Category: Unite.AI

Artificial intelligence has long been trying to mimic human-like logical reasoning. While it has made massive progress in pattern recognition, abstract reasoning and symbolic deduction have remained tough challenges for AI. This limitation becomes especially evident when AI is being used for mathematical problem-solving, a discipline that has long been a testament to human cognitive

Ashish Agarwal is an accomplished Chief Technology Officer with extensive experience in the industrial automation industry. He has a robust skill set encompassing software development, start-ups, mobile payments, embedded systems, and mobile devices. Ashish co-founded Weather Risk Management Services Pvt. Ltd. (WRMS) and has been serving as the Chief Technology Officer since January 2016. In

A financial crime investigator who once received large volumes of suspicious activity alerts requiring tedious investigation work manually gathering data across systems in order to weed out false positives and draft Suspicious Activity Reports (SARs) on the others. Today, she receives prioritized alerts with automated research and suggested content that can generate SARs in minutes.

Personal trainers can use a range of AI-powered tools to better their services. From generating customized workout programs and managing client progress to planning nutrition, these tools save time and provide data-driven insights.  Below are some of the best AI tools for personal trainers and AI health , covering workout programming, client management, and nutrition

This marks the first in a series by Unite.AI exploring the growing connections between international government bodies and AI surveillance. Across the globe, state-driven surveillance programs are rapidly evolving, often underpinned by partnerships with powerful technology exporters such as China, Israel, and Russia. Uganda serves as a compelling case study, revealing how AI surveillance has

Artificial intelligence (AI) needs data and a lot of it. Gathering the necessary information is not always a challenge in today’s environment, with many public datasets available and so much data generated every day. Securing it, however, is another matter. The vast size of AI training datasets and the impact of the AI models invite

Have you ever felt like managing your social media is a full-time job? After all, the average person spends nearly 2 hours and 21 minutes per day on social media. But for businesses and creators, it’s safe to assume that number increases when factoring in content creation, scheduling, engagement, and analytics. I recently came across

Rick Caccia, CEO and Co-Founder of WitnessAI, has extensive experience in launching security and compliance products. He has held leadership roles in product and marketing at Palo Alto Networks, Google, and Symantec. Caccia previously led product marketing at ArcSight through its IPO and subsequent operations as a public company and served as the first Chief

After testing the various models in Google’s new Gemini 2.0 family, something interesting becomes clear: Google is exploring the potential of specialized AI systems working in concert similar to OpenAI. Google has structured their AI offerings around practical use cases – from rapid response systems to deep reasoning engines. Each model serves a specific purpose

Suppose an AI assistant fails to answer a question about current events or provides outdated information in a critical situation. This scenario, while increasingly rare, reflects the importance of keeping Large Language Models (LLMs) updated. These AI systems, powering everything from customer service chatbots to advanced research tools, are only as effective as the data