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The January-March edition of Oil And Gas News Africa
(Johannesburg, April 4, 2024) – PWL Global Network, the Africa’s fastest-growing publishing company, has published the latest edition of Oil And Gas News Africa. This publication is a highly regarded voice within the Oil And Gas Sector for its in-depth reports and interviews with prominent figures in the industry.
You can visit Oil And Gas News Africa for daily news and analysis of the ever-changing financial industry.
The effect of artificial intelligence will be felt across multiple industries, and advertising is no different. From programmatic buying to e-commerce, AI is already disrupting how brands engage with consumers. Early iterations of AI-enhanced advertising have led to a somewhat negative perception surrounding ads which “stalk” people around the internet, as well as fears of job displacements, but the real future of AI in advertising will rely on people collaborating to craft experiences which bring genuine value to consumers.
“Brands aren’t just existing by what they say but by what they do. They must create and spark new customer interactions,” says Ogilvy Consulting Senior Partner Pierre Robinet, speaking at The Economist’s Innovation Summit. “These interactions have to be relevant and useful, sharable and personal, providing an essential service at the right moment and in the right place.”
AI has a role to play here, as exemplified by Nestlé’s family nutrition assistant in China. As China is a country with low levels of nutrition literacy, nutrition informatin is sorely needed. Ogilvy saw an opportunity to bring that knowledge to users in a new way, using AI-powered devices to assist and inform families about nutrition in the kitchen while they are preparing meals.
In his panel at the Innovation Summit, Robinet shared insights on how and where he sees AI fitting into the advertising industry — and the long-term impact it will have.
Human jobs will evolve, not disappear
AI will displace specific tasks, not entire roles; and organizations keen to tap into its potential will need to rethink how they do business, including breaking down the walls between silos.
As Robinet puts it:
“At Ogilvy we believe that digital transformation that is customer-centric needs to be approached from a marketing, IT, and culture change point of view. When it comes to AI, and helping move a client to an AI enterprise model, it is much the same; We first examine marketing impact and then emphasize how AI will help brands interact better with the customer and generate growth. We bring our clients IT support, ensuring they have the right AI network infrastructure, and assess and clean their data. Finally, we support them in understanding the impact AI will have on their jobs and organization.”
“No AI enterprise will fit solely into one department; they have to work collectively. Most of the success we’ve had is because we bring together every silo and combine resources from every department in one room, so that we can co-create something that brings value.”
AI offers capability which can entirely reshape how we do business
Per Gartner’s predictions, by 2020, 85 per cent of customer interactions will be managed without the need for a human being. This presents a fantastic opportunity to rethink customer strategy. How do we engage with an AI-empowered customer who speaks more than they write, who uses their face and fingers to interact with their devices, who prizes a hassle-free experience?
Rather than thinking in terms of AI destroying jobs, consider a more fruitful approach: investigate how AI will disrupt entire business models. In fact, that is already happening.
“AI is going to impact the legacy cost and revenue structure of any company,” says Robinet. “Retailers are always trying to be more accurate in predicting which product you want to get from their platform. Amazon is already moving stuff into their warehouses based entirely on predictive demand, moving the model from ‘shopping then delivery’ to ‘delivery then shopping.”
We are currently in an exciting period of experimentation, where brands and marketers are exploring the different possibilities and applications of AI. Decision makers now must figure out how AI can impact business models to being a driver of growth. “Piloting is about testing in real life, so you can access deep, valuable human insight,” says Robinet.
We must demystify AI before people will accept it
In order to overcome fear and mistrust of issues like the mishandling of data, Robinet believes that that each and every consumer is equipped to understand these technologies so they can make an informed decision. “On one side, we need more fairness and ethics and transparency in AI, as well as specific frameworks and rules to do so” he says. “While on the other, we need to empower people, give them the right tools, services and education, and motivate them to share their data.”
Acceptance will be key in AI adoption.
As AI is becoming more and more ambient every day, we must inscribe it in a logic of attentive and intentional environment, giving it the ability to express its attention and intentions towards us. We must think about the importance of customer experience design as well and how to best enable consumers to interact and communicate with machines. This is where brands come into play, sparking interactions that are both individual and universal.
Robinet outlines four broad guiding measures for companies who are looking to shift towards an AI enterprise.
In recent years, the term “Artificial Intelligence” has been making headlines in almost every industry. From healthcare to finance, AI is transforming the way we work and live. But what about the media landscape? Could AI be a game-changer in this field too? In this blog post, we will explore how AI is revolutionizing the media industry and how it is changing the way content is created, consumed, and distributed. Get ready to discover a whole new world of possibilities with AI!
Game-Changer is an understatement when it comes to the impact of Artificial Intelligence (AI) on the media landscape. From content creation and curation to advertising strategies, AI is transforming traditional models across all dimensions of media. Today’s news consumer demand personalized experiences, real-time updates and engaging visual multimedia elements that are more tailored and relevant than ever before. With AI-powered algorithms analyzing audience behaviour patterns, news organizations are now able to deliver highly-targeted content that speaks directly to the interests of their visitors.
While this presents massive opportunities for publishers seeking better engagement rates and revenue streams, these advancements also come with ethical considerations given the increasing role that technology plays in our daily lives. As we move forward into a new era where machines continually learn from our everyday interactions online; understanding how best to manage this rapid evolution will be critical for those who want success in tomorrow’s media industry.
As technology evolves, Artificial Intelligence (AI) has emerged as a game-changer in the media industry. AI refers to the simulation of human intelligence processes through machines and algorithms that are capable of learning, reasoning and problem-solving tasks. Its impact on media is largely driven by data analysis capabilities which enable personalized content distribution, targeted advertising and automated content creation.
One important aspect of AI is its ability to analyze large amounts of data quickly and accurately. This enables media companies to identify patterns in consumer behavior and tailor their content accordingly. For instance, news outlets can use AI-powered tools to curate news stories that align with readers’ interests based on their browsing history or social media activity.
Additionally, AI technologies are increasingly being used for automated journalism, where natural language generation software creates articles based on structured data such as reports or financial statements. This not only saves time but also allows journalists to focus more on investigative work.
In summary, it’s clear that understanding the potential impact of AI is crucial for any organization looking towards building a successful future in the ever-changing landscape of digital media.
AI is changing the way we consume news and information by personalizing our online experience. With AI-powered algorithms, media companies can now recommend articles, videos or social media posts tailored to our preferences, based on our browsing history and behavior. AI also helps us access relevant content faster by summarizing lengthy articles into key points or creating bite-sized news updates that can be consumed in a matter of minutes.
The rise of chatbots and virtual assistants also enables a more conversational approach to consuming news. Users can engage with these bots via messaging apps or voice commands, receiving personalized news updates without having to scroll through multiple sources manually.
However, there are concerns about the reliability and bias of AI-generated content. As algorithms learn from past behaviors, they risk perpetuating biases towards certain individuals or groups. It is crucial for media companies to prioritize transparency and accountability as they integrate AI into their operations.
Content Creation and Curation are two areas where AI is making a significant impact. With the help of Natural Language Processing (NLP) and Machine Learning (ML), AI can now generate articles, reports, and even entire books. The Washington Post’s Heliograf, for instance, is an AI-powered tool that can write news articles in real-time. Similarly, AI algorithms can analyze vast amounts of data to curate personalized content for individual users. Netflix’s recommendation engine is a prime example of this. By analyzing users’ viewing history and preferences, it suggests movies and TV shows that they are likely to enjoy. As AI continues to evolve, we can expect more sophisticated content creation and curation tools that will enable media companies to produce high-quality content at scale while delivering personalized experiences to their audiences.
The impact of AI on advertising and marketing strategies cannot be overstated. With the ability to analyze vast amounts of data, AI is transforming the way companies target and engage with their audiences. AI-powered tools such as chatbots and virtual assistants are becoming increasingly popular in customer service, providing personalized experiences and streamlining communication. In addition, AI is enabling more effective ad targeting, allowing advertisers to reach the right audience at the right time with the right message. The use of machine learning algorithms also enables marketers to optimize their campaigns in real-time, making adjustments based on user behavior and engagement. As AI continues to evolve, it will undoubtedly play an even greater role in shaping the future of advertising and marketing in the media industry.
The future of journalism is inevitably linked to AI. With the ability to gather data, analyze information, and generate accurate reports at a lightning speed rate, AI has already proven its potential in transforming the media industry. However, it also brings some concerns about the nature of news accuracy and ethics.
There are concerns that automated content creation algorithms will lead to biased reporting or make journalistic errors more common. Moreover, as machines begin writing human-like language without control, there may be cases where fake news spreads faster than we can verify it.
However, with careful planning and regulation guiding development in this field, AI could lead to significant improvements in journalism. By enabling journalists with deeper insights into complex stories through real-time fact-checking tools or enhanced research capabilities for investigative pieces they can uncover hidden truths otherwise missed by traditional methods.
Ultimately though Journalists must learn when their storytelling needs automation’s help and utilize those opportunities rather than being replaced by them wholly.
The Power and Responsibility of AI in Media Industry Ethics
AI has the potential to revolutionize the media industry, but with great power comes great responsibility. As AI technology becomes more advanced, it raises important ethical questions about its use in media. One key concern is bias – AI algorithms can inadvertently perpetuate existing biases present in society or be programmed with biases by their human creators. Another issue is accountability – who should be held responsible for mistakes made by AI systems? It’s crucial that individuals and organizations using AI in media take steps to address these concerns and prioritize transparency and fairness in all aspects of their operations involving AI.
As AI becomes more prevalent in content creation, there is a growing concern about how to balance objectivity with personalization. While AI can help tailor content to individual preferences, it can also create filter bubbles that limit exposure to diverse perspectives. Additionally, there is a risk of bias in the algorithms used by AI systems called “Hallucinations”. It is important for media companies to establish ethical guidelines for the use of AI in content creation and ensure transparency in how algorithms are developed and used. Ultimately, the challenge for AI-powered content creation is to provide personalized experiences while maintaining journalistic integrity and promoting diversity of thought.
As AI becomes more prevalent in the media industry, it is important to address the potential for bias and discrimination in its applications. AI algorithms are only as unbiased as the data they are trained on, and if that data contains inherent biases, the resulting decisions made by the AI can perpetuate those biases. This can lead to further inequality and discrimination in areas such as hiring practices or news coverage. It is crucial for media companies to actively monitor and address any biases in their AI systems to ensure fair and equal treatment for all individuals.
As AI continues to gain ground in the media industry, it is important to strike a balance between efficiency and humanity in newsroom operations. One ethical concern that arises with the use of AI is the potential for bias in automated content creation and curation. Additionally, there are concerns about privacy violations when using AI-powered tools to analyze user data for targeted advertising. It’s crucial for media companies to prioritize transparency and accountability when implementing AI technologies. This means acknowledging their limitations, regularly reviewing algorithms for biases, and ensuring that human oversight remains integral throughout production processes. By doing so, we can ensure that technology serves as an aid rather than a substitute for journalistic integrity and empathetic reporting practices.
AI Algorithms Boost Newsroom Efficiency: Case Studies from Major Media Outlets
Major media outlets like The New York Times, Associated Press and Reuters are already using AI algorithms to boost their newsroom efficiency. For instance, the AP uses AI-powered software to write quarterly earnings reports for thousands of publicly traded companies. Meanwhile, The New York Times uses an AI tool called Editor that helps suggest article topics and potential sources for writers. Similarly, Reuters employs Lynx Insight which is an AI system that analyzes data in real-time helping journalists find newsworthy stories quickly. These examples demonstrate how AI is revolutionizing the way newsrooms operate by enabling them to automate routine tasks and freeing up time for more high-value work such as investigative journalism or deep analysis.
Netflix and Spotify are two prime examples of how AI is transforming the media landscape through personalization. By analyzing user data, these platforms are able to recommend content that is tailored to individual preferences and behaviors. This not only enhances the user experience but also increases engagement and retention rates. Netflix’s recommendation algorithm, for instance, uses machine learning to suggest movies and TV shows based on viewing history, ratings, and even time of day. Similarly, Spotify’s Discover Weekly playlist uses AI to curate a personalized mix of songs based on listening habits. As AI continues to evolve, we can expect more media companies to adopt this personalized approach in order to stay competitive in the market.
Personalization in News- Soon we shall have, news curated via Bard & Bing chats and even media apps will use self trained AI to serve personalized news.
Deepfakes, a type of synthetic media created using AI, have raised concerns about the ethics of journalism. With the ability to manipulate videos and images, deepfakes can be used to spread false information and damage reputations. In 2019, a deepfake video of Nancy Pelosi went viral on social media, raising questions about the authenticity of political content. While some argue that deepfakes can be used for entertainment or satire, others worry about their potential to deceive the public. As AI continues to advance, it is crucial for journalists and media organizations to consider the ethical implications of using deepfakes in their reporting.
Facebook and Google are just two examples of how AI is transforming the way advertisers reach their target audiences. With highly sophisticated algorithms, they can analyze user behavior to deliver hyper-targeted ads that are more likely to convert into sales. Facebook’s Dynamic Ads for Broad Audiences uses machine learning to match products with users who are most likely to buy them, while Google’s Smart Bidding uses real-time data to set bids for each auction automatically. The result? A more efficient advertising process that saves marketers time and money while delivering personalized experiences for consumers. AI-driven analytics make targeted advertising smarter than ever before, changing the game in digital marketing strategies.
Preparing for the AI-Driven Future of Media Industry
As AI continues to revolutionize the media landscape, it’s important for media professionals to adapt and prepare for the changes ahead. One key step is to embrace a data-driven approach in all aspects of media production, from content creation to distribution and marketing. This means leveraging AI-powered tools and analytics to gain insights into audience behavior and preferences, and using that information to inform decision-making.
Another important consideration is investing in AI talent and expertise. As AI becomes more integral to media operations, having skilled professionals who can develop and implement AI strategies will be crucial. This may involve hiring data scientists, machine learning engineers, and other specialists who can help drive innovation and keep pace with technological advancements.
Finally, it’s important for media organizations to stay informed about the latest developments in AI. This means keeping up with industry news, attending conferences and events focused on AI in media, and networking with other professionals in the field. By staying ahead of the curve, media organizations can position themselves for success in an increasingly AI-driven world.
As the media industry continues to evolve, it’s clear that AI is a game-changer. While some may fear the impact of automation and machine learning, it’s important to embrace the opportunities that AI presents. By understanding how AI is transforming the media landscape, we can prepare for a future where technology plays an even greater role in our lives.
One key takeaway is that adaptability is crucial. As AI continues to develop and change, media professionals must be willing to learn and adapt alongside it. This means staying up-to-date with the latest technologies and trends, as well as being open to new ways of thinking about content creation, curation, and distribution.
Ultimately, the future of media with AI is both exciting and challenging. By embracing this game-changer, we can create a better media landscape that serves audiences more effectively than ever before.
In conclusion, AI is undoubtedly a game-changer in the media landscape. From transforming the way we consume news and information to revolutionizing advertising and marketing strategies, AI is opening up new opportunities for the media industry. However, as with any technological advancement, there are also ethical implications that need to be addressed. It is important for media professionals to stay informed and prepared for the AI-driven future of the industry. By embracing this game-changer, we can create a better media landscape that is more efficient, effective, and engaging for audiences around the world.
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With its solid technical expertise and market experience in dewatering, slurry and sludge pumping solutions, Integrated Pump Technology has proved its capacity to support the highest quality pump brands.
Its offering recently grew from its established range of Grindex and Faggiolati submersible pumps to include the well-respected Godwin range of diesel driven pumps. Justin Bawden, Key Accounts Manager at Jet Park-based Integrated Pump Technology, explains that this adds considerable value to customers – as the pumping business is all about matching the right pump to each specific duty and application.
“The Godwin range of diesel powered pumps is a great boost for customers wanting to deploy a robust pumping solution in locations where electricity is not available,” says Bawden. “As important as the quality of these pumps, though, is our ability to support them to the demanding standards set by the original equipment manufacturer (OEM).”
To service its submersible and diesel driven ranges of pumps, Integrated Pump Technology boasts a modern technical workshop and warehouse which ensures that customers experience quick access to the equipment, servicing and spare parts they need. He highlights that the company’s active network of distributors around southern Africa visit customers regularly to offer support and technical advice.
Making mines safer and more productive has long been the strategic intention of mine automation, and surface drill rigs are now part of this technological evolution.
According to Kabelo Nkoana, Business Line Manager for Automation and Digitisation at Sandvik Southern Africa, AutoMine® is available for Sandvik i-Series models in the company’s intelligent range of down-the-hole top hammer and rotary blast hole drill rigs. Mining customers in southern Africa have been embracing the functionality, and reporting positive results.
“Sandvik AutoMine® system essentially replicates the machine control system to enable remote automation over the mine’s Wi-Fi network,” he says. “There is an awareness that safety could be compromised when rigs are operating close to a highwall, or when there are unstable geological conditions on the bench. Automating a drill rig in these conditions is an important contributor to safety.”
Sandvik’s i-Series machines come standard with features such as the onboard data collection unit technology for engine operation and other major components. Various operational and machine health data from the sensors are collected in the OEM’s Knowledge Box, and transmitted to cloud storage for analysis and real time reporting to support informed and accurate decision making. This creates the foundation for the automation process, which also enhances reliability and performance.
Pilot Crushtec’s crushing and screening solutions are key for a wide range of applications within the energy minerals sector, and the company has built a significant footprint in these industry segments.
Wayne Warren, Sales Manager Africa at Pilot Crushtec, highlights that the company has crushing and screening equipment operating successfully in lithium, cobalt, manganese, nickel, copper and graphite operations in the region.
“The flexibility of our mobile and modular equipment allows customers to tailor solutions to match diverse ore characteristics and processing plant requirements. This adaptability is crucial, especially when dealing with variations within the same commodity category, like lithium ores that differ in behaviour,” he explains.
Pilot Crushtec’s equipment selection also considers material abrasiveness, minimising equipment wear by bypassing crushers when necessary. Their mobile equipment often includes pre-screening options as standard, reducing the need for additional screens.
The increasing reliance of South African businesses on generator sets (gensets) to mitigate power disruptions highlights a crucial need for proper selection based on specific operational demands. Despite their growing usage, there’s still widespread confusion about how to choose the appropriate genset, often leading to inefficient and costly decisions.
Understanding the differences between standby, prime and continuous applications is essential to optimise genset performance and longevity. This is according to Craig Bouwer, Senior Manager Gensets at WEG Africa, who explains that many customers mistakenly select gensets based solely on nameplate rating.
“Understanding the specific application of the genset is crucial for the right selection, and the first step is knowing that genset applications are broadly categorised into standby, prime and continuous, each with distinct operational requirements,” he says.
Standby gensets are seldom used, typically kept for emergency situations. These units have a limit on operational hours per year and a specific load factor. In South Africa, due to frequent load shedding, few gensets are used solely for standby purposes.
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Low oil level is a serious cause of contamination in the hydraulic system. When the oil level is low, more air gets into the tank, and this often leads to destructive cavitation in the pump and to condensation on the tank walls, which generates sludge. Sludge decreases the lubricity of the oil, producing scoring and friction on surfaces with close tolerances. Visit www.wearcheck.co.za for more condition monitoring information.
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Q: ‘When analysing the debris found in an oil filter, is there a standard or generally accepted method for conducting the analysis?’
A: Used oil filters provide lots of clues about the oil condition. Inspecting a dissected filter reveals information about the filter itself – looking for collapsed media, bad seals or weak points that developed during use. The debris remaining in the used filter also indicates important facts about the machine’s health.
Here, we discuss three different options for analysing this filter debris. The first method is quick, easy and free, and can be conducted on site. The next two involve the use of laboratory instruments. You can choose which debris/ filter examination method you need depending on how much detail you require.
Canister filters
For a canister style filter, a cost-effective, easy technique is to simply cut the filter in half, and remove the media. Then, conduct a visual inspection of the media, for sludge, varnish or shiny particles. An additional step at this point would be to use a magnet – this is a good way to determine whether any of the shiny particles are metallic.
For a more scientific version of this method, the media can be extracted from the filter following the above technique, and then submitting it to a reliable laboratory, where it will be analysed by trained technicians. Several methods are used in the laboratories, including separating the debris from the filter media using ultrasonic agitation
Once the debris is separated, the size of the contaminants is assessed, counted and categorised, and many additional condition monitoring tests can be conducted to determine the machine’s health.
Thirdly, a different option is not to remove the filter media, but rather to drill a hold into the filter canister to extract the oil. This is then collected in a sample bottle, and visually inspected with a laser beam for particulate matter.
When inspecting with a laser, safety is of paramount importance.
Similarly to method one, a magnet can be employed to show whether any of the particles are metallic. Again, the sample can be submitted to a laboratory for more detailed, scientific testing.
ASTM D919-14 is the standard guide for filter debris analysis using manual or automated processes. This standard can be reviewed for a more detailed, step-by-step process. Visit www.wearcheck.co.za for more condition monitoring information.
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Sources of solid contaminants in crankcase oils might include dirt and airborne dust, engine wear debris, rust, fuel soot and manufacturing or rebuild debris.
Road dust particles are typically harder than metallic wear particles and can cause far more abrasive damage and contact fatigue to interior machine surfaces than most other contaminants. Visit www.wearcheck.co.za for more condition monitoring information.
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Black diesel engine exhaust smoke can be a concern, as can white smoke. However, blue smoke is the worst. It is rarely a transient condition but rather a serious engine defect. It occurs when the engine is burning too much oil due to poor piston ring control (collapsed or worn rings), worn intake valve guides or other causes of high oil ingress into the combustion chamber. Blue smoke usually means the engine is heading for serious trouble. Don’t delay in getting the problem diagnosed and fixed to avoid excessive collateral damage. Visit www.wearcheck.co.za for more condition monitoring information.
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Synthetic oils have many notable advantages, which are most distinct when used at extremely high or low temperatures. Among the benefits are good oxidation stability, and a higher viscosity index. Additionally, a lower coefficient of friction in some synthetic oils facilitates their use at higher operating temperatures.
Furthermore, the lower pour points, coupled with a higher viscosity index, enable operation at lower temperatures. Visit www.wearcheck.co.za for more condition monitoring information.
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