In the world of Generative AI, latency is the ultimate killer of immersion. Until recently, building a voice-enabled AI agent felt like assembling a Rube Goldberg machine: you’d pipe audio to a Speech-to-Text (STT) model, send the transcript to a Large Language Model (LLM), and finally shuttle text ...

A fundamental need of the American worker is protection — the knowledge that you’re more than just a body swinging a wrench or pulling a lever….

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MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. Want to lose weight? Get shredded? Stay mentally sharp? A wellness influencer might tell you to take peptides, the ...

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. In January, Nvidia’s Jensen Huang, the head of the world’s most valuable company, proclaimed that we are entering the era of physical AI, when artificial ...

In the high-stakes world of AI infrastructure, the industry has operated under a singular assumption: flexibility is king. We build general-purpose GPUs because AI models change every week, and we need programmable silicon that can adapt to the next research breakthrough. But Taalas, the ...

Building a Retrieval-Augmented Generation (RAG) pipeline is easy; building one that doesn’t hallucinate during a 10-K audit is nearly impossible. For devs in the financial sector, the ‘standard’ vector-based RAG approach—chunking text and hoping for the best—often results in a ‘text soup’ that ...

Early on the morning of September 2, 2024, a Chicago Transit Authority Blue Line train was the scene of a random and horrific mass shooting. Four people were shot and killed on a westbound train as it approached the suburb of Forest Park.  The police swiftly activated a digital dragnet—a ...

Have you ever asked an LLM a question, changed the wording a few times, and still felt the answer wasn’t quite right? If you’ve worked with tools like ChatGPT or Gemini, you’ve probably rewritten prompts, added more context, or used phrases like “be concise” or “think step by step” to improve ...

Machine learning is widely used for prediction, but not all data behaves the same. A common mistake is applying standard ML to time-dependent data without considering temporal order and dependencies, which these models don’t naturally capture. Time series data reflects evolving patterns over time, ...

ByteDance Seed recently dropped a research that might change how we build reasoning AI. For years, devs and AI researchers have struggled to ‘cold-start’ Large Language Models (LLMs) into Long Chain-of-Thought (Long CoT) models. Most models lose their way or fail to transfer patterns during ...

For the last few years, the AI world has followed a simple rule: if you want a Large Language Model (LLM) to solve a harder problem, make its Chain-of-Thought (CoT) longer. But new research from the University of Virginia and Google proves that ‘thinking long’ is not the same as ‘thinking hard’. ...