Decoding AI: Unveiling the Future of Machine Intelligence
Supervised Learning
In the year 2024, the initial hype surrounding generative AI will start to fade away as the setbacks of this technology become more evident. While generative AI has shown promise in terms of improving productivity in various tasks, it has also been plagued by issues such as false information and hallucinations.… Read the rest
In today’s world, the coexistence of AI and data quality is not only possible but necessary. The effectiveness of AI systems, including generative AI models, depends heavily on the quality of the data they are fed. According to AI strategy advisor Marinela Profi, data is like food for humans – the better the quality of the food, the better the performance and outcomes.… Read the rest
Computers have come a long way in understanding and producing human-like language, thanks to the advancements in machine learning algorithms. One such example is the creation of innovative language models like ChatGPT and Bard by OpenAI. Let’s delve into the foundations of these models and the incredible potential they hold.… Read the rest
In recent years, deep learning has made significant advancements in various fields, and now it is being utilized in the realm of plant studies as well. The integration of deep learning techniques with point clouds has shown remarkable progress in the 3D segmentation of plant shoots.… Read the rest
Summary: The latest generation of AI models, including ChatGPT, relies on self-supervised learning and pre-training to enhance their capabilities. This approach allows AI models to build a strong foundation of knowledge before tackling specific prompts or tasks. While ChatGPT focuses on language learning, programmatic advertising can benefit from self-supervised learning by pre-training AI models on digital behavior patterns.… Read the rest