nekitamo
Joined 15 years ago
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244
Member since
Feb 10
Recent submissions
Comment · 7 days ago
Comment · 14 days ago
Could you recommend me a few?
Comment · 21 days ago
This article is a summary of the author's progress in decompiling CoD: MW2. More info and screenshots can be found on their Twitter feed:
Comment · 2 months ago
I think you're on to something. It's really concerning that the people with the money to run these ad campaigns are so removed from the bulk of the populace that they don't even bother targeting them with all the billboards anymore, just each other.
Otoh maybe I'm looking at it wrong, and maybe billboard advertising has gotten so ineffective that it's cheapened to the point that you can tuck it into your campaign as an afterthought. If you get one solid enterprise lead from it, it pays for the whole year. And besides it has branding value.
Either way, definitely feels a bit dystopian to me. How alienating must it feel for the service worker commuting to his dead end job where even the billboards don't make sense anymore?
Comment · 3 months ago
This tracks, in my experience the 27B is better at coding and instruction following. I'm shocked at how much of a difference the dense models vs MoE makes.
But it's a moot point, because for local inference on consumer hardware, the MoE is so much faster.
Comment · 3 months ago
Yes, Wine was (EDIT: partially) compatible with the Roblox anti-cheat, and there was a period in time where Roblox with its anti-cheat ran on Wine. Eventually, however, a decision was made to block Wine.
EDIT It looks like the Roblox anti-cheat devs themselves explained why Wine was blocked:
https://devforum.roblox.com/t/roblox-on-linux-everything-sum...
Comment · 3 months ago
I personally liked their Code virtualizer. And it's under active development. Sorry to hear about Theia, I haven't run into it yet.
Comment · 3 months ago
This isn't true. Roblox never had and does not have a kernel anti-cheat.
Comment · 4 months ago
I don't think that's necessarily true. Certainly the video streaming is expensive, but other things like workers and KV store are quite cheap and performant and powerful _if you structure your access patterns accordingly_ .
Cloudflare pricing introduces an additional dimension for when you're architecting software on top of them, but if you do it correctly, your product has the potential to be faster, cheaper, and easier to run than traditional solutions running on multiple geographically distributed VMs. You just can't approach them as if they're just another VM instance provider and expect a similar experience and pricing. What they do and price for is fundamentally different from that.
Comment · 4 months ago
They are still around, under the name Denuvo :)
Comment · 4 months ago
You can protect human rights without stifling progress. It's not a "pick one of the above" situation.
The EU can and should reform many parts of its sclerotic laws and bureaucracies. Whether it can do so before it becomes a subservient puppet state which serves as a battleground for competing powers remains to be seen.
Comment · 5 months ago
While AI isn't particularly good with obfuscated code, it is true that code obfuscation in most old games can be removed relatively easily. The attack and defense state-of-the-art has moved on from those days.
Comment · 5 months ago
Given that 42% of Android devices are unpatched as of now [1] it's an interesting decision on their part to release their research and make them all vulnerable
[1] https://gs.statcounter.com/android-version-market-share [2] https://www.cybersecurity-insiders.com/survey-reveals-over-1...
I've been sick with stomach flu the past few days, so I put together a small benchmark for all the top AI models where I ask them to reverse engineer a very simple small crackme (https://www.crackmes.one/crackme/6ab4ce5195b976f8f1300b54) using Ghidrasql (https://github.com/0xeb/ghidrasql)
(As an aside: I think representing tools for AI as virtual SQL tables is much better than traditional MCP servers, and that this approach deserves a lot more attention. Props to Elias Bachaalany for thinking out of the box and putting it together).
The results of the benchmark are below. It's sorted by cost, but I added notes about each AI model for myself. The notes try to talk about intelligence, speed, and cost. Intelligence is a subjective measure which I assign to each model by reading its thinking tokens and watching its tool calls. You can definitely tell which models are more intelligent, even on this small benchmarks, by their tool use, false starts, and how easily they fall for the simple misdirection in the crackme.
(gist is more readable on mobile) https://gist.github.com/markoglasgow/8812c19b6fbffed30b2661b...
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```The latest Deepseek-Flash model was the most impressive of the open models. Intelligent, fast, cheap. What more do you want? I think the Xiaomi MiMo - Flash model did well, but it might be a fluke, given how poorly the Xiaomi MiMo Pro model performed (it wandered off on a million side quests).
What's also interesting is how competitive Luna is to the lower end Chinese models. It's quite a bit more intelligent, burns a lot less tokens, is plenty fast and very cheap. After doing this experiment, I don't think it's a foregone conclusion that the American AI labs will be having the bottom of the market eaten away by the Chinese models. It seems they (at least OpenAI) can compete on the bottom end as well.
Finally, the benchmark's results reinforce a few things people have been saying about Sonnet and Terra, namely, they're not competitive for a range of tasks. For easier tasks, Haiku/Luna are plenty capable. For harder tasks, Opus and Sol are so much more intelligent, that they can get them done quicker and cheaper. Maybe there is a place for them in the "Opus designs and Sonnet implements" workflows, but in that case, why not "Opus designs and Deepseek implements?"
PS Code harness used was Claude Code. $20 in openrouter credits was used to access the models. Kimi K3 and Deepseek were also accessed directly via the API and then compared to Openrouter. Kimi K3 specifically was much faster on Openrouter, and the difference in output tokens to get the same results for Deepseek/Kimi makes me think the Openrouter providers are hosting significantly quantized versions of the model. Goes to show that Moonshot.ai's acceptance testing of providers is a useful thing, otherwise your model might look artificially bad when it's hosted as heavily quantized by providers who dont care about quality, just top-line cost and speed.