Earlier quoted context omitted.
Hear hear. These clickbaity article titles are tiresome. Thanks for saying it like it is.
Please read the article. I address some of the issues raised. My point is that Gebru's firing is symptomatic of some deep problems Google are experiencing. Thank you.
Is Google’s AI research about to implode?
31–40 of 188 posts
Re: Is Google’s AI research about to implode?
#32Earlier quoted context omitted.
Did you read the article? Gebru's firing isn't the focus of it.
Yes, I stopped reading when it mentioned the last good paper was from 2017. This is simply not true. I don't have time to go through all of their papers right now, but as someone else mentioned the protein folding one was a real breakthrough. They also have lots of great stuff in the NLP space (something similar to gpt-3 like 2 years earlier). Also tons of stuff on the actual training architecture/methods. Edit: I wa…
Re: Is Google’s AI research about to implode?
#33Re: Is Google’s AI research about to implode?
#34Earlier quoted context omitted.
Hear hear. These clickbaity article titles are tiresome. Thanks for saying it like it is.
Please read the article. I address some of the issues raised. My point is that Gebru's firing is symptomatic of some deep problems Google are experiencing. Thank you.
There is no real proof to this.
I'm following and reading research @ google (stuff like this https://ai.googleblog.com/ and other sources) for ages now and NOTHING indicates an 'implosion'.
It is strong research with real and constant results.
I have no idea why the autor would even consider using the word 'implode'.
Its not rocket science that data is biased and it just will continue be researched and a solution will be found. For the single reason that biased systems in certain areas will not deliver the results you need to use it properly.
Re: Is Google’s AI research about to implode?
#35Re: Is Google’s AI research about to implode?
#36I'm out of the loop on the whole Gebru situation, from what I know she was researching ethics wrt to AI, so I don't really get the whole "novel idea/work" part in the last paragraph. I often get the impression that such critics never see the rapid developments in AI as progress as long as they don't cover the topics they would like to see focussed. It will never be good enough and always a concern because of X.
Re: Is Google’s AI research about to implode?
#37As a casual observer, I get the impression that Google's corporate attitude toward research on Ethical AI is fundamentally analogous to Exxon's view of climate research in the 80s (and since). Namely, that Google, correctly, views research in the area as potentially undermining key revenue sources in the short and mid term. It is sad, but unsurprising. Government funded research and regulators will most likely be the…
Re: Is Google’s AI research about to implode?
#38No. Every time someone makes a big stink about someone getting fired at one of the top tech companies, it is promptly followed by an article like this. A trillion dollar company that hires thousands of researchers and consistently produces some of the highest quality research with real results is not going to implode from one person being gone. Another pattern I've seen is someone leaving a company, followed by writi…
Did you read the article? Gebru's firing isn't the focus of it.
> What does Timnit Gebru’s firing and the recent papers coming out of Google tell us about the state of research at the world’s biggest AI research department.
Re: Is Google’s AI research about to implode?
#39“ Is there hope for Google Brain? One glimmer can be found in the fact that most of the articles I cite here, criticising Google’s overall approach, are written by their own researchers. But the fact that they fired Gebru — the author of at least three of the most insightful articles ever produced by their research department and in modern AI as a whole — is deeply worrying. If the leaders who claim to be representin…
Re: Is Google’s AI research about to implode?
#40Earlier quoted context omitted.
Yes, I stopped reading when it mentioned the last good paper was from 2017. This is simply not true. I don't have time to go through all of their papers right now, but as someone else mentioned the protein folding one was a real breakthrough. They also have lots of great stuff in the NLP space (something similar to gpt-3 like 2 years earlier). Also tons of stuff on the actual training architecture/methods. Edit: I wa…
It says the high point is 2017, not the last good paper. There are of course other good papers coming out go Google. But the novelty is dropping and the angst is increasing.