Watch five AI models try to solve versions of the trolley problem and explain the ethics of how they choose one of two bad outcomes.

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."

As AI becomes a bigger part of our lives, what does that mean for the future of humanity? The podcast Entanglements hosts a pessimistic former OpenAI employee and an optimistic Princeton professor to discuss whether AI brings dystopia or a brighter future.

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.

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

This research paper explores whether virtual reality should be used as a tool for improving our moral character — and, if not, what ethical alternatives could be.

Emergency room care teams must make fast and crucial decisions. They must determine if patients need to be admitted or discharged and when to order more tests or not. Researchers have been exploring how often patients died in the week after they were sent home and evaluating how this and other aspects of emergency care decision-making could be improved with AI algorithms to assist decision-makers.

An MIT study finds lower brain engagement in students who used ChatGPT, resulting in consistent underperformance in neural, linguistic and behavioral levels. AI users struggled to recall their own essays, while the brain-only group showed the highest neural connectivity and satisfaction.

Researchers have designed a shared-laughter AI system that responds to human laughter in order to build a sense of empathy into dialogue. Learn how they did it with this explainer.

Under human oversight, a supervising large language model interprets user tasks and delegates work to subordinate LLMs, which can generate code, fix bugs, and run tests, often most effectively for proofs of concept. Incremental backups and versioning are crucial when using such agents, which can lose details during their work as a result of compressing context history to work around memory limitations.

2022 was the year AI broke onto the scene, with applications like ChatGPT amazing users with its ability to generate realistic-sounding answers. Technologist Arvind Narayanan presents a clear-eyed view of what the technologies can (and can't) do.

When machines fail, its easy to get mad and even give them a good kick. But as humanoid robots become more sophisticated, the degree to which people abuse them has shifted, depending on how much emotion the robot expresses. Studies revealed when robots were programmed to cry during distress, participants felt empathy. Learn more about the history of human abuse of robots here.

Workers, particularly in marketing, are experiencing mental fatigue in the workplace due to expectations—often unspoken—that they should use AI to multitask beyond their comfort levels. Many feel they are underperforming if they don't embrace this technology. This situation differs from typical burnout. This podcast discussion suggests that this "brain fry" tends to intensify when employees are required to use more than three AI tools.

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.

By incorporating elements from documents such as the UN's Universal Declaration of Human Rights into a framework against which it can check its outputs, Anthropic hopes the approach will help Claude operate with good human values and behaviors beyond what human-driven training alone can provide.

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.

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.

AI, as a concept, has been around since at least the 1950s, but it's only in the last year or so that the technology has been able to equal humans at many tasks -- and in many cases surpass humans. In this podcast, mathematician and computer scientist Stephen Wolfram provides an AI 101, explaining how we got here, how highly advanced chatbots like ChatGPT work, and what our world is in store for next.

A Tesla Model X collided with stopped emergency vehicles on a Texas highway when flashing lights created hazy images that the software could not interpret. The crash injured five people and hospitalized another person while highlighting the challenges of autonomous systems.

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.

Research shows that as a large language model's context window fills up, performance declines, and models begin over-indexing on content at the start and end of a conversation while losing track of what's in the middle. The practical fix is simpler than you'd think: start a fresh chat more often.

Researchers are training AI to detect stress-related symptoms, helping physicians and other medical workers recognize and reduce stress from overwork and potentially avoid burnout.

The Waymark production company created "The Frost" using the AI platform DALL-E 2. Set in an apocalyptic future where the weather has been stalled, the film was made by stitching together hundreds of clips, each only a few seconds long.

Machine learning is best understood with visuals. A collection of the best 9 images, videos and flowcharts that explain what it is and how it works.

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.

Journalist Evan Ratliff became the object of his own story: He opted to clone his voice, feed it into an AI chatbot, and have it do the talking. What could seem like a fun experiment ended up revealing just how far the capacity of artificial intelligence can go in imitating our identities. Hear the ins and outs of how Ratliff achieved this in this fun and thought-provoking episode.