SML Kinetics

12/07/2024

🤔 Building Owners, Have You Considered Your Carbon Footprint Tax for 2030? It's time to start thinking the impact of your building's carbon footprint.

11/06/2024

The vision of SML is to transform complex regulatory compliance into a seamless process, helping you unlock the full potential of your data.

Are you ready to take your document management skills to the next level? Welcome to SML Channel your ultimate destination for mastering advanced document con...

15/03/2024

🤖✨ Did you know that Language Models (LMs) like GPT-3 are revolutionizing how we process and understand vast amounts of information? From summarizing complex articles on climate change to generating creative content. Here's some quick facts with simple learning tips

06/03/2024

Are you curious about generative AI, the technology that can create new content from existing data? 🤔

Here's simple sharing with some basics of generative AI, its models, tools, and applications. 🚀

Generative AI is a type of artificial intelligence that uses neural networks to learn patterns and features from existing data, and then generate new data that aligns with the patterns they’ve learned. 🧠

Generative AI models can use different learning approaches, such as unsupervised or semi-supervised learning, to train on large, unlabeled data sets. These models can then be used for different tasks, such as natural language generation, image synthesis, speech synthesis, or product design. 🎨

Generative AI models can be evaluated based on their quality, diversity, and speed of generation. Some examples of generative AI models are ChatGPT, which can generate natural language responses based on a text input, and Stable Diffusion, which can generate photorealistic images based on a text input. 📸

Generative AI has many potential benefits and applications, such as faster product development, enhanced customer experience, improved employee productivity, and innovation in various domains. 🌟

However, generative AI also poses some challenges and risks, such as data quality, ethical issues, bias, and social impact. Therefore, generative AI requires careful evaluation and human validation before deployment. 🙏

If you want to learn more about generative AI, you can check out this course that I found on Google Cloud: Introduction to Generative AI. It explains the concepts, models, tools, and resources that Google Cloud offers for developing and deploying generative AI models, such as Vertex AI Studio, Vertex AI Search and Conversation, PaLM API, and Gemini. 💯

I hope you enjoyed this post and learned something new about generative AI. Let me know what you think in the comments below. And don’t forget to follow me for more updates on AI and technology. 😊

06/07/2022

your business with analytics with free tools Digital Marketers got to know , differences in the behavior metrics between UA and GA4. How to calculate the engagement sessions, user times spent and the views

08/06/2022

Time to read and learn. A mind stimulation process to catalyst the engineering, innovation and entrepreneurs journey

09/05/2022

Robots in work

How to optimise integration between AGV robots into robotics packaging automation.Start with collaborating with independent system integrators and consultant...

25/04/2022

How to pick an energy outlook that will get us to a carbon-neutral future.