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this was already possible with chatterbox for a long while.


Yep, this has been the reality now for years. Scammers have already had access to it. I remember an article years ago about a grandma who wired her life savings to a scammer who claimed to have her granddaughter held hostage in a foreign country. Turns out they just cloned her voice from Facebook data and knew her schedule so timed it while she would be unreachable by phone.


or anyone who refuses to use hearing aids.


these are just old senior devs not wanting to accept new changes in the industry.


These are the cutting insights I come to HN for.


Nah you are getting it wrong the issue here is YOU NO LONGER NEED TO LEARN RUST thats why you are learning it slow.


Yeah. AI will write Rust and then you only have to review .. oh.

But AI will review it and then you only have to .. oh

But AI will review AI and then you .. oh ..


Awesome openai has no more moat now


yes amphetamine I use regularly when I want to charge my android phone during travel with lid closed.


That's interesting, I have never needed to do that. My Pixels have always just charged even if the lid is closed, on Intel and Apple Silicon machines. I like to travel light so I often use my laptop as a battery bank instead of carrying a seperate one.


Actually excited 2M context window will be useful in this case


It's literally just adding one extra entry to a configuration file.


I know, but similar updates to Copilot would probably take over a year and they designed it in a way that we got the update now without having to reinstall it.


US election bullshit article


Humans learn from seeing I don't think we are the stage of training models with videos / images dataset. We only reached the plateau with text dataset to train with.


we do have self driving car but since it directly affects people's life it needs to be close to 100% accurate and no margin of errors. Not necessarily the case for LLMs.


No, we have cars that can drive themselves quite well in good weather, but fail completely in heavy snow/poor visibility. Which is actually a great analogy to LLMs - they work great in the simple cases (80% of the time), it’s that last 20% that’s substantially harder.


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