Companies are spending enormous sums of money on AI systems, and we are now at a point where there are credible alternatives ...
Learn how hyper-personalization in retail works, why IT leaders must build real-time, data-driven systems, and how to implement scalable architectures with measurable outcomes.
Admittedly it's an oversimplified description, but the economics of AI inference at scale are deceptively simple. The more ...
Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
Presearch’s “Doppelgänger” is trying to help people discover adult creators rather than use nonconsensual deepfakes.
Much of the conversation around AI today is focused on building cloud capacity and massive data centers to run models. Companies like Apple and Qualcomm are in the early stages of making on-device AI ...
On Thursday, OpenAI released its first production AI model to run on non-Nvidia hardware, deploying the new GPT-5.3-Codex-Spark coding model on chips from Cerebras. The model delivers code at more ...
Vibe coding is a new way to create software using AI tools such as ChatGPT, Cursor, Replit, and Gemini. It works by describing to the tool what you want in plain language and receiving written code in ...
Agentic applications are LLM that iteratively invoke external tools to accomplish complex tasks. Such tool-based agents are rapidly becoming the dominant paradigm for deploying language models in ...
The Solution: "The Hard Market" This engine simulates a realistic, difficult market environment where 75% of customers are 'Neutral' (ignore ads). A traditional model fails here. Our T-Learner ...
Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...
If GenAI is going to go mainstream and not just be a bubble that helps prop up the global economy for a couple of years, AI inference is going to have to come down in price – and do so faster than it ...
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