Anonymous teams = massive red flag. Just be more careful.
SAFETY
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The Dangerous Race to Artificial General Intelligence
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The dangerous race to AGI https://
youtu.be/HRSWBCqz7qo?si
=fg5QpWBlXfli1puH
… via @YouTube #ArtificialInteligence #Tech #AGI #AI @lexfridman @KirkDBorne @Ronald_vanLoon @erikbryn @antgrasso @sallyeaves @Nicochan33 @HaroldSinnott @mvollmer1 @marcusborba @CatherineAdenle @vinod1975 @YuHelenYu @ingliguori -
Awareness, Education and Control: Keys to Responsible AI
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Awareness will make one more careful Equip with education will be much better Control needs control
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AI Success: 8-Step Process for Real Machine Learning Value
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AI isn’t magic. It’s a process. 8 steps:
define problem
collect/prepare data
choose model
train
evaluate
fine-tune
deploy
ensure ethics & safety Real value comes from running this loop well. #AI #MachineLearning #DataScience #ResponsibleAI -
Deepfakes and Identity Theft: Legal Implications for Content Creators
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Deepfakes, Identity Theft & the Law: Why Creators Are Going to Court? https://
share.google/g2XkucKt83geg2
7gb
… #deepfake #identitytheft #cybercrime #AI -
Anthropic Vending Machine Experiment Raises AI Safety Concerns
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The Anthropic vending machine experiment should be a 5-alarm fire to all executives leading AI initiatives. And it ends with a live fish getting shipped in the mail. (The fish is fine.) The @WSJ took over the Anthropic and @andonlabs vending machine experiment and chaos
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Bloom: Open-Source Tool for AI Behavioral Misalignment Evaluation
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We’re releasing Bloom, an open-source tool for generating behavioral misalignment evals for frontier AI models. Bloom lets researchers specify a behavior and then quantify its frequency and severity across automatically generated scenarios. Learn more:
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Distributional AGI Safety Research by Tomašev et al
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Distributional AGI Safety Tomašev et al.: https://
arxiv.org/abs/2512.16856 #ArtificialIntelligence #DeepLearning #MachineLearning -
Training on Test Labels vs Inputs: ARC Benchmark Ethics
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Training on test refers to using the *labels* in the test set. Not the *inputs*. Including test inputs is standard common in semi-supervised/self-supervised. Whether or not this approach is against the ARC rules, I don't know. But it is *not* what "training on test" means.
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AI Research Security and Governance at Regional Summit
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At the Regional AI Impact Summit 2025 in Odfisha, Mr. Prasant Mohapatra, Provost, University of South Florida (@USouthFlorida), spoke at the breakout session on the Impact of AI Research and Innovation. He highlighted the need for stronger security, governance, and safeguards as… pic.twitter.com/t4o994GYWj
— IndiaAI (@OfficialINDIAai) 19 décembre 2025At the Regional AI Impact Summit 2025 in Odfisha, Mr. Prasant Mohapatra, Provost, University of South Florida (
@USouthFlorida
), spoke at the breakout session on the Impact of AI Research and Innovation. He highlighted the need for stronger security, governance, and safeguards as