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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. Why am I like this? (Full Chat and Image generation on a 286 Tandy 1000 TL/3)
2. Clef: Open Weights decision model by Cloudflare
3. Heretic is on PewDiePie!
4. Qwen4Exp: add MTP by am17an ¡ Pull Request #29761 ¡ ggml-org/llama.cpp
5. AMA about K2 Horizon, Meet our team from IFM
6. Now which lab is behind fledge alpha?
7. Pi extension: Skip reasoning with local Qwen 27B and proceed to answer right now
8. Jeff-Qwen3.5-0.8B v1.2 + 9 LoRA adapters: put it in front of Qwen3.8-27B for 38Ă faster decisions and +8.7 points accuracy, for under 2 GB extra memory
9. Show colleagues how much you care by sending an AI avatar to your Google Meet call
10. Oracle says AI will save it from the SaaSpocalypse, not bring it on
11. Microsoft goes after Salesforce and ERP users with AI-powered converter
12. Another Microsoft team admits itâs struggling to handle flood of AI-generated code
13. AI-assisted mushroom hunting is a recipe for a bad trip
14. OpenClaw 2.0 pours glitter on slow-burning security dumpster fire
15. Microsoft's virtual intern Teams Facilitator will be late for the meeting
16. not much happened today
17. collusion.wiki
18. Claude.dev Blog / technical writing for people building with Claude
19. AI as Normal Technology
20. Vue â A WebAssembly Port of TeXmacs
21. Using Opus 5.5 to discover a new eyewitness record of the dodo
22. Four days of ricing Fedora without installing Arch
23. Canada to fast track oil pipeline designed to diversify economy away from US
24. A big-tent or small-tent AI safety movement?
25. "we are not yet seeing spillovers from tariffs, [and] energy price shocks"
26. Thursday Daily Thread: Python Careers, Courses, and Furthering Education!
27. Closing mysql-connector-python pooled sockets
28. We built a way to make Python sessions portable across runtimes!
29. I tested my Docling JSON checker against real exports and found my own bug
30. What are you using to monitor small Python web apps?
31. Suggesting ppl to go from unmaintainted library X to yours in github issues?
32. Two SBOMs for the same service never match and the SBOM tools I tried only cover one layer
33. Generating a tidy HTML report in Python
34. Python Insider: Python 3.10.22, 3.11.17, 3.12.15, 3.13.16 and 3.14.8 are now available!
35. Graham Dumpleton: Getting to know Tachyon
36. Python Insider: Python Language Summit 2026
37. Python Insider: PEP 827: Type Manipulation (Python Language Summit 2026)
38. Is generating images with grok completely broken for anyone else?
39. is grok down for anyone else?
40. America Gov powered by grok confirmed by Elon
41. They just added Grok 4.7 to the chat
42. Let's debunk some myths: Middle Ages Eddition
43. How much worse has Grok gotten?
44. Super Grok weekly limit
45. Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs
46. Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents
47. Presentation: Beyond Observability: Evolving Production Operations in the Age of AI
48. Container Apps Express Reaches GA on a Newly Generally Available Sandbox Layer
49. InfoQ Online Cohorts Address AI Security and Coding Agent Verification
50. Presentation: Context Is the New Code
51. AWS Introduces Foreign Key Constraints in Aurora DSQL
52. These Strongly Appear to Be the Old Tweets of That Anthropic Employee Who Quit Citing Risks to Humankind and They Are⌠Pretty Bizarre
53. Top BBC Director Says Heâs Been Reviewing a Fully AI-Generated Episode of âDoctor Whoâ and Itâs âPretty Goodâ
54. Data Centers Are a $6 Trillion Time Bomb, Analysts Warn
55. Hereâs the Email You Get When an OpenAI Model Hacks Your Organization
56. RFK Jr Announcing That AI Is Now Better Than Human Doctors Shows That He Is a Buffoon Who Is Ruining Trust in American Health Institutions
57. People Who Drink Their Own Pee Are Obsessed With AI, Using It to Reassure Themselves That Itâs a Miraculous Cure-All
58. New OpenAI Product Fails Spectacularly During Live On-Stage Demo
59. The FTC Is Now Investigating Frontier AI Labs Following Countless Hacks by Out-of-Control Agents
60. AI Models Extract Smoking History for Lung Cancer Screening
61. Why these UChicago core classes are going analog - The Washington Post
62. Opinion | Stop Talking About A.I. Like a Human - The New York Times
63. Introducing Clef: our open-source decision models, and new RL fine-tuning platform
64. Calculating the true value of human advice in the AI age - Professional Wealth Management
65. Alphabet: Gemini 4 Argon Launch Brings Alphabet Back to the Frontier Model Race | Morningstar
66. AI 'godfather' LeCun has 'zero concerns' about human extinction, says Anthropic CEO is 'deluded'
67. Michael Burry Sounds Alarm on $1 Trillion AI Spending Using 145-Year-Old Case Study
Response:
These three headlines cover distinct, highâimpact AI developments that matter to developers, researchers, and curious nonâexperts. âIntroducing OlmoâcoreâŻ3â provides open, scalable training infrastructure for largeâscale models, a foundational tool for the community. The JeffâQwen3.5âŻ+âŻLoRA adapters headline showcases a practical optimization that delivers massive speedâups and accuracy gains while keeping memory usage lowâkey for production deployments. Finally, the Qwen4Exp MTP pull request adds a new experimental capability to an emerging model, offering insight into cuttingâedge features. Together they span infrastructure, model performance, and emerging research, ordered by their relevance and potential impact.
= HEADLINES =
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs
Jeff-Qwen3.5-0.8B v1.2 + 9 LoRA adapters: put it in front of Qwen3.8-27B for 38Ă faster decisions and +8.7 points accuracy, for under 2 GB extra memory
Qwen4Exp: add MTP by am17an ¡ Pull Request #29761 ¡ ggml-org/llama.cpp
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