What happens when your team builds faster than your tech stack can handle? That’s the challenge many CTOs and CIOs are facing today as generative AI reshapes how companies think, work, and deliver. Take Coca-Cola, for example, they partnered with OpenAI to revamp their marketing, using AI-generated content to speed
In 2024, a Gallup/Bentley University survey revealed that public trust in conversational AI has significantly declined, with only 25% of Americans expressing confidence in these systems. This loss of trust underscores the critical consequences of inadequate ethical frameworks in AI development. Artificial intelligence has evolved from an emerging technology
AI Adoption Types of AI Agentic AI Multimodal AI Responsible AI Explainable AI Actionable AI AI TRiSM AI Hallucinations AI Augmentation Edge AI Causal AI Composite AI Model Context Protocol Artificial Intelligence (AI) Applications AI in Manufacturing AI in Accounting AI in Cybersecurity AI in Supply Chain AI In
A recent McKinsey report found that while nearly all companies are investing in AI, only 1% consider themselves mature in its deployment. One major challenge? Bridging real-time data processing with large-scale AI models. This is where the role of cloud computing in Edge AI becomes critical—ensuring low latency, efficiency, and
“As cybersecurity expert Bruce Schneier aptly stated, ‘Amateurs hack systems; professionals hack people.’” This idea rings especially true in the context of LLM security, where even small oversights can lead to significant risks. For instance, in 2023, Samsung employees accidentally leaked sensitive corporate data by inputting proprietary information into ChatGPT
When Pinterest introduced its Lens feature, powered by Vision-Language Models, it transformed how people shop and explore new ideas. Lens lets users snap a photo to find similar items, turning inspiration into action with a single click. This experience relies on a powerful combination of computer vision and natural language
Every day, AI creates over 34 million images using diffusion models, with platforms like Midjourney alone generating over 984 million creations since its launch in August 2023. From DALL-E’s photorealistic art to Stable Diffusion’s ability to transform text into stunning visuals, diffusion models have revolutionized the AI landscape in just
Parameter-efficient Fine-tuning (PEFT) is an NLP technique designed to enhance the performance of pre-trained language models for specific tasks without needing to fine-tune all the model’s parameters. This approach optimizes resource usage while delivering high accuracy on targeted applications. Fine-tuning an LLM like GPT-4 can require terabytes of data and
Advanced AI systems are revolutionizing the way businesses operate by automating workflows, improving client interactions, and providing data-driven insights. Large Language Models (LLMs) play a significant role in this transformation by learning from vast amounts of data and utilizing computational power to streamline various processes. LLMs should go hand in
What if your smartphone could instantly recognize objects, translate languages, and detect potential health issues—all without an internet connection? What if industrial robots could make split-second decisions without relying on a distant cloud? It’s the promise of Edge AI, a revolutionary technology that’s transforming the devices we use every day.
Kanerika is a leading provider of end-to-end AI, Analytics, and Automation solutions with years of implementation expertize.
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