Technologies labeled “AI” have historically lost that title after widespread adoption

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.

Art and video produced through generative AI involve competing neural networks

Generative adversarial networks are a type of deep learning architecture that consists of a generator, which creates data that appear real, and a discriminator, which attempts to distinguish authentic from fake data. The two train in a competitive loop until the real and fictional data are indistinguishable.

Generative AI tools excel at pattern recognition, not contextual accuracy

Large language models are trained on vast amounts of unstructured data, from which they develop parameters for grammar and associations between words. These connections can introduce errors due to inapplicable reasoning when used on new data in unfamiliar contexts.

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.

Generative AI is reinventing Internet search

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.

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.

Agentic AI systems can proactively achieve user goals without user direction

Unlike large language models, which do not take follow-up actions after generating their output, agentic AI uses an initial prompt to take multiple steps, learn from its environment and outcomes, and continue working without follow-up human prompting.

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.

In 2024, Meta launched an AI video generator to create or edit videos through prompts

The tool puts the Meta in direct competition with OpenAI and Google as more companies are investing billions of dollars to capitalize on the explosion of public interest in machine learning and generative media technologies.

The next technology epoch is here

From ChatGPT to DALL-E, 2022 saw the mainstream emergence of artificial intelligence for consumer use. Here's how these platforms will disrupt today's five biggest tech companies—Apple, Amazon, Meta, Google, and Microsoft.

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.

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.

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.

The ease of deepfakes creation may soon overwhelm our sense of digital truth

Shortly after the public release of related technology in 2017, some experts saw the technical limitations of deepfakes as preventing them from becoming widespread tools of disinformation. Since then, the neural networks behind diffusion models and generative AI have eliminated the barriers to creating convincing synthetic media for propaganda.

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

This automation is expected to impact both low- and high-wage roles, with those in customer service, food service, and office support being most likely to be affected. Large-scale investments in upskilling will be necessary to help individuals find new employment opportunities.

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.

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.

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 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.

Diffusion models generate nontext media by adding and removing noise from a dataset

Unlike text-based AI tools, which rely on large language models to recognize patterns in text, diffusion models use a reward system to generate images, video, audio, and 3D models. They can also be customized to match a user’s style.

Nvidia entered its AI era after learning that its chips could be used in industries beyond gaming

Its semiconductor chips were used in the automotive industry, for data centers, and by crypto miners. And starting in 2006, Nvidia took steps that would ultimately transform it into the AI company it’s known as today. This podcast is the second part of a three-part series diving deep into Nvidia’s company evolution.

AI's growing energy demands are driving tech companies to consider nuclear power

Big Tech has rebranded nuclear power as a green solution to address the strain on the grid from millions of people using power-hungry AI tools. As of mid-2025, generating one image uses as much electricity as charging the average smartphone, or leaving a household light bulb on for 87 consecutive days.

87% of the startups in Y Combinator’s Fall 2025 batch were AI companies

Y Combinator also recently increased its number of cohorts or “batches” per year from two to four. Its leaders cited artificial intelligence’s rise as a reason for the increase.

Malware has transitioned from notoriety-driven to profit- and data-driven

Many of the first researchers and hobbyists who created viruses and worms showed a natural curiosity in experimenting with and designing such software to make a name for themselves and advance the field of computer science. In the future, AI-augmented malware may adapt in real-time or design enhanced cryptojackers, infostealers, and ransomware for cybercriminals.

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.

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.

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

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.

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.

Indefinite cloning of some endangered species may not sustain their longevity because cloning success rates decrease as genetic mutations accumulate.

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.

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

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.

In 2025, four executives from large tech companies were given positions in the US Army Reserves—including Palantir Chief Technology Officer Shyam Sankar, which reinforced Palantir's ties with the US military and its role as a leading defense partner.

About 2,000 US babies are born annually without some portion of their limbs, potentially leading to a lifetime of pricey prosthetics.

Radioactive elements can introduce software errors because the ionizing radiation they produce can detach electrons from atoms, and computer code relies on the distribution of electrons.

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.

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.

Some Pokémon have been named after real and fictional organisms, while some real-world species have been named after Pokémon, such as Chilicola charizard and Binburrum zapdos.

Art theft is the third-largest source of criminal revenues worldwide, thanks in part to the subjective nature of valuing a work of art.

Apeirophobia is an overwhelming fear of living forever, perhaps stemming from the brain's inability to conceptualize an infinite life.

US housing costs have risen by roughly 175% between 1991 and 2026—but a growing number of Gen Zers are becoming homeowners anyway. In 2025, 4% of homebuyers were Gen Z, up from 3% the year before.

Telehealth demand for GLP-1s for weight loss is booming as consumers seek easier access.

How fusion—which releases energy when two lighter atoms combine to form a heavier atom—differs from fission

The animatronic shark from Steven Spielberg's 'Jaws,' the first modern blockbuster, was a complex underwater apparatus called 'Bruce.'

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

The word 'jazz' evolved from 'jasm,' 19th-century American slang for 'energy'

One of the most famous portraits ever taken is 'Afghan Girl' (1984) by Steve McCurry, yet the subject Sharbat Gula went much of her life without being identified or benefitting from the image's success.

In 1939, baseball star Lou Gehrig delivered his inspirational 'Luckiest Man' speech after retiring due to the health condition that now bears his name.