Show HN: Fast,Compiled deep-learning based modules for inferencing on CPUs https://ift.tt/rsK1XGS

Show HN: Fast,Compiled deep-learning based modules for inferencing on CPUs Hi HN,I am Anubhav from RamanLabs.We have been developing dedicated modules based on deep-learning for purposes like face-detection,object-detection,pose-estimation etc. We hope to make it easy for developers,hobbyists to integrate such functionalities into their existing app/pipeline at the cost of a few milliseconds.All our modules run end to end in super-realtime even on consumer-grade CPUs[0]. For now we provide only Python based API. We provide Demo for each of the modules to allow testing for your desired data distribution.We also have a blog[1] where we hope to add more technical details about the framework used to develop these modules. The framework used to develop these modules is completely written in Nim language.We wrap existing ops implementations from libraries like ONEDNN and write our own code where we cannot find one or existing implementation is not good enough,mainly for preprocessing and postprocessing code.Having full access to framework code and being written in a high level language allows us to port newer architectures and optimize them quickly. We would love to hear your feedback on our attempt. [0] Quad-core Cpu with AVX2 instructions. [1] < https://ramanlabs.in/static/blog/index.html > https://ift.tt/NutIY4B April 14, 2022 at 11:38PM

देश की पहली वुमन ई-मैगजीन-'My मधुरिमा' में पढ़िए:सिंगल वुमन के लिए अलग से कोई कानून नहीं, महिलाएं और बूस्टर डोज

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योगी सरकार 2.0 में भी मुख्तार की संपत्ति पर वार:2 साल में 9 बार चला बाहुबली की संपत्तियों पर प्रशासन का हंटर, ढोल बजाकर सील करवाई मां राबिया की जमीन

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Show HN: HeftySearch – Search any number of sites at the same time https://ift.tt/IAWGbNR

Show HN: HeftySearch – Search any number of sites at the same time https://ift.tt/mZceqA4 April 14, 2022 at 02:56AM

कालका-शिमला ट्रैक पर आज से दौड़ेंगी समर स्पेशल ट्रेन:पर्यटकों के लिए शिमला पहुंचना होगा आसान, टॉय ट्रेन की टाइमिंग जानने के लिए पढ़े खबर

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Show HN: I built a tool to resize/crop/frame images uniformly for documentation https://ift.tt/r6QbhYG

Show HN: I built a tool to resize/crop/frame images uniformly for documentation https://ift.tt/HdGDmnU April 14, 2022 at 02:08AM

पाकिस्तान गए सिख की हार्ट अटैक से मौत:12 अप्रैल को SGPC की तरफ से भेजे गए जत्थे के साथ पंजा साहिब पहुंचे थे निशाबर

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Show HN: OSS Database, A crowdsourced database of Open Source alternatives https://ift.tt/BFjADU6

Show HN: OSS Database, A crowdsourced database of Open Source alternatives https://ift.tt/E5dmF4e April 13, 2022 at 10:15PM

देवघर के जांबाजों से पीएम मोदी ने की बात:बोले- आपके काम की आज पूरा देश सराहना कर रहा है, ये अनुभव बहुत काम आएगा

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Show HN: Enhanced GNU Awk https://ift.tt/8clEUHW

Show HN: Enhanced GNU Awk https://ift.tt/gteZ0xf April 13, 2022 at 07:03AM

आज का इतिहास:जलियांवाला बाग में अंग्रेजों ने निहत्थे भारतीयों पर चलवाई थीं गोलियां, 21 साल बाद उधम सिंह ने लिया बदला

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Show HN: A Simple Memory Game https://ift.tt/Vw74toU

Show HN: A Simple Memory Game https://ift.tt/iV98Jd2 April 13, 2022 at 05:08AM

ठियोग के विपिन को मिला 1.11करोड़ का पैकेज:अमेजन ने इंटरव्यू पास करने के बाद ऑफर की नौकरी, आयरलैंड में देनी है जॉइनिंग

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Show HN: Razer x Lambda Tensorbook https://ift.tt/qi5967n

Show HN: Razer x Lambda Tensorbook Hi all, long time lurker, first time poster. I want to share with you all something we've been working on for a while at Lambda: the Razer x Lambda Tensorbook: https://www.youtube.com/watch?v=wMh6Dhq7P_Q But before I tell you about it, I want to make this all about me, because I built this for me. See, while I'm genuinely interested in hearing from the community what you think as this is the culmination of a lot of effort from a lot of people across so many different fields (seriously, the number of folks across manufacturing, engineering, design, logistics, and marketing who have had to work together to launch this is nuts), I really just want to tie Tensorbook's motivations back to a larger personal narrative to explain why I'm so proud. So, flashback to 2018, and I'm a hardware engineer focusing on the compute system at Lyft's autonomous vehicle (AV) program, Level5 (L5). Here was a project that that would save lives, that would improve the human condition, that was all ready to go. I saw my role as coming in to product-ize, to take what was close to the finish line and get it over it. The disappointment was pretty brutal when I realized just how wrong I was. It's one thing to nod along when reading Knuth write "premature optimization is the root of all evil"; it's another to experience it firsthand. At Lyft L5 I thought I would be applying specialized inference accelerators (Habana, Groq, Graphcore, etc.) into the vehicle compute system. Instead, the only requirement that mattered org-wide was: "Don't do anything that slows down the perception team". Forget testing silicon with the potential to reduce power requirements by 10x, I was lucky to get a willing ear to hear my case for changing a flag in the TensorFlow runtime to perform inference at FP16 instead of FP32. Don't get me wrong, there were a multitude of other difficult technical challenges to solve outside of the deep learning ones that were gating, but I had underestimated just how not-ready the CNNs for object detection and classification were. Something I thought was a solved problem was very much not, and ultimately resulted in my team and others building a 5,000 watt monster of server (+ power distribution, + thermals, + chassis, etc etc) that took up an entire rear row of seating. I'm happy to talk about that experience in the comments because I have a lot of fond memories from my time there. Anyway, the takeaway I have from Lyft, and my first motivation here is that there is no such thing as over-provisioning or too much compute in a deep learning engineer's mind. Anything less than the most possible is a detriment to their workflow. I still truly believe AVs will save lives; so by extension, enabling deep learning engineers enables AVs enables improvement to the human condition. Transitive property, :thumbsup: So moving on, my following role in industry was characterized by working closely with the least technical people I have ever had the opportunity to work with in my life. And I mean opportunity genuinely, because doing so gave me so much perspective on the things that you and I here probably take for granted. (How do we know that Ctrl+Alt+T will open a terminal? Why does `touch` make a file? How do I quit vim?) So, the takeaway from that experience, and motivation #2 for me is that computers can be so unaccessible in surprising ways. I have a deep respect and appreciation for Linux, and I want others to see things the same way, so anything I can do to make easier the process of "self-serving" or "bootstrapping" to my level of understanding, is something worth doing to me. So, with those two personal motivations outlined, I present to you, for your consideration, the Razer x Lambda Tensorbook. A laptop with a no-compromise approach to speeds-and-feeds and shipping with OEM support for Ubuntu. sincerely, Vinay. Product Marketing @ Lambda April 13, 2022 at 12:12AM

राज ठाकरे का अल्टीमेटम:कहा- ईद तक मस्जिदों से लाउडस्पीकर उतारो, वरना हम बजाएंगे हनुमान चालीसा; हमें अपने बाण खींचने पर मजबूर मत करो

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PoK की गैंगरेप पीड़िता ने मोदी से मांगी मदद:7 साल से इंसाफ मांग रही है, अब बच्चों की जान बचाने भारत आना चाहती है

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नदिया रेप केस में TMC नेता का बेटा गिरफ्तार:ममता ने परिवार के दावे पर उठाए सवाल; पूछा- आपको कैसे पता उसके साथ रेप हुआ

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पैंगोंग झील में SUV चलाने पर भड़के लोग:युवकों ने झील में दौड़ाई गाड़ी, टेबल पर दिखी शराब की बोतलें, लोग बोले- इन पर एक्शन हो

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मॉर्निंग न्यूज ब्रीफ:देवघर के रोप-वे में फंसे 14 लोगों को बचाने की चुनौती;​​​​​​​ 'कश्मीर को अपना बनाकर रहेंगे' कहने वाले शहबाज बने पाकिस्तान के PM

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आज का इतिहास:61 साल पहले अंतरिक्ष में पड़ा था इंसान का पहला कदम, बढ़ई के बेटे यूरी गागरिन बने थे पहले अंतरिक्ष यात्री

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