The State of AI: Smaller, Smarter, and More Affordable
Models are changing and companies may soon take advantage of more efficient and cost effective
Looks at issues related to artificial intelligence technologies, including cognitive computing, deep learning, and machine learning. Considers also supervised and unsupervised learning and natural language processing.
Models are changing and companies may soon take advantage of more efficient and cost effective
Training LLMs on company-owned data equips an organization’s LLMs with the intelligence they need to act as true extensions of an
Integrating AI and GenAI into turnaround planning marks a significant shift towards proactive, efficient, and safe industrial operations. By embracing …
In this week's real-time analytics news: IBM announced a number of new technologies to scale enterprise
AI’s use of real-time data for early fraud detection, streamlined claims processing, sophisticated underwriting, and dynamic risk management is already …
Bridging the gap between AI potential and real-world impact requires a strategic investment in data literacy. Organizations that train their workforce, …
Companies that align AI initiatives with business priorities, invest in adaptable, user-friendly solutions, and continuously measure impact will see tangible …
The transition to live maps and the integration of AI into every stage of mapmaking represent a new frontier for the geospatial industry. These advancements …
Physical AI promises to reinvent industrial automation with more efficient ways to train and control entire digital workforces of autonomous mobile
In this week's real-time analytics news: Oracle teams with NVIDIA to support next-gen reasoning models and AI agents.