All about the disruption of an American-led industry – and the creative destruction thereof:

History of whaling

Decline of the US whaling industry (causes and ramifications for jobs, politics, economics, and social stability)

Rise of commercial whaling regulation and evasion

US transition from whaling to other forms of energy and byproducts (economic benefits, detriments, and innovations)

Standard Oil

See also:🧵https://x.com/AnthPB/status/1852504007341670409

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

“A Compact With the Whales”: New Bedford, the American Civil War, and a Changing Industry (Mello, 2020.05.01)

Anti-whaling (Wikipedia, 2024.10.29)

Catches taken under Objection since 1985 ban (International Whaling Commission, 2023)

Catches total since 1985 ban (International Whaling Commission, 2023)

Climate-driven environmental changes around 8,200 years ago favoured increases in cetacean strandings and Mediterranean hunter-gatherers exploited them (Mannino et al, 2015.11.17)

Estimating the Economic Value of Narwhal and Beluga Hunts in Hudson Bay, Nunavut (Hoover et al, 2012)

From Old Dartmouth to New Bedford, Whaling Metropolis of the World (Old Dartmouth Historical Society (2008.12.14)

Global whaling peaked in the 1960s (Our World in Data, 2022.11.30)

Prehistoric Inuit whalers affected Arctic freshwater ecosystems (Douglas/Smol/Savelle/Blais, 2023.12.09)

Productivity and the decline of American sperm whaling (Shuster)

Report of the 65th meeting of the International Whaling Commission (IWC, 2014)

Standard Oil (Wikipedia, 2024.10.28)

The Impact of Whaling on the Ocean Carbon Cycle: Why Bigger Was Better (Pershing et al, 2010.08.26)

The Subtle Changes that Destroyed the Whaling Industry (YouTube, Learn Something New, 2023.06.01)

The whale oil myth surfaces again (Environmental History, 2022.02.23)

The “Whale Oil Myth” (PBS News, 2008.08.20)

Too Much Is Never Enough: The Cautionary Tale of Soviet Illegal Whaling (Ivashchenko/Clapham)

Whale Hunting Still Exists in 3 Countries, but It Is Declining (Sentient Media, 2023.09.01)

Whale Population Estimates (International Whaling Commission, 2022)

Whale oil history (Pees, 2004)

Whaling (Wikipedia, 2024.10.26)

Whaling in the United States (Wikipedia, 2024.10.29)

Why Petroleum Did Not Save the Whales (York, 2017.10.25)

Not investment advice; do your own due diligence!

# kerosene petroleum whales innovation Rockefeller

While GPUs have the spotlight, high bandwidth memory (HBM) has an Oscar nomination for best supporting actor – but what's the state of the storage/memory market; what are the innovations therein; and who are the major players?

A trip down memory lane:

Memory vs compute

NAND/SSD and data lakes (HDD need not apply)

AI at the edge (client-side NVM SSDs)

HBM3, 3D DRAM, and LLMs (stacked packaging)

Future compute-in-memory architectures (memristor crossbar arrays)

Memory and manufacturing competitive landscape

See also:🧵⁠https://x.com/AnthPB/status/1658939488729460737⁠

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

AI Workloads and Data storage solutions requirements and recommended options (Medium, Sugur, 2024.02.21)

AI at the Edge: Future of memory and storage in accelerating intelligence (IoT Now, 2024.02.07)

Flash forward: The need for AI storage and security in 2024 (Fast Company, Wu, 2024.02.29)

GDDR5 vs GDDR5X vs HBM2 vs GDDR6 vs GDDR6X Memory Comparison (Graphics Card Hub, 2023.10.29)

HBM3 Update to High Bandwidth Memory Standard (JEDC, 2022.01.27)

HBM: Memory Solution for Bandwidth-Hungry Processors (Kim/Kim, 2014.08)

High Bandwidth Memory (Wikipedia, 2024.10.23)

Historical trends in technical themes: Analog systems (ISSCC, Analog and Data Converters Subcommittees, 2014)

Memory Is All You Need: An Overview of Compute-in-Memory Architectures for Accelerating Large Language Model Inference (Wolters/Yang/Schlichtmann/Suzumura, 2024.06.12)

Micron Commences Volume Production of Industry-Leading HBM3E Solution to Accelerate the Growth of AI (Micron, 2024.02.26)

Micron earnings 2024q3 (CNBC, 2024.09.25)

SK Hynix earnings 2024q3 (CNBC, 2024.10.23)

Samsung earnings 2024q3 (CNBC, 2024.10.07)

Staying Curious: Developments in Memory Chip Technology (Telecom Review, 2024.06.19)

The Value of Data Storage for the AI Era (Janukowicz, 2024.05)

The history of SK Hynix 1983-2023 (SK Hynix, 2024.10.24)

What changes in storage will AI drive? (Micron, 2023.11)

What’s Next For High Bandwidth Memory: Different approaches for breaking down the memory wall (Semiconductor Engineering, 2019.12.17)

Not investment advice; do your own due diligence!

# GPU IoT HCP hyperscale cloud datacenter edge computing Micron Samsung SK Hynix Taiwan Semiconductor $mu $tsm

Could Laplace's demon to be the theory of everything in the universe?

Evaluating a counterfactual to free will:

What is Laplace's demon?

Attempt to both prove and disprove Laplace's demon

Steelman Laplace's demon and causal determinism – are they logically possible, even if they're physically unachievable within our universe?

Highlight the potential conflict between determinism and the limitations imposed by the laws of physics themselves

See also:🧵https://x.com/AnthPB/status/895114612563218432

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

⁠A Class of Deductive Theories that cannot be Deterministic: Classical and Quantum Physics are not deterministic⁠ (Reznikoff, 2012)

⁠A Contemporary Introduction to Free Will⁠ (Kane, 2005)

⁠A New Kind of Science: A 15-Year View⁠ (Wolfram, 2015)

⁠A philosophical essay on probabilities⁠ (Laplace, 1902)

⁠Chaos: Making a New Science⁠ (Gleick, 1987)

⁠Complexity: A Guided Tour ⁠(Mitchell/Toroczkai, 2010)

⁠De Broglie–Bohm theory⁠ (Wikipedia, 2024.10.23)

⁠Does God play dice?⁠ (Hawking, 1999)

⁠If the Universe Were a Computer⁠ (Minkel, 1999)

⁠Information Theory and Statistical Mechanics⁠ (Bayes, 1956)

⁠Information, Physics, Quantum: The Search for Links⁠ (Wheeler, 1989)

⁠Laplace's demon⁠ (Wikipedia, 2024.10.23)

⁠On the origins and foundations of Laplacian determinism⁠ (Strien, 2017.10.04)

⁠The Fabric of the Cosmos⁠ (Greene, 2004)

⁠Theories of almost everything⁠ (Binder, 2008)

⁠Ultimate physical limits to computation⁠ (Lloyd, 2000)

Not investment advice; do your own due diligence!

# physics thermodynamics quantum mechanics quantum theory chaos theory black holes Heisenberg Uncertainty Principle

What's the latest with artificial intelligence and models' accuracy?

Three objectives:

Compare and contrast traditional autoregressive LLMs (Gemini/chatGPT/Claude/LLaMA) vs nonautoregressive AI (NotebookLM) vs chain of thought reasoning models (Strawberry o1) – including the benefits, detriments, and tradeoffs of each

Error rates for NotebookLM vs traditional LLMs vs CoT reasoning models – focusing on accuracy benefits from a smaller corpus of curated source materials that users feed NotebookLM when promoting (vs an LLM trained on and inferencing from the entire web)

Which model (or combination of models) will be the future standard?

See also:🧵https://x.com/AnthPB/status/1848186962856865904

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

An Investigation of Language Model Interpretability via Sentence Editing (OSU, Stevens, 2021.04)

Are Auto-Regressive Large Language Models Here to Stay? (Medium, Bettencourt, 2023.12.28)

Attention Is All You Need (Google Brain, Vaswani/Shazeer/Parmar/Uszkoreit/Jones/Gomez/Kaiser/Polosukhin, 2017.06.12)

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension (Facebook AI, Lewis/Liu/Goyal/Ghazvininejad/Mohamed/Levy/Stoyanov/Zettlemoyer, 2019.10.29)

Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs (Zhang/Du/Pang/Liu/Gao/Lin, 2024.06.13)

Contra LeCun on "Autoregressive LLMs are doomed" (LessWrong, rotatingpaguro, 2023.04.10)

Do large language models need sensory grounding for meaning and understanding? (LeCun, 2023.03.24)

Experimenting with Power Divergences for Language Modeling (Labeau/Cohen, 2019)

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Raffel/Shazeer/Roberts/Lee/Narang/Matena/Zhou/Li/Liu, 2023.09.19)

Improving Non-Autoregressive Translation Models Without Distillation (Huang/Perez/Volkovs, 2022.01.28)

Non-Autoregressive Neural Machine Translation (Gu/Bradbury/Xiong/Li/Socher, 2017.11.27)

On the Learning of Non-Autoregressive Transformers (Huang/Tao/Zhou/Li/Huang, 2022.06.13)

Towards Better Chain-of-Thought Prompting Strategies: A Survey (Yu/He/Wu/Dai/Chen, 2023.10.08).pdf

XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang/Dai/Yang/Carbonell/Salakhutdinov/Le, 2020.01.22)

Not investment advice; do your own due diligence!

# tech technology machine learning ML

What's the past/present/future of the gaming industry and Ubisoft?

Some video game macro and micro:

Overview of the video game industry – its history and evolution; market size, structure, and economics; plus current state and outlook

Ubisoft $UBSFY deep dive – its current predicament; competitive advantages/disadvantages; financials; and future, including upcoming game releases and other catalysts

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

The Historical Evolution of the US Video Game Industry: Applying the Industrial Organization Model (UGA, Seo, 2002)

Structure and Competition in the US Home Video Game Industry (UMichigan, Williams, 2008)

Vertical Integration, Exclusivity and Game Sales Performance in the US Video Game Industry (UCSC, Gil/Warzynski, 2010)

⁠Technological Tying and the Intensity of Competition: An Empirical Analysis of the Video Game Industry⁠ (Carnegie Mellon, Derdenger, 2010.10.13)

The business of video games is a multi-player game: On governance choices and performance in a two-sided market in the cultural industries (Peters, 2018)

Market Structure and Trend Chasing in the Video Games Industry (Medium, Joseph Clement, 2018.05.27)

What's possible in the gaming industry in the next dimension (EY, 2022)

Unravelling the complexity of the Video Game Industry: An integrative framework and future research directions (Goh/Al-Tabbaa/Khan, 2023.12)

Essential Facts About the US Video Game Industry (Entertainment Software Association, 2024)

Gaming industry emerging technology trends (PwC, 2024.01.16)

The Tremendous Yet Troubled State of Gaming in 2024 (Matthew Ball, 2024.01.23)

Ubisoft Universal Registration Statement 2023-24FY (Ubisoft IR, 2024.06.20)

Ubisoft financial targets update 2024-25FY (Ubisoft IR, 2024.09.05)

⁠Gaming Industry: Structure and Economics⁠ (Fiveable Study Guides, 2024.07.18)

The Success of Black Myth: Wukong And What It Means for Media (Matthew Ball, 2024.09.12)

What Is Happening To The Gaming Industry? (State of the Arc Podcast, 2024.09.23)

Assassin’s Creed maker Ubisoft faces questions over its future (CNBC, 2024.10.01)

Why is Assassin’s Creed maker Ubisoft facing questions about its future? (Invezz, 2024.10.01)

What in the world is going on at Ubisoft? (Fast Company, 2024.10.14)

Not investment advice; do your own due diligence!

# stocks tech media entertainment

How has nonbank credit affected traditional bank lending?

I'm particularly interested in three effects of nonbank lending (e.g. shadow banking and private credit):

loans and leases in bank credit(do nonbanks crowd-out or displace banks?)

bank loan performance (do nonbanks exhibit adverse selection and how do they affect broader delinquencies, chargeoffs, and defaults?)

financial conditions (do nonbanks contribute to procyclical or countercyclical loosening/tightening?)

This podcast is AI-generated with NotebookLM, using the following sources, research, and analysis:

"⁠⁠Is Shadow Banking Really Banking?⁠⁠" (St. Louis Fed, Noeth/Sengupta, 2011.10.01)

"⁠⁠Shadow Banking⁠⁠" (FRBNY, Adrian/Ashcraft/Boesky/Pozsar, 2013.12)

"⁠⁠Shadow Banking and Market Based Finance⁠⁠" (IMF, Adrian, 2017.09.14)

"⁠⁠Non-bank lending during financial crises⁠⁠" (FDIC, Aldasoro/Doerr/Zhou, 2022.01)

"⁠⁠Liquidity, pledgeability, and the nature of lending⁠⁠" (Diamond/Hu/Rajan, 2022.03)

"⁠⁠Nonbank lenders as global shock absorbers: Evidence from US monetary policy spillovers⁠⁠" (BOE, Elliott/Meisenzahl/Paydro, 2023.01.13)

"⁠⁠The Disparate Outcomes of Bank‑ and Nonbank‑Financed Private Credit Expansions⁠⁠" (FRBNY, Boyarchenko/Elias, 2023.08.20)

"⁠⁠Private Credit: Characteristics and Risks⁠⁠" (Fed, Cai/Haque, 2024.02.23)

"⁠⁠Financing Private Credit⁠⁠" (FRBNY, Boyarchenko/Elias, 2024.08)

"⁠Bank Lending to Nonbanks: A Robust Channel Fueled by Constrained Capital?⁠" (FDIC, Krainer/Vaghefi/Wang, 2024.09.05)

⁠Loans and Leases in Bank Credit⁠ (St. Louis Fed/FRED⁠, 2024.10.17)

⁠Commercial Bank Delinquency Rates⁠ (St. Louis Fed/FRED, 2024.10.17)

⁠Commercial Bank Chargeoff Rates ⁠(⁠St. Louis Fed/FRED⁠, 2024.10.17)

⁠Financial Conditions Index "FCI"⁠ (St. Louis Fed/FRED, 2024.10.17)

Not investment advice; do your own due diligence!

# finance financials capital markets