Blogs

Generative AI is transforming various industries by enabling machines to create content like images, music, and text. In this blog post, we'll explore how beginners can easily start using generative AI tools without the need for complex setups or powerful hardware.

If you’re feeling stuck because you don’t have a GPU, fear not! There are several effective alternatives that can help you run your projects smoothly. In this blog post, we'll explore two excellent options.

There are specifically two types of Data Poison Attacks - Untargeted & Targeted. However, detecting untergetted attacks is fairly simple as the overall accuracy of the model decreases. But it becomes a problem when the attack is targeted. Until and unless, the query for that specific label/feature is not triggered, you will never understand that you are hacked! There are methods to identify Targeted Attacks but lets try to figure out if these attacks can be identified / corrected using embeddings’ representation, and thus utilising the Neural Collapse to detect poisoned labels/features.

Creating large language models like GPT-3 and other recent developments in AI have made prompt engineering a popular topic. These models, which contain an incredible amount of parameters and are capable of producing text that is cohesive and contextually appropriate, are immensely flexible tools for a wide range of applications.

The creative expressions of humanity have always been reflected in art, in all of its forms. Art has changed, pushed limits, and confounded expectations throughout the ages. The world of art is undergoing yet another seismic transition in the digital era, and the groundbreaking idea of Stable Diffusion lies at the centre of this change.

In today’s world, artificial intelligence (AI) has rapidly penetrated various aspects of our lives, making it an essential technology in areas such as finance, insurance, education, retail, and manufacturing. Concerns about privacy, accountability, transparency, and the possibility of bias all figured prominently in this discourse. The key question remains: Should AI be regulated, and if so, how do we carefully strike the delicate balance between regulation and innovation?