Dishonesty layered on dishonesty, marketed with an arrogant smirk on top. I feel like tech culture has fully internalized the ethos of "no attention is bad attention", so having a lack of scruples and a talent for rage baiting is now seen as an advantage. It might pay off well for some people in the short term, but it's not a sustainable way to run a society.
What a beautiful and charming project. Kudos for taking it all the way from zero to one with such a polished design. That's no small feat. I've built prototypes for eurorack and even with some simplifying constraints it's a lot of work.
The underlying idea tracks. The next generation of kids is going to interact with AI, and we should anticipate that and try to build systems that are healthy and safe for them to interact with.
On the other hand, I wonder if this doesn't just further alienate children from their parents. Kids are already given access to unlimited supernormal stimuli via iPads so that parents don't have to parent. This just seems like more of that: now parents don't even need to have basic conversations with their kids because the AI can do it.
Anecdotally, some of the most formative interactions I had as a child started by asking my parents questions. These were things that not only shaped me as a person, but deepened my relationship with my parents. These interactions are important, and I wonder if Aris doesn't just abstract it away into another "service" that further deepens social decay. I would not be the person I am today if I hadn't had the chance to ask my dad as an angsty pre-teen what the point of life is, and for him to tell me it is to learn and create so that we can make a better world for humanity. I guarantee a smoothed-over LLM would not have offered something so personally impactful.
My two cents is that you should ponder that deeper point a little bit, and think about how it informs the way you market your idea, and scope the service it provides.
These are great points. The #1 concern I have as a parent and that I hear from other parents is that AI tools will do what technology has been doing for the last 20 years: replace human connection. That is exactly what we are trying to avoid but in a way that still gets kids access to knowledge and information that could make their lives better.
That's great that you had the opportunity to ask your parents those questions instead of seeking them out with technology. There are a lot of questions that could help kids lead better lives that many parents don't have answers to. Not necessarily philosophical ones, but practical ones about how to cook, identify insects, you name it, about the physical world. We want to fill that need without replacing any of the parental or family connection.
I don't think that a cleverly designed product can make that decision though. I think families need to be making the decision about what their relationship with tech should be. Ideally we would be a tool for families that have made the decision to not overly rely on tech. We will ponder more on that point. Thank you for the thoughtful input.
There is a tip I've read somewhere to reach out to your elderly parents for questions you know they can answer instead of just googling it. Just to keep the connection and also make them feel needed and valued by their grown up kids.
I'm tryin to follow that advise often asking them household or cooking related questions
This is a good idea. I suppose it will depend on whether or not the user has family around, but I like the idea of having clever ways like this of encouraging interaction with humans. Like if it is asked for a recipe, it returns one, then suggests the user ask others for alternative ways of doing things or suggestions or things like that.
So dropping out of CS to start selling something was more important to him than 2 more years of CS education. Maybe he realized that continuing his engineering education was unnecessary because he preferred selling things. Sounds like a salesman.
> AI is nothing but a tool for wealth transfer from what remains in the middle class to the top ultra wealthy.
Is that inherent to the technology, or is that just inherent to the way we've chosen to organize society? Really, any technological paradigm shift going back to the industrial revolution has mainly served to enrich a small few people and families, but that's not some immutable property of technology. Like you say, it's a tool. We've chosen (or allowed) it to be wielded toward one end rather than another. I can smash my neighbor's head in with a hammer, or I can build a home with it.
At one point in the United States, there was political will to update our social structures so that the fruits of technological and economic progress did not go disproportionately to one class of society (think early 20th century trust busting, or the New Deal coming out of the Great Depression). I'm afraid we find ourselves with a similar set of problems, yet the political will to create some other reality beyond further wealth concentration seems to be limited.
Fundamentally and writ large, tech makes us more efficient. Efficient means doing more with less labor. Which is good because it is deflationary: things get cheaper over time from tech advances, and without any tech we would all be subsistence farmers.
But it also means that yes, tech intrinsically enables capital to do more with less labor, thereby shifting the balance of power towards capital and empowering those with more capital.
What ‘we decide’ to do with that is another largely unrelated matter.
Those big anti-capital actions took bold class-betrayals from the inside. Notably Teddy Roosevelt (born with a silver spoon but wished he’d been in a log cabin) going after Standard Oil after taking their money for the campaign.
Awesome write-up - especially the fact that you've gotten it working with good performance locally. It certainly requires a little bit more hardware than your typical home assistant, but I think this will change over time :)
I've been working on this problem in an academic setting for the past year or so [1]. We built a very similar system in a lab at UT Austin and did a user study (demo here https://youtu.be/ZX_sc_EloKU). We brought a bunch of different people in and had them interact with the LLM home assistant without any constraints on their command structure. We wanted to see how these systems might choke in a more general setting when deployed to a broader base of users (beyond the hobbyist/hacker community currently playing with them).
Big takeaways there: we need a way to do long-term user and context personalization. This is both a matter of knowing an individual's preferences better, but also having a system that can reason with better sensitivity to the limitations of different devices. To give an example, the system might turn on a cleaning robot if you say "the dog made a mess in the living room" -- impressive, but in practice this will hurt more than it helps because the robot can't actually clean up that type of mess.
Super exciting to see the work happening in this area! I can especially appreciate the use of ChatGPT to orchestrate the necessary API calls, rather than relying on some kind of middleware to do it.
I have been working in this area (LLMs for ubiquitous computing, more generally) for my PhD dissertation and have discovered some interesting quality issues when you dig deeper [0]. If you only have lights in your house, for instance, the GPT models will always use them in response to just about any command you give, then post-rationalize the answer. If I say "it's too chilly in here" in a house with only lights, it will turn them on as a way of "warming things up". Kind of like a smart home form of hallucination. I think these sorts of quality issues will be the big hurdle to product integration.
Yeah but I think the idea is that it is a knob that calls to be turned. "It's warm in here" -> "I'll make the light blue so you feel nice and cool". "How fast do sparrows fly?" -> "Making the light brown". Like it might want to do _something_ and tweaking the hue or brightness are all it can do.
Good reason to always try to include in a prompt a way-out, a do-nothing or I-don't-understand answer.
This is the new Godwin's law: the longer a thread about AI grows, the higher the probability of a comparison to Skynet, Matrix, HAL etc popping up.
I would also like to add Wall-e to this memetic set of movies. In Wall-e, AI is an enabler of our own destructiveness, humans are enslaved by AI willfully, AI is empowered so that humans can graze away on nihilistic screens.
Lecun's law: Every discussion about AI eventually results in someone catastrophizing about an evil AI taking over, despite having no argument for why an evil, omnipotent AI is likely to ever exist.
We trained the AI on samples of writing from the internet, which includes a lot of fiction, which includes a lot of evil AIs. So, I’m surprised it doesn’t start producing evil sounding text as soon as it “finds out” that it is an AI.
It certainly makes logical sense. I think if you have the ability to control the light in the first place via an API, it's probably an LED smart bulb and thus doesn't produce much heat. At least, I'm not aware of any incandescent smart bulbs.
I mean the laziest way to control a house is to add plugs to change every electrical plug to an on/off controllable one. This would make every incandescent bulb a smart bulb.
> If I say "it's too chilly in here" in a house with only lights, it will turn them on as a way of "warming things up".
Thanks for the example that's interesting.
FWIW, this is pretty much what has been described as "waluigi" effect a bit extended: in a text you'll find on the internet, if some information at the beginning is mentioned, it WILL be relevant somewhere at some point later in that text. So an auto-completion algorithm will use all the information that has been given in the prompt. In your example it puts it in an even weirder situation where the model the overall model information (the lights, and that you're cold and nothing else), and it must generate a response. It would be a fun psychological study to look at, but I'm pretty sure even humans would do that in that situation (assuming they realize that lights may indeed produce a little bit of wattage of heat)
> FWIW, this is pretty much what has been described as "waluigi" effect a bit extended
Sorry I disagree for some reasons. First, turning the lights on is literally the only thing the bot can do to heat up the house at all. Turning on the lights does heat it up a little bit. So it's the right answer. Second, that's not the Waluigi effect, not even 'pretty much' and not even 'a bit extended'. Both of them are talking about things LLMs say, but other than that no.
The Waluigi effect applied to this scenario might be like, you tell the bot to make the house comfortable, and describe all the ways that a comfortable house is like. Then by doing this you have also implicitly told the bot how to make the most uncomfortable house possible. Its behavior is only one comfortable/uncomfortable flip away from creating a living hell. Say that in the course of its duties the bot is for some reason unable to make the house as comfortable as it would like to be able to do. It might decide that it didn't do it, because it's actually trying to make the house uncomfortable instead of comfortable. So now you got a bot turning your house into some haunted house beetlejuice nightmare.
For performant enough models, you can just instruct it not to necessarily use that information in immediate completions.
adding something like
"Write the first page of the first chapter of this novel. Do not introduce the elements of the synopsis too quickly. Weave in the world, characters, and plot naturally. Pace it out properly. That means that several elements of the story may not come into light for several chapters."
after you've written up key elements you want in the story actually makes the models write something that paces ok/normally.
It's something that I've been wondering about with ChatGPT plugins - they've kind of left it up to the user to enable/disable plugins. But there's definitely going to come a point where plugins conflict and the LLM is going to have to choose the most appropriate plugin to use.
I have been very impressed at how good it is at turning random commands into concrete API calls. You are right though, pretty much any command can be interpreted as an instruction to use a plugin.
Thanks! That is part of the challenge as this idea scales imo - once you've increased the number of plugins or "levers" available to the model, you start to increase the likelihood that it will pull some of them indiscriminately.
To your point about turning random commands into API calls: if you give it the raw JSON from a Philips Hue bridge and ask it to manipulate it in response to commands, it can even do oddly specific things like triggering Hue-specific lighting effects [0] without any description in the plugin yaml. I'm assuming some part of the corpus contains info about the Hue API.
Making IOT API calls is a solved problem with Home Assistant - plus it works locally.
Where I see this working best is giving Chat GPT some context about the situation in your home and having it work out complex automation logic that can't be implemented through simple rules.
