Victor Lee

Dr. Jeff Bezanson and Gabriel Baraldi discuss 'New Ways to Compile Julia' in this insightful #webinar. Watch the recording to learn about the 'juliac' compiler driver and trimming techniques for more efficient Julia code deployment. https://lnkd.in/gwSCuUYF #JuliaLang #juliacon #Compilers #TechTalk #Webinar

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If you'll be attending the biggest technical AI conference in San Francisco, stop by our booth and don't miss a workshop by Rick Lamers. Learn what a baseline evaluation looks like & how a tradeoff surface emerges as you decide on implementation details like fine tuning, prompt/encoding choices, streaming, retries, and more. https://hubs.la/Q02zbQCZ0

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Check out the latest blog from our fellow Data Scientist and Data Surgeon Drew Lehe sharing his thoughts on Graph Data Science (GDS). Graph Data Science is a cutting-edge field helping solve many complex data problems. In this particular blog, Drew demonstrates how GDS helped improve the results of an entity resolution issue for an existing Data Surge client. Click the link below to learn more. At Data Surge innovation is a key piece of what we deliver. That innovation includes AI/ML, MLOps, and GenAI. We apply these innovations to support Network Analytics, Entity Resolution as well as Data Governance and Responsible AI. To learn more about Data Surge's services or book a demo of our solution accelerators, visit our website at www.datasurge.com. #AI #ML #GraphDataScience #GenAI #Data #Modernize #Democratize #Transform

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🤓 We're back with the third installment of our knowledge graph series by distinguished engineer Dan Selman! Learn how to combine structured and unstructured semantic queries and to use LLMs (large language models) to orchestrate question answering over a knowledge graph. Happy coding! https://ow.ly/xPtR50SxwOz #AI #LLMs #NLP #RAG

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Great webinar next week showcasing contextual retrieval with technical videos! We are at the very beginning of handling this type of multi-modal complex data, where context is derived from a combination of audio, video, text and image/slides. Super excited to see how multi-modal RAG is evolving

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MLCommons, organizer of the popular MLPerf #benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, which is one of the most pressing needs and greatest hurdles to widespread AI adoption. https://ow.ly/Fq5O50RnEHE #artificialintelligence #AIsafety

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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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"What Unity Catalog and UC Metrics enable is the ability to start to connect with other open-source and closed-source, to a degree, semantic layers. And that's where the relationship with AtScale is so powerful because what you've been solving for is how do you unify the semantic layer." – Dael Williamson, EMEA CTO at Databricks 📊 Join AtScale’s CTO David P. Mariani and Databricks’ Dael Williamson in our latest podcast as they explore the power of open-source standards, interoperability, and the future of democratized data access. From AI-driven analytics to the freedom of open-source, this episode dives into how we’re breaking down barriers in data infrastructure! 🎧 Don’t miss it! Listen here 👉 https://lnkd.in/dRX8ZMPH #Podcast #DataDriven #AtScale #Databricks  #OpenSource #Analytics #SemanticLayer #DataScience #Interoperability

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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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Check out Michael Coté's interview.

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Get a behind-the-scenes view into Rev's 12-year journey developing groundbreaking ASR technology from our VP of AI, Miguel Jetté! Discover how our focus on data accumulation, AI research, and human-in-loop reinforcement learning has shaped our industry-leading ASR model: https://bit.ly/3WLpuVT

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DVA is not associated with this job posting Principal Product Manager, Generative AI North America https://lnkd.in/geirWApx Firefox is used by hundreds of millions worldwide. As the Principal Product Manager for Generative AI Partner Experiences, you will be responsible for integrating intelligent features into the browser to enhance user productivity. This role involves leading the product strategy and execution for these user problems, aiming to create a smarter, more efficient browsing experience. You’ll combine product excellence with strong technical skills to drive this innovation. What you'll do: Product Vision & Strategy: Lead the vision, strategy, and execution for using generative AI to improve user productivity and solve user problems within the browser. Innovative Solutions: Use cutting-edge technologies and design thinking to deliver outstanding solutions at industry-leading scale. We want you to act with urgency as you prove/disprove hypotheses. Cross-Functional Collaboration: Work closely with cross-functional teams to define product requirements, prioritize features, and deliver high-quality products that align with user needs and business goals. Design & Engineering Partnership: Collaborate with design and engineering teams to create well-designed, user-centric products that exceed business goals. Business Development: Partner with business development teams to drive adoption of new features, champion partnerships, and develop new business opportunities that drive revenue growth. Data-Driven Decisions: Track and analyze key product metrics to inform decisions and drive continuous improvement. Effective Communication: Clearly articulate product plans, benefits, and outcomes to a wide range of audiences, including internal partners, leadership, employees, and customers. Industry Awareness: Stay current with industry trends and emerging technologies to drive innovation and maintain Firefox's leadership position. #employment #jobs #hiring #job #jobsearch #recruitment #career #work #careers #recruiting #nowhiring #resume #jobhunt #business #jobseekers #hr #jobopening #staffing #humanresources #jobseeker #hiringnow #interview #recruiter #jobsearching #vacancy #covid #education #jobinterview #jobopportunity #employmentopportunities

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How to fine-tune #LLMs on custom #datasets at Scale using Qwak and #CometML Alexandru Razvant https://lnkd.in/gP4aWM69

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New blog post! We explore one method for customizing LLMs — Continued Pre-Training (CPT) — and provide guidance on executing this process effectively: https://lnkd.in/gVD2fAHP Continued Pre-Training refers to a cost-effective alternative to pre-training large language models (LLMs) from scratch. While LLMs are increasingly adept at solving general tasks, they can often fall short on specific domains that are dissimilar to the data they were trained on. In such cases, how do you effectively and efficiently adapt an open-source LLM to your needs? With CPT, Mansheej Paul, Brett Larsen, Connor Jennings, and Cody Blakeney demonstrate how to enhance a small LLM’s factual knowledge performance to match that of a much larger LLM by augmenting the small model’s general knowledge with specialized information. Check out the post for details!

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Radiant Update: Our product team has been heads down over the past few weeks building out new capabilities to detect and report anomalies in Generative AI model interactions in production systems. Explorer is designed to help users identify anomalies in real time. Radiant turns LLM interactions into structured data and applies more than a dozen metrics out of the box and allows for integrations for 3rd party evaluators. We will continue to invest in tools to ensure quality and reliability for models in production use cases. #LLMs #GenerativeAI #MLOps

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IT/OT convergence is an established practice, but adding #engineering technology means all your operations groups are working together. Learn more from Stan DeVries in his recent blog ➡️https://bit.ly/3zZuXiq

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