Welcome, innovators.

Siemens is a multinational technology conglomerate focused on industry, infrastructure, transport, and healthcare.

You know what else it’s focused on?

Using AI to take its predictive maintenance solutions to the next level. 

Keep reading for our Siemens’ AI use case…

In today’s newsletter:

• Today’s must-read stories 📰

• Generative AI: driving Siemens' predictive maintenance solution

• Prompt of the day ✍️

Today’s must-read stories 📰 

Why is Google losing to OpenAI? 🤖

Former Google chairman and CEO Eric Schmidt believes that Google's AI struggles stem from remote work and flexible hours.

HR’s role in AI policy 📜

HR is playing an ever-increasing role in AI policy implementation and rolling out the tech in corporate environments.

Elon Musk’s startup xAI comes to life 🧑‍💼

Elon Musk's startup xAI launched its Grok-2 AI assistant, featuring an image generation tool with fewer restrictions than competitors.

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AI artwork of the day 🧑‍🎨 

Miscellaneous resources ❓️ 

• AI Today Podcast: No-hype, practical, real-world insight into AI.

• The AI Podcast: NVIDIA explores the impact of AI on the world.

• Last Week in AI: Text and audio summaries of the most interesting AI news.

• Google Cloud Program: Get up to $350K of free credits*

AI tools 🔨 

• Chipp: Create branded AI assistants trained on your data.

• Leap: Scale your SEO with AI.

• Felo: Multilingual AI search engine.

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🛠️ Hedra is the most powerful character-creation tool ever made

Creating engaging video content with animated characters once took hours of meticulous editing. Now it takes seconds.

• Hedra — an AI research company founded by former Stanford PhDs —has been making waves in the tech industry.

• Their groundbreaking audio-to-video foundation model, character-1, creates long-form videos of expressive human characters from a single image.

Hedra users save 5 hours every week on character creation so they can focus on what truly matters — storytelling and creativity.

Try the future of storytelling for free today. 

Generative AI: Driving Siemens' predictive maintenance solution

Siemens has taken a significant step forward in the field of predictive maintenance by integrating generative AI into its Senseye Predictive Maintenance solution. 

This new functionality makes predictive maintenance more conversational, intuitive, and efficient to address industry challenges such as skill shortages and the need for rapid decision-making.

What’s it all about?

The enhanced Senseye Predictive Maintenance platform combines the strengths of machine learning and generative AI. 

Traditionally, machine learning algorithms analyzed data from machinery to predict potential failures, but Siemens' latest advancement introduces a conversational user interface (UI) powered by generative AI. 

This new feature allows for more interactive and flexible human-machine interactions, enabling maintenance teams to access expert knowledge quickly and streamline their decision-making processes.

Key Features

• Conversational UI: The new generative AI functionality facilitates dialogue between the user, AI, and maintenance experts.

• Knowledge sharing: The AI can scan and group cases, even in multiple languages, bringing past solutions to current issues and providing a prescriptive maintenance strategy.

• Private cloud security: All data is processed within a secure, private cloud environment.

For Siemens, the integration of generative AI into Senseye Predictive Maintenance represents a broader commitment to driving productivity and supporting digital transformation in the industrial sector.

Our Thoughts: Siemens' generative AI in predictive maintenance redefines asset management to boost efficiency and empower workforces. The company is blazing the path for others to follow.

Prompt of the day ✍️ 

Onboarding Specialist (create a best practices guide)

How it works:

The prompt creates a personalized best practices guide by interacting with the user, refining the guide through continuous evaluations, and strictly adhering to provided rules and reference materials.

Why use it:

Use this prompt to create a highly and refined best practices guide that meets user needs and adheres to industry standards.

Prompt Example:

{"prompt":"Develop a tailored Best Practices Guide aligned with the user's individual needs, drawing insights from the supplied reference materials. Initiate interaction with the user to obtain essential specifics and resolve any ambiguities. Iteratively refine the Best Practices Guide through consistent evaluations using the given evaluationRubric and gather user input to ensure the end product aligns with the users expectations.}

You can find the prompt in its entirety here.