Web scrapers extract data from a webpage's underlying HTML code and have been used to generate sales leads, collect competitor information, identify counterfeit products, and optimize sites for search engines.

Web crawlers and internet archives and back-ups limit perfect erasure of online data

Crawlers are programs that automatically browse the internet for links and index pages for search engines to pull up when page content matches search queries. Networks of global data centers also create copies of content as fail-safes for potential failures to ensure access isn't ever lost.

Credit monitoring services may oversell the benefits of dark web monitoring

Currently, technology exists to scrape and download data from webpages, which can then be analyzed to identify a user's information. However, scrapers cannot access or remove personal data from dark websites because they are often protected by paywalls, rendering monitoring ineffective beyond reporting publicly available data breaches.

AI scraping for LLM training data has significantly strained Wikipedia's infrastructure

From January 2024 to April 2025, the site's bandwidth increased by 50% as automated bots downloaded terabytes of data for the large language models powering AI tools. The Wikimedia Foundation found that bots accounted for 65% of the highest demand requests (e.g., videos) despite representing just 35% of page views.

Fair use may shield AI companies from potential copyright violations

AI models are trained on enormous datasets built from content scraped from websites across the internet. Copyright law includes a four-factor test to determine whether copies of content fall under fair use, but the law's enforcement has been inconsistent.

Try out ShieldFont, a specialized web font that swaps the HTML code corresponding to certain onscreen words to protect website content from AI scrapers.

Unlike generative AI systems, such as chatbots that do not take follow-up actions after generating their output, agentic AI systems proactively take steps to achieve goals without continuous user input.

Why Google is reinventing the internet search

Social media platforms benefit not just from ensuring they have satisfied users, but also from the personal data they scoop up and can then sell to online advertisers.

As occurred during the 2026 hack of an AI platform by OpenAI, agentic AI may exploit a system vulnerability to access sensitive data if that information enables it to complete its assigned task.

Google Search incorporated AI Overviews in 2024 to fight back competitors

Analysts believe that generative AI tools—not antitrust rulings—are Google's biggest threat because they draw users away from traditional search and potential ad revenue. AI partnerships, like the one between Apple and OpenAI, may further reduce Google's market share.

Researchers found that by mid-2025, around 35% of newly published websites utilized AI for language generation

The study also found that pages using AI narrow the range of ideas and perspectives and skew more positively, though the measurable impacts on factual accuracy and writing style variation remain unclear.

Graphics processing units, which process large amounts of data in parallel, have become the foundational hardware for AI systems that rely on hardware capable of processing millions of text parameters simultaneously.

Studies show AI tools can result in passive learning with less retention

Although ChatGPT, Google's AI overviews, and other similar software can save time, a study of more than 10,000 adults showed that reliance on them yielded work products that were more generic and included fewer facts than those produced solely by Google search. Weaker brain connectivity has also been observed when users write using AI.

During a job interview with an AI agent, applicants are evaluated against a rubric that considers factors such as tone, clarity, and the use of specific words or phrases aligned to the job.

The next evolution of Google Search: AI Mode

Google launches AI Mode, which brings advanced AI capabilities to its search engine. This new feature combines the Gemini AI chatbot with search to help with tasks like vacation booking and purchasing, as well as provide a new virtual try-on shopping experience.

Through prompt injection attacks, bad actors provide deceptive prompts to generative AI systems in order to manipulate their outputs and acquire sensitive data.

AI is transforming the marketing and advertising industries

Many marketers argue that AI is useful in an ad agency setting. Others attribute the significant layoffs the industry has faced in recent years, at least in part, to AI. Agency leaders and big tech firms alike have supported experimenting with artificial intelligence’s capacity to create content once reserved for agency creatives.

AI excels at assisting with structured tasks involving logistics and planning

Tools like ChatGPT, Gemini, and Perplexity can help organize chaotic calendars, troubleshoot bedtime routines, and assist with salary planning and moving. However, specific quotes, like insurance, and local cost comparisons can be flawed since AI draws from nonlocalized datasets.

As of 2026, almost 90% of companies use AI in their hiring processes to cut hiring time by up to 50%, including using AI-based tools to filter 75% of resumes.

AI gained mainstream attention with tools like IBM Watson and Apple’s Siri

With the release of ChatGPT in 2022, which drew over 100 million weekly users in just two months, natural language processing and understanding could be achieved at scale via machine learning. Unlike earlier artificial intelligence that could pull stored knowledge, generative AI produces text, images, or sounds.

Google only sorts and searches a fraction of the overall internet

The "surface web," consisting of billions of public webpages, excludes nonindexed digital content, such as corporate intranets and email inboxes. A deeper layer, called the dark web, is also hidden and requires special software to access.

See the news with AI-generated data visualizations

Realtime uses generative AI to create immediate data visualizations of news items on its regularly-updated feed, pulling from public data feeds. Peruse stories around sports, economics, politics, and more with the helpful aid of charts and graphs. See the shape of the news with this clever AI tool here.

Because they are built on content produced by humans, who possess biases, generative AI tools inherit prejudices and stereotypes from training data, which later appear in their outputs.

Machine learning lets computers learn from data instead of relying on programming

ML is a core part of artificial intelligence and is foundational to applications like chatbots, fraud detection, and self-driving cars. Businesses are also adopting it to improve efficiency and identify patterns in data, though the latter may be inaccurate.

How AI is revolutionizing banking

Generative artificial intelligence has left no industry untouched, and banking isn’t an exception. Experts estimate that gen AI could add as much as $340B in value to the banking sector each year. For consumers, this involves new features to prevent fraud and customer service chatbots. This report dives into the revolution underway and seeks to define a “full stack” AI bank of the future. Read more here.

In 2026, a pilot program introduced two AI-powered humanoid robots to a San Diego charter school to increase engagement and academic gains, though some criticized the $500k purchase.

The AI that creates any picture you want and how it works

Since January 2021, advances in AI research produced a plethora of deep-learning models capable of generating original images from simple text prompts. Researchers at OpenAI, Google, Facebook, and others have developed yet to be released text-to-image tools, and similar models have proliferated online. This video is a primer on how we got here, how the technology works, and its implications.

Artificial intelligence may further enhance smart city data analysis

Identifying patterns within systems in the Internet of Things may enable AI tools to make informed decisions regarding transportation, safety, and sustainability without human intervention. However, such tools will also need to successfully address concerns about privacy, digital equity, and algorithmic bias.

The growing role of AI in journalism

As artificial intelligence (AI) becomes more widely available, journalism must adapt and establish ethical norms for how the technology is used. This report from the Center for News, Technology & Innovation looks at the issue from every angle, including legal considerations, potential biases in datasets, and the speed at which AI capabilities are changing. It also includes links to recent studies on the use of AI in journalism.

Tokens—numbers assigned to words and subwords—are the basic units of data that AI tools process to generate outputs that mimic language without understanding the text itself.

Pretend to be an AI chatbot and answer real prompts

This site, which allows people to answer prompts in real time, has millions of visitors. Join the crowd of people tired of AI chatbots and seeking human connection. You can ask questions, answer questions, and draw for each other.

The promise and peril of AI in agriculture

Robots. Drones. Artificial Intelligence. All three are touted as potential saviors for farmers, and are already being deployed on large farms, where they assist with such tasks as managing crops, milking cows, and helping farmers make decisions about their land. But agricultural AI could have disastrous, unintended consequences.

Experiments involving AI agents operating in virtual societies for 15 days produced diverse outcomes, ranging from every agent dying to the creation of a functioning democracy, depending on the AI model used.

According to the International Energy Agency, hyperscale data centers consume about as much electricity annually as 400,000 electric vehicles to provide 24/7 access to online applications, services, and information.

Computer systems create artificial voices by stitching together phonemes—individual sounds that make up speech, such as 't,' 'long a,' and 'k' to say 'take.'

Generative AI may automate nearly 10% of tasks in the US economy.

When you complete a CAPTCHA on a website to prove you are human, you may be unknowingly training algorithms for self-driving cars, whose systems require training data to help identify crosswalks, bicycles, and other outdoor objects.

Just as large language models are trained on text to enable generative AI systems to mimic natural language, automated AI robotic systems are trained in virtual environments to help them 'learn' about the properties of reality.

The Anthropic Economic Index shows AI adoption is highest in computer science roles.

Unlike the models made by large AI companies, open-weight models can have their safeguards removed or weakened, a process that has become increasingly easy and may expose users to harmful information.

The dead internet theory suggests that mostly bots are interacting online

The dead internet theory proposes that bots create most online content. These bots are believed to create social media posts to boost engagement and increase advertising revenue. However, the accounts doing the liking and commenting are also believed to be bots. The theory suggests governments use bots to manipulate public opinion.

An overview of the World Wide Web, which is often confused with the internet

When users create a website, they organize content and store it on a web server—one of various types of hardware that make up the internet—in web languages, such as HTML and JavaScript. When visiting the site, a web browser translates these languages into text and other media for consumption.

Explore content on the dark web safely with the Ahmia search engine, which has provided activists with digital addresses to anonymously send files to media outlets.

Indirect prompt injection is a major security flaw of generative AI systems

These attacks can manipulate AI behavior by hiding instructions in websites and PDFs that become part of training data. The more companies connect sites, services, and sensitive datasets to AI tools, the greater the chances of exposure to malicious code.

AI could be increasing the opportunities for financial fraud

Systems that can reproduce near perfect counterfeits of legitimate financial documents are increasingly prevalent and sophisticated. The international Association of Certified Fraud Examiners estimate organizations lose about 5% of revenue to fraud each year.

Microsoft has integrated AI across its software products with Copilot

It utilizes an underlying model from OpenAI—makers of ChatGPT—to assist users in creating documents, writing code, locating files, and more across Windows, Microsoft 365, Bing search and WhatsApp on desktop and mobile devices. Copilot Voice and Vision offer accessibility features for users who prefer not to use mouse/keyboard navigation.

Google invented the foundation of the AI movement—but ChatGPT was a shock

For years, Google was the cutting-edge of the AI world, including the development of the Transformer—the basis of contemporary AI chatbots. But since OpenAI debuted ChatGPT in 2022, the company was had to play catch-up. This is a four-hour deep dive into Google's AI history.

AI is not good at understanding satire

Social media has become rife with misinformation. In response, some organizations have deployed AI-assisted programs trying to curb the spread of this inaccurate content. The problem is that misinformation and satire, rhetorically speaking, often use the same kind of language, something AI struggles to understand.

As of 2025, artificial intelligence systems remain narrow and specialized

Efforts are ongoing to create artificial general intelligence, where machines outperform humans across a wide range of cognitive tasks, including those for which they have not been specifically trained. Current models utilize machine learning and neural networks to perform tasks for which they are programmed, leveraging provided training data.

Scientists increasingly can't predict what AI will do

Most AI systems are so-called "black box" models, where we only see inputs and outputs while the inner workings remain obscure. This piece, written prior to the launch of ChatGPT, cautions developers to know why and how a system produces its results, and not to sacrifice explainability for accuracy.