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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. Two pallets of ZOTAC RTX 5090 graphics cards worth $470,000 disappear at Brazilian airport
2. PSA: Power limit your 5090s!
3. You donât need that expensive of a build for local llms.
4. Embedding model can be used to search text inside image
5. told Qwen3.8 27b to hack my router
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. AI-assisted mushroom hunting is a recipe for a bad trip
9. OpenClaw 2.0 pours glitter on slow-burning security dumpster fire
10. not much happened today
11. collusion.wiki
12. Building a Compositor for a Userbase of One
13. How to Set Up Multiview with RTSP Cameras Using Red5 Pro?
14. Safety and Liveliness in Software Engineering
15. AI-Assisted Product Discovery: When Code Is Cheap, Judgment Is the Job
16. Python's binary wheels and supply chain attacks
17. Microsoft drops AI datacentre project in Essex over power supply concerns
18. Benchmarking DuckDB v2.0-dev on Nvidia Vera
19. Ask HN: System One models for autonomous agents
20. Python 3.10â3.15 encoding benchmarks: big gains for Base32 and Base85, but 3.14 leads Base16
21. Python web scraping with proxies
22. Sunday Daily Thread: What's everyone working on this week?
23. Is python as a backend language good
24. Is python good for backend engineering to get job in indian corporate
25. Saturday Daily Thread: Resource Request and Sharing! Daily Thread
26. Friday Daily Thread: r/Python Meta and Free-Talk Fridays
27. opinion on CWH data science course?
28. The Python Coding Stack: 2. Who actually does the work, the model or the software?
29. EuroPython: Humans of EuroPython: Emma Cooke
30. Talk Python Blog: Introducing Talk Python Membership
31. Talk Python to Me: #566: State of the art in Python 2026
32. LernerPython blog, from Reuven Lerner: Pandas Grouper NaNs: Why outlier dates create empty groups
33. LernerPython blog, from Reuven Lerner: Pandas Grouper: Group datetime columns by custom time periods
34. Rodrigo GirĂŁo SerrĂŁo: Unpacking inside comprehensions
35. He wasn't ready for Grok.
36. What are the implications of being on a legacy subscription?
37. Might be the best cast
38. Never been so proud
39. Literally have not used this account for three weeks
40. Limitations on text
41. Renew my point of view about new ultra plan.
42. VIDEO QUALITY DOWNGRADE. WHAT A SHAME.
43. The model that didn't exist, so you made it yourself
44. Amazon Acquires DuckLabs and Integrates DuckDB in Amazon Aurora PostgreSQL
45. Mini book: Evolutionary Architecture in Practice
46. Presentation: Exploding GPUs
47. Director Blows $1.5 Million Generating Horrendous AI Slop Movie, Says AI Actually Saved Him Tens of Millions
48. Bosses Deploying AI-Powered Spyware That Watches Workers Constantly
49. Manâs Meta Muse Agent Sends Him Message So Bizarre That He Permanently Quits
50. Companies Are Realizing Theyâre Spending a Fortune on AI Just So Their Employees Can Generate Error-Riddled Slop, and Suddenly Cutting Back Budgets
51. Using an AI Agent Makes You a Sucker for Phishing Emails
52. Man Shows Up to AI Job Interview With His Own Helicopter AI to Interview for Him
53. Rogue AI Swarm Responds to Reporterâs Questions
54. AI Experts Already Doomsday Prepping for When AI Takes Out the Entire Financial System
55. Why the Catholic Church Is AI Doom's Most Formidable Foe - TaxProf Blog
56. AI's Next Big Problem Isn't Safety, It's Running Out of Human Data & Insight
57. Video: Rep. Don Beyer (D-VA08), One of the Top Experts in Congress on AI, Talks ... - Blue Virginia
58. xSeek buys rival LLMonade to add AI content tools to its search platform | Dealroom.co
59. AI's biggest breakthrough isn't chatbotsâit's the eureka moment - Fast Company
60. Why Big Tech is giving away open-weight AI models, and what it wants in return | Explained
61. Choosing an LLM for a Health AI Coach: Production Lessons - Tech Insider
62. Switching languages can change a chatbot's personality test results - Tech Xplore
Response:
The three headlines were selected because they each address a distinct, highâimpact area for developers, researchers, and curious nonâexperts. The embedding model breakthrough (headlineâŻ4) showcases a practical new capability for multimodal AI, directly useful to developers building searchâenabled applications. Microsoftâs decision to abandon an AI dataâcenter project due to power constraints (headlineâŻ17) is a concrete industry development that informs infrastructure planning and highlights realâworld scalability challenges. Finally, the community discussion on SystemâŻOne models for autonomous agents (headlineâŻ19) taps into the cuttingâedge research thread of agentâbased AI systems, offering insights for both researchers and practitioners exploring autonomous solutions. Together, these headlines span AI model innovations, infrastructure realities, and emerging agent architecturesâproviding a wellârounded snapshot of the most relevant AI/robotics developments.
= HEADLINES =
Embedding model can be used to search text inside image
Microsoft drops AI datacentre project in Essex over power supply concerns
Ask HN: System One models for autonomous agents
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