Category: Unite.AI
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Even State-Of-The-Art Language Models Struggle to Understand Temporal Logic
Predicting future states is a critical mission in computer vision research – not least in robotics, where real-world situations must be considered. Machine learning systems entrusted with mission-critical tasks therefore need adequate understanding of the physical world. However, in some cases, an apparently impressive knowledge of temporal reality could be deceptive: a new paper from
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Claudionor Coelho, Chief AI Officer at Zscaler – Interview Series
Claudionor Coelho is the Chief AI Officer at Zscaler, responsible for leading his team to find new ways to protect data, devices, and users through state-of-the-art applied Machine Learning (ML), Deep Learning and Generative AI techniques. Prior to joining Zscaler, he served as Chief AI Officer and Senior Vice President of engineering at Advantest. Previously
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Breaking Data Barriers: Can Anthropics Model Context Protocol Enhance AI Performance?
Anthropic’s innovative Model Context Protocol (MCP) aims to tackle fragmented data and boost the efficiency of AI-powered solutions. Could it become the standard for context-aware AI integration? One of the most pressing challenges in artificial intelligence (AI) innovation today is large language models’ (LLMs) isolation from real-time data. To tackle the issue, San Francisco-based AI
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What You Need to Know About OpenAI’s Operator
Over the past few weeks, OpenAI has been laying groundwork. While most users were just starting to really explore ChatGPT Tasks – a new feature that lets user schedule and trigger tasks – the company was preparing for something far more significant. Yesterday’s release of Operator is yet another clear signal of where artificial intelligence
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Synthetic Data: A Double-Edged Sword for the Future of AI
The rapid growth of artificial intelligence (AI) has created an immense demand for data. Traditionally, organizations have relied on real-world data—such as images, text, and audio—to train AI models. This approach has driven significant advancements in areas like natural language processing, computer vision, and predictive analytics. However, as the availability of real-world data reaches its
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Productivity Myths in Software Engineering
Over two decades, the concept of productivity has evolved and expanded in all sorts of directions within software engineering-on many occasions with confusing or contradictory results. During my early years in this field, I was under the wrong impression that more hours of work, more lines of code, and more “activity” automatically meant better results.
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10 Best AI Music Generators (January 2025)
Artificial intelligence (AI) is being increasingly implemented across artistic fields like music, film, and other forms of art. When implemented, it can impact every aspect of the music-making process including music generation, audio mastering, and music streaming. Another great opportunity provided by AI is that it gives amateur musicians an innovative way to improve their
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Rebecca Carr, CEO of SmartRecruiters – Interview Series
Rebecca Carr is the CEO at SmartRecruiters. With over 15 years of experience in recruiting and HR technology, Rebecca brings a deep understanding and passion for the space, supported by roles in product development, pre-sales, and customer success. Her contagious energy and strong leadership give her a unique perspective on this role and organization. Rebecca’s
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AI-Powered Personalization: Balancing Automation and Human Creativity in the Digital Age
Personalization has become the cornerstone of all online experiences. At the heart of every great marketing campaign is human connection. Even in our chronically online world, consumers (perhaps more than ever) expect to be known on an individual level. Whether it’s social media feeds or the brands they buy from, audiences anticipate content tailored to
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Western Bias in AI: Why Global Perspectives Are Missing
An AI assistant gives an irrelevant or confusing response to a simple question, revealing a significant issue as it struggles to understand cultural nuances or language patterns outside its training. This scenario is typical for billions of people who depend on AI for essential services like healthcare, education, or job support. For many, these tools