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Nature Machine Intelligence Profile
Nature Machine Intelligence

@NatMachIntell

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A @SpringerNature journal on AI, robotics and machine learning. Tweets by @LCVenema

London, England
Joined November 2017
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@NatMachIntell
Nature Machine Intelligence
2 years
Nature Machine Intelligence has turned 5! Many thanks to all colleagues, authors and referees for helping us shape the journal. Read our anniversary edition of AI Reflections - interviews with recent Comment and Perspective authors https://t.co/bkU8tsibQF
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@NatureGeosci
Nature Geoscience
1 year
Focus: Artificial intelligence in geoscience - collating recent @NatureGeosci research articles that use AI methods and opinion pieces on issues relating to the application of AI to geoscience https://t.co/ZU8SuIhjCJ
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nature.com
Artificial intelligence (AI) techniques are increasingly being adopted in geoscience.
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@ebervector
maggie
1 year
So pleased to have been able to write a little commentary piece with my advisor @weixx2 for @NatMachIntell! It's about this great work by @JamesGornet and Matt Thomson taking a look at how cognitive maps can arise just from predicting visual observations:
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nature.com
Nature Machine Intelligence - Constructing spatial maps from sensory inputs is challenging in both neuroscience and artificial intelligence. A recent study demonstrates that a self-attention neural...
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@SvenNyholm
Sven Nyholm
1 year
New (short) paper by Silvia Milano (@SilviaMilano1) and me: "Advanced AI assistants that act on our behalf may not be ethically or legally feasible", in Nature Machine Intelligence (@NatMachIntell) #aiethics https://t.co/0uKTGg8xmr @MunichCenterML @LMU_Muenchen @aiatlmu
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@QingxuZhu
Qingxu Zhu
1 year
I'm thrilled to announce that our paper has been published in Nature Machine Intelligence @NatMachIntell today! To encourage research on the natural and agile movement of quadrupedal robots, we've open-sourced our code and data. Check out our project page: https://t.co/XxZo9Q5ki9
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@NatMachIntell
Nature Machine Intelligence
1 year
This year may see big advances in solving longstanding robotics challenges with generative AI - or are expectations too high? We discuss various viewpoints in our June editorial.
nature.com
Nature Machine Intelligence - In the current wave of excitement about applying large vision–language models and generative AI to robotics, expectations are running high, but conquering...
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@hannahrosekirk
Hannah Rose Kirk
1 year
Great to see our personalised LLMs article in this @NatMachIntell editorial. Increased empathy exemplifies 2nd-order effects of personalised alignment...may seem preferable in the short-term but has long-term consequences for healthy human-AI interaction https://t.co/KxYKszxfLJ
nature.com
Nature Machine Intelligence - Personalized LLMs built with the capacity for emulating empathy are right around the corner. The effects on individual users need careful consideration.
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@NatComputSci
Nature Computational Science
1 year
📢Our May issue is now live, and it includes a Perspective on computational frameworks for semiconductor discovery, a database for structure-based drug discovery, an algorithm to uncover laws of skill acquisition -- and much more! Check it out! https://t.co/6b4fOPezDc
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@pschwllr
Philippe Schwaller (he/him)
1 year
More than a year after the preprint, I’m excited to have the first @SchwallerGroup study featured on the @EPFL landing page - out in @NatMachIntell! We present how LLM agents can be augmented with chemistry tools and demonstrate some of the few first successful syntheses — from
@EPFL_en
EPFL
1 year
EPFL researchers have developed ChemCrow, an AI system that enhances chemical research by integrating advanced tools for tasks like organic synthesis and drug discovery. https://t.co/uorPmvB6cQ
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@Amit_Goldenb
Amit Goldenberg
1 year
Great questions about AI and empathy in this short piece: People cannot experience love from an LLM unless they act on the supposition that LLMs can love. Because LLMs cannot love, the experience of their love is premised on self-deception. https://t.co/O7PSEwOLMV
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@jankosinski
Jan Kosinski
1 year
This is the end of the world as we know it, if this is reproducible! The new era of functional modeling has begun. I took a transcription factor with an unknown structure and folded it with its recognition sequence embedded in longer DNA. AlphaFold3 accurately positioned the
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@andrewwhite01
Andrew White 🐦‍⬛
1 year
ChemCrow is out today in @NatMachIntell! ChemCrow is an agent that uses chem tools and a cloud-based robotic lab for open-ended chem tasks. It’s been a journey to get to publication and I’d like to share some history about it. It started back in 2022. 1/8
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@BerruetaThomas
Thomas A. Berrueta
1 year
⚡️New paper in @NatMachIntell⚡️ Embodied AI is the future, but are our algorithms ready for it? With MaxDiff RL, we reveal how continuity of experience breaks the performance of RL algorithms. Continuity is a fact of embodied experience, introducing correlations between data
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@hannahrosekirk
Hannah Rose Kirk
1 year
Published in Nature Machine Intelligence today, our new article explores the trade-offs of personalised alignment in large language models ⚖️ Personalisation has potential to democratise decisions over how LLMs behave, but brings its own set of risks... https://t.co/fROWsE64nI
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@adeenflinker
Adeen Flinker 🇮🇱🇺🇦🎗️
2 years
New paper out today in @NatMachIntell, where we show robust neural to speech decoding across 48 patients. https://t.co/rNPAMr4l68
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@skinniderlab
Michael Skinnider
2 years
Very happy to share this work testing a widespread assumption in chemical AI and showing that invalid SMILES are a feature, not a bug:
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nature.com
Nature Machine Intelligence - Generative models for chemical structures are often trained to create output in the common SMILES notation. Michael Skinnider shows that training models with the goal...
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@NatComputSci
Nature Computational Science
2 years
📢Our March issue is now live, and it’s a special one, including a Focus that highlights the state of the art, challenges, and opportunities in the development and use of digital twins across different domains. 👉 https://t.co/KvsNtDvQb8 🧵1/11
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@enzoferrante
Enzo Ferrante
2 years
We made it to the cover of Nature Machine Intelligence @NatMachIntell ! Congrats @rodbonazzola @affrangi and team! If you are interested in imaging genetics and how to discover new phenotype-genotype associations for anatomy, check it out: https://t.co/nqksOurSj6 👇
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@ayushnoori
Ayush Noori
2 years
We’re pretty excited about this work from @KyleWSwanson, @james_y_zou, @ItsJonStokes and team, out now in @NatMachIntell. Kyle kindly shared the SyntheMol preprint and code with us a few months ago, and we’ve been able extend his work in some interesting new directions. 👀 1/2
@KyleWSwanson
Kyle Swanson
2 years
I'm excited to share SyntheMol, a generative AI model for drug design optimized for creating easily synthesizable molecules. We applied our model to generate, synthesize, and validate 58 novel antibiotic candidates and found 6 potent hits. @NatMachIntell
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