We wanted to buy train tickets the other day, but it was just a lottery and no way to actually buy tickets in advance, do you know what's up with that? Buying flights was just normal so sadly we just did that.
This reaction is interesting to me. In many jurisdictions around the world, police are required to call off a chase if it is deemed unsafe for any reason.
In what world do you think it is OK for a 12-year-old boy riding an e-scooter to die after being chased by police? Before you respond: Ask yourself how you would react if it was your son (or close relative). Any parent would devasted.
I don't participate in clan mentality, where every tragedy has to be blamed on an outsider. An accident is tragic, it doesn't make it any less tragic that it was the kid's own fault. Or if you can't stand not having somebody else to blame, it's clearly the parent's fault.
Both sides are to be blamed, only one side are professional adults who are trained protect our community. A pursue is always dangerous, not only for the suspect but also for the cops and bystanders so it should not be done if not absolutely necessary.
Setting aside the question who is to be blamed, using motorcycles to pursue kids on bikes will cause the deaths of more kids. Is that a price worth paying? No.
It's been at least 10 years that google translate had hallucinations.
Some translation simply change depending of a ponctuation mark.
But peoples complain only now that they heard about AI.
Of course it's not perfect, but I agree that we didn't had a machine translation as good before.
Could you please explain briefly then why my statement is wrong? What are the fundamental challenges not addressed by LLMs today? Do you think the whole approach has insurmountable roadblocks ahead, or is it more of a matter of refinement?
Context dependant phrases, from simple pronouns to whole domain specific terms, are still randomly wrong, sometimes appallingly so. Hallucinations still happen. Auto-AI translation youtube uses is, bluntly, horrid. Any jokes, even obvious ones, are still fumbled frequently.
LLM based translation looks more convincing but requires the same level of scrutiny that previous tools did. From a workflow POV they only added higher compute costs for very questionable gains.
> Auto-AI translation youtube uses is, bluntly, horrid. Any jokes, even obvious ones, are still fumbled frequently.
Youtube auto-translations are horrible indeed, and I say that as someone that has to live with the fact that Youtube decides to badly translate titles from a language I understad to Spanish because bilingual people don't exist I suppose. But that is because they use some dumb cheap model to make the translations; probably not even a Gemini-based model.
> Hallucinations still happen. Auto-AI translation youtube uses is, bluntly, horrid. Any jokes, even obvious ones, are still fumbled frequently.
I've seen that too, but these were all dedicated translation tools and auto-translate functionality.
My benchmark is against SOTA LLMs used directly. I.e. I copy the text (or media) in question, paste directly to ChatGPT or Gemini (using the best model on basic paid tier), and ask for translation. Not always perfect, but nearly so - and they naturally ingest additional context if available - such as the surrounding text, or title/ID/URI of the document/website you're looking at, or additional explanations in the prompt - and make very good use of it. This has always been missing in dedicated tools, historically built around the mistaken assumption that translation is merely a function of input text and pair of language designators (from, to). The shorter the input, the more apparent it becomes how much context matters.
RE YouTube and such - or, like any auto-transcription in video calls I've seen - I can't explain that by anything other than service providers cheapening out on this.
> From a workflow POV they only added higher compute costs for very questionable gains.
Regarding the costs - I imagine they may be an issue at scale, but for regular use (on-demand translation of individual passages, documents, recordings), it feels like it shouldn't be that noticeable anymore. You don't need to run GPT-5 for everything, some models you can run client-side already seem decent enough, and they keep improving.
> LLM based translation looks more convincing but requires the same level of scrutiny that previous tools did.
That's fair. Ultimately, if you don't know both languages, you can only trust the translation as much as you trust the translator (human or otherwise). We'll have to get a feel for this as much as we did with Google Translate, et al. In my experience, whenever I can verify them, results from LLMs are already vastly superior to prior art.
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Tangent, and why I started considering LLMs as solving universal translation in the first place: 6 months ago, when I needed to talk with someone with whom I had zero language overlap, I tried several well-known translation apps (notably Google and Samsung), and none could manage - but then, on a whim, I just asked ChatGPT (in "advanced voice" mode) to "play a game" where it listens in and repeats whatever was just said in language A, but translated to language B, and vice versa -- and it worked flawlessly on first try.
I don’t want nor need on device translation enabled by default. I’ve gone without it for the three decades in which browsers have been around. I’m sure it’s brilliantly useful for some people. A one time ‘would you like to enable AI on startup’ for at least years with user profiles that are significantly old would at least be a show of good faith.
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