work go to waste.
Why not fork Linux and call it something new, with the hardware support that is exclusively for M1/2/3/4 Mac’s?