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According to statistics, breast cancer is among the most common and second leading cause of deaths among females. Amid this when Google’s research came forward which said that artificial intelligence can read mammograms better than radiologists, it was a sigh of relief for most. Recently, DeepMind and Google Health have developed a new AI system that can detect breast cancer at an early stage. The researchers trained an algorithm on mammogram images from female patients in the US and UK. They trained it to perform better than human radiologists and hence the result has arrived. According to theSignificance
In the United Kingdom, there is a shortage of skilled radiologists and this AI system can assist doctors and specialists when reading mammograms. This move will subsequently improve the overall accuracy of mammography reading and reduce the radiologists’ workload. The real value-added potential from using AI for mammography is “immediate feedback in the screening setting”, claims study author. Providing the result immediately will enhance the standard of care. Also with AI, all mammograms could become “diagnostic” while releasing the results of mammograms on patients’ schedules. As the AI system is efficient enough in the reading film as an accompaniment to radiologists, it could give more time to experts to actually discuss to patients in person about their results. AI systems can be used to streamline the process of a breast cancer diagnosis. It can also help reduce the wait time for a biopsy.Similarity with NYU’s Research
Moreover, last October, NYU researchers published a similar study which demonstrates that the AI system can screen breast cancer similar to the skills of human radiologists. However, the difference between both the studies is that NYU only used mammograms from US patients, and it compared the system’s performance with human expert diagnoses conducted in an artificial lab environment whereas Google and DeepMind compared performance with real-world diagnoses, notes MIT Technology Review. Eventually, both the studies present the same conclusion that AI breast cancer screenings should be used in tandem with human radiologists and the combination of humans and AI can achieve the most accurate diagnostic results and reduce the workload on human radiologists. This could help free up their time to focus more on patient care.Expert’s Opinion
Dr. Mozziyar Etemadi, a research assistant professor of anesthesiology and biomedical engineering at Northwestern University and one of the paper’s co-authors says, “health care is being squeezed with the number of patients increased and the amount of time that doctors have to see patients decreasing. So tools like these are what every physician is hoping for. We just have to better understand when tools like AI help and when it doesn’t and ultimately come up with the combination of technology and human contributions what will ultimately improve care and make it more efficient.”
According to statistics, breast cancer is among the most common and second leading cause of deaths among females. Amid this when Google’s research came forward which said that artificial intelligence can read mammograms better than radiologists, it was a sigh of relief for most. Recently, DeepMind and Google Health have developed a new AI system that can detect breast cancer at an early stage. The researchers trained an algorithm on mammogram images from female patients in the US and UK. They trained it to perform better than human radiologists and hence the result has arrived. According to the MIT Technology Review , “In tests, the AI system decreased both types of error. For US patients, it reduced false negatives and positives by 9.4% and 5.7%, respectively; for UK patients it reduced them by 2.7% and 1.2%. In a separate experiment, the researchers tested the system’s ability to generalize: they trained the model using only mammograms from UK patients, and then evaluated its performance on US patients. The system still outperformed human radiologists, reducing false negatives and positives by 8.1% and 3.5%.”In the United Kingdom, there is a shortage of skilled radiologists and this AI system can assist doctors and specialists when reading mammograms. This move will subsequently improve the overall accuracy of mammography reading and reduce the radiologists’ workload. The real value-added potential from using AI for mammography is “immediate feedback in the screening setting”, claims study author. Providing the result immediately will enhance the standard of care. Also with AI, all mammograms could become “diagnostic” while releasing the results of mammograms on patients’ schedules. As the AI system is efficient enough in the reading film as an accompaniment to radiologists, it could give more time to experts to actually discuss to patients in person about their results. AI systems can be used to streamline the process of a breast cancer diagnosis. It can also help reduce the wait time for a biopsy.Moreover, last October, NYU researchers published a similar study which demonstrates that the AI system can screen breast cancer similar to the skills of human radiologists. However, the difference between both the studies is that NYU only used mammograms from US patients, and it compared the system’s performance with human expert diagnoses conducted in an artificial lab environment whereas Google and DeepMind compared performance with real-world diagnoses, notes MIT Technology Review. Eventually, both the studies present the same conclusion that AI breast cancer screenings should be used in tandem with human radiologists and the combination of humans and AI can achieve the most accurate diagnostic results and reduce the workload on human radiologists. This could help free up their time to focus more on patient chúng tôi Mozziyar Etemadi, a research assistant professor of anesthesiology and biomedical engineering at Northwestern University and one of the paper’s co-authors says, “health care is being squeezed with the number of patients increased and the amount of time that doctors have to see patients decreasing. So tools like these are what every physician is hoping for. We just have to better understand when tools like AI help and when it doesn’t and ultimately come up with the combination of technology and human contributions what will ultimately improve care and make it more efficient.”
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The health benefits of resveratrol, a compound found in the skin of grapes (and thus in red wine), have long been known. Studies have indicated that it serves as an antioxidant, that it has anti-tumor properties, that it can help you live longer, and that it may be responsible for the “French paradox” (the French have a high-fat diet and yet low instances of health disease). A new study examined resveratrol’s effects on melanoma, and found that it has anti-cancer properties. Cool! But, well, ignore.
So, definitely a lack of research here. There’s also the problem of exactly how resveratrol is introduced to the body. Without clinical trials, we can’t really say whether resveratrol as it’s present in red wine would be metabolized in any kind of beneficial way. Let’s take a look at another possible cancer-fighter for an example: mushrooms. Mushrooms, including common varieties like shiitake and maitake, contain lentinan, a substance that inhibits tumor growth and has been linked to fighting cancer. Except, to get the dose of lentinan you need, don’t bother eating a bunch of shiitakes. You have to inject it intravenously on a weekly basis, in quantities far greater than are present in any conquerable pile of mushrooms. Youch. So resveratrol in wine might not actually have the same effect as resveratrol supplements.
Red Wine Bottles
But the biggest problem, by far, with the idea that red wine will help you fight cancer is that no human alive is hardcore enough to get the benefits of resveratrol from drinking wine. To get the amount of resveratrol from wine to equal the amount given to the animals in these studies, you’d be dead from alcohol poisoning a few times over. Red wine has about 160 µg of resveratrol per ounce. Assuming each glass of wine has about five ounces, that’s 800 µg per glass, or 0.0008 grams. (That’s a pretty big glass, by the way.) The amount of resveratrol used in these studies ranges from two to five grams. So if we’re being conservative and assuming you only need two grams of resveratrol, and you’re having a pretty big glass of wine, that means you’d need 2,500 glasses of wine to get the dose used in these trials. That’s 492.9 bottles of wine.
Of course, you can buy resveratrol supplements from most health supplement stores or online. But resveratrol supplements, which are completely unregulated by the FDA and unproven in any clinical trials with humans, usually have between 200 and 500 mg of resveratrol–up to 25 times less than is used in these studies. There’s no indication that these relatively small doses of resveratrol will have the wonderful effects you might be expecting.
That’s not to say that these resveratrol studies aren’t interesting and important, of course. Very possibly this research will end up being important sometime down the road. But studies supposedly proving the magical properties of red wine are sexy and fun, much like red wine itself, which brings them an awful lot of visibility. Resveratrol is promising, but if you’ve been guzzling wine for its medical benefits, you might be getting drunk for no good reason.
Ways To Detect And Prevent High-Risk Software Vulnerabilities
So, today, in this article we will be talking about types of the software vulnerabilities and ways to detect and prevent them.Types Of Software Vulnerabilities:
Let us know about types of software vulnerabilities and how can they be used by attackers:
2. XSS or cross site scripting: Well, this is basically for web-based applications. As some of them might already have malicious code injected, so it opens the door for an attacker to bypass controls and take control of the system in an easy way.
3. SQL injection: Here, the injection of code is deployed to exploit the content of database directly. This happens usually when the inputs are not managed in a right way.How To Detect & Prevent Software Vulnerabilities?
For detection of software vulnerabilities there are two methods, which are: Dynamic and Static. Both techniques contain various methods for detection of vulnerabilities; let us take a look at them:1. Static Techniques
These are the ones that are implemented directly to program code without even running it. The basic purpose of this is to find loophole in source code before executing. There are several methods for detecting the vulnerability statically, which are:
A. Pattern Matching – Used for searching a ‘pattern’ in particular string of source code.
B. Lexical Analysis – It is an add-on step before pattern matching, where source code is converted into sequence of tokens.
C. Parsing – When code is being parsed, a parsing tree is formed to evaluate the syntax and semantics of code.
D. Type Qualifier – Used for modifying types & properties of variables in programming language.
E. Data Flow Analysis – To determine values an expression or variable can have during execution.2. Dynamic Techniques
The dynamic techniques are used to detect vulnerabilities after execution of the program code. Here are some of the dynamic methods used to detect software vulnerabilities:
A. Fault Injection – It’s a testing technique to find security flaws in system. In this work faults are deployed in system to observe the system behavior.
B. Fuzzing Testing – In this a random code or data is given as input to the application to observe if it can handle it correctly. This is also used to get better coverage of system.
C. Dynamic Taint – It allows discovery of possible input validation problems which are reported as vulnerabilities.
For prevention, there are several ways to prevent software vulnerabilities. But, the most common methods are by understanding vulnerabilities by using models and theories to find any defects or error and correct them at the early stage of development.
Basically, it is called software inspection, a process for reading and inspecting the code by an expertise. One should always follow and develop software according Software development lifecycle (SDLC), so that there would be no loopholes and vulnerabilities in software.
Also Read : Protect Yourself Against Online Shopping AttacksQuick Reaction:
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Last Updated on June 6, 2023
You may have asked yourself the question: can Copy AI write a book? AI writing assistants are particularly great in the sense that they allow you to write and edit texts more efficiently. These tools have become so popular in recent years that many people now use them for all kinds of purposes such as generating ideas, writing blogs, correcting grammatical errors, and more.But Can Copy AI Write a Book?
There’s one question many people usually ask, can Copy AI write a book? The truth is that not all AI writing tools can be used for book writing, but some are specially designed for that purpose. One AI tool that can generate all kinds of high-quality content is Copy AI.
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*Prices are subject to change. PC Guide is reader-supported. When you buy through links on our site, we may earn an affiliate commission. Learn moreWhat is Copy AI?
Copy AI is a content writing software that uses machine learning and Open AI’s GPT-3 natural language processing model to produce very human texts from only a couple of keywords. It enables writers to overcome writer’s block and get their creativity flowing. This makes it the ideal tool for anyone looking to produce large amounts of content within a short time and streamline their writing process.What Makes Copy AI Different?
Copy AI comes with a very unique set of features that differentiate it from other types of content-writing software.Supports Multiple Languages
Copy AI is a multi-language writing tool that allows you to generate content in your native language. The tool currently supports over 25 languages, such as English, Spanish, French, Chinese, and more. This allows you to easily generate writing for a global audience.Over 90 Templates to Choose From
Copy AI has a variety of templates that you can use to generate content. These templates are organized into several categories and are mostly tailored toward commercial content creation like SEO-optimized articles, long-form content, blog posts, HR, marketing, and sales.
However, the Freestyle tool allows you to input any type of prompt to create any form of text. This mode really lends itself to creative writing and fiction writing as you can generate the outline of a plot at the touch of a button. Just choose a topic and a writing style, and Copy AI will do the rest!Unique Results
Unlike some artificial intelligence-powered writing tools, Copy AI only generates unique copy results. Each variation produced by the algorithm is different and individualized.Plagiarism Checker
One of the many unique features of Copy AI is its inbuilt plagiarism checker with which you can easily check your work for plagiarism. This ensures your work is entirely original, perfect for creating a first draft in the knowledge that all the ideas that it generates are fresh. However, using this feature does require a premium subscription.FAQs Can Copy AI Write Faster Than Humans?
Yes, it is widely accepted that an AI writing tool can generate content roughly 10x faster than humans.
One of the ongoing challenges with AI generated art has been its inability to draw hands correctly. They are often deformed or have way too many fingers which really would detract from the artwork. Unless you were going for deformed hands then you are in heaven.
Finally there has been a breakthrough in this space where a AI Model checkpoint Protogen x3.4 Official Release (ProtoGen_X3.4) is available for Stable Diffusion that can draw hands correctly. This is an amalgamation of multiple checkpoint, being merged into one. It comprises of 5% of roboDiffusion_v1.ckpt, openjourney-v2-unpruned.ckpt, chúng tôi and rpg_v2Beta.ckpt.
ProtoGen_X3.4 can produce natural looking hands that are suited to the composition of the image and is able to keep the length of figures correct including the number of figures. The samples and test images submitted on the discussion page already demonstrate the correctly formed hands.
As suggested on their page it is recommended to remove “ugly” from the negative prompt when creating images. Seriously, removing off (ugly) on negative prompts brings out some really detailed shots of what real life consist of, decay, rubble, grass, worned clothing…Have fun and keep it fluffy!
Below are sample images referenced from the ProtoGen_X3.4 release page.
If you are convinced then you can head over to the Protogen x3.4 Official Release page to download this CKPT file (5.57GB) or download from Huggingface. If you are using a Paperspace notebook you can upload it to your machine within a few seconds by using this technique I referenced in another post, how to quickly upload model CKPT to Paperspace.
Prompt: modelshoot style, (extremely detailed CG unity 8k wallpaper), full shot body photo of the most beautiful artwork in the world, english medieval witch, black silk vale, pale skin, black silk robe, black cat, necromancy magic, sexy, medieval era, photorealistic painting by Ed Blinkey, Atey Ghailan, Studio Ghibli, by Jeremy Mann, Greg Manchess, Antonio Moro, trending on ArtStation, trending on CGSociety, Intricate, High Detail, Sharp focus, dramatic, photorealistic painting art by midjourney and greg rutkowski
Negative prompt: canvas frame, cartoon, 3d, ((disfigured)), ((bad art)), ((deformed)),((extra limbs)),((close up)),((b&w)), wierd colors, blurry, (((duplicate))), ((morbid)), ((mutilated)), [out of frame], extra fingers, mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), out of frame, ugly, extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck))), Photoshop, video game, ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, mutation, mutated, extra limbs, extra legs, extra arms, disfigured, deformed, cross-eye, body out of frame, blurry, bad art, bad anatomy, 3d render
Steps: 30, Sampler: DPM++ SDE Karras, CFG scale: 10, Seed: 1495009790, Face restoration: CodeFormer, Size: 760×1024, Model hash: 60fe2f34, Denoising strength: 0.5, First pass size: 0x0Testing Protogen x3.4
I uploaded the CKPT file to my own Paperspace Notebook and ran it using Automatic1111. Initially I tried with the same prompt as above but then started to vary it and have more than one person in the image. The results are better than before but not quite there yet. However, I am not being too critical about this model as it is only the first release. I’m certain that the team behind Protogen will keep improving this model to produce more consistent results.
Well formed hands
Something weird happened here
Woman’s Hand is not correctly formed Well formed hands
Left hand with three fingers
Too many fingers in this case Well formed hands
Well formed hands
Well formed handsTutorial Video
I found this wonderful tutorial video that shows how to setup and use this model in Google Colab notebook with Automatic1111. If you can get past the accent the information being shared is useful and demonstrates how to use this model.
Overall I feel with this Protogen model we are heading on the right path of improving hand formation in images created using AI and hopefully in a few months we will have this challenge completely tackled. Feel free to give this model a run, it was certainly fun for me to try various images and see the results.
A must-read for anyone responsible for SEO or Content Marketing
Importance: [rating=5] For all Webmasters, SEO Consultants, Content Producers and Web Designers
Recommended link: Google’s new Search Quality Rating Guideline
Yesterday (November 19th 2024), we saw the release of an updated ‘full’ 160(!) page version of the Search Quality Rating Guidelines. Here’s a sample:
With the adoption of Mobile Devices influencing the search landscape more and more, Google have decided to update its guidelines for Search Quality Raters.
This is big news since Google used to previously to keep these ‘behind closed doors’, but occasionally one would escape into the wild and be dissected. Back in 2013 Google published an abridged version as they looked to “provide transparency on how Google works” after previous leaks of the document in 2008, 2011 and 2012, then in 2014. However, as the use of mobile has rocketed, the need for a “Major” revision of the guidelines was deemed a necessity.
Although this is the full version, this is not the definitive version. Mimi Underwood, Senior Program Manager for Search Growth & Analysis stated:
“The guidelines will continue to evolve as search, and how people use it, changes. We won’t be updating the public document with every change, but we will try to publish big changes to the guidelines periodically.”
So, if you work in search we suggest you download a copy now before people change their mind.What are the Search Quality Guidelines?
In short, it is a document that will help webmasters and people alike, understand what Google looks for in web pages and what it takes to top the search rankings.
They work this out by using Google’s Search Quality Evaluators (third-party people hired by Google via a third-party agency to rate the search results) to measure a site’s Expertise, Authoritativeness and Trustworthiness, allowing Google to better understand what users want.Why is it important?
Referring back to the ‘What is it?’ section, it helps you to understand better what it takes to top the search rankings.
And whilst it doesn’t necessarily define the ranking algorithm, it provides you with an insight into what Google are looking for, which, as an SEO Professional, Webmaster, even Website Designer is invaluable information.How is it structured?
If you’ve read previous incarnations (excluding those who have had a peek at the leaked 2014 version) you’ll see a completely new structure, which has been rewritten from the ground up.
Looking at the monstrous contents page, it’s easy to get overwhelmed, however it’s relatively simple to follow. The first section is the General Guidelines Overview (Pages 4-6), highlighting topics such as the purpose of Search Quality rating, Browser requirements, Ad Blocking extensions, Internet Safety etc.
This is followed by the Page Quality Rating Guidelines (Pages 7-65), which discusses at great detail what Page Quality entails, providing examples of High Expertise, Authority and Trustworthy pages along with the middle tier and lowest tiers. Something interesting about this section is the Your Money or Your Life (YMYL), which discusses pages that could “potentially impact the future happiness, health, or wealth of users”.
The next section looks at Understanding Mobile User Needs (pages 67-86), there is a large emphasis on this part of the report as it is one of the key reasons behind the update. This Brand new section highlights the multiple issues that cause trouble on websites when viewed on a mobile device.
Another new section is the Needs Met Rating Guideline (87-149), which is one of the new ratings for webmasters to determine the quality of the site. It refers to mobile searcher’s needs and questions “how helpful and satisfying the result is for the mobile user?”.
The final section discusses Using the Evaluation platform for the Google Search Quality Evaluators (pages 152-158). It shows the process the Evaluators had to undergo, whilst reporting to google.Recommended sections
Here’s our analysis of the sections of the parts I felt were critical to read – there’s a lot, and you may think differently!
The sections recommended in the Page Quality Rating (pages 7-65) are:
2.2 What is the purpose of a Webpage? (page 8)
2.3 Your Money Your Life (page 9)
2.6 Website Maintenance (page 15)
2.7 Website Reputation (page 16)
3.0 Overall Page Quality Rating Scale (page 19)
5.0 High-Quality Pages (page 19-23)
7.0 Page Quality Rating: Important Considerations (page 58-59)
11.0 Page Quality Rating FAQs (page 65)
The entire Mobile User Needs (pages 67-86) is worth a scan at the very least.
Needs Met Rating (pages 87-149).
13.0 Rating Using the Needs Met Scale (page 87)
13.1 Rating Result Blocks: Block Content and Landing Pages (page 87)
13.2 Fully Meets (FullyM) (page 90)
13.4 Moderately Meets (MM) (page 107)
13.6 Fails to Meet (FailsM) (page 112)
14.6 Hard to Use Flag (page 127)
15.0 The Relationship between E-A-T and Needs Met (page 130)
18.0 Needs Met Rating and Freshness (page 141)
19.0 Misspelled and Mistyped Queries and Results (page 143)
20.0 Non-fully Meets Results for URL Queries (page 146)
21.0 Product Queries: Action (Do) vs Information (Know) Intent (page 148)
22.0 Rating Visit-in-Person Intent Queries (page 149)
For a more of an in-depth overview, check out Jennifer Slegg’s post at thesempost.
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