Abstract: In this article, we propose a hybrid combination of active inference and behavior trees (BTs) for reactive action planning and execution in dynamic environments, showing how robotic tasks ...
Google is dedicating a chip to running artificial intelligence models, and a separate processor to training models. Amazon is pursuing a similar strategy, as both companies take on Nvidia by offering ...
Vikki Velasquez is a researcher and writer who has managed, coordinated, and directed various community and nonprofit organizations. She has conducted in-depth research on social and economic issues ...
New revenue opportunity forecast marks big step-up from $500 billion seen through 2026 Nvidia unveils CPU, AI system based on Groq's technology to for inference computing Nvidia faces increased ...
Interactive LLMs (chat, copilots, agents) with strict latency targets Long‑context reasoning (codebases, research, video) with massive KV (key value) cache footprints Ranking and recommendation models ...
The creators of the open source project vLLM have announced that they transitioned the popular tool into a VC-backed startup, Inferact, raising $150 million in seed funding at an $800 million ...
Matt Greene's new novel, "The Definitions," starts with a simple, relatable scene - new dormmates getting to know each other. It could be any college campus. But there is a dystopian backstory. These ...
Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...
Quant trading uses math and data to predict stock price changes and execute trades quickly. Computers in quant trading base decisions on data, removing the emotional risks of investing. Retail access ...
Recent statistics from the World Health Organization show that non-communicable diseases account for 74% of global fatalities, with lifestyle playing a pivotal role in their development. Promoting ...
What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...
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