Author: Carter

social media, someone claims their “AI agent” will run your entire business while you sleep.It is as if they can deploy AGI across factories, finance teams, and customer service using their “secret” n8n template. n8n is a low-code automation platform that lets you connect APIs and AI models using visual workflows – (Image by Samir Saci) My reality check is that many companies are still struggling to collect and harmonise data to follow basic performance metrics. Logistics Director: “I don’t even know how many orders have been delivered late, what do you think your AI agent can do?” And these…

A UR5 cobot uses strain wave gearing for smooth motions in material handling. Source: Universal Robots Long gone are the days of rigid robotics, where arms jerk and clank in the most unintuitive ways. These movements have hindered production and industry for years, requiring massive spaces to operate and maintain the machinery. Fluid robot motion has revolutionized the game, enabling machinery to operate in tighter spaces with greater mobility. Behind these innovations are several crucial components and technologies that are often overlooked. The importance of fluid robot motion Conventional robotic locomotion is restrictive, especially in fields that require a more…

The Fool’s TakeCloud computing leaders are among the largest and most successful companies in the world. Competing with them is challenging, especially for smaller players. However, Veeva Systems’ clever strategy is helping it succeed. Rather than go toe-to-toe with giants like Amazon, Veeva built cloud services to serve the demands of one industry: life sciences.Drugmakers and medical device manufacturers must adhere to strict guidelines — from regulatory compliance to data integrity and patient privacy. If they don’t, they could lose business, fail to launch products, undergo lawsuits or incur the wrath of lawmakers. Veeva Systems helps them follow those rules,…

A machine-learning model has calculated country-specific cancer mortality-to-incidence ratios and evaluated the factors that contribute the most to each country’s survival gaps. Additionally, the artificial intelligence (AI) tool mapped out actions each country could take to improve cancer outcomes. A report explaining the establishment of the machine learning framework and its country-specific findings was published in Annals of Oncology.  “Global cancer outcomes vary greatly, largely due to differences in national health systems. We wanted to create an actionable, data-driven framework that helps countries identify their most impactful policy levers to reduce cancer mortality and close equity gaps,” said co-lead researcher…

Industrial cybersecurity is standing at a crossroads where ‘locking down the perimeter’ is no longer enough to protect increasingly interconnected factories, grids, and process environments. Traditional defenses fall short when IT networks are connected to OT systems and attackers leverage this broadened attack surface to cause production interruptions, safety degradation, and negate reliability improvements that took years to develop within a matter of a few minutes. More than one-third of manufacturers identify enhancing IT/OT security as a key business priority, and nearly half say they intend to validate uptime and quality using real-time analytics and AI, rather than just relying on…

Cargo terminals are no longer peripheral facilities operating quietly behind passenger terminals. They are becoming decisive control points in global air freight networks, shaping reliability, speed, and operational resilience. As air cargo settles into a post-disruption phase marked by fluctuating demand and tighter service expectations, the focus has shifted from short-term capacity expansion to structural transformation. Automation is increasingly being embedded in how cargo terminals are designed, operated, and governed.Across major hubs, this shift is unfolding simultaneously on the warehouse floor, within digital coordination layers, and at the level of physical infrastructure. Together, these changes are redefining what a modern…

or fine-tuned an LLM, you’ve likely hit a wall at the very last step: the Cross-Entropy Loss. The culprit is the logit bottleneck. To predict the next token, we project a hidden state into a massive vocabulary space. For Llama 3 (128,256 tokens), the weight matrix alone is over 525 million parameters. While that’s only ~1GB in bfloat16, the intermediate logit tensor is the real issue. For large batches, it can easily exceed 80GB of VRAM just to compute a single scalar loss. Optimising this layer is how libraries like Unsloth and Liger-Kernel achieve such massive memory reductions. In this…

Dr. Mehmet Oz recently highlighted Alabama’s plan to use robots for ultrasounds due to a shortage of OB-GYNs during a rural healthcare roundtable with White House officials, a statement that has sparked significant attention on social media. The initiative is part of Alabama’s use of the $203 million awarded under the federal government’s Rural Health Transformation Program, which was created in the Big Beautiful Bill.According to the grant proposal, Alabama intends to allocate some of the funding for digital obstetric regionalization and telerobotic ultrasound. However, OB-GYNs in the state expressed skepticism about the plan’s effectiveness.”This won’t take care of access…

The reliability of machine learning classification systems is increasingly threatened by inaccurate ground truth labels, despite careful data curation by expert annotators. Zan Chaudhry, Noam H. Rotenberg, and Brian Caffo, alongside Craig K. Jones et al. from Johns Hopkins University and the Johns Hopkins Bloomberg School of Public Health, address this critical issue with a new approach to identifying mislabeled data. Their research introduces Adaptive Label Error Detection (ALED), a method that leverages feature extraction and Gaussian distribution modelling to pinpoint samples with incorrect labels. This novel technique demonstrates significantly improved sensitivity in detecting errors, without sacrificing precision, across several…

Only 10% of organizations have a well-developed strategy for managing non-human and agentic identities, according to a recent Okta survey of 260 executives. This gap is alarming given that 87% of breaches involve some form of compromised or stolen identity, and agentic AI introduces entirely new categories of identity that most security frameworks were never designed to address. The challenge is not simply that AI agents are new. Traditional AI systems generate predictions or recommendations that humans review before implementation. Agentic systems close that loop entirely.  They interpret instructions, develop multi-step plans, access resources and execute operations across infrastructure with…