AI vs. machine learning vs. deep learning

Machine learning and deep learning are successive subsets of artificial intelligence

ML allows systems to learn from data, while DL uses complex neural networks to analyze large amounts of unstructured data. Neural networks enable capabilities like image and speech recognition through their use of algorithms to identify patterns in data.

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.

How generative AI differs from machine learning

Compared to machine learning - which is sort of like teaching a toddler how to recognize what a dog looks like by showing them images of one - generative AI is like teaching that same child how to actually draw a dog. Unlike machine learning, generative AI can actually generate. Read this article for a more in-depth comparison between these two types of artificial intelligence.

What does it mean for AI to "understand" something?

This Quanta article discusses how programmers are working to create a reliable test for the depth and extent of the knowledge of machines. What does AI know and how does it know it, if it knows anything at all? There's been progress, but it hasn't been easy. Even humans can still be fooled some of the time.

AI systems identify patterns involving physics and time through 'world models'

These realistic virtual environments, such as driving simulations seen in video games, allow these systems to "learn" properties about reality beyond what can be captured in samples of text, images, and videos. Training AI in these simulated environments can help develop "physical AI" for automated robotic systems. (Some readers may experience a paywall.)

Anthropic's interpretability team discusses how AI models' thinking mimics biology

Just as humans engage in complex behaviors to survive and reproduce, teams of experts in neuroscience, virology, mathematics, and other disciplines argue that large language models develop complex mechanisms to achieve their goals. These mechanisms can be manipulated to assess how they modify outputs—much like stimulating individual neurons—to uncover how LLMs "think."

View a timeline of AI deployments from 2017 to 2025

The development of transformer architecture and the release of GPTs across AI labs led to rapid changes in LLM scale and power. Companies like OpenAI, Google, Meta, Microsoft, and Anthropic have invested billions of dollars to develop reliable, versatile models.

Test your ability to identify AI-generated images

This interactive project from MIT challenges users to distinguish between AI-generated images and real ones.

Using deep learning to analyze tumors

The explosive growth of life sciences data is driving artificial intelligence methods to gain traction in biology and medicine — including cancer research.

The major AI industry players are creating a web of circular investments

Bloomberg created a network diagram that shows how companies like Nvidia and OpenAI are fueling the AI money machine. The chart shows that many top AI companies provide significant investments to one another.

The hardware powering AI was originally designed for video game graphics processing

Graphics processing units are specialized computer chips that can process multiple data streams in parallel, including pixel colors for a display. Such processing is required to find connections across text data and generate outputs quickly.

AI may enable smart cities to drastically improve public safety

By utilizing machine learning techniques to analyze real-time monitoring reports against facial recognition databases, artificial intelligence can enhance the identification of criminals and coordinate an appropriate emergency response across various scenarios.

AI expert shows the cyclical nature of AI hype—in 1988

Rodney Brooks wrote several decades ago about the boom and bust cycles of artificial intelligence. Starting from the 1950s excitement over ENIAC's multiplication through the second launch of then-novel neural networks, Brooks suggests AI progresses incrementally despite the hype.

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.

Help scientists at LIGO train AI to resolve glitches in observational data

Volunteers are provided with visual representations of signal abnormalities at various frequencies and tasked with categorizing them based on reference examples. Progressing through the tool unlocks more difficult images and additional features. Categorized images will be used to train machine learning algorithms for automated future classification.

LLMs explained simply and quickly

Large language models generate responses by predicting one token at a time, based on patterns they’ve learned from massive datasets. This explainer covers their core components: data, architecture, training, and how transformer models use context to simulate conversation.

AI superintelligence is a hypothetical system vastly more capable than humans

Researchers describe superintelligence as an artificial intelligence system that exceeds human cognitive ability in every area. It is viewed as the theoretical evolution of artificial general intelligence, in which AI systems learn and have the capability of a typical human.

AI tools are trained on human-created data containing implicit and explicit biases

Because AI tools reflect patterns in their training data, their outputs may reinforce existing societal biases—especially racial ones—rather than offering neutral or fair ones. Adequate training is necessary to undermine these biases whenever new data is incorporated.

Watch how algorithms can be designed to train themselves and self-improve without human input, to the point where the optimized code is too complex for programmers to understand.

Explore (digitally) the Computer History Museum

When IBM’s Deep Blue supercomputer won its famous chess rematch with then world champion Garry Kasparov in May 1997, the victory was hailed far and wide as a triumph of artificial intelligence. But John McCarthy—the man who coined the term and pioneered the field of AI research—didn’t see it that way. An obituary about McCarthy—who passed in 2001—and his ideas.

What are neural networks and why do they matter?

Learn how a neural network works, why it matters, and how it can be trained to recognize patterns, classify data, and forecast future events.

There’s an artificial intelligence model trained on bankruptcy law

Although it's designed for lawyers, the tool is able to help everyday browsers synthesize important cases and point users to relevant documents about them. One sample using it asks Chatlaw to explain the significance of a recent case and then to define relevant terminology.

The history of infographics: cave art to interactive visuals

When did humans first create infographics? This article and related infographics detail how artistic data representations have evolved alongside humans and other hominins. The roots of infographics can be traced back to cave paintings, such as...

An overview of 12 fundamental types of algorithms and the uses for each

These include search algorithms to quickly process and find important information, cryptographic algorithms to secure communications, randomized algorithms—such as Monte Carlo simulations for estimating probabilities of outcomes—and greedy algorithms, which make optimal choices based on available data in a step-by-step fashion, as seen in navigation apps.

The science of optical illusions

The human brain has developed cognitive shortcuts to help us navigate in a world where our visual senses are constantly bombarded of information. But these shortcuts can also be exploited, tricking the brain into telling us something is happening when it really isn't. This short video unpacks the neuroscience behind some of the most common (but perplexing) optical illusions.

Explore Anthropic Academy, which provides courses on using Claude

The online courses include Claude Code in Action, which teaches software developers how to integrate Claude Code into existing workflows; Claude 101, to learn how Claude can be used to complete everyday tasks; and an AI Fluency series to help educators, instructional designers, and students learn to apply AI in academic settings.

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.

This site reaches millions of visitors who are tired of AI chatbots and seeking human connection. Pretend to be an AI chatbot and ask questions, provide answers, and draw for people in real time.

Browse a detailed visual analysis of over 200,000 similes—comparisons that often use 'like' or 'as'—from popular fiction to see how frequently writers the same idiomatic expressions.

A vending machine run with Anthropic's AI went out of business after it was convinced to give away items for free and sell a video game console.

Explore the animals that populate the depths of the ocean, from fish and coral in the first few hundred feet, all the way down to the bottom of the Mariana Trench.

Electrical grids worldwide must double their power delivery capacity by 2050 to meet surging demand from AI and electric vehicles.

Visualize how CRISPR-Cas9—a type of immune system used by single-celled organisms to attack invasive viruses—targets and makes precise changes to a gene's DNA.

English mathematician Ada Lovelace wrote the first computer algorithm a century before computers existed and hypothesized that computing devices would one day be able to compose music—foreseeing the generative AI systems of today.

Alzheimer's can lead to brain shrinkage, with an average of around 2% of volume reduction per year

As of 2025, the most cited papers in science include a review of graphene, methods to improve image recognition, streamlining electron density calculations, and optimizing protein studies.

After 25 people used virtual reality headsets to practice flying with virtual wings—flapping their arms—their visual cortex responded to the wings almost as if they were real arms, treating them as body parts.

Watch this video that uses Lego bricks to explain how venture capital works.

See the most iconic photos from four decades of LIFE magazine

See these 16 pieces of art evoking phobias of snakes, flying, spiders, and more. 

This poison ivy knowledge quiz—accompanied by photos of the plant's varied forms—may help you identify this common rash-inducing growth.

How Amazon operates a 'flywheel' business model, a self-reinforcing cycle that drives continuous growth

Learn how your body is, scientifically, like a firework with its own slow, controlled burn.

Power lines are dotted with large, brightly colored balls to improve the visibility of these thin wires to helicopters and small planes and help prevent potential crashes.

Tattoos remain visible on your skin thanks to immune cells called macrophages

In 2019, a laptop loaded with six of the worst malware in history and described as 'an exhibit of historical weaponry' sold for $1.3M.

Ebola is a filovirus, meaning it resembles a thread under a microscope, though it sometimes twists and can resemble a bowl of spaghetti.

Memecoins are a type of cryptocurrency—a form of digital currency with a wide variety of uses—created around popular 'memes,' or viral internet jokes.

Exploring the Larry Bird punch that almost changed March Madness

Walt Disney's early film 'Alice's Wonderland' was a groundbreaking innovation in the silent film era