AIhub monthly digest: July 2024 – attending RoboCup, real-world simulators, and AI and cognitive science

by Lucy Smith

30 July 2024

Robots galore at RoboCup 2024

RoboCup is an international scientific initiative with the goal of advancing the state of the art of intelligent robots. As part of this initiative, a series of competitions and meetings are held throughout the year. The showcase event is an international affair with teams travelling from far and wide to put their machines through their paces.

This year, RoboCup 2024 took place in Eindhoven, with around 2,000 roboticists converging on the venue. Although RoboCup started out as a soccer playing competition, other leagues have since been introduced, focussing on robots in industrial, rescue, and home settings. There is even a dedicated league for young roboticists.

We were lucky enough to be able to attend in person this year and wrote a daily digest about the action, focussing on a few of the different leagues each day. You can see the write-ups here: 19 July | 20 July | 21 July.

Interview with Sherry Yang: Learning interactive real-world simulators

Sherry Yang, Yilun Du, Kamyar Ghasemipour, Jonathan Tompson, Leslie Kaelbling, Dale Schuurmans and Pieter Abbeel won an outstanding paper award at ICLR2024 for their work Learning Interactive Real-World Simulators. In the paper, they introduce a universal simulator (called UniSim) which takes image and text input to train a robot simulator. We spoke to Sherry about this work, some of the challenges, and potential applications.

Are models biased on text without gender-related language?

In their work Are Models Biased on Text without Gender-related Language?, Catarina G Belém, Preethi Seshadri, Yasaman Razeghi and Sameer Singh audit 28 popular language models to find out whether such models display gender biases in stereotype-free contexts. In this blog post, Catarina summarises their work and notes that their findings suggest that, contrary to prior assumptions, gender bias does not solely stem from the presence of gender-related words in sentences.

Interview with Yuan Yang: working at the intersection of AI and cognitive science

You may have seen our interview series where we meet some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. In this latest interview, we hear from Yuan Yang, who completed his PhD in May. Yuan’s works in the intersecting area of AI and cognitive science, focusing on how AI can help understand human core cognitive abilities, and conversely, how such understanding can facilitate the development of AI.

International Conference on Machine Learning

Another large event happening this month was the International Conference on Machine Learning (ICML2024). Taking place in Vienna, the six keynote talks tackled topics from open science to youth development, and from African languages to particle physics. You can find out what participants got up to in our social media round up. During the conference, the Test of Time award and the Best Paper awards were announced. You can see the winners here.

Summarising three papers from ICML

Speaking of ICML, Prabhu Prakash Kagitha has written accessible summaries of three papers that he found particularly interesting: “Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision”, “Interpreting and Improving Large Language Models in Arithmetic Calculation”, and “Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews”. You can read these here.

Taking on the Maths Olympiad

DeepMind models AlphaProof and AlphaGeometry 2 have been used to take on this year’s International Mathematical Olympiad, which consists of six advanced reasoning problems. DeepMind reports that the systems solved four out of the six problems, achieving the same level as a silver medalist in the competition. Mathematician Timothy Gowers explains some of the context, and qualifies the result in this handy thread.

Building a better future with data and AI

On 24 July, the Open Data Institute (ODI) released a white paper entitled: “Building a better future with data and AI”. In the document, the authors outline the ODI’s vision for AI in the UK, emphasising the need for robust data infrastructure, governance and ethical foundations to support the tech ecosystem.

Machine learning and logistic regression

IBM’s explainer series of videos continues, as Diarra Bell outlines the basics of logistic regression, its application in binary classification, and how it can be used to predict probabilities using the sigmoid function.

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Seminars in 2024
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