Soundtrack: The Dillinger Escape Plan - One Of Us Is The Killer An MIT study found that 95% of organizations are getting "zero return" from generative AI, seemingly every major outlet is now writing ...

グループ全体で10億 AI agents を作る：SoftBank World 2025 孫 正義特別講演より

SNSや生成AIの進化により拡張し続ける私たちのID（アイデンティティ）。その変化は、働き方や社会の価値観にどのような影響を与えるのでしょうか。小説家の平野啓一郎さんをお招きし、「分人主義」の視点から新たな人間モデルを紐解きます。さらに、日立製作所研究開発グループの研究者とのパネルディスカッションを通じて、分人の考え方を取り入れた社会インフラや働き方の未来像を探ります。Vol.1では、平野啓一郎さ...

Eighty years after the US bombings of Hiroshima and Nagasaki, aging survivors — some more than 100 years old — reveal the shame and stigma they endured as young women of childbearing age.

Transcribed minutes of Target Committee meeting, Los Alamos, May 10-11, 1945

An all-Christian American crew used the steeple of Japan’s most prominent Christian church as the target for an act of unspeakable barbarism, writes Gary G. Kohls. What Imperial Japan Couldn't Do in ...

HIROSHIMA -- The following is the full text of the Peace Message read on Aug. 6 by Hiroshima Gov. Hidehiko Yuzaki at a ceremony to mark 80 years since

The United States dropped the world's first atomic bomb on Hiroshima, Japan, on Aug. 6, 1945, during World War II.

広島市西区に暮らす鈴藤（すずとう）實さん（94）は朝夕2回、自宅の仏壇の前に座る。毎年8月6日だけは未明に家を出ると、平和記念公園（中区）の原爆慰霊碑へ。夜が明ける前に一人、手を合わせる。「家族が眠

LRM sta per Large Reasoning Models, una evoluzione degli LLM. Apple mostra che a volte funzionano meglio gli LLM, a volte gli LRM, in generale sono inconsistenti e falliscono con complessità elevate. So’ stagisti digitali, che vi aspettate ? Source: Apple > This is interesting as it shows that compositional reasoning failures in LLMs are not simply due to insufficient context length or inference compute, but rather reflect fundamental limitations in how models maintain algorithmic consistency across problem scales. This suggests that while these models can reach deeper into solution sequences on average, their reasoning processes are more instable and prone to inconsistent performance. … Our findings reveal fundamental limitations in current models: despite sophisticated self-reflection mechanisms, these models fail to develop generalizable reasoning capabilities beyond certain complexity thresholds. We identified three distinct reasoning regimes: standard LLMs outperform LRMs at low complexity, LRMs excel at moderate complexity, and both collapse at high complexity. These insights challenge prevailing assumptions about LRM capabilities and suggest that current approaches may be encountering fundamental barriers to generalizable reasoning. Finally, we presented some surprising results on LRMs that lead to several open questions for future work. Most notably, we observed their limitations in performing exact computation… Continua qui: _the-illusion-of-thinking.pdf_ If you like this post, please consider sharing it.

AI might seem like the pinnacle of a new frontier, opening up vast possibilities to reshape the future. But AI is backwards-facing by design, being an amalgamation of the ocean of data humanity has…