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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. StepFun 3.7 Flash
2. Beware!! Users trying to fork and steal your projects
3. I've just benchmarked myself:
4. Liquid AI releases LFM2.5-8B-A1B
5. Use HTML as the primary chat language for your agents so they can draw diagrams
6. LiquidAI/LFM2.5-8B-A1B ¡ Hugging Face
7. StepFun 3.7 Flash - Speed Benchmark in M5 Max
8. not much happened today
9. The network redesign that led AWS to forge a more resilient cloud
10. Orchestrate subagents at scale with dynamic workflows
11. Blue Origin's Rocket Explosion â How Bad Is It? [video]
12. Troops' phones gave away location data to foreign adversaries
13. Don't read any books written post-2024
14. The ÂŁ5 coffee that tells a story of global economic turmoil
15. Reuters: Tesla's FSD safety claims are misleading marketing, not safety research
16. Under the River
17. How to deal with slop PR's as a maintainer?
18. What's Python cloud hosting using these days?
19. Jupyter notebooks touching production data are application code from a security standpoint
20. Monday Daily Thread: Project ideas!
21. Friday Daily Thread: r/Python Meta and Free-Talk Fridays
22. PEP 661 (Sentinel Values) has been accepted for release in 3.15!
23. Thursday Daily Thread: Python Careers, Courses, and Furthering Education!
24. Real Python: Quiz: BNF Notation: Dive Deeper Into Python's Grammar
25. Bob Belderbos: Two Python Scoping Bugs: A Lesson in Object Lifetimes
26. Real Python: Sending Emails With Python
27. PyPy: PyPy v7.3.23 release
28. Python GUIs: Fixing Missing Icons in PyInstaller-Packaged PyQt6 Applications on Windows â Why your app icon disappears after packaging and how to fix it
29. Grok has become such shit
30. You no longer need Grok Imagine
31. Grok broken again?
32. Grok Build pays tribute to Claude Code
33. Rip Grok 2023-2026
34. SuperGrok has reached AGI
35. TF you mean uploaded photo?!
36. Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL
37. Cloudflare Adds Support for Claude Managed Agents
38. Azure Logic Apps Adds Sandboxed Code Interpreters to Agent Workflows
39. Sarang Kulkarni on Lessons from Building Deep Research Agents in Production
40. Article: Architecting Cloud-Native Kafka: From Tiered Storage Towards a Diskless Future
41. Microsoft Introduces MDASH for Large-Scale AI Vulnerability Research
42. CEO Receives Violent Threats After Kicking Off AI Layoffs
43. NBA Commissioner Announces Plans to Let AI Take Over for Lazy Referees
44. Anthropic Customers Creeped Out by Its Newest Models
45. Influential Tech Founder Says His Peers Are Suffering From Mass AI Psychosis
46. YouTube Announces Plans to Crack Down on AI Slop
47. AI Firm Trots Out Digitally Resurrected Corpse of Stan Lee You Can Use to Create Mind-Numbing Slop
48. Debt Collectors Are Being Replaced With AI Agents
49. Nvidia CEO Begs Execs to Stop Telling Workers Theyâre Fired Because of AI
50. A temporal adaptive dictionary-constrained LDA and Bi-calibrated dual granularity DTM ... - Nature
51. SpaceX IPO boldly steps into the unknown of AI economics - Financial Times
52. Open-source spectre haunts the AI feast - Reuters
53. CoreWeave introduces autonomous improvement capabilities for AI agents - SiliconANGLE
54. Start-ups are racing to revolutionise mathematics with AI | New Scientist
55. Literature support and the capabilities of autonomous research agents - CEPR
56. Samsung Electronics Begins Shipment of Industry-First HBM4E Samples
57. Training Azerbaijani language models on Amazon SageMaker AI | Artificial Intelligence
Response:
The selected headlines highlight three distinct and impactful areas of AI progress relevant to developers, researchers, and interested nonâexperts: a notable new model release, a practical approach to scaling AI agents, and a hardware advancement that enables largerâscale AI workloads. Together they cover software innovation, agent engineering, and underlying infrastructureâkey topics for anyone building or studying AI systems today.
= HEADLINES =
Liquid AI releases LFM2.5-8B-A1B
Orchestrate subagents at scale with dynamic workflows
Samsung Electronics Begins Shipment of Industry-First HBM4E Samples
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