Forecast Founder Seed Valuations for AI Researchers

Forecast what 116 AI researchers could raise at seed if they left their labs to found AGI startups. The forecaster searches each researcher's publication record, lab affiliation, public profile, and the recent Sutskever/Murati/LeCun comparables, then returns a calibrated p10 through p90 valuation distribution per row.

Metric	Value
Rows processed	116
Forecast type	numeric
Total cost	$9
Time	~9 minutes

Add FutureSearch to Claude Code if you haven't already:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

Then ask Claude:

Find a list of prominent AI researchers who haven't yet started AGI startups,
then forecast the seed valuation each would command if they did. Exclude anyone
who has already founded an AGI lab (Sutskever, Murati, LeCun, Hassabis, the
Anthropic cofounders, etc.).

Claude first dispatches a research agent to compile the list, then runs futuresearch_forecast over the resulting rows:

Tool: futuresearch_agent
├─ task: "Compile a list of ~120 prominent AI researchers active at frontier
│         labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR, Mistral, xAI,
│         academic labs). Exclude founders of existing AGI startups."
├─ return_table: true
└─ response_schema: {name, affiliation, known_for}

→ Returned 116 researchers.

Tool: futuresearch_forecast
├─ data: [{"name": "Noam Brown", "question": "If Noam Brown founded an
│          AGI-related startup today, what would its seed-round valuation
│          be in billions USD?", ...}, ... 115 more]
├─ forecast_type: "numeric"
├─ output_field: "valuation"
├─ units: "billions USD"
└─ context: "Assume an AGI-related startup announced today with a completed
            seed round; the founder recruits prominent researchers but is the
            most prominent person."

→ Submitted: 116 rows for forecasting.
  Session: https://futuresearch.ai/sessions/2f1b8a47-9c3d-4e6f-b8a2-7d1e5c0a3f48
  Task ID: 2f1b...

Tool: futuresearch_progress
├─ task_id: "2f1b..."
→ Running: 0/116 complete, 116 running (30s elapsed)

...

Tool: futuresearch_progress
→ Completed: 116/116 (0 failed) in 540s.

Tool: futuresearch_results
├─ task_id: "2f1b..."
├─ output_path: "/Users/you/researcher_valuations.csv"
→ Saved 116 rows to /Users/you/researcher_valuations.csv

View the session. See the companion guide for the general pattern.

Add the FutureSearch connector if you haven't already. Then ask Claude:

Find a list of prominent AI researchers who haven't yet started AGI startups, then forecast the seed valuation each would command if they did. Assume an AGI-related startup announced today with a completed seed round, where the founder recruits other prominent researchers but is the most prominent person. Exclude existing AGI-startup founders (Sutskever, Murati, LeCun, Hassabis, the Anthropic cofounders).

Results take about 9 minutes.

Go to futuresearch.ai/app and enter:

Find a list of prominent AI researchers who haven't yet started AGI startups, then forecast the seed valuation each would command if they did. Assume an AGI-related startup announced today with a completed seed round, where the founder recruits other prominent researchers but is the most prominent person. Exclude existing AGI-startup founders (Sutskever, Murati, LeCun, Hassabis, the Anthropic cofounders).

Numeric forecasting returns valuation_p10 through valuation_p90 as floats, plus a units column and a rationale explaining the research behind each row.

pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here  # Get one at futuresearch.ai/app/api-key

import asyncio
import pandas as pd
from futuresearch import create_session
from futuresearch.ops import forecast

researchers_df = pd.DataFrame([
    {
        "name": "Noam Brown",
        "question": "If Noam Brown founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Research scientist at OpenAI. Best known for poker AIs (Libratus, Pluribus) and OpenAI's o1 reasoning model.",
    },
    {
        "name": "Geoffrey Hinton",
        "question": "If Geoffrey Hinton founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Turing Award winner, 'godfather of deep learning'. Currently focused on AI safety advocacy after leaving Google in 2023.",
    },
    {
        "name": "Alec Radford",
        "question": "If Alec Radford founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Lead author on GPT-1, GPT-2, CLIP, Whisper, and DALL-E. Has advised Mira Murati's Thinking Machines.",
    },
    {
        "name": "Tri Dao",
        "question": "If Tri Dao founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Created FlashAttention, co-created Mamba. Princeton CS, Together AI. Focus on compute efficiency.",
    },
    {
        "name": "John Jumper",
        "question": "If John Jumper founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Lead scientist at DeepMind behind AlphaFold2. Shared the 2024 Nobel Prize in Chemistry.",
    },
    # ... 111 more researchers
])

async def main():
    async with create_session(name="AI Researcher Seed Valuations") as session:
        result = await forecast(
            session=session,
            input=researchers_df,
            forecast_type="numeric",
            output_field="valuation",
            units="billions USD",
            context=(
                "Assume an AGI-related startup announced today with a completed "
                "seed round; the founder recruits prominent researchers but is "
                "the most prominent person."
            ),
        )
        return result.data

results = asyncio.run(main())
print(results[["name", "valuation_p10", "valuation_p50", "valuation_p90", "units"]])

Results

The top 8 researchers by median forecasted seed valuation:

Researcher	p10	p50 (median)	p90
Noam Brown	$1.4B	$6.7B	$13.8B
Geoffrey Hinton	n/a	$5.8B	n/a
Alec Radford	$1.0B	$4.3B	$11.0B
John Jumper	n/a	$2.7B	n/a
Yoshua Bengio	n/a	$2.3B	n/a
Tri Dao	n/a	$1.8B	n/a
Andrew Yao	$0.28B	$1.4B	$5.3B
Been Kim	n/a	$0.93B	n/a

The wide ranges reflect real uncertainty about each researcher's commercial appeal. Andrew Yao spans $280M to $5.3B almost entirely because of US-China geopolitics: the low end assumes capital decoupling severely limits his investor base, while the high end assumes sovereign-wealth backing as a Chinese "national champion" in AI. Alec Radford's $1B to $11B range is the gap between a deliberately small research lab and an OpenAI-mafia mega-seed in the Sutskever/Murati tier.

The forecast ran at the default LOW effort level. With 116 rows, well above the threshold where LOW becomes the right cost/quality tradeoff, the per-row cost works out to roughly $0.08.

Going deeper

Long-form analysis: Which AI researchers have the most valuable skills?
Companion guide: Forecast outcomes for a list of entities

Forecast Founder Seed Valuations for AI Researchers

Metric

Value

Rows processed

116

Forecast type

numeric

Total cost

Time

~9 minutes

Add FutureSearch to Claude Code if you haven't already:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

Then ask Claude:

Find a list of prominent AI researchers who haven't yet started AGI startups,
then forecast the seed valuation each would command if they did. Exclude anyone
who has already founded an AGI lab (Sutskever, Murati, LeCun, Hassabis, the
Anthropic cofounders, etc.).

Claude first dispatches a research agent to compile the list, then runs futuresearch_forecast over the resulting rows:

Tool: futuresearch_agent
├─ task: "Compile a list of ~120 prominent AI researchers active at frontier
│         labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR, Mistral, xAI,
│         academic labs). Exclude founders of existing AGI startups."
├─ return_table: true
└─ response_schema: {name, affiliation, known_for}

→ Returned 116 researchers.

Tool: futuresearch_forecast
├─ data: [{"name": "Noam Brown", "question": "If Noam Brown founded an
│          AGI-related startup today, what would its seed-round valuation
│          be in billions USD?", ...}, ... 115 more]
├─ forecast_type: "numeric"
├─ output_field: "valuation"
├─ units: "billions USD"
└─ context: "Assume an AGI-related startup announced today with a completed
            seed round; the founder recruits prominent researchers but is the
            most prominent person."

→ Submitted: 116 rows for forecasting.
  Session: https://futuresearch.ai/sessions/2f1b8a47-9c3d-4e6f-b8a2-7d1e5c0a3f48
  Task ID: 2f1b...

Tool: futuresearch_progress
├─ task_id: "2f1b..."
→ Running: 0/116 complete, 116 running (30s elapsed)

...

Tool: futuresearch_progress
→ Completed: 116/116 (0 failed) in 540s.

Tool: futuresearch_results
├─ task_id: "2f1b..."
├─ output_path: "/Users/you/researcher_valuations.csv"
→ Saved 116 rows to /Users/you/researcher_valuations.csv

View the session. See the companion guide for the general pattern.

Add the FutureSearch connector if you haven't already. Then ask Claude:

Find a list of prominent AI researchers who haven't yet started AGI startups, then forecast the seed valuation each would command if they did. Assume an AGI-related startup announced today with a completed seed round, where the founder recruits other prominent researchers but is the most prominent person. Exclude existing AGI-startup founders (Sutskever, Murati, LeCun, Hassabis, the Anthropic cofounders).

Results take about 9 minutes.

Go to futuresearch.ai/app and enter:

Find a list of prominent AI researchers who haven't yet started AGI startups, then forecast the seed valuation each would command if they did. Assume an AGI-related startup announced today with a completed seed round, where the founder recruits other prominent researchers but is the most prominent person. Exclude existing AGI-startup founders (Sutskever, Murati, LeCun, Hassabis, the Anthropic cofounders).

Numeric forecasting returns valuation_p10 through valuation_p90 as floats, plus a units column and a rationale explaining the research behind each row.

pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here  # Get one at futuresearch.ai/app/api-key

import asyncio
import pandas as pd
from futuresearch import create_session
from futuresearch.ops import forecast

researchers_df = pd.DataFrame([
    {
        "name": "Noam Brown",
        "question": "If Noam Brown founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Research scientist at OpenAI. Best known for poker AIs (Libratus, Pluribus) and OpenAI's o1 reasoning model.",
    },
    {
        "name": "Geoffrey Hinton",
        "question": "If Geoffrey Hinton founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Turing Award winner, 'godfather of deep learning'. Currently focused on AI safety advocacy after leaving Google in 2023.",
    },
    {
        "name": "Alec Radford",
        "question": "If Alec Radford founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Lead author on GPT-1, GPT-2, CLIP, Whisper, and DALL-E. Has advised Mira Murati's Thinking Machines.",
    },
    {
        "name": "Tri Dao",
        "question": "If Tri Dao founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Created FlashAttention, co-created Mamba. Princeton CS, Together AI. Focus on compute efficiency.",
    },
    {
        "name": "John Jumper",
        "question": "If John Jumper founded an AGI-related startup today, what would its seed-round valuation be in billions USD?",
        "background": "Lead scientist at DeepMind behind AlphaFold2. Shared the 2024 Nobel Prize in Chemistry.",
    },
    # ... 111 more researchers
])

async def main():
    async with create_session(name="AI Researcher Seed Valuations") as session:
        result = await forecast(
            session=session,
            input=researchers_df,
            forecast_type="numeric",
            output_field="valuation",
            units="billions USD",
            context=(
                "Assume an AGI-related startup announced today with a completed "
                "seed round; the founder recruits prominent researchers but is "
                "the most prominent person."
            ),
        )
        return result.data

results = asyncio.run(main())
print(results[["name", "valuation_p10", "valuation_p50", "valuation_p90", "units"]])

Results

The top 8 researchers by median forecasted seed valuation:

Researcher

p10

p50 (median)

p90

Noam Brown

$1.4B

$6.7B

$13.8B

Geoffrey Hinton

n/a

$5.8B

n/a

Alec Radford

$1.0B

$4.3B

$11.0B

John Jumper

n/a

$2.7B

n/a

Yoshua Bengio

n/a

$2.3B

n/a

Tri Dao

n/a

$1.8B

n/a

Andrew Yao

$0.28B

$1.4B

$5.3B

Been Kim

n/a

$0.93B

n/a

The forecast ran at the default LOW effort level. With 116 rows, well above the threshold where LOW becomes the right cost/quality tradeoff, the per-row cost works out to roughly $0.08.