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The PR folks at my current company are in full panic mode on Linkedin, judging from the passive-aggressive tone of their posts (sometimes very nearly begging cu
by dserban 4y ago
The PR folks at my current company are in full panic mode on Linkedin, judging from the passive-aggressive tone of their posts (sometimes very nearly begging customers not to use ChatGPT and friends).
They fully understand that LLMs are stealing lunch money from established information retrieval industry players selling overpriced search algorithms. For a long time, my company was deluded about being protected by insurmountable moats. I'm watching our PR folks going through the five stages of grief very loudly and very publicly on social media (particularly noticeable on Linkedin).
Here's a new trend happening these days. Upon releasing new non-fiction books to the general public, authors are simultaneously offering an LLM-based chatbot box where you can ask the book any question.
There is no good reason this should not work everywhere else, in exactly the same way. Take for example a large retailer who has a large internal knowledge base. Train an LLM on that corpus, ask the knowledge base any question. And retail is a key target market of my company.
Needless to say I'm looking for employment elsewhere.
- mashygpig 4y ago> Here's a new trend happening these days. Upon releasing new non-fiction books to the general public, authors are simultaneously offering an LLM-based chatbot box where you can ask the book any question. Can you link to an example?
- dserban 4y agoI saw at least two examples of this here on HN. One of the books was about tech entrepreneurship 101, and I remember asking how to launch if you're a sole developer with no legal entity behind the product. I remember the answer being fairly coherent and useful. I don't have the URL handy, I suspect if you search HN for "entrepreneur book" you'll find it.
- org3 4y agohttps://portal.konjer.xyz/ https://portal.konjer.xyz/
- throwayyy479087 4y agoSome of the responses I've had so far to this are remarkable. Kind of scary.
- deleted 4y ago[deleted]
- GraphLover9000 4y agoI couldn't get "designing data intensive applications" to explain to me how to design a graph database (from scratch, without using existing graph frameworks or technologies), but it only suggested reasons why graph databases are useful and the properties I have to keep in mind while designing it. I want to know how I can build one in practice. Using a prompt like "Tell me how to build a graph database from scratch. Specifically, how to design the data model, implement the data storage layer, and design the query language." only gives a very vague answer. Sometimes it suggests using existing technologies. Anyone know what I'm missing?
- ashout33 4y agoI don't really think that book is about building a graph database from scratch
- GraphLover9000 4y agoYou're probably right. One of my initial prompts mentioned graph databases as an example of a scalable system, so I wanted to ask it about the design properties that make it so. I figured that because it was a book about designing systems, it could give me an outline of how a graph database works in practice. It's pretty annoying how the site erases your prompt once you receive your output. By the time it finishes loading I've half forgotten what my original question was.
- mashygpig 4y agoFascinating, thanks
- swatcoder 4y ago> There is no good reason this should not work everywhere else, in exactly the same way. Take for example a large retailer who has a large internal knowledge base. Train an LLM on that corpus, ask the knowledge base any question. Since LLM’s can’t scope themselves to be strictly true or accurate, there are indeed good reasons, like liability for false claims and added traditional support burden from incorrect guidance. Everybody is getting so far ahead of the horse with this stuff, but we’re just not there yet and don’t know for sure how far we’re going to get.
- iandanforth 4y ago"LLM’s can’t scope themselves to be strictly true or accurate" This isn't true though the techniques to do so are 1. Not as yet widespread 2. Decrease the generality of the model and its perceived effectiveness.
- shawntan 4y agoI'm interested to hear what these techniques are. Decreasing the generality will help, but I fail to see how that scopes the output. At best that mitigates the errors to an extent.
- 256lie 4y agoconformal prediction
- shawntan 4y agoPredicting a set of answers to some confidence interval would still result in hallucinated answers.
- HDThoreaun 4y agolow probability answers get shot to a human and reviewed for model improvement.
- 4y ago
- deleted 4y ago[deleted]
- craftyguy98 4y ago[flagged]
- smrtinsert 4y agoHow did GPS tracking companies survive Google and Google Maps? I think there will probably be many niches to explore even as the big names work hard to compete and eventually commoditize LLMs