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Thomas Ahle

Published podcast speaker

Claims
11
Episodes
1
Shows
1
Named items
0

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What Thomas said.

5 transcript-backed records

01 / evaluation

I think there are other examples later on that nearly bankrupted some of these companies like TinyBucks that managed to make it through to the to the fab and it's yeah, it's it's a really different world again from software where we just, know, people fix stuff in prod, you just move fast and and break things.

“I think there are other examples later on that nearly bankrupted some of these companies like TinyBucks that managed to make it through to the to the fab and it's yeah, it's it's a really different world again from software where we just, know, people fix stuff in prod, you just move fast and and break things.”
Speaker
Thomas Ahle
Publisher
Machine Learning Street Talk

02 / evaluation

Like in the past if if I wrote something and ask you to read it, you could at least have assumed that I would have spent 10 times more times writing it than you reading it.

“Like in the past if if I wrote something and ask you to read it, you could at least have assumed that I would have spent 10 times more times writing it than you reading it.”
Speaker
Thomas Ahle
Publisher
Machine Learning Street Talk

03 / evaluation

Like are you when you do reinforcement learning, I mean the chain of thought before the reinforcement learning and after reinforcement learning I think is very different because before it was kind of you try and prompt it and some tricks they kind of work and kind of doesn't work.

“Like are you when you do reinforcement learning, I mean the chain of thought before the reinforcement learning and after reinforcement learning I think is very different because before it was kind of you try and prompt it and some tricks they kind of work and kind of doesn't work.”
Speaker
Thomas Ahle
Publisher
Machine Learning Street Talk

04 / evaluation

Just for those licenses. And I think actually that's 1 of the reasons also why AI still is not as popular in the hardware space because they haven't been able to train like the models are not as trained to this kind of workloads because they just, it's not feasible.

“Just for those licenses. And I think actually that's 1 of the reasons also why AI still is not as popular in the hardware space because they haven't been able to train like the models are not as trained to this kind of workloads because they just, it's not feasible.”
Speaker
Thomas Ahle
Publisher
Machine Learning Street Talk

05 / evaluation

I mean that kind of maybe takes a little bit of the point out of the probability. But then you could also just, but then it's funny because you have these chips and like the chip manufacturers, they spend so much time like getting out every single little piece of noise out of their systems and like having these extremely sharp margins for everything like so much you know, precision is probably like the most precise business in the world.

“I mean that kind of maybe takes a little bit of the point out of the probability. But then you could also just, but then it's funny because you have these chips and like the chip manufacturers, they spend so much time like getting out every single little piece of noise out of their systems and like having these extremely sharp margins for everything like so much you know, precision is probably like the most precise business in the world.”
Speaker
Thomas Ahle
Publisher
Machine Learning Street Talk
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