The added value of the LLM here is probably zero. Just type a search propmt in a search engine. If the top 5 results don't cover the same ground your article is covering, at the very least, your article will expose new knowledge to people using that search term.
Typing up LLM instructions and reading the output is probably more work.
What would be the incentive for site owners to reduce the appeal of their site? The user has connected to the site, so there's obviously no immediate problem.
In the video you can see that the LED lights the logo less evenly than the EL lighting. While that's not important at all, this might be the reason behind this odd choice
A disposable sandbox wont protect you from secret exfiltration. Assuming you don't consider your code a secret, you could of course set up your sandbox so it doesn't have any secrets, but that would severely limit the kinds of tasks you can use the agent for.
If flying ever becomes efficient energy-wise, this may happen. However, right now, flying is very energy inefficient, so anything that doesn't need to be flown, is transported overland to save costs. A change of fuel won't change it, unless the underlying energy usage changes fundamentally.
Better batteries do not impact energy usage, only the means of energy delivery.
The data centre runs on a dedicated power line. My laptop runs on battery. Using coding agents currently drains battery quite fast, which is surprising, given that the vast majority of the work does not take place on my laptop.
Making the client side coding agent more efficient isn't about saving the climate. It is about extending the workday (which might actually make the climate worse)
While i agree, the current JS security model rally doesn't allow for distinguishing origin for JS code. Should that ever change, advertisers will just require that you compile their library into the first party js code, negating any benefit from such a security model.
Their own (presumably cherry picked) benchmarks put their models near the 'middle of the market' models (llama3 3b, qwen3 1.7b), not competing with claude, chatgtp, or gemini. These are not models you'd want to directly interact with. but these models can be very useful for things like classification or simple summarization or translation tasks.
These models quite impressive for their size: even an older raspberry pi would be able to handle these.
There's still a lots of use for this kind of model
Maybe the news has distorted a bit after crossing the Atlantic, but waren't there substantial outrages after the bits that couldn't be touched had in fact been touched?
Two things are holding back current LLM-style AI of being of value here:
* Latency. LLM responses are measured in order of 1000s of milliseconds, where this project targets 10s of milliseconds, that's off by almost two orders of magnitute.
* Determinism. LLMs are inherently non-deterministic. Even with temperature=0, slight variations of the input lead to major changes in output. You really don't want your DB to be non-deterministic, ever.
How do you propose we measure signal? Lines of code is renowned for being a very bad measure of anything, and I really can't come up with anything better.
From my experience, LLMs understand prompt just fine, even if there are substantial typos or severe grammatical errors.
I feel that prompting them with poor language will make them respond more casually. That might be confirmation bias on my end, but research does show that prompt language affects LLM behavior, even if the prompt message doesn't change/
Infinitief scrolling is only mentioned in the title. The actual legislation focuses on addictive patterns of which infinite scroll is just one. The exact formulation will of course matter a lot, but it will not simply be banning infinite scroll, as that would be trivial to circumvent.
The "lethal trifecta" is a limited view on security, as it's mostly concerned with leaking data. This solution focuses on a different aspect: the ability of rogue actions (instead of rogue communications per #3).
This is especially true if the marketing team claims that humans were validating every step, but the actual humans did not exist or did no such thing.
If a marketer claims something, it is safe to assume the claim is at best 'technically true'. Only if an actual engineer backs the claim it can start to mean something.
There's a daily token limit. While I've never run into that limit while operating Claude as a human, I have received warnings that I'm getting close. I imagine that an unattended setup will blow through the token limit in not too much time.
Typing up LLM instructions and reading the output is probably more work.