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What is AI - Simply Explained
Google has released Gemma 3, a new suite of open-source AI models. These models are built on the same technology as Gemini 2.0 and are designed to be efficient and accessible.
Gemma 3 is available in different sizes (1B, 4B, 12B, and 27B parameters) to suit various hardware needs, from mobile devices to powerful workstations. The models support multiple types of data, including text, images, and short videos (excluding the 1B model).
The models are pre-trained in over 140 languages, with native support for over 35 languages, enabling global application development.
Gemma 3 provides performance comparable to larger models, specifically in tasks requiring reasoning and problem-solving. It is designed to run on single GPUs or TPUs, reducing reliance on cloud resources.
The models offer an extended context window of up to 128k tokens and support function calling for task automation.
Google also introduced ShieldGemma 2, a 4B model for image safety, which categorizes images based on safety levels.
Gemma 3 is available on platforms like Hugging Face and integrates with tools such as Llama and Google’s AI Studio. It can be deployed on Vertex AI, Cloud Run, the Google GenAI API, or locally.
19/01/2025
A lot of students are now thinking: "The way AI is progressing, should I invest time in learning programming? because I think AI will eventually take software engineering’s jobs."
Well, I think you shouldn't just wait and watch what's happening. Rather take part in the change. If you have a strong foundation, you can connect the dots more easily and build great things on top of it.
A big part of software engineering is problem-solving. Even if coding is completely taken over by AI, problem-solving will always be essential unless we live in a utopian world without any problems.
One more thing, currently, we often introduce ourselves as React Developers or Python Developers, but I believe that's going to change. Instead, every software engineer will participate in end-to-end software production. Software engineers will become more like technical orchestrators who know how to combine different AI services to build unique solutions.
This means you might need to go deeper into specialized domains and become adept at leveraging AI tools. The key is to keep learning continuously.
Also, I don't think there's ever been a better time than now for learning programming. You have more than enough resources and community support on the internet, plus AI tools to answer your unique questions with examples as you wish.
Of course, there's a possibility that software will become a commodity, and software founders will face an existential crisis due to competition. However, in that case, we might see a rise in hyper-customized solutions, which will democratize innovation.
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