ΑΙhub 2024年12月31日
AIhub monthly digest: December 2024 – attending NeurIPS, multi-agent path finding, and tackling illegal mining
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本月AIhub回顾了2024年的重要活动和研究进展。包括参加NeurIPS 2024会议,关注AI研究的科学传播和获奖论文;介绍了利用机器学习和地理空间数据定位加纳非法采矿点的研究;探讨了多智能体在连续环境中路径规划的方法;以及RoboCup与机器人公司的合作。此外,还分享了关于AI伦理和人类价值的讨论,以及对多位博士研究生的访谈。最后,回顾了2024年的精选访谈和博客文章,并提供了资源和活动页面链接。

🎉AIhub参加了NeurIPS 2024会议,举办了AI研究的科学传播会议,并关注了会议的获奖论文和数据集。

⛏️研究人员利用机器学习和地理空间数据在加纳定位非法采矿点,展示了AI在环境问题上的应用。

🤖RoboCup与Booster、Fourier和Unitree三家机器人公司合作,旨在推进机器人和AI研究,并计划在未来比赛中使用人形机器人硬件。

🤔在Vox的采访中,Shannon Vallor探讨了AI的伦理问题,强调了AI的威胁在于它可能使人类放弃自我意识和自由。

🤝AIhub还采访了多位2024 AAAI/ACM SIGAI博士联盟的参与者,并回顾了2024年的精选访谈和博客文章。

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we look back at our week attending NeurIPS, hear about work localising illegal mining sites using machine learning and geospatial data, and discover how a group of agents can minimise their journey length whilst avoiding collisions.

AIhub at NeurIPS 2024

We were lucky enough to attend the thirty-eighth Conference on Neural Information Processing Systems (NeurIPS 2024) which took place in Vancouver, Canada, from Tuesday 10 December to Sunday 15 December. On the first day of the event we held a session on science communication for AI researchers. It was great to see so many people there, and so many thoughtful questions following our presentation. You can find the webpage for the session here.

The 2024 awards for outstanding main track papers (and runners-up), outstanding datasets and benchmarks paper, and the test-of-time award were announced during the opening ceremony. You can find out who won here.

You can also find out what participants got up to in our two social media summaries: #NeurIPS2024 social media round-up part 1 | #NeurIPS2024 social media round-up part 2.

We’ll be posting more content from the conference over the coming weeks, so be sure to check out our NeurIPS collection page.

Interview with Andrews Ata Kangah: Localising illegal mining sites using machine learning and geospatial data

Andrews Ata Kangah is a team leader and researcher working on democratizing AI and AI solutions for environmental problems. We spoke to him about his research using machine learning and geospatial data to localise illegal mining sites in Ghana, and his experience attending the AfriClimate AI workshop at the Deep Learning Indaba.

Multi-agent path finding in continuous environments

Multi-agent path finding describes a problem where a group of agents (robots, vehicles, or even people) are each trying to get from their starting positions to their goal positions without colliding. In this blog post, Kristýna Janovská and Pavel Surynek write about their method for multi-agent path finding in continuous environments, where agents move on sets of smooth paths.

RoboCup teams up with Booster, Fourier and Unitree

The RoboCup Federation has announced new partnerships with three robotics companies: Booster Robotics, Fourier Intelligence and Unitree Robotics. The RoboCup Federation, an international initiative, uses the RoboCup competition series and challenges as a platform to promote and advance robotics and AI research. The aim is that the companies’ humanoid robot hardware will be used in future RoboCup competitions.

AI is not a “stochastic parrot,” it’s a mirror

In this interview in Vox, Shannon Vallor talks about some of the ideas from her new book, The AI Mirror. “One thing I hear in every country that I travel to to speak about AI is: Are humans really any different from AI? Aren’t we at the end of the day just predictive text machines? Are we ever doing anything other than pattern matching and pattern generation? That rhetorical strategy is actually what scares me. It’s not the machines themselves. It’s the rhetoric of AI today that is about gaslighting humans into surrendering their own power and their own confidence in their agency and freedom. That’s the existential threat, because that’s what will enable humans to feel like we can just take our hands off the wheel and let AI drive.”

How to benefit from AI without losing your human self

In this fireside chat from IEEE Computational Intelligence Society, Tayo Obafemi-Ajayi (Missouri State University) asks Hava T Siegelmann (University of Massachusetts, Amherst) about how to benefit from AI without losing your human self.

2024 AAAI / ACM SIGAI doctoral consortium interviews

Over the course of the year, we’ve had the privilege of meeting a number of the 2024 AAAI / ACM SIGAI doctoral consortium participants. In this collection we’ve compiled links to all of the interviews.

Looking back over 2024

We’ve had the opportunity to work with many talented researchers during 2024. In these two posts, we’ve collected some of our favourite interview and blog posts. AIhub interview highlights 2024 | AIhub blog post highlights 2024.


Our resources page
Our events page
Seminars in 2024
AAAI/ACM SIGAI Doctoral Consortium interview series
AAAI Fellows 2024 interview series
AI around the world focus series
New voices in AI series

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NeurIPS 2024 机器学习 多智能体 AI伦理 RoboCup
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