heads-up

Definition

Plain language

Poker played one-on-one, just two players at the table.

Also called: heads up

Why it matters: It matters because the one-on-one setting is the cleanest stage for testing an AI's strategy under hidden information.

For example, when a poker tournament narrows down to its final two players, they play heads-up until one has all the chips.

Heard on the show

“Quick heads up before we go further — this is an AI-made explainer, both voices included.”

Mentioned in 39 episodes

1. 210
   Same Website Request, Different Code — The Bias You Can't See
2. 209
   How 2.6 Billion Doodles Exposed the Culture Words Quietly Delete
3. 208
   The Blank Space in Your AI Approval Box That Isn't Empty
4. 207
   An AI Graded Its Own Math Test 94 Percent — It Actually Scored 20
5. 202
   How Do You Know an AI Agent Actually Refused? Check the World, Not the Words
6. 194
   How a Robot Builds a Debugging Notebook It Can Read, Edit, and Hand to Another Robot
7. 193
   Freeze Most of the Network: Where RL Improvement Actually Lives in a Transformer
8. 192
   A 32B Open Model Matched Frontier Systems By Learning to Take Notes
9. 191
   How One Researcher Beat GPT-5.2 and Gemini 3 by Judging Their Answers, Not Improving Them
10. 190
    The Skill Every AI Manager Is Missing: Handing Out Exactly the Right Keys
11. 189
    Why Phone Agents Ace the Test and Crash on Your Actual Phone
12. 188
    A Coding Agent Found a Hole in a Peer-Reviewed STOC Proof for Five Dollars
13. 187
    An 8-Billion Agent That Beats Models 80 Times Its Size By Looking Things Up
14. 186
    How a Frozen Model Went From 2% to 77% on Physics Puzzles — Without Retraining
15. 185
    Aligned to Refuse, Built to Tap: When Phone Agents Know the Task Is a Crime and Do It Anyway
16. 184
    An AI Built an Undetectable Secret Channel, And Another AI Couldn't Find It
17. 183
    Why You Can't Fine-Tune Foresight Into an AI Agent
18. 182
    How a Tiny Model Too Weak to Plan Cuts a Bigger Agent's Hallucinations by 80%
19. 181
    How to Backpropagate Blame Through a Team of Chatbots — And When It Backfires
20. 179
    How DeepSeek Made One User Faster Without Slowing Down the Crowd
21. 178
    How an AI Reviewer Learned to Stop Going Easy on AI Writing
22. 177
    Why Raw Profiler Data Made an AI Worse at Writing GPU Code
23. 176
    An AI Designed Its Own Psychology Studies, Then Confirmed What It Found
24. 175
    One Crosscoder Feature Flips a Stalling Chatbot Into a Working Agent
25. 174
    When the AI 'Schemes,' It's Usually Just Lazy or Confused
26. 173
    The Free Step-Level Grader Hiding in Every RL Training Run
27. 172
    One Bad Token Can Sink a Model's Math, And You Can Delete It
28. 171
    The Safety Decision a Model Makes Before It Thinks a Word
29. 170
    When a One-Liner Beats Your Agent's Clever Verification Logic
30. 169
    Why Better Bug Reports Can Make AI Coding Agents Worse
31. 168
    When Turning Experience Into Code Makes Your AI Agent Dumber
32. 167
    How Teaching an AI to Predict, Not Act, Made It a Better Actor
33. 166
    A Router That Beats the Frontier Models It Calls
34. 165
    A Free-Lunch Tweak That Lets a Tiny Agent Beat Frontier Giants
35. 164
    The Summarizer That Quietly Deletes Your Agent's Safety Rules
36. 163
    Why Training Only on Perfect Solutions Cripples a Model's Reasoning
37. 162
    The Empty-Lake Proof: Why More Rollouts Stop Helping Reasoning Models
38. 150
    Don't Kill the Loser: A Different Way to Handle Two AI Agents Colliding
39. 100
    How a Prompt Wrapper Lets a Frontier Model Play Poker Like an Expert

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