Brian K. Buntz’s Post

A new paper, "The AI Scientist," introduces a framework for fully automated scientific discovery using LLM agents, and demonstrates the potential of these agents to generate research ideas, conduct experiments, and even write scientific papers. If successful, this could significantly disrupt the traditional research model. A somewhat scary aspect of the paper is though, that it can produce equivalent novel content as a motivated PhD student can produce. Thankfully, I am done with my PhD. #AI #Research #PhD #ownviews Link to the paper: https://lnkd.in/gqdeagTP

Recent research by teams from the University of Tübingen and Northwestern University shows that AI language models, like GPT-4, now contribute to 10% of scientific papers. This significant shift is helping to accelerate the writing process, allowing researchers to generate and edit texts faster than ever before. The study analyzed abstracts from PubMed between 2010 and 2024, revealing a notable increase in AI-generated content, especially in fields like medicine and biology. Key terms such as "pandemic" and "covid" surged, indicating the growing influence of AI in these domains. However, this rapid adoption also raises ethical concerns about transparency and the integrity of academic work. Read more about how AI is shaping the future of scientific research in this insightful article from The Economist. #AI #Science #Research #Innovation #Publishing #FutureOfScience #GPT4 #AcademicIntegrity

𝗤𝘂𝗮𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝘁𝗵𝗲 𝘂𝘀𝗲 𝗮𝗻𝗱 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗶𝗻 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵. The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of work. Despite enormous efforts devoted to understanding AI’s economic impacts, we lack a systematic understanding of the benefits to scientific research associated with the use of AI. Here, the authors develop a measurement framework to estimate the direct use of AI and associated benefits in science. We find that the use and benefits of AI appear widespread throughout the sciences, growing especially rapidly since 2015. However, there is a substantial gap between AI education and its application in research, highlighting a misalignment between AI expertise supply and demand. The present analysis also reveals demographic disparities, with disciplines with higher proportions of women or Black scientists reaping fewer benefits from AI, potentially exacerbating existing inequalities in science. These findings have implications for the equity and sustainability of the research enterprise, especially as the integration of AI with science continues to deepen. https://lnkd.in/gKNtjarq

Stanford's Annual AI Index Report is out for the year 2024. Quick Summary: 1. AI outperforms humans in tasks like image classification and English understanding but lags in complex tasks like competition-level mathematics. 2. Industry leads in frontier AI research (compared to Academia 51 vs 15 models) with notable contributions from industry-academia collaborations. 3. Training costs for AI models are skyrocketing (main contributors are GPT-4 and Google’s Gemini Ultra). 4. The U.S. remains the leader in top AI models, ahead of the EU and China combined. 5. There is a significant lack of standardization in responsible AI evaluations. 6. Investment in generative AI surged to $25.2 billion in 2023. 7. AI has increased the productivity of the worker with improved quality 8. AI-driven scientific discoveries are accelerating, with significant advancements in algorithmic sorting and materials discovery. 9. The number of AI-related regulations in the U.S. has sharply increased. 10. Public awareness and nervousness about AI’s impact are growing. Read the full report here: https://lnkd.in/gPjyiG_6

Stanford's Annual AI Index Report is out for the year 2024. Quick Summary: 1. AI outperforms humans in tasks like image classification and English understanding but lags in complex tasks like competition-level mathematics. 2. Industry leads in frontier AI research (compared to Academia 51 vs 15 models) with notable contributions from industry-academia collaborations. 3. Training costs for AI models are skyrocketing (main contributors are GPT-4 and Google’s Gemini Ultra). 4. The U.S. remains the leader in top AI models, ahead of the EU and China combined. 5. There is a significant lack of standardization in responsible AI evaluations. 6. Investment in generative AI surged to $25.2 billion in 2023. 7. AI has increased the productivity of the worker with improved quality 8. AI-driven scientific discoveries are accelerating, with significant advancements in algorithmic sorting and materials discovery. 9. The number of AI-related regulations in the U.S. has sharply increased. 10. Public awareness and nervousness about AI’s impact are growing. Read the full report here: https://lnkd.in/gPjyiG_6

🚨BREAKING: The Royal Society publishes "Science in the Age of AI - How AI is changing the nature and method of scientific research," and it's a must-read for everyone interested in AI & science. Important information: ➡️ According to the official release, the report addresses the following questions: ➵ How are AI-driven technologies transforming the methods and nature of scientific research? ➵ What are the opportunities, limitations, and risks of these technologies for scientific research? ➵ How can relevant stakeholders (governments, universities, industry, research funders, etc) best support the development, adoption, and uses of AI-driven technologies in scientific research? ➡️ Some of the key findings are: "Beyond landmark cases like AlphaFold, AI applications can be found across all STEM fields, with a concentration in fields such as medicine, materials science, robotics, agriculture, genetics, and computer science. The most prominent AI techniques across STEM fields include artificial neural networks, deep learning, natural language processing and image recognition" - "China contributes approximately 62% of the patent landscape. Within Europe, the UK has the second largest share of AI patents related to life sciences after Germany, with academic institutions such as the University of Oxford, Imperial College, and Cambridge University featuring prominently among the top patent filers in the UK. Companies such as Alphabet, Siemens, IBM, and Samsung appear to exhibit considerable influence across scientific and engineering fields." - "Interdisciplinary collaboration is essential to bridge skill gaps and optimise the benefits of AI in scientific research. By sharing knowledge and skills from each other’s fields, collaboration between AI and domain subject experts (including researchers from the arts, humanities, and social sciences) can help produce more effective and accurate AI models. This is being prevented, however, by siloed research environments and an incentive structure that does not reward interdisciplinary collaboration in terms of contribution towards career progression." ➡️ Read the full report below. ➡️ To stay up to date with the latest developments in AI policy & regulation, subscribe to my weekly newsletter. #AI #GenerativeAI #Science #scientificresearch #Aipolicy #AIregulation

#Best_Universities to #Pursue #Generative_AI in 2025, Choosing the right #university is crucial. This article explores some of the best universities to pursue generative AI #studies in 2025, #focusing on their #programs, #faculty, #research_opportunities, and #unique_offerings. https://lnkd.in/gYgtYrKY

Quantifying the use and potential benefits of artificial intelligence in scientific research - Abstract : "The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of work. Despite enormous efforts devoted to understanding AI’s economic impacts, we lack a systematic understanding of the benefits to scientific research associated with the use of AI. Here we develop a measurement framework to estimate the direct use of AI and associated benefits in science. We find that the use and benefits of AI appear widespread throughout the sciences, growing especially rapidly since 2015. However, there is a substantial gap between AI education and its application in research, highlighting a misalignment between AI expertise supply and demand. Our analysis also reveals demographic disparities, with disciplines with higher proportions of women or Black scientists reaping fewer benefits from AI, potentially exacerbating existing inequalities in science. These findings have implications for the equity and sustainability of the research enterprise, especially as the integration of AI with science continues to deepen." https://lnkd.in/eMbx3Fgb

🚀 Exciting news! The Royal Society has released "Science in the Age of AI - How AI is changing the nature and method of scientific research," a must-read for AI and science enthusiasts. 🌟 📌 **Key Questions Addressed:** - How are AI-driven technologies transforming scientific research? - What are the opportunities, limitations, and risks? - How can stakeholders best support AI in scientific research? 📌 **Key Findings:** - AI is widely used across STEM fields, especially in medicine, materials science, robotics, agriculture, genetics, and computer science. Key techniques include neural networks, deep learning, NLP, and image recognition. - China holds 62% of AI patents globally. In Europe, the UK ranks second in AI life sciences patents, with top academic institutions like Oxford, Imperial College, and Cambridge. Major companies like Alphabet, Siemens, IBM, and Samsung lead in scientific and engineering fields. - Interdisciplinary collaboration is crucial for maximizing AI benefits but is hindered by siloed research environments and a lack of incentives for such collaboration. Source: Luiza Jarovsky Link to the full report: https://lnkd.in/dJ5-aSrJ #AI #Science #Research #Innovation #InterdisciplinaryCollaboration #TechTrends

Some of the most interesting applications of AI are not incremental improvements in existing processes but new applications that help with innovation. These two papers are good resources for measuring novel combination of ideas and and generating proposed areas of new research. #ai #llm #innovation #scientificdiscovery https://lnkd.in/gUqxJFem and https://lnkd.in/gM2Xf8QX