By BY KARAN DEEP SINGH from NYT Arts https://ift.tt/On0tSaV
via IFTTT
Thursday, April 6, 2023
New top story on Hacker News: Show HN: StorySeed – AI Facilitated, immersive, creative learning experience
Show HN: StorySeed – AI Facilitated, immersive, creative learning experience
12 by nvln | 0 comments on Hacker News.
Hello HN, Are you looking for a fun and engaging way to spark your creativity or your teen's creativity? Or maybe you're interested in exploring the world of storytelling? Introducing Story Seed - an AI-facilitated learning experience that will take you on an immersive and interactive journey through the art of storytelling with movies, books and tv shows you love. With bite-sized lessons, fun guessing games, and AI facilitation, you'll be inspired to tap into your imagination and bring your stories to life like never before. This learning experience is perfect for pre-teens and teens who are interested in writing, as well as anyone who wants to improve their storytelling skills. It's a great way to spend quality time with your kids, or to explore your own creativity. It is integrated with our new tool for creative writing, Papyr. We are excited about launching them together. When you complete StorySeed, the learning experience, you are given 3 prompts to choose from and you begin writing, in Papyr. Today we are releasing our pilot, Chapter 1: Story DNA. We will be releasing the rest of the chapters during the coming months and adding new content hopefully, forever. It's free but signup is required to track credits. Please check them both out and let us know what you think. Papyr: https://ift.tt/Es07rlF StorySeed: https://seed.kood.app
12 by nvln | 0 comments on Hacker News.
Hello HN, Are you looking for a fun and engaging way to spark your creativity or your teen's creativity? Or maybe you're interested in exploring the world of storytelling? Introducing Story Seed - an AI-facilitated learning experience that will take you on an immersive and interactive journey through the art of storytelling with movies, books and tv shows you love. With bite-sized lessons, fun guessing games, and AI facilitation, you'll be inspired to tap into your imagination and bring your stories to life like never before. This learning experience is perfect for pre-teens and teens who are interested in writing, as well as anyone who wants to improve their storytelling skills. It's a great way to spend quality time with your kids, or to explore your own creativity. It is integrated with our new tool for creative writing, Papyr. We are excited about launching them together. When you complete StorySeed, the learning experience, you are given 3 prompts to choose from and you begin writing, in Papyr. Today we are releasing our pilot, Chapter 1: Story DNA. We will be releasing the rest of the chapters during the coming months and adding new content hopefully, forever. It's free but signup is required to track credits. Please check them both out and let us know what you think. Papyr: https://ift.tt/Es07rlF StorySeed: https://seed.kood.app
New top story on Hacker News: Show HN: Sym, define just-in-time access workflows in code
Show HN: Sym, define just-in-time access workflows in code
21 by abuggia | 2 comments on Hacker News.
Hello HN, My cofounder (jon918) and I started Sym three years ago because we were frustrated with how hard it was to manage access to cloud infrastructure. We wanted to build a tool for JIT access that was actually designed for developers. We were wary of tools that tried to accommodate both devs and IT but ended up with usability compromises for both. First, we figured no one wants another web app to log into so we let administrators define access workflows in Terraform and let developers request and gain access via Slack. That seemed to pay off: being code-based was a big plus for our early customers since it let them manage the logic in version control and test in CI/CD. Second, we knew that updating permissions/roles/access was a major source of toil and risk in the world of cloud infrastructure. Have you ever tried to avoid annoying, persistent access requests by setting policies that are a bit more permissive than you’d like? We felt that fully automated just-in-time access + approvals could really help here. But we also knew that a simple approval tool could end up leading to request fatigue - kind of defeating the purpose. So we built an SDK to let you define checks in code (e.g. pagerduty.on_call, okta.is_user_in_group, github.get_repo_collaborators) in order to dynamically route requests or fast-track access when appropriate. This seems to be paying off: users are creating Slack-based approvals in front of different types of risky actions like production access, sensitive queries and triggering Lambdas. We’d love your feedback on our approach so far. Does this make sense to you? Is this a tool you'd use? What would you want to see out of it? To learn more, check out the video that Nick (nmeans (Sym VPEng)) made [1]. You can also check out our docs [2] or set up your own flow [3]. thanks! -adam [1] https://ift.tt/2ITb7oC [2] https://docs.symops.com [3] https://ift.tt/oheSK9i
21 by abuggia | 2 comments on Hacker News.
Hello HN, My cofounder (jon918) and I started Sym three years ago because we were frustrated with how hard it was to manage access to cloud infrastructure. We wanted to build a tool for JIT access that was actually designed for developers. We were wary of tools that tried to accommodate both devs and IT but ended up with usability compromises for both. First, we figured no one wants another web app to log into so we let administrators define access workflows in Terraform and let developers request and gain access via Slack. That seemed to pay off: being code-based was a big plus for our early customers since it let them manage the logic in version control and test in CI/CD. Second, we knew that updating permissions/roles/access was a major source of toil and risk in the world of cloud infrastructure. Have you ever tried to avoid annoying, persistent access requests by setting policies that are a bit more permissive than you’d like? We felt that fully automated just-in-time access + approvals could really help here. But we also knew that a simple approval tool could end up leading to request fatigue - kind of defeating the purpose. So we built an SDK to let you define checks in code (e.g. pagerduty.on_call, okta.is_user_in_group, github.get_repo_collaborators) in order to dynamically route requests or fast-track access when appropriate. This seems to be paying off: users are creating Slack-based approvals in front of different types of risky actions like production access, sensitive queries and triggering Lambdas. We’d love your feedback on our approach so far. Does this make sense to you? Is this a tool you'd use? What would you want to see out of it? To learn more, check out the video that Nick (nmeans (Sym VPEng)) made [1]. You can also check out our docs [2] or set up your own flow [3]. thanks! -adam [1] https://ift.tt/2ITb7oC [2] https://docs.symops.com [3] https://ift.tt/oheSK9i
Wednesday, April 5, 2023
Dating Advice From Jay Shetty
By BY ANNA MARTIN, JULIA BOTERO, CHRISTINA DJOSSA, HANS BUETOW, SARA SARASOHN, JEN POYANT, MARION LOZANO, DAN POWELL AND ROWAN NIEMISTO from NYT Podcasts https://ift.tt/HSD50Gu
via IFTTT
China’s ambassador to the E.U. tries to distance Beijing from Moscow.
By BY MATINA STEVIS-GRIDNEFF AND STEVEN ERLANGER from NYT World https://www.nytimes.com/live/2023/04/05/world/russia-ukraine-news/chinas-ambassador-to-the-eu-tries-to-distance-beijing-from-moscow?partner=IFTTT
via IFTTT
New top story on Hacker News: Show HN: Want something better than k-means? Try BanditPAM
Show HN: Want something better than k-means? Try BanditPAM
24 by motiwari | 0 comments on Hacker News.
Want something better than k-means? I'm happy to announce our SOTA k-medoids algorithm from NeurIPS 2020, BanditPAM, is now publicly available! `pip install banditpam` or `install.packages("banditpam")` and you're good to go! k-means is one of the most widely-used algorithms to cluster data. However, it has several limitations: a) it requires the use of L2 distance for efficient clustering, which also b) restricts the data you're clustering to be vectors, and c) doesn't require the means to be datapoints in the dataset. Unlike in k-means, the k-medoids problem requires cluster centers to be actual datapoints, which permits greater interpretability of your cluster centers. k-medoids also works better with arbitrary distance metrics, so your clustering can be more robust to outliers if you're using metrics like L1. Despite these advantages, most people don't use k-medoids because prior algorithms were too slow. In our NeurIPS 2020 paper, BanditPAM, we sped up the best known algorithm from O(n^2) to O(nlogn) by using techniques from multi-armed bandits. We were inspired by prior research that demonstrated many algorithms can be sped up by sampling the data intelligently, instead of performing exhaustive computations. We've released our implementation, which is pip- and CRAN-installable. It's written in C++ for speed, but callable from Python and R. It also supports parallelization and intelligent caching at no extra complexity to end users. Its interface also matches the sklearn.cluster.KMeans interface, so minimal changes are necessary to existing code. PyPI: https://ift.tt/A3EVT8u CRAN: https://ift.tt/Ev30UdL Repo: https://ift.tt/7RPdmJG Paper: https://ift.tt/GU7qoPh If you find our work valuable, please consider starring the repo or citing our work. These help us continue development on this project. I'm Mo Tiwari (motiwari.com), a PhD student in Computer Science at Stanford University. A special thanks to my collaborators on this project, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, and Ilan Shomorony, as well as the author of the R package, Balasubramanian Narasimhan. (This is my first time posting on HN; I've read the FAQ before posting, but please let me know if I broke any rules)
24 by motiwari | 0 comments on Hacker News.
Want something better than k-means? I'm happy to announce our SOTA k-medoids algorithm from NeurIPS 2020, BanditPAM, is now publicly available! `pip install banditpam` or `install.packages("banditpam")` and you're good to go! k-means is one of the most widely-used algorithms to cluster data. However, it has several limitations: a) it requires the use of L2 distance for efficient clustering, which also b) restricts the data you're clustering to be vectors, and c) doesn't require the means to be datapoints in the dataset. Unlike in k-means, the k-medoids problem requires cluster centers to be actual datapoints, which permits greater interpretability of your cluster centers. k-medoids also works better with arbitrary distance metrics, so your clustering can be more robust to outliers if you're using metrics like L1. Despite these advantages, most people don't use k-medoids because prior algorithms were too slow. In our NeurIPS 2020 paper, BanditPAM, we sped up the best known algorithm from O(n^2) to O(nlogn) by using techniques from multi-armed bandits. We were inspired by prior research that demonstrated many algorithms can be sped up by sampling the data intelligently, instead of performing exhaustive computations. We've released our implementation, which is pip- and CRAN-installable. It's written in C++ for speed, but callable from Python and R. It also supports parallelization and intelligent caching at no extra complexity to end users. Its interface also matches the sklearn.cluster.KMeans interface, so minimal changes are necessary to existing code. PyPI: https://ift.tt/A3EVT8u CRAN: https://ift.tt/Ev30UdL Repo: https://ift.tt/7RPdmJG Paper: https://ift.tt/GU7qoPh If you find our work valuable, please consider starring the repo or citing our work. These help us continue development on this project. I'm Mo Tiwari (motiwari.com), a PhD student in Computer Science at Stanford University. A special thanks to my collaborators on this project, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, and Ilan Shomorony, as well as the author of the R package, Balasubramanian Narasimhan. (This is my first time posting on HN; I've read the FAQ before posting, but please let me know if I broke any rules)
