Analytics, BIG data, ML/AI Predictive Models FIRST - CRMportals Inc.- netAIsys, and Institute of Analytics USA - Billion people predictive inspirations
๐จ Google just dropped 150 pages on Health AI Agents. 7,000 annotations. 1,100 expert hours โ but the real value isnโt in the big metrics. Itโs the shift in design philosophy.
Instead of a monolithic โDoctor-GPT,โ Googleโs Personal Health Agent (PHA) orchestrates 3 specialists:
โธ Data Science Agent โ analyzes wearables + labs.
โธ Domain Expert Agent โ grounds outputs in medical knowledge + checks facts.
โธ Health Coach Agent โ guides conversations, goals, empathy.
10 benchmarks.
7,000 annotations.
1,100+ expert hours.
The outcome?
More accurate insights.
More trusted summaries.
Stronger engagement than baseline LLMs.
The orchestrator ties them together with memory (user goals, barriers, insights).
โก Results
โธ Outperformed baselines across 10 benchmarks.
โธ End-users preferred PHA over single-agent + parallel systems (20 participants, 50 personas).
โธ Experts rated it 5.7%โ39% better than baselines on complex health queries.
โก Design principles
โธ Address comprehensive user needs.
โธ Adaptive support โ dynamically combine agents.
โธ Low user burden โ donโt ask for data you can infer.
โธ Keep it simple โ avoid unnecessary latency.
โก User journeys tested
โข General health Q&A
โข Personal data interpretation (wearables, biomarkers)
โข Wellness advice (sleep, nutrition, activity)
โข Symptom assessment (still limited, no diagnosis)
โก Limitations + future
โธ Slower than single-agent (244s vs 36s avg).
โธ Needs safeguards: bias audits, privacy, regulatory compliance.
โธ Next frontier: adaptive style โ empathy vs accountability depending on user state.
โก The takeaway
Googleโs PHA shows the path forward:
Not a โsuper doctor bot.โ
But modular, specialized, agentic crews.
Healthcare is just the first test.
Tomorrow: finance, law, education, science.
Google 150 Health AI Agents: https://t.co/cDp9kCiPxm
โฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃโฃ
โซธ From confused to confident AI agent builder in 30 days?
Stop watching tutorials. Start building.
๐ฏ๐ฌ ๐๐ฎ๐๐ ร ๐ญ ๐๐ผ๐๐ฟ/๐๐ฎ๐ = ๐๐ ๐๐ด๐ฒ๐ป๐ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐
โ 9 real-world agents
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๐ ๐ฆ๐๐ฎ๐ฟ๐ ๐ฌ๐ผ๐๐ฟ ๐ฏ๐ฌ-๐๐ฎ๐ ๐๐ผ๐๐ฟ๐ป๐ฒ๐ (๐ฑ๐ฒ% ๐ข๐๐): https://t.co/5i2v1fIrhJ
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GIF file explaining how Transformers are doing the encoding... the other half is how the decoding is done... which is not here. Nonetheless, a great effort by the creator.
@shushant_l Hi Shushant, thanks for the post. How do we know these are not just videos taken and prompt engineering statement is reverse engineered; in other words, this is not done by AI, but posted using actual videos? Thanks
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