Trill News

The secret of success is to do the common thing uncommonly well. — John D. Rockefeller Jr.
  1. U.S. sanctions Turkish bank accused of enabling Iran as Bessent says he 'hopes for' no further bank penalties President Donald Trump hyped the sanctions plan as "economic D-Day" against Iran, but the U.S. has so far taken few steps to implement it.
  2. 8 New TV Shows to Watch This Weekend on Netflix, Prime Video, and Hulu (September 4-6) In this week's column, we include newly released TV shows alongside other series that have been made available on platforms like Netflix.
  3. Pro Football HOF overhauling selection process The Pro Football Hall of Fame has made sweeping changes to its selection process that include a significant reduction in the number of selectors and the elimination of the separate Seniors category.
  4. Hemp entrepreneurs in Florida receive a reprieve  — at least for another month Included in a congressional continuing resolution that President Trump signed Wednesday to fund the federal government through Dec.
  5. Trump's peace envoys to visit Moscow and Kyiv over weekend Steve Witkoff and Jared Kushner have led President Donald Trump's efforts to end the Russia-Ukraine war - but talks have stalled.
  6. The Best Deals on Tools and Appliances From Home Depot's Labor Day Sale Save up to 50% on grills, landscaping equipment, outdoor lights, tools, security cameras, and more.
STEM FEATURED STORY

How Large Language Models Develop Unexpected Skills

Topics in Cognitive Science

Large language models (LLMs) have been observed to develop unexpected and emergent capabilities that were not explicitly programmed and did not appear in smaller versions of the same architectures. These emergent abilities — including in-context learning, multi-step arithmetic reasoning, instruction following, and rudimentary theory of mind — tend to appear suddenly at certain scales of model size, a phenomenon researchers have described as a phase transition rather than a gradual improvement. The unpredictability of these emergent skills poses both scientific and safety challenges. Because researchers cannot reliably forecast which new capabilities will appear at what scale, models may develop unintended or potentially dangerous behaviors without warning. The debate over whether these abilities represent genuine reasoning or sophisticated pattern matching remains unresolved, but the implications — for education, security, and AI governance — are already reshaping how developers and policymakers think about increasingly powerful language models.

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How Large Language Models Develop Unexpected Skills
OPINION

Michał Kalecki and Challenging the Norms of Capitalist Theory

Jacobin

Michał Kalecki was a self-taught Polish economist who independently developed many of the same macroeconomic insights as John Maynard Keynes, yet remains far less known today. Working from a Marxian class perspective, Kalecki built models of business cycles, effective demand, and income distribution that challenged the assumption that households, not firms, are the key economic decision-makers.

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