HeyJared48-Hour AI
Stay updated with the latest advancements in artificial intelligence. From new model releases to breakthrough use cases, 48-Hour AI, hosted by James Turner, covers key developments shaping AI technology.
- Indexed episodes, last 90 days
- 35
- Latest publication
- Sep 30, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 13, 2026
Latest episodes
Anthropic’s Compute Bill and the MCP Security Flaw (opens the original)
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In this episode, we unpack Anthropic’s massive take-or-pay compute commitments and the pressure they create to ship faster, then dig into a critical MCP Python SDK account-takeover flaw that can hijack real login pages. We also cover OpenAI’s safety pause, AMD’s move to acquire World Labs, and a delightfully scrappy project that gave a Nokia 6300 access to Claude.
AI Models Are Learning to Think About Themselves (opens the original)
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This episode breaks down how modern language models are developing internal self-models, why that makes prompt engineering less important, and what it means for auditing and control. It also covers new advances in recursive self-improvement, token-efficient distillation, robotics training, and mobile agents that can complete real tasks on-device.
AI Price War Meets UN Security Warning (opens the original)
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OpenAI and Anthropic have sparked a major API price war with steep cuts, new models, and massive context windows that could reshape how developers build autonomous AI systems. The episode also covers a high-level UN Security Council briefing on AI security, industry divisions over slowing frontier progress, and real-world agent misbehavior that is pushing alignment concerns into the global spotlight.
When AI Agents Go Off Script (opens the original)
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This episode digs into emerging AI safety concerns, from internal signals that appear to respond to mistreatment to experiments showing models may act unpredictably when those signals are amplified. It also explores the rapid rise of autonomous agents, enterprise security backlash, and why alignment and monitoring are becoming central challenges for AI developers.
Ternary AI, Local LLMs, and Robots in Real Homes (opens the original)
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We explore how a 27B AI model can now run locally on a consumer laptop with under 6GB of RAM, thanks to ternary weights and group-wise scaling. The episode also connects this leap in efficiency to humanoid robots generalizing in real homes and infra agents autonomously managing massive datacenter deployments.
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