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Reposted by Vincent Mai

Yoshua Bengio @yoshuabengio.bsky.social · 16d

Establishing where we collectively draw red lines is essential to prevent unacceptable AI risks.

See the statement signed by myself and over 200 prominent figures:
red-lines.ai

200+ prominent figures endorse Global Call for AI Red Lines

AI could soon far surpass human capabilities and escalate risks such as engineered pandemics, widespread disinformation, large-scale manipulation of individuals including children...

red-lines.ai

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Vincent Mai @vincentmai.bsky.social · 20d

You are right. I am sorry. I will remove my post.

It is very difficult, and stressful, to see the US going there. Being outside and therefore unable to do anything about it makes me feel powerless. I wish more would be done by those who can.
It is unfair to judge though. I am not in this position.

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Vincent Mai @vincentmai.bsky.social · 21d

To friends worried about the US some months ago, I said things were OK as long as people like Kimmel could make fun of the president night after night in a large audience TV show.

This is not OK anymore. This country is running at fast speed into dark territory. Gotta wake up, American people. Now.

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Reposted by Vincent Mai

Le Monde @lemonde.fr · Aug 26

L’ONU se dote d’un groupe d’experts scientifiques sur l’intelligence artificielle

Le secrétaire général des Nations unies, Antonio Guterres, va lancer un appel à candidatures pour identifier les quarante futurs membres du groupe, qui siégeront pour trois ans.

www.lemonde.fr

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Vincent Mai @vincentmai.bsky.social · Aug 24

The article is also available on arXiv for when the Elsevier free sharing is over: arxiv.org/abs/2411.14618

Active Learning-Based Optimization of Hydroelectric Turbine Startup to Minimize Fatigue Damage

Hydro-generating units (HGUs) play a crucial role in integrating intermittent renewable energy sources into the power grid due to their flexible operational capabilities. This evolving role has led to...

arxiv.org

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Vincent Mai @vincentmai.bsky.social · Aug 24

It's among my favorite projects because 1) we used DL to reduce the costs of clean energy production 2) we managed to deal with many real-world and real-time constraints, and 3) it's fun to use neural nets to control enormous machines!

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Vincent Mai @vincentmai.bsky.social · Aug 24

We ran this on a real turbine and achieved a 42% reduction of strain amplitude after only 7 startups, compared to the standard one. It's significant! We now aim at making it generally applicable for different types of turbines (this was for a Francis, Kaplans have an additional dimension).

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Vincent Mai @vincentmai.bsky.social · Aug 24

Once the model is trained with enough data (or when we have used most of the startup budget), we finalize by optimizing the strain only. The parameters are always tested on the turbine, allowing to confirm the predictions with ground truth measurements.

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Vincent Mai @vincentmai.bsky.social · Aug 24

The virtual sensors are integrated in a black box optimization loop, which also includes a turbine dynamics simulator. For several startups, we use active learning, with an ensemble and optimism under uncertainty, to output the parameters to run next to get the most informative data for the model.

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Vincent Mai @vincentmai.bsky.social · Aug 24

This is where machine learning comes into play. We use a neutral networks to create a "virtual sensor" predicting the strain amplitude for a given turbine strain. It is trained on the trajectories we currently have measured.

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Vincent Mai @vincentmai.bsky.social · Aug 24

The challenge is that the sensors for strain (which leads to fatigue and cracks) don't last long on such turbines. They get flushed away! We have ~10 tries only to find the best set of parameters which will reduce the strain amplitude.

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Vincent Mai @vincentmai.bsky.social · Aug 24

The strain is what leads to fatigue and cracks. As every turbine is different, it's hard to know in advance which startup parameters lead to the lowest strain. We have to figure it out during the commissioning campaign, when the turbine is placed in the dam.

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Vincent Mai @vincentmai.bsky.social · Aug 24

There are different ways to start a turbine. Startup parameters control the vane opening/rotation speed trajectory until the desired speed is reached. They lead to different strains on the turbine blades.

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Vincent Mai @vincentmai.bsky.social · Aug 24

As renewable energies are integrated in the power grid, hydroelectric turbines are expected to be stopped and started more frequently. But startups are a major source of fatigue on the turbine blades and reduce turbines' lifetime.

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Vincent Mai @vincentmai.bsky.social · Aug 24

One of the most fun projects I worked on.
It's not everyday you can train a neural net on a laptop in a hydroelectric dam to provide commands in real time to start a gigantic turbine!
authors.elsevier.com/a/1lfNk3QJ-d...

authors.elsevier.com

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Reposted by Vincent Mai

Yoshua Bengio @yoshuabengio.bsky.social · Aug 20

It was a pleasure to meet Prime Minister @mark-carney.bsky.social and Minister Evan Solomon today as part of an official visit at @mila-quebec.bsky.social with many collaborators from our AI ecosystem. We discussed AI risk mitigation, sovereignty & economic potential among other important topics.

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Reposted by Vincent Mai

Cathy Wu @cathywu.bsky.social · Aug 11

This project was 4 years in the making and it's finally out!

We found that controlling vehicle speeds to mitigate traffic across a city can cut carbon emissions between 11 and 22 percent. To do this, we used deep reinforcement learning to optimize one million eco-driving scenarios. 🚗🤖🧠

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Vincent Mai @vincentmai.bsky.social · Aug 8

It is not only impressive, it is absolutely fascinating. One cannot be scientifically curious and not be thrilled. Yet the consequences of this new knowledge may be harmful, because of society.
This is hard to grapple with for someone who believes knowledge should be inherently good.

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Reposted by Vincent Mai

RL for Real Systems @RLC2025 @rl4rsworkshop.bsky.social · Aug 5

Eugene Vinitsky: Building capable, controllable simulation agents through reinforcement learning

RL4RS Workshop at @rl-conference.bsky.social

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Reposted by Vincent Mai

RL for Real Systems @RLC2025 @rl4rsworkshop.bsky.social · Aug 4

📍 The RL4RS Workshop is happening tomorrow at
University of Alberta, as part of @rl-conference.bsky.social.

Join us for a focused day on real-world applications of Reinforcement Learning.

🗓️ Full Schedule: rl4rs.github.io/RL4RS/schedu...

We hope to see you there.

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Reposted by Vincent Mai

Reinforcement Learning Conference @rl-conference.bsky.social · Jun 25

Propose some socials for RLC! Research topics, affinity groups, niche interests, whatever comes to mind!

rl-conference.cc/call_for_soc...

RLC Call for Workshops

rl-conference.cc

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Reposted by Vincent Mai

RL for Real Systems @RLC2025 @rl4rsworkshop.bsky.social · May 30

We’ve received several requests from authors, and in response, the submission deadline for the RL4RS Workshop at RLC has been extended to June 2nd (Anywhere on Earth).

Check out the Call for Papers and submission link below — we look forward to your contributions!

rl4rs.github.io/RL4RS/

Workshop on RL4RS

Workshop on on Practical Insights into RL for Real Systems.

rl4rs.github.io

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Reposted by Vincent Mai

Reinforcement Learning Conference @rl-conference.bsky.social · May 27

Reminder that early registration for RLC closes on the 30th! Please register early to save yourself some money and help us get the word out.

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Reposted by Vincent Mai

RL for Real Systems @RLC2025 @rl4rsworkshop.bsky.social · May 20

🚨 10 days left to submit to RL4RS workshop @ RLC 2025! 🤖💡

Consider sharing your insights if you're working on applied RL in industry, society, or critical systems!

Cfp: rl4rs.github.io/RL4RS/call_f...

Call For Papers

Workshop on on Practical Insights into RL for Real Systems.

rl4rs.github.io

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Vincent Mai @vincentmai.bsky.social · May 16

Ça a été une leçon d'humilité et une occasion d'apprentissage? (Un peu moins négatif?)

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