GPT-4 Boosts Skilled Kenyan Entrepreneurs by 15% Profit While Costing Unprepared Businesses 10% in Six-Month Study
A six-month experiment by researchers from UC Berkeley, Harvard, and Columbia University tested how a GPT-4-powered AI advisor influenced small business owners in Kenya.
The most capable entrepreneurs increased their profits by 15 percent after using the tool. They treated the model’s suggestions as starting points rather than ready-made instructions and adapted them to real-world constraints, such as purchasing generators to handle frequent power outages or expanding their service offerings.
In contrast, less experienced participants lost approximately 10 percent of their income. They frequently implemented the AI’s generic recommendations without scrutiny, for example by lowering prices in ways that reduced overall revenue despite appearing logical in the chat interface.
The study concludes that GPT-4 functions less as a business consultant and more as a highly confident generator of losses when users forgo critical evaluation. The researchers emphasize that the problem stems primarily from the human tendency to stop thinking critically rather than from any flaw in the underlying technology.
Supporting evidence comes from an earlier Dickinson College experiment in which 97 percent of participants copied a clearly wrong answer generated by ChatGPT on a straightforward task, while the control group without AI performed better. A simple prompt reminding users to verify the output doubled accuracy rates.
Analysis of 1.4 million work sessions at KPMG produced similar findings: roughly 95 percent of users request a draft or summary and accept the first result, whereas only 5 percent treat the model as a collaborative reasoning partner by supplying context, guiding the chain of thought, and questioning outputs.
For organizations, these patterns mean that simply providing access to generative AI tools says little about expected productivity gains. Universal guidelines can even prove counterproductive because different tasks require different degrees of human oversight. The technology can accelerate strong performers while convincingly leading weaker users in the wrong direction.
Related articles
R-Vision SIEM Demonstrates Resilience During Intense Standoff 17 Cyber Defense Exercise
A mixed team from akPots defended the Telecom sector at Standoff 17 using R-Vision SIEM as the central correlation platform while facing more than ten simultaneous red-team groups. The exercise featured nine realized critical events out of 37 planned scenarios, including satellite tracking disruption, IPTV broadcast manipulation, and unlimited eSIM issuance. Team members had to master the SIEM in real time rather than through pre-loaded logs, relying on raw search, custom dashboards, and grouping features to cut through massive alert volumes. Additional tools such as PT Application Firewall, PT NAD, PT Sandbox, and PT Container Security provided visibility into network traffic, file behavior, and Kubernetes environments. The team organized work through dedicated chat threads, a shared living document for IOCs, and a captain role to balance workload across distributed participants. Feedback highlighted the need for one-click widget-to-raw-event navigation, vendor-supplied detection scenarios, and nested grouping to improve future investigations.
Avanpost Launches Identity Cloud Service, CURATOR Becomes First Partner
Avanpost has begun commercial operation of its Identity Cloud platform, a subscription-based service for multi-factor authentication and single sign-on aimed at employees and contractors. The service removes the need for heavy on-premises IAM deployments by allowing organizations to adopt cloud identity protection through flexible subscription plans. CURATOR became the first partner to roll out the platform, offering it under the CURATOR.IDENTITY brand. Four tariff tiers are available, ranging from basic Start to the upcoming Zero Trust package that includes device verification and continuous trust assessment. Each customer receives an isolated environment with its own database, while Access Bridge keeps infrastructure secrets on-premises and supports offline authentication during connectivity loss. Partners can either resell the Avanpost service or deploy the platform in their own infrastructure and sell it under their own branding.
Microsoft 365 Admin Tool Exposes Pitfalls in Graph, Exchange PowerShell and Intune Management
An open-source developer has released version 2.0 of SwissKnife for MS Graph, a tool that adds a safe preview-and-apply layer on top of Microsoft 365 administration. The project addresses the lack of a native what-if mode in Microsoft Graph and the incomplete coverage of Exchange tasks in the Graph API. It implements a two-step plan-and-apply workflow, supports fallback to Exchange Online PowerShell or the Admin API, and runs community scripts under strict constraints. The author details multiple real-world obstacles including named-location ID drift in Conditional Access policies, masked secrets returned by Intune, and limitations when restoring Transport Rules from snapshots. The tool also provides a worker mode for macOS and Linux users and enforces script signing plus AST-based command whitelisting. Feedback is requested on error messages and tasks that still require manual PowerShell use.
Neuromorphic Processors Lag Behind GPUs for Large AI Models Despite Energy Advantages
Neuromorphic chips such as Intel Loihi promise major energy savings by activating only when events occur, yet data centers remain dominated by GPUs optimized for dense matrix operations in generative AI. The mismatch arises because modern large language models rely on high-precision linear algebra, massive memory bandwidth, and mature software stacks that neuromorphic architectures currently lack. Researchers are exploring spiking transformers and on-chip plasticity via mechanisms like STDP, but scaling to billions of parameters remains challenging. Companies including BrainChip, SynSense, and SpiNNaker2 have released commercial neuromorphic hardware, yet the absence of standardized tools and clear performance gains for mainstream workloads slows adoption. Hybrid approaches combining neuromorphic blocks with in-memory computing, analog circuits, and photonic accelerators may define future heterogeneous systems rather than outright replacement of GPUs.