🏭 AI To Aid Manufacturing

Latest AI Prompts for Business Letter, Sales Email, Architecture, Software Application, and Business Negotiation

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👀 AI Happenings...

  • ⚠ Using AI for loans and mortgages is big risk, warns EU boss (link)

  • ⚖EU moves closer to passing one of the world’s first laws governing AI (link)

  • 😲 Accenture announces jaw-dropping $3 billion investment in AI (link)

🧠 Best New AI Tools

  • Wordtune: Your personal writing companion that paraphrases & rewrites any text (link)

  • Levity: Build automated workflows for your daily repetitive tasks without a single line of code. (link)

🤖 Today’s Best New ChatGPT Prompts

 🎨 Today’s Best New Midjourney Prompts

Prompt:

[Something]. Covered in [description] slime.

Prompt:

old man, natural light, overcast, digital retouch, 8K , colorful fashion, daylight, in front of pink moulin with a green door, preppy dress, detailed, cactus, photo session, full body shot--ar 2:3 --q 2 --s 800

Prompt:

a bearded man in white standing in a group of people, in the style of futuristic glam, dystopian landscapes, fawncore, cinestill 50d, uniformly staged images, shiny eyes, aurorapunk --ar 81:58 --s 750

Prompt:

a woman is standing with a group of people in white, in the style of futuristic glam, aykut aydogdu, daria endresen, cinestill 50d, uniformly staged images, shiny eyes, unicorncore --ar 81:58 --s 750

Prompt:

A canvas of white paint

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🤯 Insight: Will AI Significantly Benefit Manufacturers?

Manufacturers aim to develop AI models for edge computing to enhance their operations. The focus is on creating a transparent shop floor with automated, AI-driven insights that enable faster quality assessment, problem-solving, and predictive maintenance.

However, AI implementation at the manufacturing edge poses unique challenges. IT teams typically deploy general-use solutions, while operational technology (OT) teams require specific solutions for unique problems.

Collaboration between IT and OT is crucial to extract meaningful data from OT devices for AI models. Upgrading IT systems to handle large data sets and recognizing that AI is an augmentation, not a replacement for human expertise, are key challenges.

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