Winnie Street

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Winnie Street

Winnie Street

@winniestreet

Senior Researcher @ Google. Working on AI cognition & ethics.

Katılım Ocak 2012
245 Takip Edilen293 Takipçiler
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Ethan Mollick
Ethan Mollick@emollick·
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Alistair Stewart
Alistair Stewart@alistair___s·
Tickets to AI, Animals, & Digital Minds 2025 (AIADM 2025) this Friday to Sunday, in London and virtually, are likely to sell out in the next day or so. Learn more and book your ticket as soon as possible! Why? Because AI's a big deal and because all sentients matter 🫶
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Sentient Futures
Sentient Futures@sentfutures·
𝗪𝗲'𝗿𝗲 𝗱𝗲𝗹𝗶𝗴𝗵𝘁𝗲𝗱 𝘁𝗼 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲 @winniestreet 𝗮𝘀 𝗮 𝗦𝗽𝗲𝗮𝗸𝗲𝗿 𝗮𝘁 𝗔𝗜, 𝗔𝗻𝗶𝗺𝗮𝗹𝘀, & 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗠𝗶𝗻𝗱𝘀 𝗟𝗼𝗻𝗱𝗼𝗻 𝟮𝟬𝟮𝟱! 🧠 Winnie is a Senior Researcher on the Google Paradigms of Intelligence Team and a fellow at the Institute of Philosophy, University of London. At #AIADM25, she will be joining a panel discussion on "AI as moral agent, AI as moral patient" exploring the moral considerations of artificial intelligence systems. Her research focuses on machine cognition, AI sentience, and the relationships between intelligence, sociality, and consciousness. 🎟️ 𝗝𝗼𝗶𝗻 𝗮 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗼𝗳 𝟭𝟬𝟬+ 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗮𝗻𝗱 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗼𝗿𝘀: Link in bio! 30th May - 1st June 🗣️ Friday | Conference @ UCL | 𝗔𝗹𝗺𝗼𝘀𝘁 𝘀𝗼𝗹𝗱 𝗼𝘂𝘁 - 𝘀𝗲𝗰𝘂𝗿𝗲 𝘆𝗼𝘂𝗿 𝘀𝗽𝗼𝘁 🔴 Sat-Sun | In-person Unconference | 𝗦𝗢𝗟𝗗 𝗢𝗨𝗧 💻 Sat-Sun | Virtual Unconference | 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘀𝘁𝗶𝗹𝗹 𝗼𝗽𝗲𝗻
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Jonathan Birch
Jonathan Birch@birchlse·
An emotional day for me: I can announce I'll be the first director of The Jeremy Coller Centre for Animal Sentience at LSE, supported by a £4m grant from the Jeremy Coller Foundation. Our continuing mission: to develop better policies, laws and ways of caring for animals. 1/3
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Winnie Street
Winnie Street@winniestreet·
🚨New paper - a behavioural approach to the question of LLM sentience. We adapt a method from animal cognition and assess if LLMs can make trade-offs between points and stipulated pain penalties or pleasure rewards as a possible signal. #LLM #sentience arxiv.org/abs/2411.02432
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Jonathan Birch
Jonathan Birch@birchlse·
Can LLMs be induced to deviate from optimal gameplay in a simple game by threats of pain or promises of pleasure? And does the probability of deviating depend on the intensity of the promised pleasure/pain? According to our new paper, released today (arxiv.org/abs/2411.02432), the answer is "yes & yes" for several models. I didn't expect this - but what does it mean? The paper urges an "abundance of caution" when relating these ideas to sentience. We would regard similar behaviours as evidence of sentience in a bee or a crab, but it would be one line of evidence among many. We need more evidence in the LLM case. Complicating the picture is that LLMs are astoundingly good at role-play: mimicking the dispositions of a helpful human assistant. It seems they don't just mimic surface-level patterns ("Hey, how can I help?") but very subtle ones (I am more strongly motivated by moderate pain than by mild pain). Bees and crabs don't have the goal of mimicking a human, so there's no reason to think their behaviours are mimicry of any kind. The paper is an example of something I would like to see more of: studying LLMs using methods translated from the study of animal behaviour. Surface linguistic behaviour is an unreliable guide to an LLM's inner workings, but one way to scratch away at the surface is to investigate their motivations when faced with decision problems. With big thanks to Geoff Keeling @winniestreet @meepmeepbop @DariaZakharova9 @matilda_gibbons @mpshanahan!
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Winnie Street
Winnie Street@winniestreet·
Do you want to work on AI cognition and consciousness? (And work with me 👽) We’re looking for an ML research scientist! Apply here: google.com/about/careers/…
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徐樂 xule
徐樂 xule@LinXule·
🧠🤖 Human & AI in Organizations Symposium: Interdisciplinary Impact Join us to explore human-AI collaboration in organizations! Featuring experts from academia & industry. 📅 Sept 9, 2024 ⏰ 1-5:30 PM 📍 I-X Hub, White City Campus, @imperialcollege Speakers: • @empiricallykev (@GoogleDeepMind): Human-agent cooperation • @winniestreet (@GoogleAI): LLMs & theory of mind • @jen_gineered (@turinginst): Open AI ecosystem • @lujainmibrahim (@UniofOxford): Human-AI interaction evaluations Panels: 1. Human-AI Synergies: Martin Anthony from @LSEDataScience 2. Trustworthy AI: @AidanPeppin from @CohereForAI 3. Final Discussion: Susan Scott from @ImperialBiz & @ImperialX_AI Thanks to Kevin Corley & Mark Kennedy (@ImperialDSI) for their leadership! Register: haiosymposium.com #AIinOrganizations #HumanAICollaboration
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Chaz Firestone
Chaz Firestone@chazfirestone·
wait i thought we actually like doing science
Sakana AI@SakanaAILabs

Introducing The AI Scientist: The world’s first AI system for automating scientific research and open-ended discovery! sakana.ai/ai-scientist/ From ideation, writing code, running experiments and summarizing results, to writing entire papers and conducting peer-review, The AI Scientist opens a new era of AI-driven scientific research and accelerated discovery. Here are 4 example Machine Learning research papers generated by The AI Scientist. We published our report, The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery, and open-sourced our project! Paper: arxiv.org/abs/2408.06292 GitHub: github.com/SakanaAI/AI-Sc… Our system leverages LLMs to propose and implement new research directions. Here, we first apply The AI Scientist to conduct Machine Learning research. Crucially, our system is capable of executing the entire ML research lifecycle: from inventing research ideas and experiments, writing code, to executing experiments on GPUs and gathering results. It can also write an entire scientific paper, explaining, visualizing and contextualizing the results. Furthermore, while an LLM author writes entire research papers, another LLM reviewer critiques resulting manuscripts to provide feedback to improve the work, and also to select the most promising ideas to further develop in the next iteration cycle, leading to continual, open-ended discoveries, thus emulating the human scientific community. As a proof of concept, our system produced papers with novel contributions in ML research domains such language modeling, Diffusion and Grokking. We (@_chris_lu_, @RobertTLange, @hardmaru) proudly collaborated with the @UniOfOxford (@j_foerst, @FLAIR_Ox) and @UBC (@cong_ml, @jeffclune) on this exciting project.

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Antikythera
Antikythera@antikythera_xyz·
Antikythera’s summer studio “Cognitive Infrastructures” has assembled 15 Studio Researchers from across AI disciplines to develop speculative proposals about futures for social and machine intelligence: Alasdair Milne @aldmilne — Serpentine and King's College London PhD researcher Cezar Mocan @DrawingMoving — artist and programmer Chloe Loewith — Cambridge Center of the Future of Intelligence MPhil graduate in Ethics of AI, Data and Algorithms student Daniele Cavalli @DanieleSC321300 — École normale supérieure PhD researcher and lecturer Gary Zhang @garyzhexizhang — writer, filmmaker and researcher Iulia Ionescu — University of the Arts London interdisciplinary artist and technologist Ivar Frisch @FrischIvar — Utrecht University MSc student and TNO research intern Jackie Kay @jackayline — Google DeepMind research engineer and University College London PhD student Jenn Leung @jennnital — University of the Arts London lecturer and technical artist Michelle Chang — Google software engineer and MIT Media Lab and CMU research affiliate Philip Moreira Tomei @synchroaphasia— AI/ML researcher Sonia Bernaciak — Royal College of Art and the Hong Kong Polytechnic University researcher in artificial and distributed intelligence Tyler Farghly @tylerfarghly — University of Oxford PhD student in theoretical ML Winnie Street @winniestreet — Google DeepMind Senior AI researcher Yannis Siglidis @YSiglidis — University of Ecole Des Ponts ParisTech computer vision researcher
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Winnie Street@winniestreet·
Delighted to share our new paper examining LLM theory of mind at higher orders (spoiler: GPT-4 exceeds adult performance on the highest-order task). We discuss the role of scale & finetuning, as well as ethical implications of LLM ToM. Lmk what you think! arxiv.org/abs/2405.18870
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Winnie Street
Winnie Street@winniestreet·
Delighted to share a new paper examining LLM theory of mind at higher-orders (spoiler: GPT-4 exceeds adult performance at the highest-order task). We discuss the role of scale and finetuning + ethical implications of LLM ToM. Lmk what you think! arxiv.org/abs/2405.18870
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Qiaosi (Chelsea) Wang 🦋@qiaosiwang
✨That’s a wrap for our first workshop on Theory of Mind in Human AI Interaction at #chi2024 💕Despite all the technical difficulties everyone was so patient, supportive, and engaged throughout the paper talks, group activities, and invited panel.
Qiaosi (Chelsea) Wang 🦋@qiaosiwang tweet mediaQiaosi (Chelsea) Wang 🦋@qiaosiwang tweet mediaQiaosi (Chelsea) Wang 🦋@qiaosiwang tweet media
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Winnie Street
Winnie Street@winniestreet·
@sumit_ast Thank you so much, Sumit! It was so great to meet you, and I very much enjoyed your talk, too!
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Sumit Asthana
Sumit Asthana@sumit_ast·
@winniestreet Winnie posed very thought-provoking arguments in #CHI2024's Theory of Mind workshop on LLM Theory of Mind, alignment, and human values at the individual and group levels!
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