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Here's How AI Helps Modern Healthcare


The term AI means a lot of things to many people. Unfortunately, most of them are bad. Pop culture has almost always portrayed AI as something bad, something that will spell the end of humanity if it's not kept in check. But there is one good thing about it that people might not be too aware of: its potential in modernizing healthcare. And the world has seen what artificial intelligence can really do in the medical field, with experts believing that artificial intelligence in healthcare will grow at an almost 50% rate between 2017 and 2023, according to Business Insider.



The graph represents a network of 1,251 Twitter users whose tweets in the requested range contained "#iiot", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 14 September 2021 at 21:00 UTC. The requested start date was Tuesday, 14 September 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 1-day, 16-hour, 41-minute period from Sunday, 12 September 2021 at 07:20 UTC to Tuesday, 14 September 2021 at 00:01 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

EETimes - AI Startup Deep Vision Raises Funds, Preps Next Chip


Edge AI chip startup Deep Vision has raised $35 million in a series B round of funding led by Tiger Global, joined by existing investors Exfinity Venture Partners, Silicon Motion and Western Digital. The company began shipping its first-generation chip last year. ARA-1 is designed for power-efficient, low-latency edge AI processing in applications like smart retail, smart city and robotics. While the company's name suggests a focus on convolutional neural networks, ARA-1 can also accelerate natural language processing with support for complex networks such as long short-term memory (LSTMs) and recurrent neural networks (RNNs). A second-generation chip, ARA-2 with additional features for accelerating LSTMs and RNNs will launch next year.

DCGAN from Scratch with Tensorflow Keras -- Create Fake Images from CELEB-A Dataset


Generator: the generator generates new data instances that are "similar" to the training data, in our case celebA images. Generator takes random latent vector and outputs a "fake" image of the same size as our reshaped celebA image. Discriminator: the discriminator evaluate the authenticity of provided images; it classifies the images from the generator and the original image. Discriminator takes true of fake images and outputs the probability estimate ranging between 0 and 1. Here, D refers to the discriminator network, while G obviously refers to the generator.

Deep Learning for NLP - Part 9 - CouponED


Deep Learning for NLP - Part 9 Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modeling how people share information. Description Since the proliferation of social media usage, hate speech has become a major crisis. On the one hand, hateful content creates an unsafe environment for certain members of our society. On the other hand, in-person moderation of hate speech causes distress to content moderators. Additionally, it is not just the presence of hate speech in isolation but its ability to dissipate quickly, where early detection and intervention can be most effective.

Various Machine learning methods in predicting rainfall - Tutors India Blog


The term machine learning (ML) stands for "making it easier for machines," i.e., reviewing data without having to programme them explicitly. The major aspect of the machine learning process is performance evaluation. Four commonly used machine learning algorithms (BK1) are Supervised, semi-supervised, unsupervised and reinforcement learning methods. The variation between supervised and unsupervised learning is that supervised learning already has the expert knowledge to developed the input/output [2]. On the other hand, unsupervised learning takes only the input and uses it for data distribution or learn the hidden structure to produce the output as a cluster or feature [3].

Top deep learning algorithm to know in 2021 -


What is deep learning algorithm? It is a crucial and advanced technology of the modern times. The technology happens to form an excellent and integral part of the machine learning system. If the industry buzz is to be taken into consideration, this kind of a learning mode provides you a great experience, which you would choose to treasure for sure. Deep learning algorithm is doing the rounds these days.

Republicans may abandon infrastructure bill because Pelosi 'linked' it with reconciliation: GOP Rep. Johnson

FOX News

Fox News Flash top headlines are here. Check out what's clicking on As Democrats charge ahead with writing their massive $3.5 trillion spending bill, which they aim to pass on a party-line vote through budget reconciliation, at least one moderate Republican is warning the bipartisan infrastructure bill may lose GOP votes because it's too intertwined with the reconciliation bill. "I think Nancy Pelosi did this whole process a real disservice by linking them together so strongly and she continues to do that. And that makes it very difficult to bring Republicans to the party," Dusty Johnson, R-S.D., a member of the Problem Solvers Caucus (PSC), told Fox News Wednesday.

How Companies Are Using Artificial Intelligence? - AWPLife Blog


Take a look at how AI companies are implementing AI. By automating procedures and operations that formerly required human intervention, Artificial Intelligence (AI) is increasing company efficiency and production. AI is also capable of comprehending data at a level that no human has ever achieved. This skill has the potential to be extremely useful in the workplace. AI has the potential to enhance every function, business, and industry. Thinking in Algorithms: How to Combine Computer Analysis and Human Creativity for Better Problem-Solving and Decision-Making (Strategic Thinking Skills Book 2) eBook : Rutherford, Albert: Kindle Store


We often have blind spots for the reasons that cause problems in our lives. We try to fix our issues based on assumptions, false analysis, and mistaken deductions. These create misunderstanding, anxiety, and frustration in our personal and work relationships. Resist jumping to conclusions prematurely. Evaluate information correctly and consistently to make better decisions.