92. Daniel Filan - Peering Into Neural Nets For AI safety Towards Data Science podcast

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92. Daniel Filan - Peering into neural nets for AI safety

3y ago 1:06:02

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Innhold levert av The TDS team. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The TDS team eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Many AI researchers think it’s going to be hard to design AI systems that continue to remain safe as AI capabilities increase. We’ve seen already on the podcast that the field of AI alignment has emerged to tackle this problem, but a related effort is also being directed at a separate dimension of the safety problem: AI interpretability.

Our ability to interpret how AI systems process information and make decisions will likely become an important factor in assuring the reliability of AIs in the future. And my guest for this episode of the podcast has focused his research on exactly that topic. Daniel Filan is an AI safety researcher at Berkeley, where he’s supervised by AI pioneer Stuart Russell. Daniel also runs AXRP, a podcast dedicated to technical AI alignment research.

… continue reading

132 episoder

#Tech #The TDS team #Data Science #Science

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92. Daniel Filan - Peering into neural nets for AI safety

Towards Data Science

317 subscribers

published 3y ago

Del

M4A•Episoder hjem

Innhold levert av The TDS team. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The TDS team eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Many AI researchers think it’s going to be hard to design AI systems that continue to remain safe as AI capabilities increase. We’ve seen already on the podcast that the field of AI alignment has emerged to tackle this problem, but a related effort is also being directed at a separate dimension of the safety problem: AI interpretability.

Our ability to interpret how AI systems process information and make decisions will likely become an important factor in assuring the reliability of AIs in the future. And my guest for this episode of the podcast has focused his research on exactly that topic. Daniel Filan is an AI safety researcher at Berkeley, where he’s supervised by AI pioneer Stuart Russell. Daniel also runs AXRP, a podcast dedicated to technical AI alignment research.

… continue reading

132 episoder

#Tech #The TDS team #Data Science #Science

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