Let's discuss ethologist John B. Calhoun's research on the effects of overpopulation on behavior, primarily through his rat and mouse "utopia" experiments:

1) https://en.wikipedia.org/wiki/Behavioral_sink

2) https://www.the-scientist.com/universe-25-experiment-69941

These experiments, most notably "Universe 25," aimed to observe societal collapse in controlled environments with unlimited resources but limited space.

Calhoun coined the term "behavioral sink" to describe the resulting breakdown of social norms and destructive behaviors observed under high population density. While his work was influential and seen as a potential model for human societal issues, its applicability to humans is debated, and modern ethical standards would likely prohibit such experiments today.

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Samuel Benner was a 19th-century farmer who developed a cyclical theory to forecast market movements based on recurring periods of panic, good times, and hard times.

Benner observed patterns in commodity prices, linking them to agricultural and solar cycles, notably an 11-year cycle for corn and pigs and a 27-year cycle for pig iron. His work, published in 1875, suggested specific years for buying and selling assets, claiming a high degree of accuracy for over a century, even predicting events like the 2008 crash. The text presents this Benner Cycle as a long-term indicator for potential market shifts, recommending its use alongside other trading tools and encouraging readers to explore further resources offered by the TRI blog and school for trading education.

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Dynamic Programming (DP) as an algorithmic technique for optimizing recursive solutions by storing results of subproblems to avoid redundant computations.

Our sources:

https://www.geeksforgeeks.org/dsa/introduction-to-dynamic-programming-data-structures-and-algorithm-tutorials/

https://stackoverflow.blog/2022/01/31/the-complete-beginners-guide-to-dynamic-programming/

They highlight two main characteristics for problems suitable for DP: optimal substructure, where optimal solutions to larger problems can be built from optimal solutions to subproblems, and overlapping subproblems, where the same subproblems are solved repeatedly. The sources describe two primary approaches to DP: top-down (memoization), which involves storing results of recursive calls, and bottom-up (tabulation), which iteratively builds solutions from base cases. Both articles use the Fibonacci sequence as a key example to illustrate how DP improves efficiency from exponential to linear time complexity compared to brute-force recursion.

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Kashmir Hill's "Your Face Belongs to Us" explores the rise of Clearview AI, a secretive startup that built a powerful facial recognition technology. The book investigates the company's origins, its founders Hoan Ton-That and Richard Schwartz, and their controversial methods of gathering images. It examines the ethical and legal implications of Clearview AI's technology, highlighting potential dangers such as misuse by law enforcement and the erosion of privacy.

The text references legal documents, emails, interviews, and other primary sources to illustrate the development of Clearview AI and the broader implications of facial recognition technology. Hill explores the technology's history, its potential for misuse, and the ongoing debate about privacy in an age of increasing surveillance, spanning from ancient practices of physiognomy to modern-day AI systems. It presents a critical analysis of Clearview AI's impact on society and the future of privacy.

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Today we're talking about Manus, China's autonomous AI agent, designed to operate independently across diverse domains like finance and recruitment.

Our sources highlight Manus's multi-agent architecture, which allows it to break down and execute complex tasks without human prompts, distinguishing it from AI assistants requiring constant oversight.

The rise of Manus signals a potential shift from AI as an assistant to AI as an independent actor, sparking both excitement and concern in Silicon Valley regarding China's lead in autonomous systems. The articles also raise important ethical and regulatory questions about AI autonomy and accountability in a world where intelligence is no longer uniquely human.

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"Superintelligence" by Nick Bostrom explores the potential development and implications of superintelligence, focusing on its paths, dangers, and strategies for ensuring a positive outcome. It considers various aspects, such as the history and current state of AI, different forms of superintelligence, and the possible timelines for its emergence.

The book addresses challenges related to controlling superintelligent systems and aligning their values with those of humanity. It further investigates multipolar scenarios and the importance of international collaboration in managing the risks associated with advanced AI.

The book also discusses the ethical and societal implications of superintelligence, including its potential impact on economics, human values, and the future of life. Finally, the text suggests strategies for risk mitigation and promoting a beneficial outcome from the development of superintelligence.

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Today we're looking at this paper:

"AI-Powered Lawyering: AI Reasoning Models, Retrieval Augmented Generation, and the Future of Legal Practice"

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5162111

It investigates the impact of new AI technologies on legal work, specifically examining Retrieval Augmented Generation (RAG) and AI reasoning models. It presents findings from a randomized controlled trial where law students used either a RAG-powered tool (Vincent AI), an AI reasoning model (OpenAI’s o1-preview), or no AI while completing legal tasks. The study found that both AI tools improved the quality and efficiency of legal work, but with distinct strengths: the AI reasoning model enhanced analytical depth, while RAG reduced hallucinations. These technologies appear to help attorneys, but it's important to keep human supervision over AI-driven legal tasks. The research suggests that integrating RAG and reasoning models could lead to even more significant advancements in AI-powered lawyering.

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How do socks actually not have holes? This and more in the newest Swetlana AI podcast episode on topology and holes.

#mathematics #topology #geometry

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The paper, written by Eric Schmidt (Google) and others, examines the national security implications of advanced AI:

https://drive.google.com/file/d/1JVPc3ObMP1L2a53T5LA1xxKXM6DAwEiC/view

It explores the dangers of an AI arms race, focusing on the potential for strategic instability and catastrophic misuse by rogue actors. The documents propose a three-pronged "Multipolar Strategy" based on deterrence, nonproliferation, and competitiveness, advocating for a "Mutual Assured AI Malfunction" (MAIM) regime. This approach suggests proactively disabling threatening AI projects controlled by rival nations, similar to Cold War nuclear strategy. Furthermore, they recommend export controls on AI chips, information security measures to protect AI models, and incentivizing AI safety practices. Finally, the pieces also discuss the importance of managing the economic and political consequences of AI-driven automation.

#asi #agi #superintelligence

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"Machine Learning for the Quantified Self" discusses leveraging machine learning for quantified self data, generated from wearables and smartphones.

It focuses on techniques to analyze self-tracking data, including cleaning, feature extraction, clustering, and predictive modeling. Unique challenges posed by self-tracking data, such as noise, missing measurements, and temporal dependencies, are addressed.

The book explores various machine learning algorithms, including supervised, unsupervised, and semi-supervised learning, with a practical emphasis on application. A case study using the crowdsignals dataset illustrates these concepts, with code examples provided in Python and R. Ultimately, the book aims to empower individuals to gain meaningful insights from their personal sensory data, while also noting considerations such as user privacy and ethical implications.

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