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Stephen Grugett: Predicting the Future with Manifold Markets — #55

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Conteúdo fornecido por Steve Hsu. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Steve Hsu ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

Stephen Grugett is the co-founder of Manifold Markets, the world's largest prediction market platform where people bet on politics, tech, sports, and more.

Steve and Stephen discuss:

0:00 Introduction

0:52 Stephen Grugett’s background

5:20 The genesis and mission of Manifold Markets

11:25 The play money advantage: Legalities and user engagement

20:47 Manifold’s user base and the power of calibration

23:35 Simplifying prediction markets for broader engagement

27:31 Revenue streams and future business directions

30:46 Legal challenges in prediction markets

31:47 Dating markets

32:53 The Art of PR

38:32 Global reach and community engagement

39:27 The future of Manifold Markets and user predictions

43:38 Life in the Bay Area; Tech, culture, and crazy stuff

Manifold Markets: https://manifold.markets/

Music used with permission from Blade Runner Blues Livestream improvisation by State Azure.

--

Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation at MSU and Director of the Institute of Theoretical Science at the University of Oregon. Hsu is a startup founder (SuperFocus.ai, SafeWeb, Genomic Prediction, Othram) and advisor to venture capital and other investment firms. He was educated at Caltech and Berkeley, was a Harvard Junior Fellow, and has held faculty positions at Yale, the University of Oregon, and MSU.

Please send any questions or suggestions to manifold1podcast@gmail.com or Steve on Twitter @hsu_steve.

  continue reading

123 episódios

Artwork
iconCompartilhar
 
Manage episode 405146242 series 3318322
Conteúdo fornecido por Steve Hsu. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Steve Hsu ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

Stephen Grugett is the co-founder of Manifold Markets, the world's largest prediction market platform where people bet on politics, tech, sports, and more.

Steve and Stephen discuss:

0:00 Introduction

0:52 Stephen Grugett’s background

5:20 The genesis and mission of Manifold Markets

11:25 The play money advantage: Legalities and user engagement

20:47 Manifold’s user base and the power of calibration

23:35 Simplifying prediction markets for broader engagement

27:31 Revenue streams and future business directions

30:46 Legal challenges in prediction markets

31:47 Dating markets

32:53 The Art of PR

38:32 Global reach and community engagement

39:27 The future of Manifold Markets and user predictions

43:38 Life in the Bay Area; Tech, culture, and crazy stuff

Manifold Markets: https://manifold.markets/

Music used with permission from Blade Runner Blues Livestream improvisation by State Azure.

--

Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation at MSU and Director of the Institute of Theoretical Science at the University of Oregon. Hsu is a startup founder (SuperFocus.ai, SafeWeb, Genomic Prediction, Othram) and advisor to venture capital and other investment firms. He was educated at Caltech and Berkeley, was a Harvard Junior Fellow, and has held faculty positions at Yale, the University of Oregon, and MSU.

Please send any questions or suggestions to manifold1podcast@gmail.com or Steve on Twitter @hsu_steve.

  continue reading

123 episódios

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