Alex Murphy
@Alxmrphi
NeuroAI Curriculum Specialist @neuromatch. Technical ML/GenAI Trainer. Ex-Postdoc @amiithinks / PhD in ML & Neuroscience
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❗️Github Repo for Autumn 2023 class Machine Learning and the Brain. Three broad topics: vision 👀 language 💬and RL 🤖 Mainly centred around student paper presentations, but most taught components (+ coding workshop) recorded & uploaded (w/ slides). github.com/Alxmrphi/ml_an…
@ NeuroAI researchers. Please consider this short 10-hour/month (paid) commitment to supervise a group of budding NeuroAI researchers (part of Neuromatch's Impact Scholars Programme). I did it last year and it was one of the most fulfilling experiences I've had in recent years🤗
We’re #hiring Impact Scholar Program Supervisors! 💼 Support small scholar teams in #neuroscience, #AI, and #ClimateScience. Paid, #RemoteWork, ~10 hrs/month (Nov 2025–May 2026). Apply by Oct 3 buff.ly/c7vn0Fy
Anyone who has an interest in LLMs and human (brain) processing of language please consider this opportunity. Alona is fantastic to work with and the AI community in Edmonton is amazing (speaking from first-hand experience!)
I am hiring a post doc at @UAlberta , affiliated with @AmiiThinks ! We study language processing in the brain using LLMs and neuroimaging. Looking for someone with experience with ideally both neuroimaging and LLMs, or a willingness to learn. Email me Qs apps.ualberta.ca/careers/postin…
Our Brain and AI team will be at #ccn2025 this week: 3 highlights 1. 🏆1st place for the Algonauts competition: 🧵 below! 2.🗣Keynote: Language in the Brain: 2025.ccneuro.org/k-and-t-langua… 3. 🚀Tutorial: Scale your decoding pipeline in the notebook: docs.google.com/document/d/1is…
🏆 Thrilled to announce we reached 1st position in the Algonauts 2025 Competition with our 1B model of the brain watching movies! 📄Paper: arxiv.org/abs/2507.22229 🧑💻Code: github.com/facebookresear… 💿Data: cneuromod.ca ⚔️Challenge: algonautsproject.com/challenge.html 👇Thread:
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They've only listed those that agree☹️ I told them "I don't agree. I don't think CoT has much of a useful role to play. It's only really showing something that appears to be a meaningful trace because they're trained to appear that way, but actually they're not faithful at all"
A simple AGI safety technique: AI’s thoughts are in plain English, just read them We know it works, with OK (not perfect) transparency! The risk is fragility: RL training, new architectures, etc threaten transparency Experts from many orgs agree we should try to preserve it:…
Exciting new preprint from the lab: “Adopting a human developmental visual diet yields robust, shape-based AI vision”. A most wonderful case where brain inspiration massively improved AI solutions. Work with @lu_zejin @martisamuser and Radoslaw Cichy arxiv.org/abs/2507.03168
Last week, @Daniel_Sexton16 (7th year Neurosurgery Resident at Duke University) presented @EvansonLinnea's new paper on comparing the development of language from childhood to adulthood and how it relates to LLMs. This 🧵 explores our thoughts (🤍 & ❔)
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I am pleased to announce a new version of my RL tutorial. Major update to the LLM chapter (eg DPO, GRPO, thinking), minor updates to the MARL and MBRL chapters and various sections (eg offline RL, DPG, etc). Enjoy! arxiv.org/abs/2412.05265
“I have always been convinced that the only way to get artificial intelligence to work is to do the computation in a way similar to the human brain.” — @GeoffreyHinton 🧠
HuggingFace released a nice blog post about the current state of VLMs Here's a summary, covering recent trends, specialized capabilities, agents, video LMs, new alignment techniques, and HF's fav VLMs [1/8] Recent trends:
![gabriberton's tweet image. HuggingFace released a nice blog post about the current state of VLMs
Here's a summary, covering recent trends, specialized capabilities, agents, video LMs, new alignment techniques, and HF's fav VLMs [1/8]
Recent trends:](https://pbs.twimg.com/media/Gq-Bt8NWcAAT4El.jpg)
Really happy to see this paper out, led by @nishpathead in collaboration with @stefsmlab and @SaxeLab: we apply the statistical physics toolbox to analyse a simple model of reinforcement learning, and find some cool effects, like a speed-accuracy trade-off for generalisation 🚀
The RL-Perceptron model grants new insights into the capabilities of policy learning in neural networks, including identifying trade-offs between #speed and #accuracy, and a transition between “easy” and “hybrid-hard” learning regimes. Learn more: go.aps.org/3SnDP7L
Very happy to see our latest study featured by @AIatMeta: 'Emergence of Language in the Developing Brain', by @EvansonLinnea et al, - paper: ai.meta.com/research/publi… - thread: x.com/EvansonLinnea/… - blog: ai.meta.com/blog/meta-fair…
We’re very pleased to release our latest study ‘Emergence of Language in the Developing Brain’ Paper: tinyurl.com/5h49xpjv Blog: tinyurl.com/mrtdk8p2 The first systematic investigation of how the neural representations of language evolve as the brain develops. A…
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