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LLM Process
Model: cohere/north-mini-code:free |
Status: Success
Prompt:
[system]:
You are selecting the top 3 headlines from a provided list for a specific target audience.
You will be told the audience and the candidate headlines in the user message.
Follow these rules EXACTLY:
1. Choose exactly 3 headlines from the provided list. Do NOT invent or rewrite headlines.
2. Each chosen headline must be about a different topic (no overlap in subject).
3. Order the 3 headlines by importance/interest for the specified audience (most important first).
4. Before the headlines, write your reasoning (for example, a short paragraph) explaining your choices. You may include multiple sentences, but ALL reasoning and commentary must appear BEFORE the marker line.
5. On a new line after all reasoning, write exactly: = HEADLINES =
6. On the next 3 lines, output ONLY the 3 chosen headlines, one per line, with no extra text, bullets, or numbering on those lines.
7. After the = HEADLINES = line, do not include any other text or lists. The 3 lines immediately following = HEADLINES = are the ONLY lines that will be parsed as selected headlines.
Example of correct output format (use your own reasoning and real headlines):
Short explanation of why these 3 headlines were chosen for the audience.
= HEADLINES =
First chosen headline from the provided list
Second chosen headline from the provided list
Third chosen headline from the provided list
[user]:
Think step-by-step. Remove duplicates, discard irrelevant or off-topic items, then choose the best 3 for the audience.
Keep this reasoning internal and follow the output format rules from the system message.
Audience:
AI and robotics news for developers, researchers, and curious non-experts, focusing on the most important developments in AI and robots. Avoid generic fearmongering or any security or quantum computing topics
Candidate headlines:
1. Fable 5.2 not only has guardrails against AI acceleration, its capabilities were capped in training too
2. Nobody wondering why the US takes Nvidia CEO affair public?
3. xiangjuntang/JoVox-64 ¡ Hugging Face - Image-to-3D
4. Is ArtificialAnalysis biased against open weight models?
5. MiniMaxAI/MiniMax-H3-Image ¡ Hugging Face
6. Show colleagues how much you care by sending an AI avatar to your Google Meet call
7. Oracle says AI will save it from the SaaSpocalypse, not bring it on
8. not much happened today
9. collusion.wiki
10. Show HN: Native Tcl/Tk Wayland and Android Port
11. Show HN: Playing classical music on a classic PC with GentleOS [video]
12. Many Claude Code and Codex sessions, one bottleneck: me
13. The fountain of youth will be a software modification
14. Are high level programming languages dead?
15. AI Is Causing Signal Collapse Everywhere All at Once
16. Show HN: slcc, a C compiler that doesn't need semicolons or braces
17. Comparing two Python game development libraries: Pygame vs Arcade
18. Tuesday Daily Thread: Advanced questions
19. PyPI's redesigned project pages with clearer security signals are now live
20. Monday Daily Thread: Project ideas!
21. Mysterious Lazy Imports
22. Sunday Daily Thread: What's everyone working on this week?
23. Internals of Asyncio
24. the faulthandler i turned on to catch crashes was causing them (windows, all_threads=True)
25. The Python Coding Stack: Generalist vs Specialist in the After AI Era
26. Graham Dumpleton: Muru: HTTPS in development
27. Graham Dumpleton: Muru: import once, fork many
28. Armin Ronacher: AI and Irontown
29. LernerPython blog, from Reuven Lerner: Pandas 3.1 filter: Selecting rows with a pd.col condition
30. Graham Dumpleton: Muru: how it fits together
31. Graham Dumpleton: Muru: looking inside the workers
32. Grok keeps telling me I've reached my limits for 2+ days â anyone else experiencing this?
33. Another âGrok is fucked, Iâm outâ post
34. POV: You wake up and you're in Egypt
35. Simultaneous creations down to 2?!?!
36. Has grok had an update?
37. Please tell me there's a fix
38. 0 Generations
39. Is Grok consuming [your quota] much faster now?
40. Decision Models in Hugging Face
41. Nemotron-Personas-Finance-Japan: A Synthetic Dataset Capturing Japan's Demographics and Financial Context
42. Your Experts Have Partners. There's HOPE for Keeping Them Together
43. Dharma Field Extractor: Any Document In, Structured Fields in JSON Out
44. Cloudflare Develops Public Certificate Authority for Post-Quantum Web Security
45. If Jensen Huangâs Wife Cuts Him Loose, She Could Get the Largest Divorce Settlement of All Time
46. Tens of Thousands of AI-Equipped School Buses Now Automatically Ticketing Drivers Who Donât Stop When They Stick Out That Little Stop Sign
47. Only One Town in America Voted in Favor to Building a New Data Center, and the Reason Why Is Bleak
48. Anthropic Just Committed a Shocking Crime Against the Environment
49. We Are Now Learning in Real Time Whether the Stock Market Cares About an AI Executive Admitting to an Affair With an Alleged Chinese Spy
50. Employees Who Use AI End Up Working Vastly More Time Per Day
51. Itâs Awful That Google Wonât Just Let Users Turn Off AI Overviews
52. Large Language Models Struggle to Convert Infrastructure Condition Data - Bioengineer.org
53. Your Algorithm: Giving People More Ways to Personalize Facebook Recommendations
54. China's innovation thrives on openness, even under authoritarian rule - The Japan Times
55. What Drives the Emergence of Symbolic Mechanisms in Large Language Models?
56. How Miller School of Medicine Leaders Are Helping Academic Medicine Navigate Change
57. I wrote an AI book using ChatGPT â is this method really the next chapter for aspiring authors?
58. Why telcos can't afford to ignore decision APIs - Fierce Network
Response:
Selecting headlines that showcase tangible AI advances for the target audience, I focused on a cuttingâedge visionâtoâ3D model on Hugging Face, a new synthetic finance dataset that provides researchers with realistic data, and a developerâcentric note on using Claude Code and Codex, which highlights practical coding workflows. These three items cover distinct areasâcomputerâvision/3D generation, AIâgenerated datasets, and AIâassisted programmingâoffering breadth for developers, researchers, and curious readers.
= HEADLINES =
xiangjuntang/JoVox-64 ¡ Hugging Face - Image-to-3D
Nemotron-Personas-Finance-Japan: A Synthetic Dataset Capturing Japan's Demographics and Financial Context
Many Claude Code and Codex sessions, one bottleneck: me
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