What happens when the algorithms we trust to make crucial decisions—like who gets a job or how medical resources are allocated—are flawed or biased? The concept of Responsible AI becomes vital in answering this question. According to a report by MIT Sloan and BCG, while 52% of companies claim to adopt
Machine Learning Frameworks ML frameworks give the structure and tools required to develop and deploy machine learning models. Let’s say we are designing a great castle. You have all the bricks (data) and blueprints (algorithms), but wouldn’t it be helpful to have a sturdy scaffolding and a toolbox full of
Why deploy machine learning models? Machine learning models are only valuable when used to solve real problems. Here are some reasons why deployment is essential: Making Predictions: Deploying enables your model to make predictions on new data that was not seen before. For instance, a deployed model could examine the
Think of a virtual AI assistant that could do everything from creating schedules to writing captivating marketing copy to translating a complicated legal document in a matter of seconds. Does it seem too good to be true? It’s not – it’s the reality of large language model (LLM) agents, LLM
Did you know that around 22% of companies worldwide are vigorously trying to integrate AI into a diverse range of technology products and business processes for enhanced business performance? Artificial intelligence (AI) has come a long way in recent years, with large language models (LLMs) revolutionizing the field of natural
Think of a future where AI can create music, translate languages flawlessly, and write realistic movie dialogues. Large Language Models (LLMs) have brought that future closer than you can imagine. With LLMs, companies can quickly interpret customer feedback, analyze market trends, and automate responses to common inquiries. Moreover, enabling firms
You would agree that Artificial Intelligence and Natural Language Processing (NLP) have become an integral part of various technological applications today–for many good reasons. From powering intelligent chatbots to providing critical insights through NLP sentiment analysis, our interaction with machines has revolutionized. However, the real game-changer in the NLP landscape
The Rise of Enterprise AI Artificial Intelligence (AI) is no longer a futuristic concept but a business imperative for CIOs and CTOs seeking tangible business outcomes. According to a recent survey by Deloitte, 83% of enterprises believe AI is a strategic priority for their business. As AI use cases mature,
DevOps, a set of practices that combines software development and IT operations, enables enterprises to be efficient and effective. By adopting a DevOps approach, your enterprise can streamline critical processes, reduce time-to-market, and foster a culture of collaboration between traditionally siloed teams. When implementing DevOps in an enterprise setting, selecting
What if your AI system could not only understand text but also seamlessly interpret images, audio, and video in one cohesive flow? This is where Multimodal Retrieval-Augmented Generation (RAG) steps in, transforming the way we interact with technology. According to a report by MarketsandMarkets, the multimodal AI market is expected
Kanerika is a leading provider of end-to-end AI, Analytics, and Automation solutions with years of implementation expertize.
Subscribe for the latest updates.
Services
Business Functions
Industries
Company
© 2024 Copyright. All rights reserved
