Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data. While consumer-facing AI tools have dazzled users with speed and ease, enterprise leaders are discovering that deploying AI a...
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
AI needs a strong data fabric to deliver business value
Artificial intelligence is moving quickly in the enterprise, from experimentation to everyday use. Organizations are deploying copilots, agents, and predictive systems across finance, supply chains, human resources, and customer operations. By the end of 2025, half of companies used AI in at least t...
AI systems have already gained impressive mastery over the digital world, but the physical world is still humanity’s domain. As it turns out, building an AI system that can compose a novel or code an app is far easier than developing one that can fold laundry or navigate a city street. To get there,...
When ChatGPT launched as an experimental prototype in late 2022, OpenAI’s chatbot became an everyday everything app for hundreds of millions of people. LLMs like ChatGPT were the new future: The entire tech industry was consumed by the inferno, with companies racing to spin up rival products. The as...
When ChatGPT was released to the public in late 2022, it opened people’s eyes to how easily generative AI could churn out vast amounts of human-seeming text from simple prompts. This quickly caught the attention of criminals, who soon began using large language models to produce malicious emails—bot...
As AI agents increasingly work alongside humans across organizations, companies could be inadvertently opening a new attack surface. Insecure agents can be manipulated to access sensitive systems and proprietary data, increasing enterprise risk. In some modern enterprises, non-human identities (NHI)...
Chinese tech workers are starting to train their AI doubles–and pushing back
Tech workers in China are being instructed by their bosses to train AI agents to replace them—and it’s prompting a wave of soul-searching among otherwise enthusiastic early adopters. Earlier this month a GitHub project called Colleague Skill, which claimed workers could use it to “distill” their co...
Roboticists used to dream big but build small. They’d hope to match or exceed the extraordinary complexity of the human body, and then they’d spend their career refining robotic arms for auto plants. Aim for C-3P0; end up with the Roomba. The real ambition for many of these researchers was the robo...
Bringing AI-driven protein-design tools to biologists everywhere
Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.
There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks — GPT versus Gemini, reasoning scores, and marginal capability gains. But in practice, the more durable advantage is structural: ...
The practice of privacy-led user experience (UX) is a design philosophy that treats transparency around data collection and usage as an integral part of the customer relationship. An undertapped opportunity in digital marketing, privacy-led UX treats user consent not as a tick-box compliance exercis...
Software engineering has experienced two seismic shifts this century. First was the rise of the open source movement, which gradually made code accessible to developers and engineers everywhere. Second, the adoption of development operations (DevOps) and agile methodologies took software from siloed...
Q&A: MIT SHASS and the future of education in the age of AI
As the School of Humanities, Arts, and Social Sciences marks 75 years, Dean Agustín Rayo reflects on how AI is reshaping higher education and why SHASS disciplines continue to be central to MIT’s mission.
Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, people, and other agents in real time, AI agents can execute entire workflows autonomously. But unlocking their potential requires redesigning processes around age...
AI is changing how small online sellers decide what to make
For years Mike McClary sold the Guardian LTE Flashlight, a heavy-duty black model, online through his small outdoor brand. The product, designed for brightness and durability, became one of his most popular items ever. Even after he stopped offering it around 2017, customers kept sending him emails ...
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.
The gig workers who are training humanoid robots at home
When Zeus, a medical student living in a hilltop city in central Nigeria, returns to his studio apartment from a long day at the hospital, he turns on his ring light, straps his iPhone to his forehead, and starts recording himself. He raises his hands in front of him like a sleepwalker and puts a…
Shifting to AI model customization is an architectural imperative
In the early days of large language models (LLMs), we grew accustomed to massive 10x jumps in reasoning and coding capability with every new model iteration. Today, those jumps have flattened into incremental gains. The exception is domain-specialized intelligence, where true step-function improveme...
AI benchmarks are broken. Here’s what we need instead.
For decades, artificial intelligence has been evaluated through the question of whether machines outperform humans. From chess to advanced math, from coding to essay writing, the performance of AI models and applications is tested against that of individual humans completing tasks. This framing is ...