• Using ChatGPT as a Reporting Assistant: What Went Wrong?
    Jan 11 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/using-chatgpt-as-a-reporting-assistant-what-went-wrong.
    Overall, the sessions were a lot of work trying to figure out where the agent got its information, and redirecting it with precise instructions.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #chatgpt, #ai-in-journalism, #chatgpt-as-research-assistant, #ai-tools-in-journalism, #data-journalism, #the-markup, #chatgpt-4, #using-ai-for-research, and more.

    This story was written by: @TheMarkup. Learn more about this writer by checking @TheMarkup's about page, and for more stories, please visit hackernoon.com.

    ChatGPT is an artificial intelligence tool that can be used to help journalists with workflows and summarize dense documents. At Investigative Reporters & Editors’ annual data journalism conference in Baltimore last week, 14 of the 200 plus sessions were related to AI.

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    6 mins
  • MiniMax M2.1 Bets That ‘Most Usable’ Beats ‘Most Massive’
    Jan 11 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/minimax-m21-bets-that-most-usable-beats-most-massive.
    LLMs are getting bigger, but most developers still have to work within tight limits. MiniMax M2.1 is an attempt to square that circle.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #minimax-m2.1, #minimax, #chinese-ai-startup, #chinese-ai-startup-ipo, #minimax-m2, #ai-native-development, #ai-native-dev, and more.

    This story was written by: @ainativedev. Learn more about this writer by checking @ainativedev's about page, and for more stories, please visit hackernoon.com.

    LLMs are getting bigger, but most developers still have to work within tight limits on speed, cost, and hardware. MiniMax M2.1 is an attempt to square that circle: a large model that behaves more like a much smaller one at inference time.

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    8 mins
  • Why OpenAI is Set to Become the Most Lucrative IPO of 2026 on Wall Street
    Jan 10 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/why-openai-is-set-to-become-the-most-lucrative-ipo-of-2026-on-wall-street.
    The prospect of OpenAI becoming Wall Street’s largest-ever debut isn’t beyond the realms of possibility, but does it represent value to investors?
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #artificial-intelligence, #openai, #sam-altman, #wall-street, #openai-debut, #openai-ipo, #hackernoon-top-story, and more.

    This story was written by: @dmytrospilka. Learn more about this writer by checking @dmytrospilka's about page, and for more stories, please visit hackernoon.com.

    The prospect of OpenAI becoming Wall Street’s largest-ever debut isn’t beyond the realms of possibility, but does it represent value to investors at such a high price?

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    7 mins
  • The Next Big Thing Isn’t on Your Phone. It’s AI-Powered XR and It’s Already Taking Over. Part II
    Jan 10 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/the-next-big-thing-isnt-on-your-phone-its-ai-powered-xr-and-its-already-taking-over-part-ii.
    AI-powered XR won’t be won by smart glasses alone. Why Big Tech is stuck optimizing and how deep tech, AI-driven R&D, and new materials are reshaping computing
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #ar, #xr, #smart-glasses, #deep-tech, #smart-contact-lenses, #materials-science, #hackernoon-top-story, and more.

    This story was written by: @romanaxelrod. Learn more about this writer by checking @romanaxelrod's about page, and for more stories, please visit hackernoon.com.

    The next big thing in tech is AI-powered XR computing. But what form factor will it take? Which innovations will it require?

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    12 mins
  • 5 Ways Your AI Agent Will Get Hacked (And How to Stop Each One)
    Jan 8 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/5-ways-your-ai-agent-will-get-hacked-and-how-to-stop-each-one.
    Production AI agents fail from prompt injection, tool poisoning, credential leaks, and more. Learn 5 attack patterns and defensive code for each.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-agents, #ai-security, #prompt-injection, #llm-security, #mcp, #cybersecurity, #python, #hackernoon-top-story, and more.

    This story was written by: @paoloap. Learn more about this writer by checking @paoloap's about page, and for more stories, please visit hackernoon.com.

    AI agents are vulnerable to prompt injection, tool Poisoning, credential leakage and identity theft. Most teams just don’t know the threats exist.

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    8 mins
  • How I stopped fighting AI and started shipping features 10x faster with Claude Code and Codex
    Jan 8 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/how-i-stopped-fighting-ai-and-started-shipping-features-10x-faster-with-claude-code-and-codex.
    A deep dive into my production workflow for AI-assisted development, separating task planning from implementation for maximum focus and quality.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #vibe-coding, #claude-code, #codex, #problem-with-vibe-coding, #ai-assisted-coding, #ai-assisted-development, #claude.-md-foundation, and more.

    This story was written by: @tigranbs. Learn more about this writer by checking @tigranbs's about page, and for more stories, please visit hackernoon.com.

    A deep dive into my production workflow for AI-assisted development, separating task planning from implementation for maximum focus and quality.

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    11 mins
  • IA2 Preprocessing: Establishing the Foundation for Index Selection
    Jan 7 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/ia2-preprocessing-establishing-the-foundation-for-index-selection.
    The IA2 preprocessing phase uses a workload model and index candidates enumerator to create accurate state representations and action spaces.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #deep-learning, #ia2-preprocessing-phase, #database-workload-modeling, #index-candidates-enumerator, #tokenized-query-embedding, #heuristic-index-selection, #ia2, #deep-reinforcement-learning, and more.

    This story was written by: @instancing. Learn more about this writer by checking @instancing's about page, and for more stories, please visit hackernoon.com.

    The IA2 preprocessing phase uses a workload model and index candidates enumerator to create accurate state representations and action spaces.

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    3 mins
  • Prompt Reverse Engineering: Fix Your Prompts by Studying the Wrong Answers
    Jan 7 2026

    This story was originally published on HackerNoon at: https://hackernoon.com/prompt-reverse-engineering-fix-your-prompts-by-studying-the-wrong-answers.
    Learn prompt reverse engineering: analyse wrong LLM outputs, identify missing constraints, patch prompts systematically, and iterate like a pro.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #prompt-engineering, #llms, #ai, #productivity, #prompt-reverse-engineering, #backtracking-prompts, #prompt-fails, #hackernoon-top-story, and more.

    This story was written by: @superorange0707. Learn more about this writer by checking @superorange0707's about page, and for more stories, please visit hackernoon.com.

    Most “bad” LLM outputs are diagnostics. Treat them like stack traces: classify the failure, infer what your prompt failed to specify, patch the prompt, and re-test with a minimal change. Build a prompt changelog so you stop re-learning the same lesson.

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    10 mins
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