mikelma (@mimalazz) 's Twitter Profile
mikelma

@mimalazz

PhD student in the Intelligent Systems Group at EHU/UPV.
I do research on RL, continual RL, and open-endedness.
I also like climbing and bizarre music.

ID: 1862239266731905025

calendar_today28-11-2024 20:57:14

7 Tweet

3 Followers

93 Following

ISG (@isg_ehu) 's Twitter Profile Photo

Publication of a survey: "Adversarial Attacks in Explainable Machine Learning: A Survey of Threats Against Models and Humans" intelligentsystemsgroup.blogspot.com/2024/11/public…

Publication of a survey: "Adversarial Attacks in Explainable Machine Learning: A Survey of Threats Against Models and Humans"
intelligentsystemsgroup.blogspot.com/2024/11/public…
Sebastian Risi (@risi1979) 's Twitter Profile Photo

Excited to share our latest work: “Bio-Inspired Plastic Neural Networks for Zero-Shot Out-of-Distribution Generalization in Complex Animal-Inspired Robots” 🪲🦎 We show that Hebbian learning outperforms LSTM-based adaptation for real-world transfer. It even works without domain

Jingyu Song (@justsimonjust) 's Twitter Profile Photo

Introducing OceanSim: A High-Fidelity, GPU-Accelerated Underwater Robotics Simulator 🌊 Explore our project website: umfieldrobotics.github.io/OceanSim/ OceanSim is built for realistic & efficient underwater robot simulation. #Robotics #UnderwaterRobotics #OpenSource

Haider. (@slow_developer) 's Twitter Profile Photo

Richard Sutton says that the current dominance of LLMs is a "momentary fixation" the real breakthroughs will come from scaling computation, not building AI systems based on how humans think they work. LLMs will not be the leading edge of AI for more than another decade, perhaps

Yi Ma (@yimatweets) 's Twitter Profile Photo

In the quest to understand intelligence, the roles of the industry and the academia seem to be switched: While most young folks in academia are dying to work on technology (wanting to work for the industry for more data and compute), while the folks in industry like to declare

METR (@metr_evals) 's Twitter Profile Photo

We ran a randomized controlled trial to see how much AI coding tools speed up experienced open-source developers. The results surprised us: Developers thought they were 20% faster with AI tools, but they were actually 19% slower when they had access to AI than when they didn't.

We ran a randomized controlled trial to see how much AI coding tools speed up experienced open-source developers.

The results surprised us: Developers thought they were 20% faster with AI tools, but they were actually 19% slower when they had access to AI than when they didn't.
Jakob Foerster (@j_foerst) 's Twitter Profile Photo

Our benchmarks test knowledge and skill, but what matters is exploration and discovery. Same disconnect is true for our education system.