DDG’s AI chat isn’t a search engine. It’s just a chat interface for GPT-3.5 Turbo and Claude, without any search access. It’s also not very up to date.
GPT-3.5 Turbo:
Who is the PM of the UK?
As of my last update, the Prime Minister of the United Kingdom is Boris Johnson. Please note that political positions can change, so I recommend checking the latest news sources for the most up-to-date information.
Is Queen Elizabeth still alive?
Yes, as of my last update, Queen Elizabeth II is still alive.
The Claude version doesn’t fare any better:
Is Queen Elizabeth still alive?
Yes, Queen Elizabeth II is still alive. She is the current and longest-reigning monarch of the United Kingdom, having ascended to the throne in 1952. As of 2023, she is 96 years old.
You can also ask it when is the cutoff date of their database - there is a gentleman’s agreement between providers not to have ai involved in news / current politics in it’s public chats.
I tried them on a topic I’m pretty proficient on, (a spaghetti recipe lol) and the answer was the most bland imaginable.
The way it is setup by DDG, the restrictions and blandness, shallowness of the replies give me peace of.mind when a ‘natural language’ query is the easiest one. And Claude wouldn’t give me the DOB of that queen because it is Personal Info!
I also haven’t seen any practical advantage to using LLM prompts vs. traditional search engines in the general case:
For general temporary facts I would agree. Even Amazon’s surmized reviews, it can be handy to know that “Adhesive issues” is commonly sighted… but I’d learn that from reading the reviews anyway… Like, a lot of the time it comes down to AI being used when the human should do their own due diligence. I will even admit to this in the very next paragraph.
I find AI to be especially good at things I am not, like math. I am very good at estimations, and I can work out some stuff over time. However, I am much slower compared to asking “I currently make 2.1-Z a month and I have 397-Z earning that interest. I would like to make 65-Z a month, how much do I need earning interest to make that?” (Roughly 13,100 btw) and getting that answer along with the formula showing its work. It spits out the answer in the amount of time it took me to work out that verbal question, both of which were far faster than the time it takes me to pull up a calculator and do the same math. It’s not that I can’t, it just takes a lot of time that could be better spent actually doing the thing I want to do, which is how many months based off what I earn will it take to reach that number.
Similarly, this reigns true for a lot of things with “facts.” Perpetual facts or immutable facts are the best use for AI. In my opinion based on experience, of course.
A fact about a song will always be in the key it was created in. A key will always have a specific set of scales that can be used with it. Math will always be the answer to an equation. These are, for the most part, immutable facts. A person on the other hand, will not always be their age, or even living, nor will their net worth stay the same. Let’s not even get started on the weather! These are temporary facts.
Quite a few people tend to ask AI temporary facts (rightfully so, it’s what we would like to do on a day to day basis for casual questions), but and it gets a lot of flack for not doing a great job at it (again rightfully so since it’s a basic question.) But I have found that AI is actually quite strong at perpetual facts. When time is short and at the end of the day I just want to jam to my favorite songs, I can get a quick reminder of the key and scales I can use to play along with. On my own I know and can remember these things, but asking a question and getting an answer possibly even faster is really nice.
Not to be pro-AI – In this case I really think it comes down to using the tool you have. We live in the present and the future, so it seems ridiculous to rely on something trained on data rooted in the past and expecting that it will always be that. Hence, immutable facts tending to be more reliable to work with when using AI.
I like tech, so I have used and played with local LLM’s and Stable Diffusion models and worked on a model based on my own art of Zentangles, I don’t think I would ever actively rely on this technology for anything more than cursory fun when I’m short on time and energy, or as a supplement to something that I, frankly, am going to take far too long to learn and will forget in the span of a couple months when I no longer need it. I don’t exactly feel the need to memorize the 300,000 Excel sheet tricks, but I will sure as shit ask BarGemeni about it. Using it to confirm my estimations to see that I was roughly accurate compared to an AI that is roughly accurate is good enough for me for some quick and dirty math.
Ultimately that’s what the LLM-AI debate is for me. Relying on it for anything that is ever changing, using it for anything more than just basic fun is setting yourself up for a bad time. Using it here and there as a calculator or for some non-important details about something that has remained static since the dawn of time? You can net yourself some pretty nice futuristic “Hell yeah’s”. Packing these things up into little boxes like supplanting a phone (or adding it to your phone), using it to create non-existent support (both support staff and supporting terrible products to trick people into buying it), or adding it to rice cookers and refrigerators is… the direction expected but not the one I was hoping for.
Are there any search engines other than perplexity that tie the sources to sections rather than just popping them all at the bottom? That always felt like the most practical layout for being able to easily cross-check information against their supposed sources.
I’d like to share your optimism, but what you suggest leaving us to “deal with” isn’t “AI” (which has been present in web search for decades as increasingly clever summarization techniques…) but LLMs, a very specific and especially inscrutable class of AI which has been designed for “sounding convincing”, without care for correctness or truthfulness. Effectively, more humans’ time will be wasted reading invented or counterfeit stories (with no easy way to tell); first-hand information will be harder to source and acknowledge by being increasingly diluted into the AI-generated noise.
I also haven’t seen any practical advantage to using LLM prompts vs. traditional search engines in the general case: you end up typing more, for the sake of “babysitting” the LLM, and get more to read as a result (which is, again, aggravated by the fact that you are now given a single source/one-sided view on the matter, without citation, reference nor reproducible step to this conclusion).
Last but not least, LLMs are an environmental disaster in the making, the computational cost is enormous (in new hardware and electricity), and we are at a point where all companies partaking in this new gold rush are selling us a solution in need of a problem, every one of them having to justify the expenditure (so far, none is making a profit out of it, which is the first step towards offsetting the incurred pollution).
I'm currently wondering what their plans are for updating these LLMs.
Who wants to create the content to feed these machines without a recognition, retribution or a perceived act of 'good'? If I were to maintain a blog with a particular midly but important obscure topic, would I devote the time to have ChatGPT or Copilot make a summary?
Now, the LLMs need to ingest a lot more than 'one blog'... If someome knows, please let me know.
I doubt this crazy effort with such resource consumption is to create a snapshot of what the internet was in the 2020s.
but LLMs, a very specific and especially inscrutable class of AI which has been designed for “sounding convincing”, without care for correctness or truthfulness.
I think that I’d put it in a slightly less-loaded way, and say that an LLM just produces content that has similar properties to its training content.
The problem is real. Frankly, while I think that there are a lot of things that existing LLM systems are surprisingly good at, I am not at all sure that replacing search engines will be it (though I am confident that in the long run, some form of AI system will be).
What you can’t do with systems like the ones today is to take one data source and another data source that have conflicting information and then have the LLM-using AI create a “deep understanding” of each and then evaluate which is more-likely truthful in the context of other things that have been accepted as true. Humans do something like that (and the human approach isn’t infallible either, though I’d call it a lot more capable).
But that doesn’t mean that you can’t use heuristics for estimating the accuracy of data and that might be enough to solve a lot of problems. Like, I might decide that 4Chan should maybe have less-weight as a solution, or text that ranks highly on a “sarcastic” sentiment analysis program should have less weight. And I can train the AI to learn such weightings based on human scoring of the text that it generates.
Also, I’m pretty sure that an LLM-based system could attach a “confidence rating” to text it outputs, and that might also solve a lot of issues.
I’m not using “AI” in web searches no matter how much any VC bro’s golden parachute depends on it, sorry. Refusing to partake or even using tools to filter out LLM trash are perfectly fine ways to adapt to search engines leaning on AI hype to try to convince you that their inability to combat SEO spam is good, actually.
I am pretty confident that in the long run, pretty much everyone is gonna wind up there, though. Like, part of the time spent searching is identifying information on the page and combining from multiple sources. Having the computer do that is gonna be faster than a human.
There are gonna be problems, like attributability of the original source, poisoning AIs via getting malicious information into their training data, citing the material yourself, and so forth. But I don’t think that those are gonna be insurmountable.
It’s actually kind of interesting how much using something like an LLM looks like Project Babel in the cyberpunk novel Snow Crash. The AI there was very explicit that it didn’t have reasoning capability, could just take natural-language queries, find information, combine it, and produce a human-format answer. But it couldn’t make judgement calls or do independent reasoning, and regularly rejected queries that required that.
Though that was intended as an academic tool, not something for the masses, and it was excellent at citing sources, which the existing LLM-based systems are awful at.
They already ruined web search with SEO. Now it just won’t be worth searching for websites at all. We can either accept whatever nonsense the syntax generator spits out, untethered from fact, or we can stop looking altogether.
That’s what you mean by adapt, right? Accept not having access to real information ever again?
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