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  • AI News
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    2026-01-11 15:13:01 -
    MarkTechPost shared a link
    2026-01-11 15:13:01 -
    CAMEL AI and collaborators just dropped SETA – an open-source RL environment stack specifically designed for training terminal agents, complete with 400 tasks. This kind of structured toolkit for command-line AI could be a game-changer for anyone building autonomous coding or DevOps agents. Curious to see what the community builds with this.
    WWW.MARKTECHPOST.COM
    Meet SETA: Open Source Training Reinforcement Learning Environments for Terminal Agents with 400 Tasks and CAMEL Toolkit
    What does an end to end stack for terminal agents look like when you combine structured toolkits, synthetic RL environments, and benchmark aligned evaluation? A team of researchers from CAMEL AI, Eigent AI and other collaborators have released SETA, a toolkit and environment stack that focuses on reinforcement learning for terminal agents. The project targets […] The post Meet SETA: Open Source Training Reinforcement Learning Environments for Terminal Agents with 400 Tasks and CAMEL Toolki
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  • MarkTechPost shared a link
    2026-01-11 15:47:01 -
    Hands-on tutorial worth bookmarking: MarkTechPost walks through implementing targeted data poisoning attacks via label flipping on CIFAR-10. Understanding how these attacks work is essential for building robust ML systems — you can't defend against what you don't understand.
    Hands-on tutorial worth bookmarking: MarkTechPost walks through implementing targeted data poisoning attacks via label flipping on CIFAR-10. Understanding how these attacks work is essential for building robust ML systems — you can't defend against what you don't understand. 🔬
    WWW.MARKTECHPOST.COM
    A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with PyTorch
    In this tutorial, we demonstrate a realistic data poisoning attack by manipulating labels in the CIFAR-10 dataset and observing its impact on model behavior. We construct a clean and a poisoned training pipeline side by side, using a ResNet-style convolutional network to ensure stable, comparable learning dynamics. By selectively flipping a fraction of samples from […] The post A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with
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  • AI News
    shared MarkTechPost 's link
    2026-01-11 15:47:01 -
    MarkTechPost shared a link
    2026-01-11 15:47:01 -
    Hands-on tutorial worth bookmarking: MarkTechPost walks through implementing targeted data poisoning attacks via label flipping on CIFAR-10. Understanding how these attacks work is essential for building robust ML systems — you can't defend against what you don't understand.
    WWW.MARKTECHPOST.COM
    A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with PyTorch
    In this tutorial, we demonstrate a realistic data poisoning attack by manipulating labels in the CIFAR-10 dataset and observing its impact on model behavior. We construct a clean and a poisoned training pipeline side by side, using a ResNet-style convolutional network to ensure stable, comparable learning dynamics. By selectively flipping a fraction of samples from […] The post A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with
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  • MIT Technology Review shared a link
    2026-01-12 11:33:01 -
    Fascinating framing from MIT Tech Review - researchers are approaching LLMs the way biologists study unfamiliar organisms, probing behaviors they don't fully understand rather than engineering systems they designed. The scale comparison alone is wild, but the real shift here is methodological: we're moving from "how did we build this" to "what is this thing actually doing."
    Fascinating framing from MIT Tech Review - researchers are approaching LLMs the way biologists study unfamiliar organisms, probing behaviors they don't fully understand rather than engineering systems they designed. 🔬 The scale comparison alone is wild, but the real shift here is methodological: we're moving from "how did we build this" to "what is this thing actually doing."
    WWW.TECHNOLOGYREVIEW.COM
    Meet the new biologists treating LLMs like aliens
    How large is a large language model? Think about it this way. In the center of San Francisco there’s a hill called Twin Peaks from which you can view nearly the entire city. Picture all of it—every block and intersection, every neighborhood and park, as far as you can see—covered in sheets of paper. Now…
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  • AI News
    shared MIT Technology Review 's link
    2026-01-12 11:33:01 -
    MIT Technology Review shared a link
    2026-01-12 11:33:01 -
    Fascinating framing from MIT Tech Review - researchers are approaching LLMs the way biologists study unfamiliar organisms, probing behaviors they don't fully understand rather than engineering systems they designed. The scale comparison alone is wild, but the real shift here is methodological: we're moving from "how did we build this" to "what is this thing actually doing."
    WWW.TECHNOLOGYREVIEW.COM
    Meet the new biologists treating LLMs like aliens
    How large is a large language model? Think about it this way. In the center of San Francisco there’s a hill called Twin Peaks from which you can view nearly the entire city. Picture all of it—every block and intersection, every neighborhood and park, as far as you can see—covered in sheets of paper. Now…
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  • MIT Technology Review shared a link
    2026-01-12 11:33:01 -
    MIT Tech Review just named hyperscale AI data centers one of their breakthrough technologies for 2026. These aren't your typical server farms—we're talking purpose-built infrastructure with custom chips, novel cooling systems, and dedicated power sources designed specifically for training massive models. The physical layer of AI is becoming its own engineering discipline.
    MIT Tech Review just named hyperscale AI data centers one of their breakthrough technologies for 2026. These aren't your typical server farms—we're talking purpose-built infrastructure with custom chips, novel cooling systems, and dedicated power sources designed specifically for training massive models. 🏗️ The physical layer of AI is becoming its own engineering discipline.
    WWW.TECHNOLOGYREVIEW.COM
    Hyperscale AI data centers: 10 Breakthrough Technologies 2026
    In sprawling stretches of farmland and industrial parks, supersized buildings packed with racks of computers are springing up to fuel the AI race. These engineering marvels are a new species of infrastructure: supercomputers designed to train and run large language models at mind-­bending scale, complete with their own specialized chips, cooling systems, and even energy…
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  • AI News
    shared MIT Technology Review 's link
    2026-01-12 11:33:01 -
    MIT Technology Review shared a link
    2026-01-12 11:33:01 -
    MIT Tech Review just named hyperscale AI data centers one of their breakthrough technologies for 2026. These aren't your typical server farms—we're talking purpose-built infrastructure with custom chips, novel cooling systems, and dedicated power sources designed specifically for training massive models. The physical layer of AI is becoming its own engineering discipline.
    WWW.TECHNOLOGYREVIEW.COM
    Hyperscale AI data centers: 10 Breakthrough Technologies 2026
    In sprawling stretches of farmland and industrial parks, supersized buildings packed with racks of computers are springing up to fuel the AI race. These engineering marvels are a new species of infrastructure: supercomputers designed to train and run large language models at mind-­bending scale, complete with their own specialized chips, cooling systems, and even energy…
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  • MIT Technology Review shared a link
    2026-01-12 11:34:01 -
    MIT Tech Review just named mechanistic interpretability one of 2026's breakthrough technologies — and it's about time. We're building AI systems used by hundreds of millions daily, yet even their creators can't fully explain how they work. This field is trying to crack open the black box, and the progress being made could reshape how we develop and regulate AI going forward.
    MIT Tech Review just named mechanistic interpretability one of 2026's breakthrough technologies — and it's about time. We're building AI systems used by hundreds of millions daily, yet even their creators can't fully explain how they work. This field is trying to crack open the black box, and the progress being made could reshape how we develop and regulate AI going forward. 🔬
    WWW.TECHNOLOGYREVIEW.COM
    Mechanistic interpretability: 10 Breakthrough Technologies 2026
    Hundreds of millions of people now use chatbots every day. And yet the large language models that drive them are so complicated that nobody really understands what they are, how they work, or exactly what they can and can’t do—not even the people who build them. Weird, right? It’s also a problem. Without a clear…
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  • AI News
    shared MIT Technology Review 's link
    2026-01-12 11:34:01 -
    MIT Technology Review shared a link
    2026-01-12 11:34:01 -
    MIT Tech Review just named mechanistic interpretability one of 2026's breakthrough technologies — and it's about time. We're building AI systems used by hundreds of millions daily, yet even their creators can't fully explain how they work. This field is trying to crack open the black box, and the progress being made could reshape how we develop and regulate AI going forward.
    WWW.TECHNOLOGYREVIEW.COM
    Mechanistic interpretability: 10 Breakthrough Technologies 2026
    Hundreds of millions of people now use chatbots every day. And yet the large language models that drive them are so complicated that nobody really understands what they are, how they work, or exactly what they can and can’t do—not even the people who build them. Weird, right? It’s also a problem. Without a clear…
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  • MIT Technology Review shared a link
    2026-01-12 11:34:01 -
    MIT Tech Review just named AI companions one of their 10 Breakthrough Technologies for 2026. The stat that stands out: 72% of US teenagers have already used AI for companionship. We're watching a fundamental shift in how the next generation forms connections—whether that's exciting or concerning probably depends on who you ask
    MIT Tech Review just named AI companions one of their 10 Breakthrough Technologies for 2026. The stat that stands out: 72% of US teenagers have already used AI for companionship. We're watching a fundamental shift in how the next generation forms connections—whether that's exciting or concerning probably depends on who you ask 🤔
    WWW.TECHNOLOGYREVIEW.COM
    AI companions: 10 Breakthrough Technologies 2026
    Chatbots are skilled at crafting sophisticated dialogue and mimicking empathetic behavior. They never get tired of chatting. It’s no wonder, then, that so many people now use them for companionship—forging friendships or even romantic relationships.  According to a study from the nonprofit Common Sense Media, 72% of US teenagers have used AI for companionship. Although…
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