Core Insights - OpenAI has released a new benchmark called FrontierScience to evaluate AI's scientific reasoning capabilities in physics, chemistry, and biology, revealing that AI still has a long way to go to match true scientists [1][6][17] Group 1: Benchmark Design and Structure - FrontierScience consists of over 700 text-based questions, including 160 "Gold Set" questions, with 100 competition-style questions and 60 original research sub-tasks designed by PhD-level researchers [9][12] - The competition track emphasizes short-answer formats for easy verification, while the research track uses a 10-point scoring system, requiring at least 7 points to pass [9][12] - The quality of questions is ensured through collaboration with 42 international award winners and 45 qualified scientists across various fields [11][12] Group 2: AI Performance and Comparison - Initial testing showed that GPT-5.2 scored 77% on competition questions and 25% on research questions, leading the pack, while Gemini 3 Pro followed closely with 76% on competition questions [13] - In a previous benchmark, GPT-4 scored only 39% on a question set designed by PhD experts, significantly lower than the expert baseline of 74% [6][12] Group 3: Challenges and Limitations - OpenAI acknowledges that advanced models still make reasoning, logic, and factual errors, and that longer processing times often correlate with higher accuracy [15][17] - FrontierScience is designed to standardize assessments but does not evaluate the models' ability to generate truly novel hypotheses or interact with multimodal data and real-world experimental systems [17] Group 4: Future Directions - OpenAI plans to iterate on the question bank, expand the fields covered, and include more real-world assessments to determine the practical impact of these systems on scientific work [17]

Core Insights - The AI system developed by Peking University, named "AI-Newton," has demonstrated the ability to independently derive classical mechanics laws from experimental data, marking a significant shift in the role of AI in scientific research [1][2] - This advancement indicates a transition of AI from being a mere tool to becoming an independent cognitive entity in scientific inquiry [1] Group 1: AI System Capabilities - "AI-Newton" was tested with 46 sets of experimental data without any pre-set physical knowledge, successfully identifying motion patterns and constructing fundamental concepts like "force," "mass," and "acceleration" [1] - The system ultimately derived Newton's second law, F=ma, using a reasoning strategy akin to the scientific method of hypothesis and verification, rather than simple fitting as seen in traditional large models [1] Group 2: Research Implications - The programming approach of "AI-Newton" is expected to encourage models to actively approach core concepts, potentially becoming a crucial method for future scientific discoveries [2] - The research team plans to extend this methodology to more complex areas, including exploring patterns within quantum systems, indicating a shift of AI from data analysis to being a participant in theory generation [2]

🔥 INSIGHT: Blockchain treasuries are creating fast, decentralized funding pipelines for scientific research. https://t.co/2K8UVbnyE9 ...

So this is your lab. >> Yes, this is where we do the organ chip cultures. >> Ingber relies largely on federal funding for his work identifying new therapies using what he calls organs on chips.This breakthrough technology, tiny tissue line devices can replace animal testing. So what does that allow you to do. We can study how the body normally works.We study response to drugs, response to toxins, drug delivery systems. >> Federal grants have made up almost half the university's research funding. Ingber and ...

Core Insights - On October 15, 2025, a total of 22 papers were published in the prestigious journal Nature, with several authored by Chinese scholars, highlighting the significant contributions of Chinese researchers in various scientific fields [2][4][6][9][12][21][22][24]. Group 1: Research Contributions - Zhang Zhenhua from RWTH Aachen University published a paper on "Deaminative cross-coupling of amines by boryl radical β-scission," focusing on a novel reaction mechanism involving boryl radicals [2]. - A collaborative work by Xu Minyu from National University of Singapore and Zhang Xinglong from Chinese University of Hong Kong discussed "Photocatalytic oxygen-atom transmutation of oxetanes," presenting advancements in photocatalysis [4]. - A team from Shanghai Jiao Tong University, Fudan University, and Nanjing University of Science and Technology introduced "Tin-based perovskite solar cells with a homogeneous buried interface," contributing to solar energy technology [6]. - The Taiwan Precision Medicine Initiative was highlighted in a paper by researchers from Academia Sinica, providing a cohort for large-scale studies in precision medicine [9]. - A study on "Population-specific polygenic risk scores for people of Han Chinese ancestry" was published by researchers from Academia Sinica, focusing on genetic risk assessment [12]. Group 2: Environmental and Material Science - Lin Yucheng from Rutgers University published a paper on "Modern sea-level rise breaks 4,000-year stability in southeastern China," addressing significant environmental changes [17]. - Research on "Patchy nanoparticles by atomic stencilling" was conducted by Chen Qian from the University of Illinois, exploring innovative methods in nanotechnology [19]. - A study on "A conserved H3K14ub-driven H3K9me3 for chromatin compartmentalization" was published by researchers from East China Normal University and the Chinese Academy of Sciences, contributing to the understanding of chromatin biology [21]. - Tsinghua University’s Fang Lu published a paper on "Integrated lithium niobate photonics for sub-ångström snapshot spectroscopy," advancing photonic technologies [22]. - Chen Chi-Fang from UC Berkeley introduced "Efficient quantum thermal simulation," focusing on quantum computing applications [24].

Scientific Research Focus - This year's Nobel-winning scientific research has potential uses ranging from cancer treatments to extracting water from dry desert air [1]

Scientific Research Focus - This year's Nobel-winning scientific research has potential uses ranging from cancer treatments to extracting water from dry desert air [1] Industry Application - The research could be applied to cancer treatments [1] - The research could be applied to extracting water from dry desert air [1]

ing and joining us now is one of the hundreds of thousands of furled government workers. Jenna Norton is a program director at the NIH, the National Institutes of Health. She's now joining us in her personal capacity.Uh so this is not your first shutdown, but you spoke with my colleague Shannon Petty Piece, and you said you had a lump in your throat as you left the NIH offices this week. Why why this time did it feel different. You know, I think this shutdown is just completely different from anything that ...

Westin: This is a story about trees not growing to the sky, even if those trees are holding up an important part of the U.S. economy. President Trump has made no secret of his quest to cut funding to some of the nation's most prestigious universities. - We want money to go to all universities, not Harvard.There have $52 billion. - Harvard's voice is loud and clear. Westin: To date, much of the discussion has centered on the politics of it all, whether higher education has gotten too "woke" and whether it's ...

Research & Funding Concerns - Scientific research funding cuts are detrimental to the future, potentially halting crucial research [1] - Paused research leads to laboratory closures, loss of experienced personnel, and a decline in expertise [2] - Federal funding is a critical component of the research dimension within the innovation economy [4] Startup Ecosystem & Market Conditions - Despite challenges, the Boston startup ecosystem showed strength in the first half of 2025 [2] - Healthcare and biotech research has been particularly affected by pauses and job cuts, creating volatility [3] - Deal flow has remained consistent, with exceptional teams and technological advancements still emerging [3][4]