AI UK 2024: Camden Council case study
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by Lucy Smith
3d ago
Hosted by The Alan Turing Institute, AI UK is a yearly event that brings together representatives from government, academia and industry to showcase data science and AI research and innovation in the UK. This year, the two-day conference featured talks, panel discussions, and hands-on workshops, and participants could attend in-person or remotely. One of the sessions focussed on an on-going case study in a London borough whereby the local council is using data and AI to help inform their decision making, and to improve what they do. This panel discussion, chaired by Timandra Harkness, feature ..read more
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How will generative artificial intelligence affect political advertising in 2024?
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by University of Illinois
5d ago
Illinois advertising professor Michelle Nelson says voters should expect to see a lot more generative AI in political ads during the 2024 election cycle, warning that it might be difficult to impossible to tell what’s real and what’s fake. Photo credit: L. Brian Stauffer By Lois Yoksoulian It’s estimated that $12 billion will be spent on political ads this [USA] election cycle – 30% more than in 2020. The sheer volume of ads is remarkable, and there is vast potential to use this political information to contribute to democracy: to reach more potential voters and provide accurate information. T ..read more
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Using machine learning to discover stiff and tough microstructures
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by MIT News
1w ago
A new computational pipeline developed over three years efficiently identifies stiff and tough microstructures suitable for 3D printing in a wide range of engineering applications. The approach greatly reduces the development time for high-performance microstructure composites and requires minimal materials science expertise. Image credit: Alex Shipps/MIT CSAIL. By Rachel Gordon Every time you smoothly drive from point A to point B, you’re not just enjoying the convenience of your car, but also the sophisticated engineering that makes it safe and reliable. Beyond its comfort and protective fea ..read more
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Interview with Raffaele Galliera: Deep reinforcement learning for communication networks
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by Lucy Smith
1w ago
The AAAI/SIGAI Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. This year, 30 students were selected for this programme, and we’ve been meeting them and talking about their research. In this interview, Raffaele Galliera, tells us about his work on deep reinforcement learning for communication networks. Could you give us a quick introduction – where are you studying and what’s the main topic of your research? My name is ..read more
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Machine learning helps improve quality assurance for wind turbines
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by EPFL
1w ago
By Sandrine Perroud Faulty wind turbine blades can incur huge costs for the companies that operate them, especially if the defects go unnoticed until it’s too late. That’s why quality assurance is such a strategic issue for global wind-turbine manufacturers. Today, quality inspections are limited to surface inspection of limited areas as these composite structures roll off the production line. But under a new approach co-created by EPFL and University of Glasgow researchers, inspection engineers can use a new patented radar technology, combined with an AI assistant, to detect possible anomali ..read more
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#AAAI2024 workshops round-up 3: human-centric representation learning, and AI to accelerate science and engineering
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by AIhub
1w ago
In this third round-up article of the workshops at AAAI 2024, we hear from the organisers of the workshops on: Human-Centric Representation Learning AI to Accelerate Science and Engineering Human-Centric Representation Learning Organisers: Dimitris Spathis, Aaqib Saeed, Ali Etemad, Stefanos Laskaridis, Shohreh Deldari, Sana Tonekaboni, Patrick Schwab, Shyam Tailor, Ian Tang. The Human-Centric Representation Learning workshop at AAAI 2024 brought together researchers who are broadly interested in modern representation learning for human-centric data. Representation learning has become a key ..read more
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The shift from models to compound AI systems
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by BAIR blog
1w ago
By Matei Zaharia, Omar Khattab, Lingjiao Chen, Jared Quincy Davis, Heather Miller, Chris Potts, James Zou, Michael Carbin, Jonathan Frankle, Naveen Rao, Ali Ghodsi AI caught everyone’s attention in 2023 with Large Language Models (LLMs) that can be instructed to perform general tasks, such as translation or coding, just by prompting. This naturally led to an intense focus on models as the primary ingredient in AI application development, with everyone wondering what capabilities new LLMs will bring. As more developers begin to build using LLMs, however, we believe that this focus is rapidly c ..read more
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Interview with Aaquib Tabrez: explainability and human-robot interaction
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by Lucy Smith
1w ago
The AAAI/SIGAI Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. This year, 30 students were selected for this programme, and we’ve been meeting them and talking about their research. In this interview, Aaquib Tabrez tells us about his work at the intersection of explainability and human-robot interaction. Tell us a bit about your PhD – where are you studying, and what is the topic of your research? I am doing my PhD at ..read more
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#AAAI2024 workshops round-up 2: AI for credible elections, and are large language models simply causal parrots?
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by AIhub
2w ago
A packed room for the workshop “Are Large Language Models Simply Causal Parrots?” Photo credit: Emily McMilin. In this second round-up of the workshops at AAAI 2024, we hear from the organisers of the workshops on: Are Large Language Models Simply Causal Parrots? AI for Credible Elections: A Call To Action with Trusted AI Are Large Language Models Simply Causal Parrots? Organisers: Matej Zečević, Amit Sharma, Lianhui Qin, Devendra Singh Dhami, Alex Molak, Kristian Kersting. The aim of this workshop was to bring together researchers interested in identifying to what extent we could consider t ..read more
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Forthcoming machine learning and AI seminars: March 2024 edition
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by Lucy Smith
2w ago
This post contains a list of the AI-related seminars that are scheduled to take place between 11 March and 30 April 2024. All events detailed here are free and open for anyone to attend virtually. 11 March 2024 Role of Analytics Professionals in Building a Data Driven Culture Speaker: Pooja Dewan (Otis Elevator Company) Organised by: Machine Learning NeEDS Mathematical Optimization Join here. Navigating Tomorrow: Putting People at the Helm of Maritime Digitalization and Automation Speaker: Mashrura Musharraf (Aalto University) Organised by: Finnish Center for Artificial Intelligence Zoom link ..read more
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