> Machine learning technologies like the Bergamot translation project offer real, tangible utility. Bergamot is transparent in what it does (translate text locally, period), auditable (you can inspect the model and its behavior), and has clear, limited scope, even if the internal neural network logic isn’t strictly deterministic.
This really weakens the point of the post. It strikes me as a: we just don't like those AIs. Bergamot's model's behavior is no more or less auditable or a black box than an LLM's behavior. If you really want to go dig into a Llama 7B model, you definitely can. Even Bergamot's underlying model has an option to be transformer-based: https://marian-nmt.github.io/docs/
The premise of non-corporate AI is respectable but I don't understand the hate for LLMs. Local inference is laudable, but being close-minded about solutions is not interesting.
It's not necessarily close minded to choose to abstain from interacting with generative text, and choose not to use software that integrates it.
I could say it's equally close minded not to sympathize with this position, or various reasoning behind it. For me, I feel that my spoken language is effected by those I interact with, and the more exposed someone is to a bot, the more they will speak like that bot, and I don't want my language to be pulled towards the average redditor, so I choose not to interact with LLMs (I still use them for code generation, but I wouldn't if I used code for self expression. I just refuse to have a back and forth conversation on any topic. It's like that family that tried raising a chimp alongside a baby. The chimp did pick up some human like behavior, but the baby human adapted to chimp like behavior much faster, so they abandoned the experiment.)
I’m not too worried about starting to write like a bot. But, I do notice that I’m sometimes blunt and demanding when I talk to a bot, and I’m worried that could leak through to my normal talking.
I try to be polite just to not gain bad habits. But, for example, chatGPT is extremely confident, often wrong, and very weasely about it, so it can be hard to be “nice” to it (especially knowing that under the hood it has no feelings). It can be annoying when you bounce the third idea off the thing and it confidently replies with wrong instructions.
Anyway, I’ve been less worried about running local models, mostly just because I’m running them CPU-only. The capacity is just so limited, they don’t enter the uncanny valley where they can become truly annoying.
That's an interesting example to use. I only use turn signals when there are other cars around that would need the indication. I don't view a turn signal as politeness, its a safety tool to let others know what I'm about to.
I do also find that only using a turn signal when others are around is a good reinforcement to always be aware of my surroundings. I feel like a jerk when I don't use one and realize there was someone in the area, just as I feel like a jerk when I realize I didn't turn off my brights for an approaching car at night. In both cases, feeling like a jerk reminds me to pay more attention while driving.
I would strongly suggest you use your turnsignals, always, without exception. You are relying on perfect awareness of your surroundings which isn't going to be the case over a longer stretch of time and you are obliged to signal changes in direction irrespective of whether or not you believe there are others around you. I'm saying this as a frequent cyclist who more than once has been cut off by cars that were not indicating where they were going because they had not seen me, and I though they were going to go straight instead of turn into my lane or the bike path.
Signalling your turns is zero cost, there is no reason to optimize this.
Its a matter of approach and I wouldn't say what I've found to work for me would work for anyone else.
In my experience, I'm best served by trying to reinforce awareness rather than relying on it. If I got into the habit of always using blinkers regardless of my surroundings I would end up paying less attention while driving.
I rode motorcycles for years and got very much into the habit of assuming that no one on the road actually knows I'm there, whether I'm on an old parallel twin or driving a 20' long truck. I need that for us while driving and using blinkers or my brights as motivation for paying attention works to keep me focused on the road.
Signaling my turns is zero cost with regards to that action. At least for me, signaling as a matter of habit comes at the cost of focus.
The point of making signaling a habit is that you don't think about it at all. It becomes an automatic action that just happens, without affecting your focus.
I have also ridden motorcycles for many years, and I am very familiar with the assumption that nobody on the road knows I exist. I still signal, all the time, every time, because it is a habit which requires no thinking. It would distract me more if I had to decide whether signalling was necessary in each case.
You're making a huge leap here. I'm raising only had signaling intentionally rather than automatically has made me pay more attention to others on the road. You're claiming that that action which has proven to make me pay closer attention will kill someone.
By not signaling you are robbing others on the road the opportunity to avoid a potential accident should you not have seen them. It's maximum selfish fuck everyone else asshole behavior.
No, I'm not claiming it will kill someone, I'm claiming it may kill someone.
There is this thing called traffic law and according to that law you are required to signal your turns. If you obstinately refuse to do so you are endangering others and I frankly don't care one bit about how you justify this to yourself but you are not playing by the rules and if that's your position then you should simply not participate in traffic. Just like you stop for red lights when you think there is no other traffic. Right?
Again: it costs you nothing. You are not paying more attention to others on the road because you are not signalling your turns, that's just a nonsense story you tell yourself to justify your wilful non-compliance.
There is no such thing as not signaling. By not using the turn signal, you are lying to anyone around that you might not see, signaling that you are going straight forward when you aren't.
> I only use turn signals when there are other cars around that would need the indication.
That is a very bad habit and you should change it.
You are not only signalling to other cars. You are also signalling to other road users: motorbikes, bicycles, pedestrians.
Your signal is more important to the other road users you are less likely to see.
Always ALWAYS indicate. Even if it's 3AM on an empty road 200 miles from the nearest human that you know of. Do it anyway. You are not doing it to other cars. You are doing it to the world in general.
> when there are other cars around that would need the indication
This has a failure state of "when there's a nearby car [or, more realistically, cyclist / pedestrian] of which I am not aware". Knowing myself to be fallible, I always use my turn signals.
I do take your point about turn signals being a reminder to be aware. That's good, but could also work while, you know, still using them, just in case.
You're not the only one raising that concern here - I get it and am not recommending what anyone else should do.
I've been driving for decades now and have plenty of examples of when I was and wasn't paying close enough attention behind the wheel. I was raising this only as an interesting different take or lesson in my own experience, not to look for approval or disagreement.
You said something fairly egregious on a public forum and are getting pretty polite responses. You definitely do not get it because you’re still trying to justify the behavior.
Just consider that you will make mistakes. If you make a mistake and signal people will have significantly more time to react to it.
Not to dog pile, just to affirm what jacquesm is saying. Remember, what you do consciously is what you end up doing unconsciously when you're distracted.
Here is a hypothetical: A loved one is being hauled away in an ambulance and it is a bad scenario. And you're going to follow them. Your mind is busy with the stress, trying to keep things cool while under pressure. What hospital are they going to, again? Do you have a list of prescriptions? Are they going to make it to the hospital? You're under a mental load, here.
The last thing you need is to ask "did I use my turn signal" as you merge lanes. If you do it automatically, without exception, chances are good your mental muscle memory will kick in and just do it.
But if it isn't a learned innate behavior, you may forget to while driving and cause an accident. Simply because the habit isn't there.
It's similar for talking to bots, as well. How you treat an object, a thing seen as lesser, could become how a person treats people they view as lesser, such as wait staff, for example. If I am unerring polite to a machine with no feelings, I'm more likely to be just as polite to people in customer service jobs. Because it is innate:
Watch your thoughts, they become words; Watch your words, they become actions.
I think it makes much more sense to treat the bot like a bot and avoid humanizing it. I try to abstain from any kind of linguistic embellishments when prompting AI chat bots. So, instead of "what is the area of the circle" or "can you please tell me the area of the circle", I typically prefer "area of the circle" as the prompt. Granted, this is suboptimal given the irresponsible way it has been trained to pretend it's doing human-like communication, but I still try this style first and only go to more conversational language if required.
It is possible that this is a personality flaw, but I’m not really able to completely ignore the human-mimicking nature of ChatGPT. It does too good a job of it.
Sure, I am more referring to advocating for Bergamot as a type of more "pure" solution.
I have no opinion on not wanting to converse with a machine, that is a perfectly valid preference. I am referring more to the blog post's position where it seems to advocate against itself.
It’s insane this has to be pointed out to you but here we go.
Hammers are the best, they can drive nails, break down walls and serve as a weapon. From now on the military will, plumber to paratrooper, use nothing but hammers because their combined experience of using hammers will enable us to make better hammers for them to do their tasks with.
No, a tank is obviously better at all those things. They should clearly be used by everyone, including the paratrooper. Never mind the extra fuel costs or weight, all that matters is that it gets the job done best.
You can't really dig into a model you don't control. At least by running locally, you could in theory if it is exposed enough.
The focused purpose, I think, gives it more of a "purpose built tool" feel over "a chatbot that might be better at some tasks than others" generic entity. There's no fake persona to interact with, just an algorithm with data in and out.
The latter portion is less a technical and more an emotional nuance, to be sure, but it's closer to how I prefer to interact with computers, so I guess it kinda works on me... If that were the limit of how they added AI to the browser.
Yes I agree with this, but the blog post makes a much more aggressive claim.
> Large language models are something else entirely. They are black boxes. You cannot audit them. You cannot truly understand what they do with your data. You cannot verify their behaviour. And Mozilla wants to put them at the heart of the browser and that doesn’t sit well.
Like I said, I'm all for local models for the exact reasons you mentioned. I also love the auditability. It strikes me as strange that the blog post would write off the architecture as the problem instead of the fact that it's not local.
The part that doesn't sit well to me is that Mozilla wants to egress data. It being an LLM I really don't care.
Exactly this. The black box in this case is a problem because it's not in my computer. It transfers the users data to an external entity that can use this data to train it's model or sell it.
Not everyone uses their browser just to surf social media, some people use it for creating things, log in to walled gardens to work creatively. They do not want to send this data to an AI company to train on, to make themselves redundant.
Discussing the inner workings of an AI isn't helping, this is not what most people really worry about. Most people don't know how any of it works but they do notice that people get fired because the AI can do their job.
The local part is the important part here. If we get consumer level hardware that can run general LLM models, there we can actually monitor locally what goes in and what goes out, then it meets the privacy needs/wants of power users.
My take is that I'm ok with anything a company wants to do with their product EXCEPT when they make it opt out or non-opt-outable.
Firefox could have an entire section dedicated to torturing digital puppies built into the platform and... Ok, well, that's too far, but they could have a costco warehouse full of AI crap and I wouldn't mind at all as long as it was off by default and preferably not even downloaded to the system unless I went in and chose to download it.
I know respecting user preference doesn't line their pockets but neither does chasing users down and shoving services they never asked for and explicitly do not want into their faces.
Translation AI though has provable behavior cases though: round tripping.
An ideal translation is one which round-trips to the same content, which at least implies a consistency of representation.
No such example or even test as far as I know exists for any of the summary or search AIs since they expressly lose data in processing (I suppose you could construct multiple texts with the same meanings and see if they summarize equivalently - but it's certainly far harder to prove anything).
Getting byte exact text isn't the point though: even if it's different, I as the original writer can still look at roundtripped text and evaluate that it has the same meaning.
It's not a lossy process, and N round-trips should not lose any net meaning either.
This isn't a possible test with many other applications.
English to Japanese loses plurals, Japanese to English loses most honoriffics and might need to invent a subject (adding information that shouldn't be there and might be wrong). Different languages also just plain have more words than others with their own nuances, and a round trip translation wouldn't be able to tell which word to choose for the original without a additional context.
Translation is lossy. Good translation minimizes it without sounding awkward, but that doesn't mean some detail wasn't lost.
How about a different edge case. It's easier to round trip successfully if your translation uses loan words. It can guarantee that it translates back to the same word. This metric would prefer using loan words even if they are not common in practice and would be awkward to use.
I think the author was close to something here but messed up the landing.
To me the difference between something like AI translation and an LLM is that the former is a useful feature and the latter is an annoyance. I want to be able to translate text across languages in my web browser. I don't want a chat bot for my web browser. I don't want a virtual secretary - and even if I did, I wouldn't want it limited to the confines of my web browser.
It's not about whether there is machine learning, LLMs, or any kind of "AI" involved. It's about whether the feature is actually useful. I'm sick of AI non-features getting shoved in my face, begging for my attention.
This really weakens the point of the post. It strikes me as a: we just don't like those AIs. Bergamot's model's behavior is no more or less auditable or a black box than an LLM's behavior. If you really want to go dig into a Llama 7B model, you definitely can. Even Bergamot's underlying model has an option to be transformer-based: https://marian-nmt.github.io/docs/
The premise of non-corporate AI is respectable but I don't understand the hate for LLMs. Local inference is laudable, but being close-minded about solutions is not interesting.