4 experts across 3 network communities independently surfaced this.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Dr. Rachael Bedard's essay highlights the tension every med educator is feeling: AI makes experienced clinicians better, and it may keep trainees from ever building the judgment needed to check it (never-skilling). I'm currently teaching clinical students a…”
evidence ↗
4 experts
3 communities
1 sources clustered
Concern & critique
1 expert
Risks, limits and unintended consequences.
“I don’t mean this as a criticism of this piece, but this was obvious from the start. If you don’t know anything, AI is a substitute, not a tool. www.nytimes.com/2026/09/25/o...”
Building & implementation
1 expert
How teams are shipping and applying it.
“Dr. Rachael Bedard's essay highlights the tension every med educator is feeling: AI makes experienced clinicians better, and it may keep trainees from ever building the judgment needed to check it (never-skilling). I'm currently teaching clinical students a…”
Anthropic Claude Opus 5.5 launch
5 experts across 4 network communities independently surfaced this.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Stephen Turner
“"Because Opus 5.5 is comparable to Claude Mythos 5.1 in biology and cybersecurity, we’re deploying it with safeguards similar to those on Claude Fable 5.1." www.anthropic.com/claude-opus-...”
evidence ↗
5 experts
4 communities
1 sources clustered
“"Because Opus 5.5 is comparable to Claude Mythos 5.1 in biology and cybersecurity, we’re deploying it with safeguards similar to those on Claude Fable 5.1." www.anthropic.com/claude-opus-...”
“Opus 5.5 better and cheaper than Opus 5 — typically 40% cheaper, $4/mtok input, $20/mtok out www.anthropic.com/claude-opus-...”
3 experts discussed this · 14 posts
Tim Kellogg: Opus 5.5 better and cheaper than Opus 5 — typically 40% cheaper, $4/mtok input, $20/mtok out www.anthropic.com/claude-opus-...
Tim Kellogg: it writes fine
Tim Kellogg: Sonnet 5.5 & Haiku 5.5 coming soon
Open the full discussion →
clinical AI global hospital scaling
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
clinical AI global scaling lessons
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 22 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
clinical AI hospital million patients scaling
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 24 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 24 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 28 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 28 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 30 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 30 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 34 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 34 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 36 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 36 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 40 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
Established
AI field signal
Signal
4d ago
⚡ 40 h early
2 directory members surfaced this signal.
Why this matches
Building & implementation reaction
1 attributable expert contribution
· Scott McGrath
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
evidence ↗
2 experts
1 community
1 sources clustered
“Over a million patients were screened for diabetic eye disease as Google scaled its clinical tool across India, Thailand, and Australia. One of the biggest challenges wasn't the model itself; it was sorting out camera operator turnover, local workflows, and…”
