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LLM Process
Model: nvidia/nemotron-3-super-120b-a12b: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. Stop using Ollama
2. Evalatro: an open benchmark where LLMs play the real Balatro
3. "My son is a genius coder" - honest Alpha Tester review
4. What's the lesson chat?
5. Why there is a lack of new 100B-120B models?
6. Cheapest hardware for Qwen 3.6: both 27B and 35B-A3B
7. Local coding agents are good now, but only if you babysit them
8. Google has seriously leaned into AI enshittification lately
9. not much happened today
10. Bundling of Microsoft Windows
11. Protestware Xsnow
12. Distributed Compaction in SlateDb
13. Jerry Gretzinger's map of a place, 40 years of "analogue generative art" [video]
14. Windows 1.0 and the WinAPI, 40 years later
15. The JIT of PHP 8
16. How and why to run modified Python code using the ast module
17. The Elm Architecture in Python?
18. Are we happy with SQLAlchemy?
19. Monday Daily Thread: Project ideas!
20. EXISTE ALGUM MOTOR DE EXTRAĂĂO QUE REALMENTE CONSIGA FAZER OQUE UMA AI FAZ ?
21. Sunday Daily Thread: What's everyone working on this week?
22. TY is still not professionally good
23. System and game performance monitoring with Python
24. Kay Hayen: Nuitka Release 4.1
25. Eli Bendersky: Plugins case study: Pluggy
26. Bob Belderbos: Why Rust does not need OOP
27. Armin Ronacher: Dangerous Technology For Americans Only
28. Real Python: The Real Python Podcast â Episode #299: EuroPython 2026: Celebrating 25 Years
29. EuroPython: June Newsletter: Talks Schedule Released
30. Hugo van Kemenade: I'm delighted to rejoin the Sovereign Tech Fellowship
31. Wtf just happened?
32. The xAI business model explained
33. The more Grok updates, the worse it gets.
34. Someone needs to do this but to Grok
35. It was good while it lasted
36. A sinking ship or an unexpected come back?
37. Complete session deleted
38. Grok is anti human.
39. Article: Governing AI in the Cloud: A Practical Guide for Architects
40. AWS Introduces Durable Storage Option for ElastiCache for Valkey
41. Google CEO Humiliated by Graduating Stanford Students as They Walk Out of His Speech in Protest
42. CEOs Now Being Forced to Reverse Course, Cut AI Spending
43. Metaâs Super Expensive New AI Team Is Already a Complete Catastrophe
44. Womanâs Death Blamed on Hospitalâs AI System
45. Consulting Firmâs Report on How Awesome AI Is Found to Contain Idiotic AI Hallucinations
46. Meta Employee Laid Off, Immediately Detained by ICE
47. Visa Officially Allowing AI Agents to Go Ham With Your Credit Card
48. VLMs Go Beyond Text Data in Helping Supply Chains
49. Indian AI startup Sarvam has become a unicorn after raising $234 million in the first close of ...
50. AI Lab Radical Numerics Launches with $50M Seed Round To Build General Biological Intelligence
51. AI models have a troubling knack for discovering legal loopholes | Science | AAAS
52. Can Humanlike Reasoning Be Replicated in Large Language Models for Clinical Decision-Making?
53. How do language models (LLM) help break down a large problem into understandable steps?
54. AI stakeholders urge Lutnick to lift controls on Anthropic's Fable, Mythos | InsideTrade.com
55. An Evaluation of Pretrained Generative Models for Augmenting Small Health Data
Response:
For developers and researchers interested in practical AI work, hardware advice for running recent models like Qwen 3.6 is highly actionable. For those focused on evaluation and progress measurement, a novel open benchmark where LLMs engage with a real game offers a fresh way to assess capabilities. Finally, showcasing how visionâlanguage models extend beyond text to improve realâworld logistics highlights an exciting applied direction that will appeal to curious nonâexperts as well.
= HEADLINES =
Cheapest hardware for Qwen 3.6: both 27B and 35B-A3B
Evalatro: an open benchmark where LLMs play the real Balatro
VLMs Go Beyond Text Data in Helping Supply Chains
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