Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI agents are starting to eat SaaS

martinalderson.com

Post reply on HN
Print view View original

21–30 of 398 posts

Re: AI agents are starting to eat SaaS

#21

Post by fzeroracer »

Aurornis wrote: post #16
Oarch wrote: post #9

Earlier this year I thought that rare proprietary knowledge and IP was a safe haven from AI, since LLMs can only scrub public data. Then it dawned on me how many companies are deeply integrating Copilot into their everyday workflows. It's the perfect Trojan Horse.

Using an LLM on data does not ingest that data into the training corpus. LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. None of the mainstream paid services ingest operating data into their training sets. You will find a lot of conspiracy theories claiming that companies are saying one thing but secretly stealing your data, of course.

> You will find a lot of conspiracy theories claiming that companies are saying one thing but secretly stealing your data, of course.

It's not really a conspiracy when we have multiple examples of high profile companies doing exactly this. And it keeps happening. Granted I'm unaware of cases of this occuring currently with professional AI services but it's basic security 101 that you should never let anything even have the remote opportunity to ingest data unless you don't care about the data.

Re: AI agents are starting to eat SaaS

#22

Post by lioeters »

leptons wrote: post #18
Aurornis wrote: post #16

Earlier quoted context omitted.

Using an LLM on data does not ingest that data into the training corpus. LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. None of the mainstream paid services ingest operating data into their training sets. You will find a lot of conspiracy theories claiming that companies are saying one thing but secretly stealing your data, of course.

> LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. Nothing is really preventing this though. AI companies have already proven they will ignore copyright and any other legal nuisance so they can train models.

They're already using synthetic data generated by LLMs to further train LLMs. Of course they will not hesitate to feed "anonymized" data generated by user interactions. Who's going to stop them? Or even prove that it's happening. These companies have already been allowed to violate copyright and privacy on a historic global scale.

Re: AI agents are starting to eat SaaS

#23

Post by sotrusting »

Aurornis wrote: post #16
Oarch wrote: post #9

Earlier this year I thought that rare proprietary knowledge and IP was a safe haven from AI, since LLMs can only scrub public data. Then it dawned on me how many companies are deeply integrating Copilot into their everyday workflows. It's the perfect Trojan Horse.

Using an LLM on data does not ingest that data into the training corpus. LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. None of the mainstream paid services ingest operating data into their training sets. You will find a lot of conspiracy theories claiming that companies are saying one thing but secretly stealing your data, of course.

[flagged]

Re: AI agents are starting to eat SaaS

#25

Post by GCUMstlyHarmls »

findjashua wrote: post #19
Oarch wrote: post #9

Earlier this year I thought that rare proprietary knowledge and IP was a safe haven from AI, since LLMs can only scrub public data. Then it dawned on me how many companies are deeply integrating Copilot into their everyday workflows. It's the perfect Trojan Horse.

providers' ToS explicitly states whether or not any data provided is used for training purposes. the usual that i've seen is that while they retain the right to use the data on free tiers, it's almost never the case for paid tiers

I wonder how much wiggle there is for collect now (to provide service, context history, etc), then later anonymise (some how, to some level) and then train on it?

Also I wonder if the ToS covers "queries & interaction" vs "uploaded data" - I could imagine some tricky language in there that says we wont use your word document, but we may at some time use the queries you put against it, not as raw corpus but as a second layer examining what tools/workflows to expand/exploit.

Re: AI agents are starting to eat SaaS

#26

Post by Archelaos »

leptons wrote: post #18
Aurornis wrote: post #16

Earlier quoted context omitted.

Using an LLM on data does not ingest that data into the training corpus. LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. None of the mainstream paid services ingest operating data into their training sets. You will find a lot of conspiracy theories claiming that companies are saying one thing but secretly stealing your data, of course.

> LLMs don’t “learn” from the information they operate on, contrary to what a lot of people assume. Nothing is really preventing this though. AI companies have already proven they will ignore copyright and any other legal nuisance so they can train models.

How should they dinstinguish between real and fake data? It would be far to easy to pollute their models with nonesense.

Re: AI agents are starting to eat SaaS

#27

Post by sotrusting »

findjashua wrote: post #19
Oarch wrote: post #9

Earlier this year I thought that rare proprietary knowledge and IP was a safe haven from AI, since LLMs can only scrub public data. Then it dawned on me how many companies are deeply integrating Copilot into their everyday workflows. It's the perfect Trojan Horse.

providers' ToS explicitly states whether or not any data provided is used for training purposes. the usual that i've seen is that while they retain the right to use the data on free tiers, it's almost never the case for paid tiers

Right, so totally cool to ignore the law but our TOS is a binding contract.

Re: AI agents are starting to eat SaaS

#28

Post by arealaccount »

The where this doesn’t work section is chefs kiss

- anything that requires very high uptime

-very high volume systems and data lakes

-software with significant network effects

-companies that have proprietary datasets

-regulation and compliance is still very important

Re: AI agents are starting to eat SaaS

#29

Post by austinjp »

scotty79 wrote: post #3

Let me give you an example of my workflow from tonight: 1. I had two text documents containing plain text to compare. One with minor edits (done by AI). 2. I wanted to see what AI changed in my text. 3. I tried the usual diff tools. They diffed line by line and result was terrible. I searched google for "text comparison tool but not line-based" 4. As second search result it found me https://www.diffchecker.com/ (It's…

> 3. I tried the usual diff tools. They diffed line by line and result was terrible.

Um. I don't want to be That Guy (shouting at clouds, or at kids to get off my lawn or whatever) but ... what "usual diff" tools did you use? Because comparing two text files with minor edits is exactly what diff-related tools have excelled at for decades.

There is word-level diff, for example. Was that not good enough? Or delta [0] perhaps?

[0] https://github.com/dandavison/delta

Re: AI agents are starting to eat SaaS

#30

Post by weitendorf »

This is why I started working on an open source, generic protobuf sqlite ORM + CRUD server (with search/filtering) + type/service registry + grpc mesh, recently: https://github.com/accretional/collector Note: collector's docs are mostly from LLMs, partially because it's more of a framework for tool-calling LLMs than humans

Then this project lets you generate static sites from svelte components (matches protobuf structures) and markdown (documentation) and global template variables: https://github.com/accretional/statue

A lot of the SaaS ecosystem actually has rather simple domain logic and oftentimes doesn't even model data very well, or at least not in a way that matches their clients/users mental models or application logic. A lot of the value is in integrations, or the data/scaling, or the marketing and developer experience, or some kind of expertise in actually properly providing a simple interface to a complex solution.

So why not just create a compact universal representation of that? Because it's not so big a leap to go beyond eating SaaS to eating integrations, migration costs/bad moats, and the marketing/documentation/wrapper.

Post reply on HN