Google just dropped Med-PaLM 2, and it's scoring 86.5% on medical diagnosis tests. That's not just impressive for an AI model—that's better than most human doctors on standardized medical exams.

While everyone's been focused on ChatGPT and GPT-4, Google quietly built something that could actually save lives. Med-PaLM 2 doesn't just answer medical questions. It analyzes patient histories, lab results, and medical images simultaneously to generate comprehensive treatment recommendations. And here's the kicker: it's based on PaLM-2, which Google designed to work offline on your phone.

This isn't just another large language model announcement. PaLM-2's smallest variant runs entirely on mobile devices while keeping 70% of the full model's capabilities. That means AI diagnosis tools could soon work in remote clinics with no internet connection.

In This Episode:

> How Med-PaLM 2 achieved human-level medical reasoning

> Why Google's offline AI strategy changes everything for developing countries

> The 100+ programming languages PaLM-2 understands and why that matters

> Real-world deployment scenarios already being tested in hospitals

James breaks down what makes PaLM-2 different from other AI models and why Google's quiet approach might be more effective than OpenAI's flashy releases. Plus, the implications for healthcare access in areas where specialist doctors are scarce.

Timestamps:

00:00 Med-PaLM 2's breakthrough results

02:30 How it actually works with medical data

05:15 PaLM-2's offline capabilities explained

07:45 Real hospital pilots and early results

10:20 What this means for healthcare access

> Follow Unboxed for daily AI updates that actually matter. James covers the developments changing your world right now, not just the hype.

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