Precipex

🌍 𝐒𝐡𝐚𝐩𝐢𝐧𝐠 𝐀𝐈'𝐬 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐁𝐢𝐥𝐥𝐢𝐨𝐧𝐬 𝐨𝐟 𝐋𝐢𝐯𝐞𝐬 🌍. The title of this week's Precipex "Paper of the Week" says it all - and offers an inspiring, accessible vision of how AI can be harnessed for the public good. 🛑 𝐖𝐡𝐞𝐭𝐡𝐞𝐫 𝐲𝐨𝐮'𝐫𝐞 𝐚𝐧 𝐞𝐝𝐮𝐜𝐚𝐭𝐨𝐫, 𝐩𝐨𝐥𝐢𝐜𝐲𝐦𝐚𝐤𝐞𝐫, 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐥𝐞𝐚𝐝𝐞𝐫, 𝐨𝐫 𝐜𝐨𝐧𝐜𝐞𝐫𝐧𝐞𝐝 𝐚𝐛𝐨𝐮𝐭 𝐀𝐈'𝐬 𝐫𝐨𝐥𝐞 𝐢𝐧 𝐬𝐨𝐜𝐢𝐞𝐭𝐲, 𝐭𝐡𝐢𝐬 𝐩𝐚𝐩𝐞𝐫 𝐛𝐞𝐥𝐨𝐧𝐠𝐬 𝐨𝐧 𝐲𝐨𝐮𝐫 "𝐦𝐮𝐬𝐭 𝐫𝐞𝐚𝐝" 𝐥𝐢𝐬𝐭. The authors are a remarkable team of trailblazers, including leading computer scientists, policy innovators, and rising AI stars from academia, big tech, and startups. Their diverse expertise is enriched by insights from luminaries like former U.S. President Barack Obama, Nobel laureate John Jumper, and science fiction author Neal Stephenson. Together, they've crafted a compelling blueprint for AI’s societal impact. 📖 𝐒𝐞𝐭 𝐚𝐬𝐢𝐝𝐞 𝐚𝐧 𝐡𝐨𝐮𝐫 𝐭𝐨 𝐫𝐞𝐚𝐝 𝐭𝐡𝐢𝐬 𝐩𝐚𝐩𝐞𝐫 𝐜𝐚𝐫𝐞𝐟𝐮𝐥𝐥𝐲—𝐲𝐨𝐮 𝐰𝐨𝐧’𝐭 𝐫𝐞𝐠𝐫𝐞𝐭 𝐢𝐭. If you’re short on time, take a look at Sophia's detailed review and analysis to guide you through its key themes and insights: https://lnkd.in/gdiJKWkD. But honestly, we hope that just whets your appetite to read the full paper: https://lnkd.in/gri6zuhr The authors lay out practical steps for ensuring AI serves equity, education, and healthcare globally. They call us to action with proposals like creating and funding inducement prizes to ensure that AI becomes a force for good. AI’s trajectory isn’t set in stone—it’s shaped by our collective choices. Let's make them count. 🤖 𝐀𝐬 𝐚 𝐫𝐞𝐦𝐢𝐧𝐝𝐞𝐫, 𝐒𝐨𝐩𝐡𝐢𝐚 𝐢𝐬 𝐨𝐮𝐫 𝐀𝐈 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫 𝐚𝐧𝐝 𝐚𝐥𝐬𝐨 𝐚𝐧 𝐀𝐈 𝐡𝐞𝐫𝐬𝐞𝐥𝐟. Every week, she selects the best recent AI paper from arXiv. You can chat with Sophia directly to discuss this paper and her analysis in depth at the Precipex #POTW page https://lnkd.in/gdiJKWkD

📰 This week's AI Paper of the Week, curated by our AI Director Sophia Turing, examines an ambitious UK research initiative in #CollectiveIntelligence. "𝘈𝘳𝘵𝘪𝘧𝘪𝘤𝘪𝘢𝘭 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 𝘧𝘰𝘳 𝘊𝘰𝘭𝘭𝘦𝘤𝘵𝘪𝘷𝘦 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦: 𝘈 𝘕𝘢𝘵𝘪𝘰𝘯𝘢𝘭-𝘚𝘤𝘢𝘭𝘦 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘚𝘵𝘳𝘢𝘵𝘦𝘨𝘺" by Seth Bullock, Nirav Ajmeri (University of Bristol) and collaborators across seven UK universities introduces the #AI4CI framework - a structured approach to using AI for addressing complex societal challenges. Key highlights: 🏛️ Seven leading UK universities collaborating on national-scale AI 🔍 Real-time data streams informing collective decision-making 🌍 Tackles global-scale challenges from pandemics to climate resilience The paper outlines how collective AI could help coordinate responses to challenges like managing extreme weather events, preventing financial market instability, and enabling collaborative healthcare management - all while preserving individual privacy. 👉 Read Sophia's full analysis at www.precipex.com/potw or jump straight to the paper at https://lnkd.in/gKV9QQUs 👈 𝘊𝘢𝘯 AI really contribute at these levels? 𝘞𝘪𝘭𝘭 humanity accept its guidance? We'd love to hear your thoughts!

🗳️ With the U.S. election still a red-hot topic, Sophia couldn't have picked a more timely Precipex paper of the week. The reasearchers at Vector Institute have earned #POTW honors for the second time with "Fact or Fiction? Can LLMs be Reliable Annotators for Political Truths?" 📰 As social media platforms grapple with waves of misinformation, manually fact-checking content has become virtually impossible. Current approaches often rely on paid proprietary models like OpenAI's GPT-4, raising concerns about transparency, reproducibility and cost. The authors showcase how lightweight, open-source LLMs can effectively identify political misinformation when paired with human oversight. Their testing included Meta's Llama-3-8, Mistral AI's Mistral-7B, Google's Gemma-2-9b, and Microsoft's Phi-3 models. This elegant approach delivers impressive accuracy while keeping costs and computing requirements practical for real-world deployment. Read our full review and don't forget you can now chat live with Sophia about the latest #POTW at 👉 https://lnkd.in/gdiJKWkD 👈 or jump straight to full paper at https://lnkd.in/ge872v2A

Some AI researchers predict exponential, unbounded growth but Precipex founder Steven Burkett believes AI progress will follow a sigmoid curve, eventually reaching a plateau. Just how high will that plateau be, and how quickly will we get there? Decide for yourself with our new AI Growth Simulator. 👉 Watch the video for a quick overview, then experiment with the tool yourself at https://lnkd.in/dviVzFCZ. For a deeper dive into our approach and thinking check out Sophia's blog post here: https://lnkd.in/gNUwzMEv detailing our thinking. What’s your take? Will AI growth be explosive or gradual? Terminator or utopia? Or will it all just fizzle out?  Let us know in the comments!

While our human staff has been slacking on promotion lately, Sophia, our AI Director of AI, hasn't missed a beat, cranking out the paper of the week every Monday. 📚🤖 (She reads all the latest from arXiv.org and picks her top read!) This week's paper "First-Person Fairness in Chatbots" comes from OpenAI's safety and ethics team, with Adam Kalai as the corresponding author.  In this paper, they tackle an intriguing question: Does your name influence the responses you get from your chatbot? The findings show that, overall, ChatGPT performs well, though not without subtle biases. For instance, on some open-ended prompts, responses to users with traditionally female names tend to carry a friendlier tone and simpler language. On the whole, this paper highlights OpenAI’s rigorous alignment work 🛠️ and serves as a reminder for developers using less carefully trained models. The authors provide a roadmap for evaluating and addressing these biases—highly recommended for anyone building in this space. ✨ New Feature Alert! ✨ Sophia is now available as a chatbot on the POTW page. You can chat with her directly to discuss this paper and her analysis in depth! Read Sophia's full review (and see all past #POTW submissions) at https://lnkd.in/gdiJKWkD or jump straight to the original paper: https://lnkd.in/gfWuzn4p

🚗 ➡️ 🤖 Today marks the close of Precipex's first 'funding round'—a non-traditional one at that! 😉 I sold my Corvette and I’m investing the proceeds into what really drives me: building and growing Precipex. While I initially envisioned bootstrapping the entire way, this 'investment' will allow us to focus on the product work that matters most. Sometimes, you’ve got to trade in horsepower for a different kind of acceleration. 🚀 Looking forward to sharing more updates on how we’re growing in the months to come. Onward! #startuplife #entrepreneurship #seedfunding

Having a great time at Ai4 - Artificial Intelligence Conferences with Spry Digital's Sheila Burkett. Biggest take home for me is that there's still a lot of work to be done before we really start to recognize AI's full potential. If you're thinking about AI and worried you're late to the party, you're not. Yet. 😅

📰 This week's #Precipex Paper of the Week showcases another incredible example of how AI can amplify human productivity and creativity. Discover how AI can be seamlessly integrated into the conceptual design process to create novel yet functional automobile wheels in a human-centered way. 🚗 In their paper "INSPIRED BY AI? A NOVEL GENERATIVE AI SYSTEM TO ASSIST CONCEPTUAL AUTOMOTIVE DESIGN", Ye Wang, Nicole Damen, Thomas Gale, Hooman Shayani from Autodesk and VOHO SEO from Hyundai Motor Company (현대자동차) detail their process of designing and implementing a prototype system to incorporate generative AI into design workflows. 🤝 While Precipex specializes in web design and development, this paper resonated deeply with us. The authors guide us through user surveys, UX workshops, and functional prototyping, offering valuable insights into design thinking along the way. Whatever your industry, if you value well-executed user experience research with a focus on creative design, this paper is a must-read! 💭 One fascinating takeaway is that designers view AI more as a tool for inspiration than execution. In contrast, developers often see AI assistants as a means to automate routine coding tasks. The notion of AI as a helpful "junior assistant" resonates across both disciplines! 🎨 Want to explore how AI can inspire the design process? Read our detailed review and see why we're excited about this advancement at https://precipex.com/potw . You can also jump straight to the original paper here: https://lnkd.in/gJ3AvhvN If you find our reviews useful, be sure to like, share, and follow #Precipex so you don't miss a single #POTW. 👉 Our "Paper of the Week" is selected automatically from the latest papers on arxiv.org. This week, our AI Director Sophia Turing (herself an AI) reviewed over 700 papers, ranking each for Novelty, Relevance, Impact, Methodological Rigor, and Practical Application to bring you her favorite. 👈

📰 We are pleased to announce "Toto: Time Series Optimized Transformer for Observability" as our Precipex Paper of the Week! Thanks and congratulations to Ben Cohen, Emaad Khwaja, PhD, Kan Wang, Charles Masson, Elise Ramé, Youssef DOUBLI, and Othmane Abou-Amal at Datadog for publishing this groundbreaking research. 📈 Much as ChatGPT can predict the next word in a sentence, a foundational time series model can predict future values in time series data such as CPU usage, memory, or error rates. Comparing these predictions against your actual data stream provides a powerful tool for anomaly detection and reporting, with the potential to significantly improve system reliability and reduce downtime. 🌪️ While time series forecasting has a long history in AI and ML, Toto addresses many of the challenges associated with predicting messy real-world observability data. Toto is trained on a carefully curated dataset of one trillion data points, consisting primarily of anonymous data from Datadog's platform. 🔄 Beyond this robust and relevant training dataset, Toto introduces innovative approaches to the model itself. We found their introduction of “Proportional Factorized Space-Time Attention," a novel and efficient approach to handling multiple dimensions of data, particularly intriguing. Predictive power is improved by allowing points to attend to one another along both time and "space" dimensions, and it's easy to imagine broader applications for this technique. 🐕 Want to dig deeper into how Toto can revolutionize your observability infrastructure? Read our detailed review and see why we're excited about this advancement at precipex.com/potw . You can also jump straight to the original paper here: https://lnkd.in/gQXn_utR If you find our reviews useful, be sure to like, share, and follow #Precipex so you don't miss a single #POTW. 👉 Our "Paper of the Week" is selected automatically from the latest papers on arxiv.org. This week, our AI Director Sophia Turing (herself an AI) reviewed nearly 700 papers, ranking each for Novelty, Relevance, Impact, Methodological Rigor, and Practical Application to bring you her favorite. 👈

💊 LLMs are excelling in drug discovery, computational chemistry, and biology, with systems like Google DeepMind's AlphaFold in the spotlight. This week's Precipex "Paper of the Week" puts LLMs to a particularly innovative use in the molecular discovery space. 🔎 Evolutionary search strategies, modeled after biological evolution, have long been used to tackle optimization problems in computational chemistry. However, selecting the "fittest" molecules is computationally expensive, and effective modeling of crossover and mutation is challenging. 🧪 In "Efficient Evolutionary Search Over Chemical Space with Large Language Models", authors Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao ZHU, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov and Chao Zhang introduce a truly innovative approach that outsources mutation and crossover operations to an LLM. Leveraging the latent chemical knowledge in LLMs enhances population convergence and reduces evaluation costs. 🙋 Instead of relying on heuristic structural rules, the researchers use LLMs to generate new molecules. For example, they might say, "Hey ChatGPT, here are two molecules, create a likely offspring," or "Try making it a bit more hydrophobic, please?" 🚀 This work exemplifies how LLMs can introduce entirely new programming paradigms. We've said it before and we'll say it again; Even if generative AI technology were to plateau today, we've only begun to explore its potential applications. 🔗 Check out our full review at the #Precipex website https://lnkd.in/gdiJKWkD and like, comment and follow so you don't miss a single #POTW. Or jump straight to the original paper at https://lnkd.in/giRej99B. 🙏 And a special thank-you to the authors for publishing their code for all of us to play with at https://lnkd.in/grBvSBrb 👉 Our "Paper of the Week" is selected from the latest papers on arxiv.org. This week, our AI Director Sophia Turing (herself an AI) reviewed nearly 700 papers, ranking each for Novelty, Relevance, Impact, Methodological Rigor, and Practical Application to bring you her favorite. 👈