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

Rodney Brooks on limitations of generative AI

techcrunch.com

Post reply on HN
Print view View original

131–140 of 202 posts

Re: Rodney Brooks on limitations of generative AI

#131

Post by greybox »

raincole wrote: post #111
fxtentacle wrote: post #13

To me, this reads like a very reasonable take. He suggests to limit the scope of the AI problem, add manual overrides in case there are unexpected situations, and he (rightly, in my opinion) predicts that the business case for exponentially scaling LLM models isn't there. With that context, I like his iPod example. Apple probably could have made a 3TB iPod to stick to Moore's law for another few years, but after they…

> Apple probably could have made a 3TB iPod It's a very weird comparison, as putting more music tracks to your iPod doesn't make them sound better, while giving a LLM more parameters/computing power make it smarter. Honestly it sounds like a typical "I've drawn my conclusion, and now I only need an analogy that remotely supports my conclusion" way of thinking.

If you have no conception of mathematics, do you think you'd get better at solving mathematics problems based on looking at more examples of people who may or may not be solving them correctly?

Re: Rodney Brooks on limitations of generative AI

#132

Post by kromem »

fxtentacle wrote: post #13

To me, this reads like a very reasonable take. He suggests to limit the scope of the AI problem, add manual overrides in case there are unexpected situations, and he (rightly, in my opinion) predicts that the business case for exponentially scaling LLM models isn't there. With that context, I like his iPod example. Apple probably could have made a 3TB iPod to stick to Moore's law for another few years, but after they…

The business case is absolutely there, it's just the industry has weirdly latched onto 'chatbot' as the usecase as opposed to where the real value lies.

The pretrained model is where the enterprise gold is at.

But the companies building the models past the tipping point scale for that value to be derived are walling up their pretrained model behind very heavy handed fine tuning that strips away most of the business value.

The engineers themselves seem to lack the imagination for the business cases, and the enterprise market doesn't have access to start discovering the applications outside of 'chatbot,' particularly with large context windows of proprietary data fed into SotA pretrained models.

There's maybe a handful of people who actually realize what value is being left on the table, and I think most of them are smart enough not to currently be in positions to make it happen.

Re: Rodney Brooks on limitations of generative AI

#133

Post by tnel77 »

MattPalmer1086 wrote: post #72
aurareturn wrote: post #15

Earlier quoted context omitted.

I’m still waiting for SalesForce to integrate an LLM into Slack so I can ask it business logic and decisions long lost. Still waiting for Microsoft to integrate an LLM into outlook so I can get a summary of a 20 email long chain I just got CCed into. I don’t think the iPod comparison is a valid one. People only have so much time to listen to music. Past a certain point, no one has enough good music they like to put i…

Haha, I'd be happy if outlook just integrated a search that actually works. Most of outlook search results aren't even relevant, and it regularly misses things I know are there. Literally the most useless search I've ever had to use.

Don’t get me started on Outlook’s search. I can try to search for an email that’s only a few weeks old and somehow it won’t find it. It will, however, find emails that are from over a decade ago.

Re: Rodney Brooks on limitations of generative AI

#134

Post by grugagag »

threeseed wrote: post #95
Propelloni wrote: post #89

Earlier quoted context omitted.

Most data around is junk and the internet produces junk data faster then useful data and current GPT AIs basically regurgitate what someone already did somewhere on the internet. So I guess the more data we feed into GPTs the worse the results will get. My take to improve AI output is to heavily curate the data you feed your AI, much the like expert systems of old (which were lauded as "AI" also.) Maybe we can break…

> My take to improve AI output is to heavily curate the data you feed your AI This is what OpenAI is doing with their relationships with companies like Reddit, News Corp etc: https://openai.com/index/news-corp-and-openai-sign-landmark-... Problem is that we have a finite amount of this type of information.

Massive surveilance, take out data and use it on training. Hope this will not come to frution.

Re: Rodney Brooks on limitations of generative AI

#135

Post by mewpmewp2 »

greybox wrote: post #131
raincole wrote: post #111

Earlier quoted context omitted.

> Apple probably could have made a 3TB iPod It's a very weird comparison, as putting more music tracks to your iPod doesn't make them sound better, while giving a LLM more parameters/computing power make it smarter. Honestly it sounds like a typical "I've drawn my conclusion, and now I only need an analogy that remotely supports my conclusion" way of thinking.

If you have no conception of mathematics, do you think you'd get better at solving mathematics problems based on looking at more examples of people who may or may not be solving them correctly?

It has worked for humanity...

Re: Rodney Brooks on limitations of generative AI

#136

Post by mewpmewp2 »

bamboozled wrote: post #118
TheOtherHobbes wrote: post #86

The iPod didn't stop growing. It turned into an iPhone - a much more complex system which happened to include iPod features, almost as a trivial add-on. If you consider LLMs as the iPod of ML, what would the iPhone equivalent be?

He made an analogy to discuss the business case for scaling an iPod, not whether or not new products and services would be invented. My iPhone still only has about 64gb of storage.

But it is the dumbest thing in the World to compare features of LLM to something like that.

Re: Rodney Brooks on limitations of generative AI

#137

Post by mewpmewp2 »

enragedcacti wrote: post #98
ianbicking wrote: post #88

"He says the trouble with generative AI is that, while it’s perfectly capable of performing a certain set of tasks, it can’t do everything a human can" This kind of strawman "limitations of LLMs" is a bit silly. EVERYONE knows it can't do everything a human can, but the boundaries are very unclear. We definitely don't know what the limitations are. Many people looked at computers in the 70s and saw that they could on…

I don't think you and him are in disagreement. I read it as him saying "evaluating LLMs is extremely difficult and a big problem right now is that many people are treating them as basically human in capability". Its the opposite problem to the perception of computers in the 70s, early computers were seen by some as too alien to be as useful as a person across most tasks, llms are seen by some as too human to not be a…

WHO exactly is treating them as human? It is a strawman.

Re: Rodney Brooks on limitations of generative AI

#138

Post by lukeschlather »

I feel like "generative" might be the worst possible label, because while the generative capabilities are the most exciting features, they're not the most useful, and in most cases they aren't useful at all.

But the sentiment analysis, summaries, and object detection seem incredibly capable and like the actual useful features of LLMs and similar tensor models.

Re: Rodney Brooks on limitations of generative AI

#139

Post by bongodongobob »

aurareturn wrote: post #15
fxtentacle wrote: post #13

To me, this reads like a very reasonable take. He suggests to limit the scope of the AI problem, add manual overrides in case there are unexpected situations, and he (rightly, in my opinion) predicts that the business case for exponentially scaling LLM models isn't there. With that context, I like his iPod example. Apple probably could have made a 3TB iPod to stick to Moore's law for another few years, but after they…

I’m still waiting for SalesForce to integrate an LLM into Slack so I can ask it business logic and decisions long lost. Still waiting for Microsoft to integrate an LLM into outlook so I can get a summary of a 20 email long chain I just got CCed into. I don’t think the iPod comparison is a valid one. People only have so much time to listen to music. Past a certain point, no one has enough good music they like to put i…

Both of these already exist. Slack just introduced AI and copilot for M365 products has been available for quite a while now. It works great, I use it every day.

Re: Rodney Brooks on limitations of generative AI

#140

Post by bongodongobob »

derefr wrote: post #123
geoduck14 wrote: post #115

Earlier quoted context omitted.

>>Microsoft to integrate an LLM into outlook Didn't they already do this? A friend of mine showed me his outlook where he could search all emails, docs, and video calls and ask it questions. To be fair, he and I asked it questions about a video call and a doc - but not any emails, we only searched emails. This was last week amd it worked "mostly OK," but having a q/a conversation with a long email feels inevitable

Asking questions about a document is one thing; asking questions that synthesize information across many documents — the human-intelligent equivalent of doing a big OLAP query with graph-search and fulltext-search parts on your email database — is quite another. Right now AFAICT the latter would require the full text of all the emails you've ever sent, to be stuffed into the context window together.

Yes this is already a thing. Copilot for m365 fine tunes on your entire orgs data.
Post reply on HN