Computer scientist Louis Castricato was in his eighth year studying large language models—the artificial intelligence technology behind chatbots like ChatGPT and Claude—when he started to feel like he was hitting a dead end.Computer scientist Louis Castricato was in his eighth year studying large language models—the artificial intelligence technology behind chatbots like ChatGPT and Claude—when he started to feel like he was hitting a dead end.Machine learning & AI[#item_full_content]
When a building inspector takes a photo of a cracked wall, a leaking pipe or a faulty ceiling panel, that image carries almost no information about where exactly it was taken. There’s no GPS signal indoors, and manually recording locations is slow, error-prone and easily forgotten. As a result, thousands of inspection photos sit in folders with no spatial context, making it hard to track problems over time or link them to the correct part of a building’s maintenance records.When a building inspector takes a photo of a cracked wall, a leaking pipe or a faulty ceiling panel, that image carries almost no information about where exactly it was taken. There’s no GPS signal indoors, and manually recording locations is slow, error-prone and easily forgotten. As a result, thousands of inspection photos sit in folders with no spatial context, making it hard to track problems over time or link them to the correct part of a building’s maintenance records.Engineering[#item_full_content]
Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, Abishek Thamma (University of Amsterdam) and Micha Heilbron (Max Planck Institute for Psycholinguistics) show that small language models equipped with a transient memory learn grammar more efficiently when trained on child-scale amounts of language input. The findings demonstrate how insights from psycholinguistics can inspire new approaches to AI learning. The findings are published in the journal Transactions of the Association for Computational Linguistics.Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, Abishek Thamma (University of Amsterdam) and Micha Heilbron (Max Planck Institute for Psycholinguistics) show that small language models equipped with a transient memory learn grammar more efficiently when trained on child-scale amounts of language input. The findings demonstrate how insights from psycholinguistics can inspire new approaches to AI learning. The findings are published in the journal Transactions of the Association for Computational Linguistics.[#item_full_content]
Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, Abishek Thamma (University of Amsterdam) and Micha Heilbron (Max Planck Institute for Psycholinguistics) show that small language models equipped with a transient memory learn grammar more efficiently when trained on child-scale amounts of language input. The findings demonstrate how insights from psycholinguistics can inspire new approaches to AI learning. The findings are published in the journal Transactions of the Association for Computational Linguistics.Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, Abishek Thamma (University of Amsterdam) and Micha Heilbron (Max Planck Institute for Psycholinguistics) show that small language models equipped with a transient memory learn grammar more efficiently when trained on child-scale amounts of language input. The findings demonstrate how insights from psycholinguistics can inspire new approaches to AI learning. The findings are published in the journal Transactions of the Association for Computational Linguistics.Computer Sciences[#item_full_content]
Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.Hardware[#item_full_content]
Cate Blanchett brought Hollywood star power to Brussels on Tuesday as she launched a free tool to give people the right to decide how their image can be used by AI firms.Cate Blanchett brought Hollywood star power to Brussels on Tuesday as she launched a free tool to give people the right to decide how their image can be used by AI firms.Machine learning & AI[#item_full_content]
A new chip developed by MIT researchers could help tiny, low-power UAVs avoid obstacles as they zip around tight corners inside an industrial HVAC system to check for gas leaks. The chip allows small autonomous robots and other battery-limited devices to construct detailed 3D maps of their environments in real time using only about as much power as a single LED. A robot could use such a map to plan a collision-free path to reach its goal.A new chip developed by MIT researchers could help tiny, low-power UAVs avoid obstacles as they zip around tight corners inside an industrial HVAC system to check for gas leaks. The chip allows small autonomous robots and other battery-limited devices to construct detailed 3D maps of their environments in real time using only about as much power as a single LED. A robot could use such a map to plan a collision-free path to reach its goal.[#item_full_content]
A technology developed at the Technion enables ordinary users to create realistic video clips intuitively, without the need for massive computing resources. Called Time-to-Move (TTM), it offers unprecedented control over the movement of objects and characters in AI-generated videos using nothing more than mouse movements, eliminating the need for complex and expensive infrastructure or training on millions of videos.A technology developed at the Technion enables ordinary users to create realistic video clips intuitively, without the need for massive computing resources. Called Time-to-Move (TTM), it offers unprecedented control over the movement of objects and characters in AI-generated videos using nothing more than mouse movements, eliminating the need for complex and expensive infrastructure or training on millions of videos.Software[#item_full_content]
It may look like a picture of a panda bear to you, but to your business’s AI agent, it can act like a skeleton key, bypassing safety safeguards and potentially causing the model to generate harmful, misleading or policy-violating outputs.It may look like a picture of a panda bear to you, but to your business’s AI agent, it can act like a skeleton key, bypassing safety safeguards and potentially causing the model to generate harmful, misleading or policy-violating outputs.Security[#item_full_content]
As governments, companies and public institutions move from experimenting with AI to deploying it in the real world, questions are becoming increasingly urgent: What does it mean to trust AI? And what does it take for that trust to be earned?As governments, companies and public institutions move from experimenting with AI to deploying it in the real world, questions are becoming increasingly urgent: What does it mean to trust AI? And what does it take for that trust to be earned?Machine learning & AI[#item_full_content]
