Jorge Dobón Montagut

As AI continues to integrate more deeply into our daily lives, concerns about the future of human jobs naturally arise. However, Yann LeCun, Meta's Chief AI Scientist, has highlighted a key distinction between AI and human intelligence: motivation. Unlike humans, AI systems do not possess desires or ambitions—they require human input to pursue specific goals. As LeCun aptly put it, "AI has no desire to replace us because it has no desire." This synergy between AI and human programmers enables us to bypass the repetitive aspects of coding, freeing us to focus on more creative and passion-driven projects. This week’s article of the week delves into how the AI boom has actually been a boon for human engineers, underscoring the continued importance of understanding coding—even in an era where AI can assist. We also want to give a special shout-out to Girls Who Code! Bio::Neos has proudly supported our local chapter, and we're excited to announce that registration is now open for 3rd-5th graders. This program is a fantastic introduction to coding and an important step toward building vital skills for the future. This week’s #Articleoftheweek: https://lnkd.in/gJrS8D-D Learn more about Girls Who Code and register here: https://lnkd.in/gqa7YvyV 

3

The IV curve, or volatility surface, describes how IV varies across different strikes and expirations.  Understanding the IV curve as a function of expiration is essential for option traders The Implied Volatility Curve as a Function of Expiration🧵 https://lnkd.in/gw3RHtZx

35

1 comentario

At PyData Amsterdam 2024, join Vitalie Spinu for his talk, "Drift Detection on Irregular Time Series with Multiple Non-Uniform Seasonal Patterns Using MIST and DTW Algorithms." In this session, Vitalie will explore the complex challenges of detecting drifts in irregular time series with non-uniform seasonal patterns, like end-of-month or holiday effects. Vitalie will introduce a powerful four-step approach to drift detection, combining MIST (Multiple Irregular Seasonalities and Trend decomposition) and DTW (Dynamic Time Warping) algorithms. He’ll demonstrate how this method can efficiently handle issues like missing data, irregular time points, and complex seasonal patterns, making it adaptable across various domains. Don’t miss this opportunity to learn how to manage long-term drifts in large-scale datasets with millions of time series, and discover how to apply these techniques directly to raw data with minimal pre-processing. 🎟 https://lnkd.in/eEtC9ESU #PyDataAmsterdam2024 #MachineLearning #AI #LLM #PyData2024 #data #datascience #python

28

Discover how Retrieval-Augmented Generation (RAG) revolutionizes AI by combining real-time retrieval and generative models for accurate, relevant responses. RAG enhances accuracy, reduces errors, and adapts effortlessly to new info. Explore how RAG is transforming industries and setting new benchmarks for AI performance. #ArtificialIntelligence #MachineLearning #Innovation #TechTrends #CustomerSupport

11

Check out the key features in this powerful module inside #subsurfaceAI https://lnkd.in/gPH64zAU Geoscientists without any coding skills in Python can take full advantages of the latest algorithms in #MachineLearning for improved reservoir characterization & property prediction. SubsurfaceAI Inc Mark Tobin Cindy Luo David Gray Rongfeng Zhang Renjun Wen

19

Thread: A Comprehensive Guide to Relative Value Volatility Trading 🧵 with mathematical breakdown https://lnkd.in/gHAp-Rvi

15

Following up on a classroom question, I wrote a blog exploring the Python array type and how it compares to Python lists and NumPy ndarrays in terms of computational speed and memory consumption. Read it on the Diller Digital blog: https://lnkd.in/g7bKMPGa

3

🎉New tutorial about QRAO！🎉 Jij added QRAO! This methods embeds multiple bits into fewer qubits, solving larger optimization problems with limited quantum resources. It can also be used as a relaxation method! Get started easily with Qamomile! #QuantumComputing https://lnkd.in/gWBVbv_m

21

1 comentario

Image #annotation helps #machinelearning and #AI models to label the #datasets to perform #classification and regression of annotated images much easier and with more accuracy. https://hubs.ly/Q02xbkrq0 #ComputerVision #DeepLobe #datalabeling #FutureTech #ImageSegmentation

2

Strawberry project represents a significant leap towards more intelligent and autonomous AI systems, with the potential to revolutionize various sectors through improved problem-solving and planning capabilities

1

Discover how PCA can be used not just for dimensionality reduction, but also for outlier detection in numeric data. Check out Brett Kennedy's article now! #DataAnalytics #DataScience

71

Microsoft researchers developed Orca 2, using a technique that allows small language models to achieve performance nearly on par with larger models by following more cautious reasoning strategies. Read our summary of the paper in #TheBatch: https://hubs.ly/Q02BpKy90

430

4 comentarios

Prompt Obfuscation for Large Language Models https://lnkd.in/efiYH93U #AI #LLM #GenAI #optimization

1

🚀 𝐖𝐡𝐲 𝐃𝐨𝐦𝐚𝐢𝐧 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐎𝐮𝐭𝐬𝐡𝐢𝐧𝐞𝐬 𝐓𝐨𝐨𝐥𝐬 𝐢𝐧 𝐂𝐀𝐄 🚀 In Computer-Aided Engineering (CAE), domain knowledge often proves more powerful than just knowing how to use tools. Here’s why: 🛠️🔍 🌟 𝐃𝐫𝐢𝐯𝐢𝐧𝐠 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: A deep understanding of principles and theories fuels creative problem-solving, allowing for breakthroughs that tools alone can’t achieve. 🎯 𝐄𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬: While tools execute tasks, domain knowledge helps in identifying the right approach and diagnosing complex issues, leading to more robust solutions. 📚 𝐓𝐨𝐨𝐥 𝐕𝐞𝐫𝐬𝐚𝐭𝐢𝐥𝐢𝐭𝐲: Expertise in fundamental concepts applies across different CAE tools, making it easier to adapt and leverage new software effectively. 🔍 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐟𝐮𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Domain knowledge enables critical thinking, helping to interpret and validate results accurately, and refine outputs for better outcomes. 🌐 𝐇𝐨𝐥𝐢𝐬𝐭𝐢𝐜 𝐏𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞: Engineers with strong domain knowledge see how various project elements interconnect, leading to more comprehensive and sustainable engineering solutions. 💡 𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧: While CAE tools are essential, domain knowledge amplifies their effectiveness and drives true engineering excellence. Invest in your expertise to get the most out of any tool! 🚀🔧📚 Visit our website https://lnkd.in/esXrVPU4 for more updates #CAE #engineering #domainknowledge #innovation #problemsolving #criticalthinking #professionaldevelopment #CAD #fesolve

74

1 comentario