Fibre optic communication system is expected to increase exponentially in terms of application due to the numerous advantages over copper wires. The optical network evolution presents several advantages such as over long-distance, low-power requirement, higher carrying capacity and high bandwidth among others Such network bandwidth surpasses methods of transmission that include copper cables and microwaves. Despite these benefits, free-space optical communications are severely impacted by harsh weather situations like mist, precipitation, blizzard, fume, soil, and drizzle debris in the atmosphere, all of which have an impact on the Quality of Service (QoS) rendered by the systems. The primary goal of this article is to optimize the QoS using the ensemble learning models Random Forest, ADaBoost Regression, Stacking Regression, Gradient Boost Regression, and Multilayer Neural Network. To accomplish the stated goal, meteorological data, visibility, wind speed, and altitude were obtained from the South Africa Weather Services archive during a ten-year period (2010 to 2019) at four different locations: Polokwane, Kimberley, Bloemfontein, and George. We estimated the data rate, power received, fog-induced attenuation, bit error rate and power penalty using the collected and processed data. The RMSE and R-squared values of the model across all the study locations, Polokwane, Kimberley, Bloemfontein, and George, are 0.0073 and 0.9951, 0.0065 and 0.9998, 0.0060 and 0.9941, and 0.0032 and 0.9906, respectively. The result showed that using ensemble learning techniques in transmission modeling can significantly enhance service quality and meet customer service level agreements and ensemble method was successful in efficiently optimizing the signal to noise ratio, which in turn enhanced the QoS at the point of reception.

South Africa's Emoyamed Hospital has experienced a stunning 180% revenue growth within just three months of adopting cutting-edge AI and ChatGPT technology. The hospital's new Board of Directors and Management team have also leveraged the power of the 3-I's model – Integrity, Innovation, and Impact – to transform patient care and outcomes. Emoyamed Hospital in Bloemfontein, South Africa, has pivoted from old systems and embraced AI and ChatGPT to build better patient care and financial systems. These new technology innovations have allowed the hospital to serve a larger patient population and expand rapidly. In just two months, the hospital was authorized by the Free State Department to open 57% more beds, a remarkable feat that speaks to the effectiveness of the new AI decision-making systems for patient and system-management protocols. According to Professor Terrence Kommal, the Executive Chairman of Emoyamed, the new board and management team are "rooted in servant leadership and have a deep empathy for humanity."

England's Mike Brown said he is "not a robot" after he was involved in a verbal altercation with a fan following Saturday's defeat by South Africa. Full-back Brown and prop Joe Marler exchanged words with a supporter after the second Test in Bloemfontein. Brown, 32, told BBC Sport that when an England fan is "screaming obscenities and saying you're not trying, you are going to have a reaction". "I just told him to shut up basically," added the Harlequins player. "You can call me whatever in terms of how I've played, that's fine.

Thanks to recent improvements in internet connectivity and the emergence of numerous global big-hitters, South Africa has finally made a name for itself in the technological space. But while one might expect the country's'next big thing' to be found in tech-centric cities like Stellenbosch, it's in fact in an unassuming corner of Bloemfontein where the foundations for South Africa's own Silicon Valley are being laid. Founded in 2014, Bloem-based performance marketing company Xineoh is making waves internationally thanks to its unique vectorization algorithm, which has already generated in excess of $30 million in revenue for clients across the globe, attracting the interest of investors, with $2million received in backing to date in 2017. A pioneer in the AI and machine learning space, Xineoh's distinctive algorithm bears similarities to those used by the likes of Amazon.com and Netflix, tapping into user behaviour to predict potential purchasing behaviour and serve users bespoke information likely to incite conversion. Yet unlike these tried and tested models, Xineoh's algorithm relies on available rather than inputted information, creating associations based on the way other users have interacted with the same product or service, thus enabling it to be used across a wide variety of industries and generate uncannily accurate recommendations.