Join us for the Compound AI Systems, Inference-time Compute Meetup @ NeurIPS 2024 Meetup for practitioners and researchers working on and interested in topics related to compound AI systems, inference-time strategies and scaling laws, networks of networks, and agentic systems. The venue has limited space for 250 people max, so please apply below to join. https://lu.ma/q5r8b67t Timing: Dec 12th from 4-6pm local time, at the Fairmont Waterfront Ballroom. Featuring presentations and a panel with leading experts from industry and academia. Schedule 50 min of introduction and an industry-academia panel 15 min of 1-min featured poster lightning talks 45 min of posters and networking Poster link If you have a poster you'd like to bring to the event to feature during the poster/networking session, request via the following link → https://lnkd.in/gvGsGaSb Panelists and organizers include: Matei Zaharia (UC Berkeley, Databricks) Jared Quincy Davis (Foundry, Stanford) Boris Hanin (Princeton, Foundry) Michael Carbin (MIT, Databricks) Yejin Choi (NVIDIA, UW) Chi Wang (Google DeepMind) James Zou (Stanford) Heather Miller (CMU) Lingjiao Chen (Microsoft Research) ... and others Thanks to our event sponsors, Databricks (databricks.com) and Foundry (mlfoundry.com).
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We are thrilled to make AMPLIFY available to customers and researchers via AWS HealthOmics and Amazon SageMaker. Customers can get started quickly with a catalog of protein structure and property prediction models in AWS HealthOmics: https://lnkd.in/g3wM3bYk.
I’m excited to share new ways to run AMPLIFY, Amgen and Mila’s new open-sourced AI protein embedding model, leveraging AWS SageMaker and HealthOmics and accelerated compute such as NVIDIA GPUs. Amgen and Mila - Quebec Artificial Intelligence Institute have democratized the access model for their generative biology model to enable labs worldwide to train and perform inference to drive research breakthroughs. See more in Dan Sheeran (he/him)’s re:Invent 2024 innovation talk on Healthcare & Life Sciences innovation with GenAI, about 18min into the video (https://lnkd.in/g4USK94u). The first way to run AMPLIFY on AWS is via SageMaker: builders can access this repository (https://lnkd.in/gMCVMwKJ) to train and deploy AMPLIFY models - kudos to Shamika Ariyawansa, Ujjwal Ratan, Christopher Langmead, Benjamin Schulz, and Maxim Ivanov. Second, builders can access AMPLIFY on the AWS HealthOmics Drug Discovery Workflows repository (https://lnkd.in/gQuY7NHF): AWS uses the AMPLIFY model to calculate a pseudo-perplexity score for de novo designed antibody sequences. This is an important quality metric that indicates how likely it is that the sequence would appear in nature. Kudos to Brian Loyal; check out the example from his BioFM re:Invent session HLS205 at https://lnkd.in/g3zdPASf. We’re excited to continue partnering with AMPLIFY’s leaders including the Amgen team (Christopher Langmead, Alan Russell, Robert Vernon, Marti Head, Jayanthi Subramani, Scott Skellenger, David Reese, Matthew Foster, DBA Pan Wittinghofer and many more), Mila - Quebec Artificial Intelligence Institute (Quentin Fournier, Almer Van Der Sloot, and Sarath Chandar), and NVIDIA (Gregory Zynda, Youssef Nashed, David Klein, Mat Torgow, Rory Kelleher, Lyndi Wu). AWS users running AMPLIFY can leverage best-in-class accelerated compute such as NVIDIA-powered EC2 instances for either short or long periods. #GenAI #GenerativeBiology #proteinembeddingmodel #GPU #awsreinvent2024 #amgen #mila #aws #nvidia #acceleratedcomputing Kevin Moore Ryan Greene Jason Dean
AWS re:Invent 2024 - Accelerating healthcare & life sciences innovation with generative AI (HLS201)
https://www.youtube.com/
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Here's some great cutting-edge news from the life sciences community - new ways to run the AMPLIFY protein embedding model on AWS SageMaker and HealthOmics while using accelerated compute on NVIDIA GPUs. Full details and a link to a re:Invent video are in Stephanie Louis's post.
I’m excited to share new ways to run AMPLIFY, Amgen and Mila’s new open-sourced AI protein embedding model, leveraging AWS SageMaker and HealthOmics and accelerated compute such as NVIDIA GPUs. Amgen and Mila - Quebec Artificial Intelligence Institute have democratized the access model for their generative biology model to enable labs worldwide to train and perform inference to drive research breakthroughs. See more in Dan Sheeran (he/him)’s re:Invent 2024 innovation talk on Healthcare & Life Sciences innovation with GenAI, about 18min into the video (https://lnkd.in/g4USK94u). The first way to run AMPLIFY on AWS is via SageMaker: builders can access this repository (https://lnkd.in/gMCVMwKJ) to train and deploy AMPLIFY models - kudos to Shamika Ariyawansa, Ujjwal Ratan, Christopher Langmead, Benjamin Schulz, and Maxim Ivanov. Second, builders can access AMPLIFY on the AWS HealthOmics Drug Discovery Workflows repository (https://lnkd.in/gQuY7NHF): AWS uses the AMPLIFY model to calculate a pseudo-perplexity score for de novo designed antibody sequences. This is an important quality metric that indicates how likely it is that the sequence would appear in nature. Kudos to Brian Loyal; check out the example from his BioFM re:Invent session HLS205 at https://lnkd.in/g3zdPASf. We’re excited to continue partnering with AMPLIFY’s leaders including the Amgen team (Christopher Langmead, Alan Russell, Robert Vernon, Marti Head, Jayanthi Subramani, Scott Skellenger, David Reese, Matthew Foster, DBA Pan Wittinghofer and many more), Mila - Quebec Artificial Intelligence Institute (Quentin Fournier, Almer Van Der Sloot, and Sarath Chandar), and NVIDIA (Gregory Zynda, Youssef Nashed, David Klein, Mat Torgow, Rory Kelleher, Lyndi Wu). AWS users running AMPLIFY can leverage best-in-class accelerated compute such as NVIDIA-powered EC2 instances for either short or long periods. #GenAI #GenerativeBiology #proteinembeddingmodel #GPU #awsreinvent2024 #amgen #mila #aws #nvidia #acceleratedcomputing Kevin Moore Ryan Greene Jason Dean
AWS re:Invent 2024 - Accelerating healthcare & life sciences innovation with generative AI (HLS201)
https://www.youtube.com/
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Two great options for running AMPLIFY on AWS!
I’m excited to share new ways to run AMPLIFY, Amgen and Mila’s new open-sourced AI protein embedding model, leveraging AWS SageMaker and HealthOmics and accelerated compute such as NVIDIA GPUs. Amgen and Mila - Quebec Artificial Intelligence Institute have democratized the access model for their generative biology model to enable labs worldwide to train and perform inference to drive research breakthroughs. See more in Dan Sheeran (he/him)’s re:Invent 2024 innovation talk on Healthcare & Life Sciences innovation with GenAI, about 18min into the video (https://lnkd.in/g4USK94u). The first way to run AMPLIFY on AWS is via SageMaker: builders can access this repository (https://lnkd.in/gMCVMwKJ) to train and deploy AMPLIFY models - kudos to Shamika Ariyawansa, Ujjwal Ratan, Christopher Langmead, Benjamin Schulz, and Maxim Ivanov. Second, builders can access AMPLIFY on the AWS HealthOmics Drug Discovery Workflows repository (https://lnkd.in/gQuY7NHF): AWS uses the AMPLIFY model to calculate a pseudo-perplexity score for de novo designed antibody sequences. This is an important quality metric that indicates how likely it is that the sequence would appear in nature. Kudos to Brian Loyal; check out the example from his BioFM re:Invent session HLS205 at https://lnkd.in/g3zdPASf. We’re excited to continue partnering with AMPLIFY’s leaders including the Amgen team (Christopher Langmead, Alan Russell, Robert Vernon, Marti Head, Jayanthi Subramani, Scott Skellenger, David Reese, Matthew Foster, DBA Pan Wittinghofer and many more), Mila - Quebec Artificial Intelligence Institute (Quentin Fournier, Almer Van Der Sloot, and Sarath Chandar), and NVIDIA (Gregory Zynda, Youssef Nashed, David Klein, Mat Torgow, Rory Kelleher, Lyndi Wu). AWS users running AMPLIFY can leverage best-in-class accelerated compute such as NVIDIA-powered EC2 instances for either short or long periods. #GenAI #GenerativeBiology #proteinembeddingmodel #GPU #awsreinvent2024 #amgen #mila #aws #nvidia #acceleratedcomputing Kevin Moore Ryan Greene Jason Dean
AWS re:Invent 2024 - Accelerating healthcare & life sciences innovation with generative AI (HLS201)
https://www.youtube.com/
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We’re living our mission to build incredible products & level-up technologists in real life. Our community members attend Shadows and Workshops live - but our broader community (cough you cough 😉) can enjoy edited versions on YouTube! Give our channel a follow and check out a select list of videos below: 💻 Data Scientist Reacts to Nvidia's Nemotron-70b: Does Nvidia’s Nemotron live up to the hype? 📣 Silicon Society, Shadows, & the Future of Education: Because who doesn’t love hearing Frank Fusco share SiSo’s mission? 🔓 How to think about Open vs. Closed AI Systems: A three-minute primer on AI systems. 😲 Data Scientist Reacts to OpenAI’s GPT4o: An oldie but a goodie - a must watch for all SiSo-ers. YouTube Link: https://lnkd.in/ed-Ehurd
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Register for this webinar and learn how Insight, Lenovo, and NVIDIA are diving deep into the streamlined developer experience offered by NVIDIA #AI Workbench and #NVIDIARTX powered AI Workstations, making AI and machine learning accessible to everyone.
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Patronus AI has a new open-weights, SOTA eval model for hallucinations, probably the most common kind of eval for RAG applications! If you've found LLM-as-a-judge inadequate for your RAG eval, may be worth trying this. Lynx beats prompted frontier models like 4o and sonnet 3.5. It's super encouraging to see: (1) Companies like Patronus pushing open source forward not just on the fancy demos and capabilities side, but also on core pieces of infra like eval. (2) Results like this that demonstrate finetuned open models being practically useful and valuable over large frontier models in the right hands.
Introducing Lynx - the leading hallucination detection model 🚀 - Beats GPT-4o on RAG hallucination tasks - Open source, open weights, open data - Excels in practical domains like medicine and finance We are excited to launch Lynx with Day 1 integration partners: NVIDIA, MongoDB, and Nomic AI. The best is yet to come 🌟 Download Lynx on Hugging Face: https://lnkd.in/ezzWscAb Read the arXiv paper: https://lnkd.in/eznVjrWA Read our blog: https://lnkd.in/eYaP5Zpe Use Lynx with NVIDIA's Nemo Guardrails: https://lnkd.in/eXaUzCZ9 Read about our Nomic AI Atlas integration: https://lnkd.in/ebFwccUx
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SMALL AI MODELS ARE GOOD MODELS Sky-T1 is a foundation model which was trained on a $450 budget. Imagine what you can do if you can build tailored foundation models on a dime. Your large action model for a specific set of tools? Your company specific LLM? Your code generator for the programming language you invented? Your company specific style generator? Yadayadayada Small models are good on the planet. They are democratizing AI. They offer low latency. They offer more privacy (on device). They are the future. Large models are counterintuitive and hinder innovation in the long run. Big tech is running on them. Science and normal businesses are not. Please all support the efforts, especially here in Europe. Joerg Bienert Nicolas Flores-Herr Joachim Koehler https://lnkd.in/d-KEQSKi
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Customer-Obsessed Technologist | Delivering Exceptional Experiences through Cloud Innovation & Strategy | AI, Hybrid Cloud, IOT, Digital Transformation @ CloudSyntrix
NVIDIA’s recent earnings call delivered groundbreaking insights, reinforcing its leadership in the AI and computing space. In our latest post, CloudSyntrix dives deep into the top 5 takeaways, with a special focus on Generative AI and Machine Learning leading the charge. Check out the highlights and see how these advancements are shaping the future of tech! 👇
XTX Markets & University of Texas at Austin
3moi wish I could be there!