My colleagues are hosting a workshop for this years #GECCO: evolving-self-organisation-workshop.github.io/gecco-2026/ The headline is Evolving Self-Organisation. Can't wait to see all your interesting submissions! Great for #ALife and #ALICE researchers as well!

Neural Network Quines: training a model to output its own weights arxiv.org/abs/1803.05859

Neural Network Quine

Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems. Here we describe how to build and train self-replicating neural networks. The n...

arxiv.org

Looking forward to this!

Elias Najarro@najarro.science · 11mo ago

We're excited to announce final program of the @alife2025.bsky.social SONI session which will host a panel discussion with @blaiseaguera.bsky.social, @risi.bsky.social, @emilydolson.bsky.social & Sidney Pontes-Filho Check out the full program: sites.google.com/view/soni-al... See you in Kyoto ⛩️

These perspectives formulated by Joe Hudson resonate a lot with me as an AI researcher with a background in psychology every.to/thesis/knowl...

Knowledge Work Is Dying—Here’s What Comes Next

While AI devours information-based roles, OpenAI, Alphabet, and Apple are investing in wisdom work—and you can, too

every.to

Introducing The Darwin Gödel Machine sakana.ai/dgm The Darwin Gödel Machine is a self-improving agent that can modify its own code. Inspired by evolution, we maintain an expanding lineage of agent variants, allowing for open-ended exploration of the vast design space of such self-improving agents.

“Continuous Thought Machines” Blog → sakana.ai/ctm Modern AI is powerful, but it's still distinct from human-like flexible intelligence. We believe neural timing is key. Our Continuous Thought Machine is built from the ground up to use neural dynamics as a powerful representation for intelligence.

arxiv.org/abs/2504.01990

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust pe...

arxiv.org

New submission deadline: April 2nd! So still some time to put interesting thoughts on Evolving Self-Organization together! Also: We are very fortunate to have the great Risto Miikkulainen as the keynote speaker at the workshop! Can't wait to see you all there! 🤩🙌 #Evolution #Gecco #ALife

Joachim W Pedersen@joachimwpedersen.bsky.social · last yr.

Join us for the Evolving Self-Organisation workshop at #GECCO this year! Great chance to submit your favourite ideas concerning self-organisation processes and evolution, and how they interact. Relevant for Alifers #ALife and anyone interested in #evolution, #self-organisation, and #ComplexSystems.

www.youtube.com/watch?v=jnoa... Bio-Inspired Plastic Neural Nets that continually adapt their own synaptic strengths can make for extremely robust locomotion policies! Trained exclusively in simulation, the plastic networks transfer easily to the real world, even under various extra OOD situations.

[IROS25] Bio-Inspired Plastic Neural Nets for Zero-Shot Out-of-Distribution Generalization in Robots

YouTube video by Worasuchad Haomachai

youtube.com

Remember that 4-page submissions of early results are also welcome! Also, does anyone know if #GECCO has an official 🦋 account? I cannot seem to find it...

Joachim W Pedersen@joachimwpedersen.bsky.social · last yr.

Join us for the Evolving Self-Organisation workshop at #GECCO this year! Great chance to submit your favourite ideas concerning self-organisation processes and evolution, and how they interact. Relevant for Alifers #ALife and anyone interested in #evolution, #self-organisation, and #ComplexSystems.

Join us for the Evolving Self-Organisation workshop at #GECCO this year! Great chance to submit your favourite ideas concerning self-organisation processes and evolution, and how they interact. Relevant for Alifers #ALife and anyone interested in #evolution, #self-organisation, and #ComplexSystems.

Sebastian Risi@risi.bsky.social · last yr.

We're excited to announce the first Evolving Self-organisation workshop at GECCO 2025! Submission deadline: March 26, 2025 More information: evolving-self-organisation-workshop.github.io

Ever wish you could coordinate thousands of units in games such as StarCraft through natural language alone? We are excited to present our HIVE approach, a framework and benchmark for LLM-driven multi-agent control.

With all the research coming from Sakana AI, this figure needs to be updated fast! direct.mit.edu/isal/proceed... #LLM #ALife #ArtificialIntelligence

hardmaru@hardmaru.bsky.social · 2y ago

Transformer²: Self-adaptive LLMs arxiv.org/abs/2501.06252 Check out the new paper from Sakana AI (@sakanaai.bsky.social) paper. We show the power of an LLM that can self-adapt its weights to its environment!

Transformer²: Self-adaptive LLMs arxiv.org/abs/2501.06252 Check out the new paper from Sakana AI (@sakanaai.bsky.social) paper. We show the power of an LLM that can self-adapt its weights to its environment!

Sakana AI@sakanaai.bsky.social · 2y ago

We’re excited to introduce Transformer², a machine learning system that dynamically adjusts its weights for various tasks! sakana.ai/transformer-... Adaptation is a remarkable natural phenomenon, like how the octopus blends into its environment, or how the brain rewires itself after injury. 🧵 1/N

Vi har samlet et starter pack med forskere og repræsentanter fra ITU på Bluesky. Mød dem her 👇 go.bsky.app/E8WJwXS

Can Dynamic Neural Networks boost Computer Vision and Sensor Fusion? We are very happy to share this awesome collection of papers on the topic!

Fabio Montello@zioictus.bsky.social · 2y ago

First little project of the year: an awesome collection of papers on Dynamic Neural Networks for Computer Vision and Sensor Fusion! Each paper comes with a brief summary and code link. 👉 github.com/DTU-PAS/awes...

If microchip ~= silicon then AGI ~= huge pile of sand

Neural Attention Memory Models are evolved to optimize the performance of Transformers by actively pruning the KV cache memory. Surprisingly, we find that NAMMs are able to zero-shot transfer its performance gains across architectures, input modalities and even task domains! arxiv.org/abs/2410.13166

Sakana AI@sakanaai.bsky.social · 2y ago

An Evolved Universal Transformer Memory sakana.ai/namm/ Introducing Neural Attention Memory Models (NAMM), a new kind of neural memory system for Transformers that not only boost their performance and efficiency but are also transferable to other foundation models without any additional training!

In deep learning research, we often categorize meta-learning approaches as either gradient-based or black-box meta-learning. In my PhD thesis, I argued that it can sometimes be useful to classify approaches based on how the outer-loop optimization affects the inner-loop optimization.

Like 130,000 others, I made a starter pack. This one is people working on or with evolutionary computation in its many forms: genetic algorithms, genetic programming, evolution strategies. If you like to be added, or suggest someone else, message me or reply to this post.

For the Blueskyers interested in #NeuroAI 🧠🤖, I created a starter pack! Please comment on this if you are not on the list and working in this field 🙂 go.bsky.app/CscFTAr

A visionary Ross Ashby writing this, 62 years ago: “A type of system that deserves much more thorough investigation is the large system that is built of parts that have many states of equilibrium” csis.pace.edu/~marchese/CS... #ComplexSystems #Cybernetics

Here's an attempt to bring together ALife researchers and enthusiasts here, who am I missing? go.bsky.app/LgoJN2N

Nothing like a country-side writing retreat in cozy surroundings! Expect new things from the Grow-AI project soon!