This is a great example of why scaling data and compute beats injecting human priors into the system.
Real world is too messy to be bounded by well defined rules
This is a great example of why scaling data and compute beats injecting human priors into the system.
Real world is too messy to be bounded by well defined rules
Strong agree!
Having focused on robotics for past 10+ years and ran circles to build intelligent agents, it feels like we are finally approaching a tipping point where the line between fiction and reality will fade and we will feel confident about deploying these systems in…
Strong agree!
Having focused on robotics for past 10+ years and ran circles to build intelligent agents, it feels like we are finally approaching a tipping point where the line between fiction and reality will fade and we will feel confident about deploying these systems in…
Extremely counterintuitive and extremely true:
"It is easier for a team to do a hard thing that really matters than to do an easy thing that doesn’t really matter; audacious ideas motivate people."
Extremely counterintuitive and extremely true:
"It is easier for a team to do a hard thing that really matters than to do an easy thing that doesn’t really matter; audacious ideas motivate people."
Stating the obvious: When churning through experiments, continue playing with variants of your model extensively, even if they aren’t SOTA on metrics.
90% success on a metric doesn’t mean much if you haven’t intuitively mapped it to real world performance.
This !
It is morally incorrect to hold back a better product - especially when it’s safer.
If it were for biased media / decels, we’d still be riding around on horses
This !
It is morally incorrect to hold back a better product - especially when it’s safer.
If it were for biased media / decels, we’d still be riding around on horses
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