#image recognition machine learning

[arataneo-a]

whenever i see news about some company using ai to do something i can just imagine whoever let them use the ai model cackling. like ai is NOT that impressive from a compsci sense but these ppl are using buzz words to sell shit that either already exists or is shitty

[spinatt]

[technology-123s-blog]

Deep Learning Projects for Students - Takeoff Projects

Deep Learning Projects are exciting and advanced applications of artificial intelligence that solve complex problems by mimicking the way humans think. At Takeoff Projects, we provide a platform for students and professionals to explore and work on innovative deep learning projects that are both educational and practical. These projects involve training neural networks to analyze large amounts of data and make intelligent decisions.

Some popular deep learning projects include image recognition, where models identify objects or faces in pictures, and natural language processing, which helps in building chatbots or translating languages. Deep learning is also used in healthcare to analyze medical images like X-rays to detect diseases, and in self-driving cars to recognize objects on the road and ensure safe navigation.

At Takeoff Projects, we guide learners through real-world projects such as creating speech recognition systems, building recommendation engines like those used by Netflix or Amazon, and designing AI models for time-series forecasting like stock price prediction. We simplify these concepts with hands-on support, making them easy to understand and implement.

We also focus on innovative areas like Generative Adversarial Networks (GANs), which can create realistic images or enhance low-resolution photos, and robotics, where deep learning enables machines to perform tasks like sorting or assembly. These projects not only build technical skills but also prepare learners for a bright future in AI and data science.

Whether you are a beginner or an advanced learner, Takeoff Projects helps you take the first step toward mastering deep learning. By working on these projects, you can gain practical experience and showcase your expertise, opening up exciting career opportunities in this rapidly growing field. Let’s take off into the world of deep learning Projects together!

[mlembug]

this is because people take a look at tech and project their feelings into the tech itself rather than how forces in society encourage use of the tech, therefore expecting the tech to be neatly separated into "the good AI" vs "the wretched generative AI" or similar.

also see "enshittification" and how people came to think it's what companies do to ruin your free online services for funsies, rather than an inevitability of a for-profit company running a free-to-use non-profitable service, that costs money merely by existing.

i think people realized that "AI" has been applied far too generously and came to mean any kind of machine learning ever, creating mass hysteria and confusion. The clearer replacement, I've noticed, is "generative AI" and I'm just gonna say, no, try again, that's also already a widely used term for art with randomizing/procedural elements. i recently got an angry comment on my "1 hour of generative breakcore" video from someone who thought it was machine learning.

[adasitecompliance]

Digital Content Accessibility

Discover ADA Site Compliance's solutions for digital content accessibility, ensuring inclusivity online!

[jeffsperandeo]

Neurons and NPCs: Wiring the Future of Gaming AI

The Dawn of Dynamic Realms | AI-Driven NPCs Reshaping Video Gaming Introduction:A revolution is unfolding in the world of video gaming. Artificial Intelligence (AI) is transforming Non-Player Characters (NPCs) from scripted entities into dynamic, lifelike figures. This evolution is not just technological; it’s a redefinition of interaction and narrative immersion, offering new dimensions to…

[regsagc]

Need me an anti-facial-recognition, Italian-knit, crop-top

x

[medicaldevicesindustrynews]

Automatic Number Plate Recognition System Market To Have Faster Growth in the Software Category

The automatic number plate recognition system market is USD 3,219.9 million in 2023, and will increase to USD 6,010.8 million by 2030, at a rate of 9.5% by the end of this decade. This is because of the increasing use by agencies, such as parking, police force, toll plaza, and traffic management; the growing trend for pay-per-use roads; the evolving automotive industry; the high capital fundings…

[itesservices]

Harness the Value of Visual Data With Image Annotation for Machine Learning

Image annotation is important to help computers see and understand the data. Thus, it becomes an important process for businesses looking to implement Computer Vision and NLP models.

At the same time, it is important for you to know the image annotation prerequisites and how outsourcing visual data labeling tasks can be beneficial for you. 

[bi-writes]

whats wrong with ai?? genuinely curious <3

okay let's break it down. i'm an engineer, so i'm going to come at you from a perspective that may be different than someone else's.

i don't hate ai in every aspect. in theory, there are a lot of instances where, in fact, ai can help us do things a lot better without. here's a few examples:

ai detecting cancer

ai sorting recycling

some practical housekeeping that gemini (google ai) can do

all of the above examples are ways in which ai works with humans to do things in parallel with us. it's not overstepping--it's sorting, using pixels at a micro-level to detect abnormalities that we as humans can not, fixing a list. these are all really small, helpful ways that ai can work with us.

everything else about ai works against us. in general, ai is a huge consumer of natural resources. every prompt that you put into character.ai, chatgpt? this wastes water + energy. it's not free. a machine somewhere in the world has to swallow your prompt, call on a model to feed data into it and process more data, and then has to generate an answer for you all in a relatively short amount of time.

that is crazy expensive. someone is paying for that, and if it isn't you with your own money, it's the strain on the power grid, the water that cools the computers, the A/C that cools the data centers. and you aren't the only person using ai. chatgpt alone gets millions of users every single day, with probably thousands of prompts per second, so multiply your personal consumption by millions, and you can start to see how the picture is becoming overwhelming.

that is energy consumption alone. we haven't even talked about how problematic ai is ethically. there is currently no regulation in the united states about how ai should be developed, deployed, or used.

what does this mean for you?

it means that anything you post online is subject to data mining by an ai model (because why would they need to ask if there's no laws to stop them? wtf does it matter what it means to you to some idiot software engineer in the back room of an office making 3x your salary?). oh, that little fic you posted to wattpad that got a lot of attention? well now it's being used to teach ai how to write. oh, that sketch you made using adobe that you want to sell? adobe didn't tell you that anything you save to the cloud is now subject to being used for their ai models, so now your art is being replicated to generate ai images in photoshop, without crediting you (they have since said they don't do this...but privacy policies were never made to be human-readable, and i can't imagine they are the only company to sneakily try this). oh, your apartment just installed a new system that will use facial recognition to let their residents inside? oh, they didn't train their model with anyone but white people, so now all the black people living in that apartment building can't get into their homes. oh, you want to apply for a new job? the ai model that scans resumes learned from historical data that more men work that role than women (so the model basically thinks men are better than women), so now your resume is getting thrown out because you're a woman.

ai learns from data. and data is flawed. data is human. and as humans, we are racist, homophobic, misogynistic, transphobic, divided. so the ai models we train will learn from this. ai learns from people's creative works--their personal and artistic property. and now it's scrambling them all up to spit out generated images and written works that no one would ever want to read (because it's no longer a labor of love), and they're using that to make money. they're profiting off of people, and there's no one to stop them. they're also using generated images as marketing tools, to trick idiots on facebook, to make it so hard to be media literate that we have to question every single thing we see because now we don't know what's real and what's not.

the problem with ai is that it's doing more harm than good. and we as a society aren't doing our due diligence to understand the unintended consequences of it all. we aren't angry enough. we're too scared of stifling innovation that we're letting it regulate itself (aka letting companies decide), which has never been a good idea. we see it do one cool thing, and somehow that makes up for all the rest of the bullshit?

[capnsoapy]

Here is a hypothetical scenario:

The NHS develops a new piece of software which can analyse the public and– using a combination of image recognition, medical history, geographic data, and machine learning– determine if a person has undiagnosed appendiceal cancer.

Via randomised control trialing they determine that the software is 99% accurate, and so run it on the entire British population and offer treatment to all positive cases before the cancers develop.

For reference, the British population is ≈70 million, and appendiceal cancer is found in ≈20 people per million.

[mudwerks]

(via Vending machine error reveals secret face image database of college students | Ars Technica)

Canada-based University of Waterloo is racing to remove M&M-branded smart vending machines from campus after outraged students discovered the machines were covertly collecting facial-recognition data without their consent.

The scandal started when a student using the alias SquidKid47 posted an image on Reddit showing a campus vending machine error message, "Invenda.Vending.FacialRecognitionApp.exe," displayed after the machine failed to launch a facial recognition application that nobody expected to be part of the process of using a vending machine.

"Hey, so why do the stupid M&M machines have facial recognition?" SquidKid47 pondered.

The Reddit post sparked an investigation from a fourth-year student named River Stanley, who was writing for a university publication called MathNEWS.

Stanley sounded alarm after consulting Invenda sales brochures that promised "the machines are capable of sending estimated ages and genders" of every person who used the machines without ever requesting consent.

This frustrated Stanley, who discovered that Canada's privacy commissioner had years ago investigated a shopping mall operator called Cadillac Fairview after discovering some of the malls' informational kiosks were secretly "using facial recognition software on unsuspecting patrons."

Only because of that official investigation did Canadians learn that "over 5 million nonconsenting Canadians" were scanned into Cadillac Fairview's database, Stanley reported. Where Cadillac Fairview was ultimately forced to delete the entire database, Stanley wrote that consequences for collecting similarly sensitive facial recognition data without consent for Invenda clients like Mars remain unclear.

Stanley's report ended with a call for students to demand that the university "bar facial recognition vending machines from campus."

what the motherfuck

[smellslikebot]

"how do I keep my art from being scraped for AI from now on?"

if you post images online, there's no 100% guaranteed way to prevent this, and you can probably assume that there's no need to remove/edit existing content. you might contest this as a matter of data privacy and workers' rights, but you might also be looking for smaller, more immediate actions to take.

...so I made this list! I can't vouch for the effectiveness of all of these, but I wanted to compile as many options as possible so you can decide what's best for you.

Discouraging data scraping and "opting out"

robots.txt - This is a file placed in a website's home directory to "ask" web crawlers not to access certain parts of a site. If you have your own website, you can edit this yourself, or you can check which crawlers a site disallows by adding /robots.txt at the end of the URL. This article has instructions for blocking some bots that scrape data for AI.

HTML metadata - DeviantArt (i know) has proposed the "noai" and "noimageai" meta tags for opting images out of machine learning datasets, while Mojeek proposed "noml". To use all three, you'd put the following in your webpages' headers:

<meta name="robots" content="noai, noimageai, noml">

Have I Been Trained? - A tool by Spawning to search for images in the LAION-5B and LAION-400M datasets and opt your images and web domain out of future model training. Spawning claims that Stability AI and Hugging Face have agreed to respect these opt-outs. Try searching for usernames!

Kudurru - A tool by Spawning (currently a Wordpress plugin) in closed beta that purportedly blocks/redirects AI scrapers from your website. I don't know much about how this one works.

ai.txt - Similar to robots.txt. A new type of permissions file for AI training proposed by Spawning.

ArtShield Watermarker - Web-based tool to add Stable Diffusion's "invisible watermark" to images, which may cause an image to be recognized as AI-generated and excluded from data scraping and/or model training. Source available on GitHub. Doesn't seem to have updated/posted on social media since last year.

Image processing... things

these are popular now, but there seems to be some confusion regarding the goal of these tools; these aren't meant to "kill" AI art, and they won't affect existing models. they won't magically guarantee full protection, so you probably shouldn't loudly announce that you're using them to try to bait AI users into responding

Glaze - UChicago's tool to add "adversarial noise" to art to disrupt style mimicry. Devs recommend glazing pictures last. Runs on Windows and Mac (Nvidia GPU required)

WebGlaze - Free browser-based Glaze service for those who can't run Glaze locally. Request an invite by following their instructions.

Mist - Another adversarial noise tool, by Psyker Group. Runs on Windows and Linux (Nvidia GPU required) or on web with a Google Colab Notebook.

Nightshade - UChicago's tool to distort AI's recognition of features and "poison" datasets, with the goal of making it inconvenient to use images scraped without consent. The guide recommends that you do not disclose whether your art is nightshaded. Nightshade chooses a tag that's relevant to your image. You should use this word in the image's caption/alt text when you post the image online. This means the alt text will accurately describe what's in the image-- there is no reason to ever write false/mismatched alt text!!! Runs on Windows and Mac (Nvidia GPU required)

Sanative AI - Web-based "anti-AI watermark"-- maybe comparable to Glaze and Mist. I can't find much about this one except that they won a "Responsible AI Challenge" hosted by Mozilla last year.

Just Add A Regular Watermark - It doesn't take a lot of processing power to add a watermark, so why not? Try adding complexities like warping, changes in color/opacity, and blurring to make it more annoying for an AI (or human) to remove. You could even try testing your watermark against an AI watermark remover. (the privacy policy claims that they don't keep or otherwise use your images, but use your own judgment)

given that energy consumption was the focus of some AI art criticism, I'm not sure if the benefits of these GPU-intensive tools outweigh the cost, and I'd like to know more about that. in any case, I thought that people writing alt text/image descriptions more often would've been a neat side effect of Nightshade being used, so I hope to see more of that in the future, at least!

[ms-demeanor]

the most minorly annoying thing about this photo class is that the professor required us to put our first and last names in the metadata and i'm too lazy to figure out how to strip that out in lightroom so i need to go through and edit all the good shit properly before I can share the high res versions.

Also hello i learned to take photos in a journalism context and I am old man yells at cloud about lightroom. Clarity? DEHAZE? AI SELECTING THE SKY?

Back in my day we didn't have smart masks we had to do a magnetic lasso with a 10px feather and it always covered the wrong shit at least part of the time and that's why you take snapshots to correct after the fact and now you've just got a robot to tell you where the sky is? What's the world coming to!? (But actually seriously for real, "select the sky" is a great example of how machine image recognition trained on large public facing image sets is/can be a really useful tool for artists and is not just a fucking plagiarism machine and ALSO a good example of the democratization that people love to deride when talking about AI "everybody already could draw, AI isn't doing anything special" - yeah, well everybody could also spend an hour meticulously clicking around the edge of the subject to remove the background but it was a pain in the ass wasn't it? are you telling me you don't want a mask that you can use to fill with content aware hatching? Are you telling me you don't want a stippling brush that will correct distribution when multiple passes are applied?)

[adasitecompliance]

AI Influences Web Accessibility

The Future Of AI And Web Accessibility

In our increasingly digital world, equal access to information is crucial. However, many individuals with disabilities face challenges in accessing online content, such as websites, articles, and videos, due to various barriers.

Imagine a world where technology empowers everyone to access information effortlessly, regardless of their abilities. Thanks to artificial intelligence (AI), this vision is becoming a reality. AI is breaking down barriers and making technology more accessible.

By improving information accessibility, AI not only aids individuals with disabilities but also enhances the overall user experience for everyone. ChatGPT-3 has accelerated AI-driven innovation, and while the future of AI and website accessibility is unknown, innovative technologies like GPT-5 have immense potential to enhance accessibility.

We at ADA Site Compliance have a team of accessibility experts who stay updated with the latest regulatory trends and emerging technology. They help organizations like yours ensure that all digital content meets accessibility standards.

Exploring the Future Potential of Artificial Intelligence

Artificial Intelligence (AI) involves creating computer systems designed to mimic human intelligence. A fundamental aspect of AI is machine learning algorithms, a subset that allows computers to learn and evolve based on experience without explicit programming.

Technological advancements have unlocked AI’s vast potential, enabling intelligent devices to perform tasks that once were solely within the realm of human cognition.

What is AI?

To grasp how AI influences web accessibility, we first need to define it.

Artificial Intelligence involves developing software and systems that perform tasks requiring human intelligence. AI achieves this through various technologies, including natural language processing and computer vision. As these functions become more accessible, they benefit society even more

What Are Accessibility Technologies?

Accessibility technologies provide tools and solutions to ensure that people with disabilities can access and use web content effectively. These technologies, including AI-powered tools like chatbots, digital platforms like GPT, screen readers, and alternative input devices, are designed to enhance digital accessibility and foster inclusivity.

Current AI Technologies

AI is rapidly enhancing web accessibility. Improved computer vision algorithms are making it easier for visually impaired users and seniors to understand web content through better descriptions of visual content.

Here are a few examples of current AI technologies:

1. GPT-4:

OpenAI’s newest chatbot, GPT-4, enhances accessibility for third-party companies. In partnership with Be My Eyes, GPT-4 introduces an AI-powered Virtual Volunteer to assist visually impaired individuals.

2. Apple’s Accessibility Features:

Apple continues to set the standard in accessibility with a suite of new tools launched on Global Accessibility Awareness Day. These enhancements include improved Voice Control, customizable Siri options, and a unique Assistive Access mode to simplify device usage for people with motor or cognitive disabilities.

3. Google’s Enhanced Navigation Features:

In October, Google upgraded its navigation features for Google Maps and business pages. These enhancements include wheelchair-accessible walking routes, improved Live View for visually impaired users, and a new identity attribute label to help locate disabled-owned businesses.

4. Natural Language Processing (NLP):

NLP enhances text readability, aiding individuals with cognitive disorders, learning disabilities, and age-related cognitive decline.

Despite these advancements, this cutting-edge technology is not yet perfect. Image recognition still struggles with complex scenes and context, and NLP-based text simplification can sometimes lead to a loss of significance. Nevertheless, these developments represent a promising beginning for enhanced digital accessibility.

Examples of How AI Enhances Digital Accessibility

Individuals with visual, auditory, or mobility impairments often face challenges in navigating the digital landscape of the web. Here are some ways AI is making accessibility improvements:

1) Speech Recognition

Speech recognition technology is incredibly beneficial for those with physical limitations, restricted mobility, or typing difficulties. AI-powered speech and voice recognition technologies enable users to control devices and navigate the web using voice commands, significantly enhancing their online accessibility and overall experience.

2) Enhanced Browsing Experience

Did you know that AI-powered virtual assistants and chatbots can significantly enhance online browsing?

These technologies provide personalized support, helping individuals with disabilities access important information and navigate websites more effectively. Accessible websites perform better in search engines but also offer a superior user experience for everyone.

3) AI-Enhanced Visualization for Visually Impaired Users

Imagine a world where images and text describe everything around you. AI-powered screen readers and text-to-speech technologies make written content accessible for visually impaired individuals. Additionally, image recognition systems can describe photos, videos, and live scenes, offering valuable assistance to those with visual impairments.

A crucial accessibility element for visually impaired users is “alt text.” AI can automatically generate alt text for images and videos, ensuring quick and accurate descriptions that describe images. This allows screen readers to interpret and explain on-screen images, making web content more inclusive and accessible.

AI Benefits for Web Accessibility

AI is revolutionizing web accessibility, offering numerous benefits that enhance the online experience for individuals with disabilities. Here are some key advantages AI brings to web accessibility:

a) Enhanced Access

AI has significantly advanced web accessibility for individuals with disabilities. It removes obstacles, enabling users to navigate websites, consume multimedia content more, and engage in online communities more effectively.

b) Boosted Independence and Autonomy

AI empowers individuals with disabilities to use the internet independently. This innovation allows them to manage their online activities without assistance, fostering greater inclusion and promoting autonomy.

Challenges Posed by AI on Web Accessibility

AI enhances online accessibility, but it also introduces several challenges. Here are some key issues AI poses for web accessibility:

i) Accuracy Challenges

Despite advancements, AI often struggles with providing reliable captions, descriptions, translations, and voice recognition. Errors in these areas can make it difficult for users to understand content, thereby limiting the effectiveness of accessibility features.

ii) Over-Reliance

Relying too heavily on AI to improve web accessibility can result in overlooking other essential aspects of accessible design. Use AI alongside comprehensive other accessibility guidelines and principles and not seen as a universal solution.

Future of AI-Driven Web Accessibility

With AI becoming more advanced, it will continue enhancing technology usability and improving web accessibility. Developers will save time and resources when using these tools to discover and fix accessibility issues.

Remember that automated tools cannot guarantee accessibility compliance.

Human knowledge and manual testing by experienced accessibility auditing specialists will still be needed to discover complicated issues and create a fully inclusive user experience for elders and disabled people.

This is where we at ADA Site Compliance can help. We have a team of accessibility experts and web developers who stay updated with the latest regulatory trends to help organizations like yours ensure all web content meets accessibility standards.

For all your website and digital content accessibility needs, contact ADA Site Compliance today!