Bill Wisotsky

Join Carnegie Mellon University's Philip Koopman on Sept 11, 10 AM EDT, for insights on leveraging #AI effectively. Learn about: • Classification & generative outputs • Addressing bias & safety • The 90/10 principle • Real-world Machine Learning applications Understand AI's potential and limitations. Register now! https://lnkd.in/gvhVk33y #MachineLearning #TechInnovation #BOSS2024 #ArtificialIntelligence #DeepLearning #Semiconductor #ML

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Are you interested in vector search, indexing, or database efficiency? Then you won't want to miss this talk by Etienne Dilocker from Weaviate at Carnegie Mellon University's Database Group with Andy Pavlo! Etienne breaks down key challenges and innovations that are powering the future of search: ✨ Bit-Sliced Indexing - tackling complex range queries like price filters with innovative indexing. ✨ BM25 Hybrid Search - combining keyword and vector search to handle nuanced queries. ✨ Graph-Based Indexing (HNSW) - optimizing for high update rates and recalls without latency drops. ✨ Overcoming the Minority Filter Problem - enhancing search relevance through in-place filtering, based on the ACORN paper. ✨ Weaviate's Roadmap - performance, enterprise readiness, and pioneering "Recommendations as a Service." Check out the full talk for an in-depth look at how Weaviate is setting new standards in search technology: https://lnkd.in/gavAZRrn

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Researchers at CDS have unveiled that transformer language models can solve complex problems without clear intermediate reasoning, challenging existing assumptions about their operation. Led by CDS PhD students Jacob Pfau and William Merrill, and CDS Associate Professor of Linguistics and Data Science Sam Bowman, this study highlights the use of nonsensical filler tokens that achieve perfect accuracy in specific tasks, raising concerns about  interpretability and accountability in LLMs. Explore the full findings: https://lnkd.in/eERzzKsU

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In his latest blog post for GWSC, Sambadi Majumder, PhD shares how he built a user friendly graphical user interface (GUI) for spaciotemporal data visualizations to help the Center's analysis team complete their work more efficiently. https://lnkd.in/eDXXYHUv #water #watersecurity #dataviz #datavisualization #GUI #analysis #dataanalysis #environment #climate

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At #SC24 earlier this month, Bob Sorensen from Hyperion Research delivered a presentation on "Successfully Navigating the Changing Advanced Computing Landscape". We summarize the key points in a new blog post here: https://hubs.ly/Q02-g5qm0

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ReSi Benchmark: A Comprehensive Evaluation Framework for Neural Network Representational Similarity Across Diverse Domains and Architectures Representational similarity measures are essential tools in machine learning, used to compare internal representations of neural networks. These measures help researchers understand learning dynamics, model behaviors, and performance by providing in... https://lnkd.in/eJdPbJBp #AI #ML #Automation

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In the next featured #DigitalDiscovery article, Zou, Wang and Tiwary introduce a Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) framework which automatically learns low-dimensional representations as features (such as reaction coordinates) for enhanced sampling calculations. Read the open access paper for more: https://lnkd.in/d-vPAxA3

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Exciting to see Eric Korman featured in Data Science Spotlight, sharing valuable perspectives on techniques that data scientists can use to ensure reproducibility in data analysis workflows. In a field where reliable and repeatable results are paramount, Eric shares a small bit of knowledge on the methodologies and best practices that empower data teams to deliver consistent, trustworthy insights. Read his response here: https://bit.ly/3NTnghu #DataScience #Reproducibility #DataIntegrity Featured

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📢Remote Sensed and/or Global Datasets for Distributed #HydrologicalModelling: A Review by Muhammad Haris Ali, Ioana Popescu, Andreja Jonoski and Dimitri P. Solomatine https://lnkd.in/e9FEM4a3 #hydrology

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#WTCS24 attendees can explore how algorithms learn through trial and error, a cornerstone of Reinforcement Learning (RL). We will try our luck while raising the stakes, discuss theory and pseudocode, and touch on recent RL advances. #cs4yall Learn more: https://buff.ly/452R2bB

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Learn the basics of nonlinear dimensionality reduction, kernel PCA, and multidimensional scaling by following along Biman Chakraborty's clear, hands-on Python tutorial.

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LongRoPE is making it possible to extend language model context windows, including for the Microsoft Phi-3 family of SLMs, while maintaining performance. Learn about the work, featured at #ICML2024, with podcast guest and Senior Researcher Li Lyna Zhang. https://msft.it/6043lbpeH

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With data becoming bigger and bigger business, the Alliance for Data Science Professionals is leading the way to best industry standards and accreditation 🎖️ Read about the Alliance, as well as its first cohort of accredited Advanced Data Science Professionals, in this blog from its Chair, Ed Rochead. https://ow.ly/Nosc50Sopuh

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"Webaccess to HPC via Open OnDemand" by Erica Bianco, PhD (Computational Scientist / HPCNow! – Do IT Now Alliance) Abstract: Open OnDemand (OOD) is becoming increasingly popular as a user-friendly web interface for accessing High-Performance Computing (HPC) resources and data. With OOD the end-user can access the login nodes from the webpage, access the file explorer, and spin applications to the compute nodes with a simple click. In addition to the OOD default features, we developed the possibility of adding different kinds of applications. For example, documentation or dashboards can be embedded directly into the OOD interface, and CLI application jobs can be submitted via webform, retrieving the output in the file explorer. Finally, we are working on spinning GUI applications from the file explorer. Open OnDemand allows end-users with minimal expertise in scheduling and job submission to load complex applications, move data in and out of the file system, and execute jobs independently even more easily. #HPC #HPCKP #HPCKP24

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