My concern is that it doesn't just change war, but security in general. I don't think that we have realized the real implications of this technology, especially the fiber optic drones.
> I don't think that we have realized the real implications of this technology
Define “we.” The defence community has been deeply engaged with what’s going on in Ukraine since ‘22. (And the supremacy of sensor fusion in India’s air battle with Pakistan.)
We as a society. I don't want to write down my detailed thoughts on this, but anyone with a red team mind can imagine the implications for personal security.
Kim Stanley Robinson wrote down pretty bluntly what society might do against the vicious nasty foes of the world with drones, in Ministry for the Future. A book very well reviewed by for example Bill Gates. https://www.gatesnotes.com/books/science-fiction/reader/the-...
Alas it feels optimistic to hope that asymmetric confrontation would be downtrodden people of the earth against bad world damaging take-take-take pests. Merely a science fiction. The world having powerful forces working strongly for the world rather than self interest: hardly believable science fiction.
It's cheaper now, it's easier to pull off remotely, but most airports already were vulnerable to terrorist attacks. It feels like the primary mechanism that protected civilian airports is that the weapons you'd use aren't easy to get, and states didn't want to supply their sponsored terror groups with that kind of weaponry because it'd be dangerously close to an act of war and very hard to deny.
Individually, you were never safe by default. Your safety depends on not being an interesting target.
So you know, if instead of being one guy he was a substantial portion of intelligence operatives of a nation-state with significant industrial resources backing him?
Ukraine isn't wealthy, but it's still an entire country.
Bluntly: nothing is safe from drones + a determined operator. No airfield, no aircraft on the ground, no government institution. Drones have changed warfare forever and Ukraine is writing the manual for future operations. What happened today was unthinkable 10 years ago. As one side effect I predict that at least in some places private drone ownership will become illegal. Think about it: for a few hundred K you get to take out a good chunk of a nuclear power's strike capability.
We’re in a strategic imbalance. Cold War air defences were trained on high-value targets, like strategic bombers and spy planes. So currently our air defences are overspecced for something like this.
Nothing about drones makes them inherently undetectable. You just need a different model. I suspect those should be commonplace within 20 years, potentially a decade.
> at least in some places private drone ownership will become illegal
I could see ownership being restricted in wartime. More likely is eager air defences shredding birds on perimeters.
Won't the cat and mouse game ultimately tilt to the side of defense? I imagine automated rifles are basically impossible to dodge. Automated rifles sound much more scary to me. Plant a rifle and wait a year, works on people and drones.
> Won't the cat and mouse game ultimately tilt to the side of defense?
Probably not. Most of the history of war is weapons getting stronger and stronger and defence getting harder and harder. E.g. in ancient times a shield or simple palisade could protect you, now even tanks and trenches are not safe. The days of being able to build a wall along a border and hold it against a peer adversary are long gone and not coming back.
I feel like this correlates with nations getting bigger over time and the square-cube law (or line-square law for national borders?) but I am not smart enough at military stuff to figure it out
I've read that it's kind of the converse - as military technology advances the size of a "minimum viable nation" increases. E.g. as gunpowder technology developed, anywhere that couldn't afford to field a gunpowder military got absorbed into somewhere that could.
On the other hand defensive alliances like NATO and the like pretty much work. A couple of centuries ago war was all over the place. These days most people never see it unless they deliberately go to a war zone.
You need a globe - an old school one, physical, a map of the black soils, population density and to remember how long it took Prigozhin to get to Moscow outskirts, with all the stops, interviews and scuffles with VVS.
To be fair, these planes were out in the open, protected by tires on the wings. If they were in simple hangars, this operation would have already been way harder.
I doubt they're claiming to have anything novel in their heads. It is like WWII where the militarily engaged people probably had a pretty good idea of what was about to happen as Europe descended into war. The citizens didn't really understand and there wasn't the level of diplomacy and panic in the early stages that the eventual crisis would have justified.
If the average citizen had a good understanding of what an industrial war looked like and what was possible, they'd (taking an optimistically charitable view) have spent the 20s and 30s being a lot more vigorous in trying to keep the peace. Like the efforts we say from the 40s to around the 2010s where people who remembered WWII put huge amounts of effort into not letting it happen again.
Real implications are that once again you don’t want your personal shit being public, which will still take some while for gen.audience to understand about social media and all sorts of corporate surveillance.
This is a common mistake and very badly communicated. The GIL do not make the Python code thread-safe. It only protect the internal CPython state. Multi-threaded Python code is not thread-safe today.
Internal cpython state also includes say, a dictionary's internal state. So for practical purposes it is safe. Of course, TOCTOU, stale reads and various race conditions are not (and can never be) protected by the GIL.
It's memory safe, but it's not necessarily free of race conditions! It's not only C extensions that release the GIL, the Python interpreter itself releases the GIL after a certain number of instructions so that other threads can make progress. See https://docs.python.org/3/library/sys.html#sys.getswitchinte....
Certain operations that look atomic to the user are actually comprised of multiple bytecode instructions. Now, if you are unlucky, the interpreter decides to release the GIL and yield to another thread exactly during such instructions. You won't get a segfault, but you might get unexpected results.
This should not have been downvoted. It's true that the GIL does not make python code thread-safe implicitly, you have to either construct your code carefully to be atomic (based on knowledge of how the GIL works) or make use of mutexes, semaphores, etc. It's just memory-safe and can still have races etc.
We already have. Chrysler laid off 3600 people in Canada due to tariffs, and 900 people in the US that worked at plants supplying the Canadian factory.
From my use case, the Gemini 2.5 is terrible. I have a complex Cython code in a single file (1500 lines) for a Sequence Labeling. Claude and o3 are very good in improving this code and following the commands. The Gemini always try to do unrelated changes. For example, I asked, separately, for small changes such as remove this unused function, or cache the arrays indexes. Every time it completely refactored the code and was obsessed with removing the gil. The output code is always broken, because removing the gil is not easy.
That matches my experience as well. Gemini 2.5 Pro seems better at writing code from scratch, but Claude 3.7 seems much better at refactoring my existing code.
Gemini also seems more likely to come up with 'advanced' ideas (for better or worse). I for example asked both for a fast C++ function to solve an on the surface fairly simple computational geometry problem. Claude solved it in a straight ahead and obvious way. Nothing obviously inefficient, will perform reasonably well for all inputs, but also left some performance on the table. I could also tell at a glance that it was almost certainly correct.
Gemini on the other hand did a bunch of (possibly) clever 'optimisations' and tricks, plus made extensive use of OpenMP. I know from experience that those optimisations will only be faster if the input has certain properties, but will be a massive overhead in other, quite common, cases.
With a bit more prompting and questions from my part I did manage to get both Gemini and Claude to converge on pretty much the same final answer.
You can fix this using a system prompt to force it to reply just with a diff. It makes the generation much faster and much less prone to changing unrelated lines. Also try reducing the temperature to 0.4 for example, I find the default temperature of 1 too high. For sample system prompts see Aider Chat: https://github.com/Aider-AI/aider/blob/main/aider/coders/edi...
This reflects my experience 1:1... even telling 2.5 Pro to focus on the tasks given and ignore everything else leads to it changing unrelated code.
It's a frustrating experience because I believe at its core it is more capable than Sonnet 3.5/3.7
Playing devils advocate here, it's because removing a function is not always as simple as deleting the lines. Sometimes there are references to that function that you forgot about that the LLM will notice and automatically update for you. Depending on your prompt it will also go find other references outside of the single file and remove those as well. Another possibility is that people are just becoming used to interacting with their codebase through the "chat" interface and directing the LLM to do things so that behavior carries over into all interactions, even perceived "simple" ones.
I like to code with an LLMs help making iterative changes. First do this, then once that code is a good place, then do this, etc. If I ask it to make one change, I want it to make one change only.
For me I had to upload the library's current documentation to it because it was using outdated references and changing everything that was working in the code to broken and not focusing on the parts I was trying to build upon.
If you don't mind me asking how do you go about this?
I hear people commonly mention doing this but I can't imagine people are manually adding every page of the docs for libraries or frameworks they're using since unfortunately most are not in one single tidy page easy to copy paste.
Have the AI write a quick script using bs4 or whatever to take the HTML dump and output json, then all the aider-likes can use that json as documentation. Or just the HTML, but that wastes context window.
I am hoping MCP will fix this. I am building an MCP integration with kapa.ai for my company to help devs here. I guess this doesn’t work if you don’t add in the tool
That's expected, because they almost all have training cut-off dates from a year ago or longer.
The more interesting question is if feeding in carefully selected examples or documentation covering the new library versions helps them get it right. I find that to usually be the case.
Adjusting temperature is something I often forget. I think Gemini can range between 0.0 <-> 2.0 (1.0 default). Lowering the temp should get more consistent/deterministic results.
How are you asking Gemini 2.5 to change existing code? With Claude 3.7, it's possible to use Claude Code, which gets "extremely fast but untrustworthy intern"-level results. Do you have a prefered setup to use Gemini 2.5 in a similar agentic mode, perhaps using a tool like Cursor or aider?
For all LLMs, I´m using a simple prompt with the complete code in triple quotes and the command at the end, asking to output the complete code of changed functions. Then I use Winmerge to compare the changes and apply. I feel more confident doing this than using Cursor.
Should really check out aider. Automates this but also does things like make a repo map of all your functions / signatures for non-included files so it can get more context.
The focus on benchmarks affords a tendency to generalize performance as if it's context and user independent.
Each model really is a different piece of software with different capabilities. Really fascinating to see how dramatically different people's assessments are
I take the same prompt and give it to 3.7, o1 pro, and gemini. I do this for almost everything, and these are large 50k+ context prompts. Gemini is almost always behind
Am I in a bubble? There is any justification about Trump actions? From my perceptive(Brazilian) the US is dissolving all the soft-power it had in a record-breaking speed.
Your perspective is no different than mine (as an American).
Trump's actions (in general, not just this one) are driven entirely by petty revenge and self-enrichment and are harming America to the point where it is going to take decades to recover, if ever.
I´m super excited, sleepless for a couple of days already. I´m trying to use all tricks possible to improve a Sequence Labeling using Conditional Random Fields. I need to NER billion of documents, and need to be fast.
CRFSuite is a workhorse, and a baseline very hard to beat with speed and precision. But with o3 I´m created a frank-stain with many tricks such as CRF with variable order, feature interactions, bidirectional, jointly learning with word embeddings. The precision is already over than CRFSuite. And I believe that would be better than many other solutions such as bi-lstm-crf. Definitely much faster.
Now i´m trying to port to Cython to make as fast as possible. Here o3 is almost useless, but I´m progressing.
Every six months, I explore switching from MySQL to something new for a more modern tech stack. However, MyRocks (https://docs.percona.com/percona-server/8.4/myrocks-index.ht...) is truly impressive. It allows me to efficiently compress my text-rich rows.
Read the parent post to this one, AI slop has an uncanny valley associated with it. Somehow it sticks out like a sore thumb but i can't put my finger on why.
I don't know, I didn't spot that this was AI generated. Perhaps because there's some truth that MyRocks is actually really good at compression.
Back when I was exploring migrating from TokuDB to MyRocks the only problem with it was that it didn't have a file per partition, meaning if you were doing retention you couldn't just drop old daily partitions cheaply.
