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RELU vs SIGMOID 🐱 🏍

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This is just a brief understanding to all excited learners wishing to know more about what we call the activation layer. A concept I took quite a long time to understand throughout my journey into Neural Networks (NN)( A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes.). The whole concept took birth from call feature scaling (is a method used to normalize the range of independent variables or features of data.). A machine learning technique usually used to fight against bias (Bias is a disproportionate weight in favor of or against an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair.). Throughout this technique you will observe that a large-scale feature or feature whose distribution seems to outstand the other features with have an extremely big mean and variance, which tends to affect the computational result where a lot of emphasis is put on.


Top Ways Artificial Intelligence Helps Students for Better Results - The Education Outlook

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New technology and gadgets will be able to record and track speech, visual, and biological data as they grow more complex and sophisticated. Artificial intelligence (AI)will subsequently be able to judge complicated abilities using these technologies. Artificial intelligence (AI) will be able to track eye contact during group talks, for example. What impact does this have on educators? It enables them to assess their students' comprehension and attention.


Writing Better Is Now Easier Than Ever: Edit With Trinka AI - Enago Academy

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We are hosting a series of webinars to demonstrate how Trinka AI will assist authors and researchers in writing academic and technical papers more effectively. Academic writing is nuanced and other currently available tools do not consider these nuances. Trinka is tailor made for academic and formal writing and offers the right assistance for this genre of writing. Trinka's Cloud Editor offers the convenience of real-time writing assistance, with improvements tailored to academic and formal writing. Trinka Cloud makes writing and reviewing easy and fun.


Man arrested after using AI to beat Japan's smut censorship

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In brief A man was detained in Japan for selling uncensored pornographic content that he had, in a way, depixelated using machine-learning tools. Masayuki Nakamoto, 43, was said to have made about 11 million yen ($96,000) from peddling over 10,000 processed porn clips, and was formally accused of selling ten hardcore photos for 2,300 yen ($20). Explicit images of genitalia are forbidden in Japan, and as such its porn is partially pixelated. Don't pretend you don't know what we're talking about. Nakamato flouted these rules by downloading smutty photos and videos, and reportedly used deepfake technology to generate fake private parts in place of the pixelation.


Smart Edge Cam with Gesture Alarm

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Gesture Triggered Alarm for Security based on CV, Vector Concavity Estimation, OpenVINO, MQTT, and Pimoroni Blinkt on RPi or Jetson Nano. Notwithstanding notable advancements in technology, the developing economies are still trapped in the clutches of patriarchal evils like molestation, rape, or crime against women, in general. Women are often not allowed to stay back in their professional workspaces during late hours, nor are considered safe alone even during day time, especially in the developing world. Imperative, it has become, to enable the other half of population to be more safe & productive. Why not use advancements in technology to arm them with more power?


TRB Webinar: Using Artificial Intelligence to Predict Deterioration of Highway Bridges

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Often, advanced sensor technologies can assess highway bridge infrastructure. TRB will host a webinar on Monday, February 22, 2021 from 2:00-3:30 PM Eastern to explore how artificial intelligence (AI) and deep learning (DL) may be used to predict the deterioration of bridges. Presenters will discuss recent case studies related to the application of AI in integrating highway data to better explain and predict system performance. They will also identify how AI and DL may improve sensor signal data, and explain how these technologies can provide support design, operations, and management of highway systems. This webinar was organized by the TRB Standing Committee on Testing and Evaluation of Transportation Structures.


Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training

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The remarkable development of deep learning over the past decade relies heavily on sophisticated heuristics and tricks. To better exploit its potential in the coming decade, perhaps a rigorous framework for reasoning about deep learning is needed, which, however, is not easy to build due to the intricate details of neural networks. For near-term purposes, a practical alternative is to develop a mathematically tractable surrogate model, yet maintaining many characteristics of neural networks. This paper proposes a model of this kind that we term the Layer-Peeled Model. The effectiveness of this model is evidenced by, among others, its ability to reproduce a known empirical pattern and to predict a hitherto-unknown phenomenon when training deep-learning models on imbalanced datasets. All study data are included in the article and/or supporting information. Our code is publicly available at GitHub ().


BrainChip Begins Taking Orders of Akida AI Processor Development Kits

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WIRE)--BrainChip Holdings Ltd (ASX: BRN), (OTCQX: BRCHF), a leading provider of ultra-low power high performance artificial intelligence technology, today announced BrainChip will be taking orders of two development kits for its Akida advanced neural networking processor, enabling partners, large enterprises, and OEMs to begin internal testing and validation of Akida's high-performance, small, ultra-low power AI chip. Akida NSoC and intellectual property enable a wide array of edge AI capabilities that include continuous learning and inference. BrainChip is offering two development kits, both including the AKD1000 chip on a mini-PCI board: an X86 Shuttle PC development kit, as well as an ARM-based Raspberry Pi development kit. "Offering development kits is not only a major step towards full commercialization, it's also an exciting opportunity to see how our partners and future customers will put Akida to work in environments and scenarios like consumer electronics, industrial applications, aerospace and defense systems, healthcare and medical devices, automotive technology, and more," said Anil Mankar, BrainChip co-founder and chief development officer. "We believe the AKD1000 silicon, or the licensing of Akida in a configurable IP format, will lead to major changes in industries using AI at the edge because of its performance, security, low power requirements, and mainly Akida's ability to perform AI training and learning on the device itself, without dependency on the cloud."


La veille de la cybersécurité

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Artificial intelligence (AI) is easily one of the most anticipated upcoming technologies. Understanding the impact that a piece of technology will have on your business will not only allow you to prepare for any adverse impacts, but it will also allow you to adapt your business to assimilate the technology to optimize your business. Despite being one of the older industries, the real estate sector is one that has been gradually adapting to emerging technologies. While it may seem like artificial intelligence is still a long way from being implemented into the industry, it has been used in the real estate industry since 2018. The first AI transaction took place in Philadelphia, where two buildings were purchased for a sum of $26 million based on a "soon to market" algorithm.


Starbucks customer segmentation

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Once every few days, Starbucks sends out an offer to users of the mobile app. An offer can be merely an advertisement for a drink or an actual offer such as a discount or BOGO (buy one get one free). Some users might not receive any offer during certain weeks. And also, not all users receive the same offer, and that is the challenge to solve with this data set. The data set contains simulated data that mimics customer behavior on the Starbucks rewards mobile app.