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130. Edouard Harris - New Research: Advanced AI may tend to seek power *by default*
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129. Amber Teng - Building apps with a new generation of language models
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128. David Hirko - AI observability and data as a cybersecurity weakness
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127. Matthew Stewart - The emerging world of ML sensors
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126. JR King - Does the brain run on deep learning?
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125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?
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124. Alex Watson - Synthetic data could change everything
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123. Ala Shaabana and Jacob Steeves - AI on the blockchain (it actually might just make sense)
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122. Sadie St. Lawrence - Trends in data science
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121. Alexei Baevski - data2vec and the future of multimodal learning
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120. Liam Fedus and Barrett Zoph - AI scaling with mixture of expert models
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119. Jaime Sevilla - Projecting AI progress from compute trends
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118. Angela Fan - Generating Wikipedia articles with AI
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117. Beena Ammanath - Defining trustworthy AI
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116. Katya Sedova - AI-powered disinformation, present and future
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115. Irina Rish - Out-of-distribution generalization
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114. Sam Bowman - Are we *under-hyping* AI?
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113. Yaron Singer - Catching edge cases in AI
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112. Tali Raveh - AI, single cell genomics, and the new era of computational biology
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111. Mo Gawdat - Scary Smart: A former Google exec’s perspective on AI risk
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110. Alex Turner - Will powerful AIs tend to seek power?
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109. Danijar Hafner - Gaming our way to AGI
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108. Last Week In AI — 2021: The (full) year in review
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107. Kevin Hu - Data observability and why it matters
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106. Yang Gao - Sample-efficient AI
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105. Yannic Kilcher - A 10,000-foot view of AI
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104. Ken Stanley - AI without objectives
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103. Gillian Hadfield - How to create explainable AI regulations that actually make sense
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102. Wendy Foster - AI ethics as a user experience challenge
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101. Ayanna Howard - AI and the trust problem
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100. Max Jaderberg - Open-ended learning at DeepMind
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99. Margaret Mitchell - (Practical) AI ethics
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98. Mike Tung - Are knowledge graphs AI’s next big thing?
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97. Anthony Habayeb - The present and future of AI regulation
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96. Jan Leike - AI alignment at OpenAI
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95. Francesca Rossi - Thinking, fast and slow: AI edition
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94. Divya Siddarth - Are we thinking about AI wrong?
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93. 2021: A year in AI (so far) - Reviewing the biggest AI stories of 2021 with our friends at the Let’s Talk AI podcast
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92. Daniel Filan - Peering into neural nets for AI safety
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91. Peter Gao - Self-driving cars: Past, present and future
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90. Jeffrey Ding - China’s AI ambitions and why they matter
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89. Pointing AI in the right direction - A cross-over episode with the Banana Data podcast!
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88. Oren Etzioni - The case against (worrying about) existential risk from AI
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87. Evan Hubinger - The Inner Alignment Problem
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86. Andy Jones - AI Safety and the Scaling Hypothesis
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85. Brian Christian - The Alignment Problem
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84. Eliano Marques - The (evolving) world of AI privacy and data security
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83. Rosie Campbell - Should all AI research be published?
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82. Jakob Foerster - The high cost of automated weapons
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81. Nicolas Miailhe - AI risk is a global problem
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80. Yan Li - The Surprising Challenges of Global AI Philanthropy
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79. Ryan Carey - What does your AI want?
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78. Melanie Mitchell - Existential risk from AI: A skeptical perspective
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77. Josh Fairfield - AI advances, but can the law keep up?
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76. Stuart Armstrong - AI: Humanity's Endgame?
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75. Georg Northoff - Consciousness and AI
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74. Ethan Perez - Making AI safe through debate
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73. David Roodman - Economic history and the road to the singularity
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72. Margot Gerritsen - Does AI have to be understandable to be ethical?
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71. Ben Garfinkel - Superhuman AI and the future of democracy and government
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70. Sarah Williams - What does ethical AI even mean?
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69. Anders Sandberg - Answering the Fermi Question: Is AI our Great Filter?
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68. Silvia Milano - Ethical problems with recommender systems
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67. Joaquin Quiñonero-Candela - Responsible AI at Facebook
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66. Owain Evans - Predicting the future of AI
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65. Helen Toner - The strategic and security implications of AI
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64. David Krueger - Managing the incentives of AI
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63. Geordie Rose - Will AGI need to be embodied?
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62. Nicolai Baldin - AI meets the law: Bias, fairness, privacy and regulation
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61. Ben Goertzel - The unorthodox path to AGI
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60. Rob Miles - Why should I care about AI safety?
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59. Matthew Stewart - Tiny ML and the future of on-device AI
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58. David Duvenaud - Using generative models for explainable AI
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57. Dylan Hadfield-Menell - Humans in the loop
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56. Annette Zimmermann - The ethics of AI
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55. Rohin Shah - Effective altruism, AI safety, and learning human preferences from the state of the world
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54. Tim Rocktäschel - Deep reinforcement learning, symbolic learning and the road to AGI
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53. Edouard Harris - Emerging problems in machine learning: making AI "good"
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52. Sanyam Bhutani - Networking like a pro in data science
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51. Adrien Treuille and Tim Conkling - Streamlit Is All You Need
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50. Ken Jee - Building your brand in data science
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49. Catherine Zhou - The data science of learning
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48. Emmanuel Ameisen - Beyond the jupyter notebook: how to build data science products
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47. Goku Mohandas - Industry research and how to show off your projects
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46. Ihab Ilyas - Data cleaning is finally being automated
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45. Kenny Ning - Is data science merging with data engineering?
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44. Jakob Foerster - Multi-agent reinforcement learning and the future of AI
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43. Ian Scott - Data science at Deloitte
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42. Will Grathwohl - Energy-based models and the future of generative algorithms
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41. Solmaz Shahalizadeh - Data science in high-growth companies
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40. David Meza - Data science at NASA
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39. Nick Pogrebnyakov - Data science at Reuters, and the remote work after the coronavirus
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38. Matthew Stewart - Data privacy and machine learning in environmental science
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37. Sean Knapp - The brave new world of data engineering
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36. Max Welling - The future of machine learning
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35. Rubén Harris - Learning and looking for jobs in quarantine
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34. Denise Gosnell and Matthias Broecheler - You should really learn about graph databases. Here’s why.
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33. Roland Memisevic - Machines that can see and hear
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32. Bahador Khaleghi - Explainable AI and AI interpretability
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31. Russell Pollari - Building habits and breaking into data science
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