Alaa Mohasseb, University of Portsmouth
For many years, the US company Nvidia shaped the foundations of modern artificial intelligence. Its graphics processing units (GPUs) are a specialised type of computer chip originally designed to handle the processing demands of graphics and animation. But they’re also great for the repetitive calculations required by AI systems.
Black Lotus Ventures, an Atlanta-based AI studio, outlines the successful use of Artificial Intelligence (AI) for content automation and marketing execution. The firm detailed a case study where they transformed an obscure exercise device into a viral product, generating $3.5 million in revenue and over 100 million views in just eight months. This success was achieved through a strategic “Hybrid-AI” framework built upon four central pillars, which included using machine learning for market research and deploying AI avatars to scale user-generated content. A key result highlighted was a single AI-designed video that quickly generated $800,000 in revenue in a 30-day period. Founded by a former Meta product manager, the company suggests this methodology represents a new wave of marketing where AI solutions are used to amplify human ingenuity at scale, offering proven commercial viability across market segments. Continue reading
Nov. 23, 2025 /Mpelembe Media/ — ExperienceBypass™, an advisory firm, announced their new report titled “The Real AI Bubble.” This report, authored by CEO Honorio J. Padron, warns that the AI market faces a structural collapse, arguing the actual bubble is architectural, not financial. The core thesis is that tens of thousands of smaller AI point solution companies will disappear over the next 36 to 48 months as global enterprises consolidate their technology around a few AI Native Platforms (or “AI Factories”) such as NVIDIA and Palantir. This consolidation is driven by the failure of most enterprise AI pilots and a demand for unified architecture, mirroring the standardisation seen in the ERP sector during the 1990s. Padron asserts that non-integrated point solutions lack a place as the AI Enabled Enterprise™ becomes the new operating model, acting as the central nervous system for modern businesses. Continue reading
This is a market research report from Grand View Research whose primary focus is the global artificial intelligence (AI) market, projecting that it will reach $3.5 trillion by 2033, driven by a 31.5% annual growth rate. The document details key market drivers, such as the integration of AI into consumer wearables and advances in deep learning technology, while also segmenting the market by solutions, technologies, functions, end-use (with healthcare and the Asia Pacific region leading in 2024), and region. The report also includes supplementary information from Grand View Research on related AI markets, such as mobile AI and automotive AI. Continue reading
Seeing Machines Limited, an Australian company specialising in computer vision technology for transport safety announced launch of its “attention sharing” feature for the Guardian Generation 3 safety solution, which is marketed to commercial vehicle fleets globally. This world-first feature tracks the cumulative time a driver spends with their eyes off the road, detecting repeated, short glances—a major contributor to crash risk—that other systems often miss. The AI-powered technology continuously monitors eye gaze direction in real time to provide accurate distraction detection and subsequent intervention before safety is compromised. The announcement highlights that the feature is being deployed over-the-air to existing Guardian Gen 3 systems and includes references to supporting scientific studies on driver inattention. Continue reading
Performativ, a technology company, announced the launch of two new offerings: Custom Agents and the AgentKit Builder. These new capabilities are specifically designed to help financial institutions (such as banks and asset managers) safely and compliantly integrate artificial intelligence (AI) agents into their core operations and existing enterprise infrastructure. The solution is built to meet stringent regulatory oversight requirements, including those similar to the European AI Act, by ensuring all agent actions are logged, auditable, permissioned, and have traceability for regulatory review, thus transitioning enterprises from AI experimentation to secure, governed deployment. Continue reading
Nov. 2, 2025 /Mpelembe Media/ — AI agents are primarily used in specialised applications designed to act alongside humans within specific fields and manage complex business processes, often forming the basis of “artificial specialised intelligence” (ASI). Continue reading
The analysis, which examined over ten thousand job postings, found a surprisingly low demand for AI-ready workers, with only 11 per cent of positions mentioning AI, suggesting a potential disconnect between corporate AI ambition and practical implementation. Furthermore, the report highlights an expensive “fire-to-hire cycle” among these top companies, noting that mass layoffs are prevalent but do not appear to be primarily aimed at building a more AI-ready workforce. The source includes commentary from Orgvue’s Chief Product Officer, Jessica Modrall, who asserts that while AI will transform the workforce, many organizations are mistakenly assuming it will simply replace staff. Continue reading
This document addresses the growing complexity of research computing at universities and how many institutions lack the necessary tools and governance to align IT capabilities with faculty research goals. The advisory firm outlines a four-phase strategic approach for higher education IT leaders to evaluate their systems, translate findings into actionable initiatives using the MoSCoW method for prioritisation, and ultimately strengthen research outcomes by better supporting faculty. The resource aims to help institutions overcome issues like fragmented systems and funding challenges by providing a structured framework for improving research IT maturity. Continue reading
This research indicates that employees who utilise artificial intelligence (AI) are saving an average of 7.5 hours per week, which is the equivalent of one full workday, equating to substantial productivity gains. A critical finding is that two-thirds of employees (68%) have not received AI training, leaving potential efficiency unrealised. The study emphasises that training, not generational cohort, is the key determinant of AI success, noting that trained Gen X employees outperform untrained Gen Z employees in AI benefits.Continue reading