What does power seeking really mean? And does all this imply for the safety of future, general-purpose reasoning systems? Edouard Harris, an AI alignment researcher and one of Jeremie's co-founders of the AI safety company (Gladstone AI) comes back on the TDS Podcast to discuss AI's potential ability to seek power. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 4:00 Alex Turner’s research 7:45 What technology wants 11:30 Universal goals 17:30 Connecting observations 24:00 Micro power seeking behaviour 28:15 Ed’s research 38:00 The human as the environment 42:30 What leads to power seeking 48:00 Competition as a default outcome 52:45 General concern 57:30 Wrap-up

Joining Jeremie Harris this episode is Amber Teng, a data scientist and TDS author (and former editor!) who recently published a blog that got quite a bit of attention, about a resume cover letter generator that she created using GPT-3, OpenAI's powerful and now-famous language model. They discussed the applied side of language modelling and prompt engineering, understanding how large language models have made new apps not only possible but also much easier to build, and the likely future of AI-powered products. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:30 Amber’s background 5:30 Using GPT-3 14:45 Building prompts up 18:15 Prompting best practices 21:45 GPT-3 mistakes 25:30 Context windows 30:00 End-to-end time 34:45 The cost of one cover letter 37:00 The analytics 41:45 Dynamics around company-building 46:00 Commoditization of language modelling 51:00 Wrap-up

David Hirko, co-founder of data observability company Zectonal, joined Jeremie Harris in discussing data observability, data as a new vector for cyberattacks, and the future of enterprise data management. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 3:00 What is data observability? 10:45 “Funny business” with data providers 12:50 Data supply chains 16:50 Various cybersecurity implications 20:30 Deep data inspection 27:20 Observed direction of change 34:00 Steps the average person can take 41:15 Challenges with GDPR transitions 48:45 Wrap-up

Matt Stewart, a deep learning and TinyML researcher at Harvard University, is back on the TDS Podcast to discuss ML sensors and the challenging ethical, privacy, and operational questions introduced by them. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 3:20 Special challenges with TinyML 9:00 Most challenging aspects of Matt’s work 12:30 ML sensors 21:30 Customizing the technology 24:45 Data sheets and ML sensors 31:30 Customers with their own custom software 36:00 Access to the algorithm 40:30 Wrap-up

JR King, a CNRS researcher at the Ecole Normale Supérieure, joined the TDS Podcast to explore the fascinating intersection of biological and artificial information processing. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:30 What is JR’s day-to-day? 5:00 AI and neuroscience 12:15 Quality of signals within the research 21:30 Universality of structures 28:45 What makes up a brain? 37:00 Scaling AI systems 43:30 Growth of the human brain 48:45 Observing certain overlaps 55:30 Wrap-up

The TDS Podcast is back with an exciting episode on the art of the possible when it comes to China AI policy. Ryan Fedasiuk, a Research Analyst at Georgetown University's Center for Security and Emerging Technology and Adjunct Fellow at the Center for a New American Security, joined host Jeremie Harris to discuss the U.S. and China's shared interest in building safe AI, how reach side views the other, and what realistic China AI policy looks. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro + disclaimer 2:15 China as a core point of focus 4:30 Chinese AI strategy 10:00 Competition as risk 17:20 Having constructive conversations 22:20 Understanding China’s policies 27:15 A shared interest in AI alignment 32:45 Issues with regulating AI on an international level 40:15 Is collaboration a good thing? 44:15 Impact of the highly scaled transformer models trend 47:15 Wrap-up

Alex Watson, the Chief Product Officer and co-founder of Gretel AI, came on the podcast to discuss data privacy, data synthesis, and what could be the very strange future of the data lifecycle. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:40 What is synthetic data? 6:45 Large language models 11:30 Preventing data leakage 18:00 Generative versus downstream models 24:10 De-biasing and fairness 30:45 Using synthetic data 35:00 People consuming the data 41:00 Spotting correlations in the data 47:45 Generalization of different ML algorithms 51:15 Wrap-up

Ala Shaabana and Jacob Steeves, two ML researchers, unpack the problem of designing robust benchmarks to rewarding good AI research and even the centralization of power in the hands of a few large companies building powerful AI systems. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:40 Ala and Jacob’s backgrounds 4:00 The basics of AI on the blockchain 11:30 Generating human value 17:00 Who sees the benefit?22:00 Use of GPUs 28:00 Models learning from each other 37:30 The size of the network 45:30 The alignment of these systems 51:00 Buying into a system 54:00 Wrap-up

Sadie St. Lawrence, the founder of Women in Data and Data Bytes podcast host, came on the podcast to talk about her founder's journey, what data science looks like today, and even the possibilities that blockchains introduce for data science. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:00 Founding Women in Data 6:30 Having gendered conversations 11:00 The cultural aspect 16:45 Opportunities in blockchain 22:00 The blockchain database 32:30 Data science education37:00 GPT-3 and unstructured data 39:30 Data science as a career 42:50 Wrap-up

Alexei Baevski, a researcher at Meta AI one of the creators of data2vec, came on the podcast to talk about how data2vec works and what's next for that research direction, as well as the future of multi-modal learning. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:00 Alexei’s background 10:00 Software engineering knowledge 14:10 Role of data2vec in progression 30:00 Delta between student and teacher 38:30 Losing interpreting ability 41:45 Influence of greater abilities 49:15 Wrap-up

Liam Fedus and Barrett Zoph, research scientists at Google Brain, came on the podcast to talk about AI scaling, sparsity and the present and future of MoE models. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:15 Guests’ backgrounds 8:00 Understanding specialization 13:45 Speculations for the future 21:45 Switch transformer versus dense net 27:30 More interpretable models 33:30 Assumptions and biology 39:15 Wrap-up

Host Jeremie Harris talks compute trends and AI forecasting with Jaime Sevilla, an independent researcher and AI forecaster and affiliate researcher at Cambridge University's Centre for the Study of Existential Risk. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:00 Trends in compute 4:30 Transformative AI 13:00 Industrial applications 19:00 GPT-3 and scaling 25:00 The two papers 33:00 Biological anchors 39:00 Timing of projects 43:00 The trade-off 47:45 Wrap-up

Host Jeremie Harris talks the implications of high-quality long-form text generation and the future of human/AI collaboration with Angela Fan, an AI researcher at Meta. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 1:45 Journey into Meta AI 5:45 Transition to Wikipedia 11:30 How articles are generated 18:00 Quality of text 21:30 Accuracy metrics 25:30 Risk of hallucinated facts 30:45 Keeping up with changes 36:15 UI/UX problems 45:00 Technical cause of gender imbalance 51:00 Wrap-up

Global Head of Deloitte AI Institute and Deloitte Tech & AI Ethics Lead Beena Ammanath joined the TDS Podcast to discuss her new book "Trustworthy AI", explainability and robustness in AI, as well as the future of AI regulation and self-regulation. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 1:55 Background and trustworthy AI 7:30 Incentives to work on capabilities 13:40 Regulation at the level of application domain 16:45 Bridging the gap 23:30 Level of cognition offloaded to the AI 25:45 What is trustworthy AI? 34:00 Examples of robustness failures 36:45 Team diversity 40:15 Smaller companies 43:00 Application of best practices 46:30 Wrap-up

Katya Sedova, a former Congressional Fellow and Microsoft alumna who now works at Georgetown University's Center for Security and Emerging Technology, came on the TDS Podcast to talk malicious AI-powered chatbots, fake news generation, and the future of AI-augmented influence campaigns. Intro music: ➞ Artist: Ron Gelinas ➞ Track Title: Daybreak Chill Blend (original mix) ➞ Link to Track: https://youtu.be/d8Y2sKIgFWc 0:00 Intro 2:40 Malicious uses of AI 4:30 Last 10 years in the field 7:50 Low handing fruit of automation 14:30 Other analytics functions 25:30 Authentic bots 30:00 Influences of service businesses 36:00 Race to the bottom 42:30 Automation of systems 50:00 Manufacturing norms 52:30 Interdisciplinary conversations 54:00 Wrap-up