Aera Technology announced the next evolution of the company’s Aera Decision Cloud™ platform for the future of work. Major advancements, including Aera Agentic AI, Aera Workspaces, and Aera Control Room, empower users with one system of intelligence to automate routine decisions, model scenarios to support strategic decisions, and execute and track the full spectrum of enterprise decisions.
Aera Technology Introduces Agentic AI, Workspaces, and Control Roomto Enable the Full Spectrum of Enterprise Decisions
Chatbots Walked So AI Concierges Could Run
In this contributed article, Dr. Peter Graf, SVP of Strategy at Genesys, imagines a world where an AI-powered concierge can navigate complex customer support requests on your behalf. He believes the chatbots we’re familiar with today are paving the way forward for these concierges to become a reality.
Unisys AI Report: New Leadership Roles and Tech Innovation on the Rise
Unisys released its latest survey findings, The AI Equation: 2024 AI Business Impact Research, revealing how AI is reshaping industries by creating leadership roles and boosting tech training initiatives.
GenAI and the Role of GraphRAG in Expanding LLM Accuracy
In this feature article, Daniel D. Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, discusses RAG techniques, particularly those involving graph-based knowledge representation, can significantly enhance their performance. One such innovative solution is GraphRAG, which combines the power of knowledge graphs with LLMs to boost accuracy and contextual understanding.
The Path to AI Everywhere: New Study Unveils Human-First Strategy for AI-Fuelled Future of Work
Unit4, a leader in enterprise cloud applications for people-centric organizations, launched an IDC InfoBrief, sponsored by Unit4, entitled “The Path to AI Everywhere: Exploring the Human Challenges,” illustrating the strategies required to successfully build an AI-fuelled workplace of the future.
At 2024 AI Hardware & Edge AI Summit: Gayathri Radhakrishnan, Partner – Investment Team, Hitachi Ventures
At the recent 2024 AI Hardware & Edge AI Summit in San Jose, Calif., I caught up with Gayathri Radhakrishnan, Partner – Investment Team with Hitachi Ventures, a venture firm that looks for the best solutions to address the world’s technical, social and environmental challenges The discussion starts with a brief tour of the company’s mission and market […]
The Role of AI in Customizing the Driving Experience
In this contributed article, Boaz Mizrachi, Co-Founder and CTO of Tactile Mobility, discusses how AI and machine learning are redefining the driving experience by personalizing every aspect of vehicle interaction, from tailored comfort settings to predictive maintenance. These technologies enable cars to adapt in real time to driver preferences and behaviors, making driving more intuitive, enjoyable, and safe.
Five Ways AI Will Break Software Development
In this contributed article, Cory Hymel, VP of Research & Innovation at Crowdbotics, discusses why we need to think bigger about AI’s role in software development. The growing capabilities of AI models, particularly large language models, have the potential to fundamentally disrupt the software development lifecycle (SLDC).
WEKA Introduces New WEKApod Appliances to Accelerate Enterprise AI Deployments
WekaIO (WEKA), the AI-native data platform company, unveiled two new WEKApod™ data platform applianced: the WEKApod Nitro for large-scale enterprise AI deployments and the WEKApod Prime for smaller-scale AI deployments and multi-purpose high-performance data use cases.
Why Data Quality is the Secret Ingredient to AI Success
In this contributed article, engineering leader Uma Uppin emphasizes that high-quality data is fundamental to effective AI systems, as poor data quality leads to unreliable and potentially costly model outcomes. Key data attributes like accuracy, completeness, consistency, timeliness, and relevance play crucial roles in shaping AI performance and minimizing ethical risks. Uppin argues that robust data governance practices, including regular data checks and a company-wide data management culture, are essential for sustaining AI accuracy and reducing discrimination.