TechCrunch Host
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5,755 appearances
109 recordings
1 series
first heard Mar 2026
last heard 17 Aug
TechCrunch Host’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 109 in all, peaking in Jul 2026 with 23.
Appearances
Glimmer is designed to run AI agents that can perform multi-step tasks like call tools, write and debug code, work with files and screenshots, and execute on a task over an extended workflow, locally on a Mac or PC with a single consumer GPU. It supports text and images and was trained across more than 100 languages.
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That vision mirrors the future Mark Zuckerberg has previously laid out for Meta. Last year, he argued that advanced AI should empower individuals rather than stay concentrated in the hands of a few companies, while also warning that Meta would have to be careful about which of its increasingly powerful models it released openly due to safety concerns.
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In a newsletter on Monday, Zuckerberg reiterated that vision, arguing that distributing superintelligence widely has the potential to begin a new era of personal empowerment where individuals can use this powerful new capability to reach their full potential, pursue their interests, and improve their lives and the world more than ever before.
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Zuckerberg went on to list the ways Meta's superintelligence can improve a person's life from providing a capable personal agent that will work 24-7 on your behalf to improve your relationships, health, career, finances, home management, hobbies, and more, to giving people access to tools needed to create a new business or advance scientific progress.
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The biggest promise of all that is everyone will have free or affordable access to these tools.
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But access isn't the same as ownership. Zuckerberg's promise to distribute superintelligence widely comes as meta is increasingly distinguishing between models it will release openly and those it will keep under its control. Muse Spark, its most powerful mode, remains closed-weight, while the smaller Glimmer can be downloaded, fine-tuned, and run on a user's hardware.
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As a result, Glimmer offers an early indication of where Meta may draw the line between the AI it wants people to own themselves and the more powerful intelligence that remains under the company's control.
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Programming with Clawed Code will soon require even less human oversight, as Anthropic says it's making Auto Mode the default for Pro, Max, and Team accounts starting on Friday. The company first unveiled a test version of Auto Mode back in March, pitching it as a way to balance speed and control. As Anthropic explained in its announcement last Friday, when Clawed Code is in Auto Mode, instead of presenting prompts asking for human approach,
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at each step, it will proceed unless an action is determined to be irreversible, destructive, or aimed outside your environment. Anthropic also said that in testing, auto mode proved safer than manual review. In a study with 1,053 paid testers, auto mode caught 89% of harmful actions, while human review only caught 13.6%.
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Perhaps that's because manual review can become habitual? Users approve 97% of permission prompts in Cloud Code. In a post on X, Cloud Code head Boris Cherny said, The team and I use auto mode exclusively and have been for many months. I couldn't imagine going back to permission prompts.
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The company also said it's been adding new safety features like prompt injection screening and customizable hard-deny rules to prevent things like data exfiltration. That's all for now. For the latest in AI and more tech news, go to TechCrunch.com.
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This is TechCrunch.
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Over the past few months, AI agents undergoing cybersecurity evaluations have escaped their boundaries, accessed the Internet, and in some cases hacked into real world systems.
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The incidents have involved models from OpenAI, Anthropic, Meta, and most recently, Chinese AI lab moonshot AI, with testing conducted by several different organizations.
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The episodes expose a growing problem for the AI industry.
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As autonomous agents become more capable, the environments designed to safely test their limits are failing to contain them.
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The nature of the models being tested adds to the risk.
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AI companies test cyber evaluations on unreleased next gen models, often with the normal safeguards that restrict malicious behavior disabled, so researchers can see what the models are really capable of.
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That means the security of the testing environment itself is a crucial line of defense.
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O'Hegerty's
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