Recent advancements of generative LLMs (Large Language Models) have exhibited human-like language capabilities but have shown a lack of domain-specific understanding. Therefore, the research community has started the development of domain-specific LLMs for many domains. In this work we focus on discussing how to build mining domain-specific LLMs, as the global mining industry contributes significantly to the worldwide economy. We report on MiningGPT, a mining domain-specific instruction-following 7B parameter LLM model which showed a 14\% higher mining domain knowledge test score as compared to its parent model Mistral 7B instruct.

Mining is an important sector in India, contributing to the country's economic growth. The Indian mining industry encompasses exploration, extraction, and processing of minerals and metallic and non-metallic minerals. With increasing demand for minerals, the mining industry in India has seen significant growth in recent years. In this report, we will analyze the current state of mining technology in India and its impact on the mining industry. The mining industry in India has made significant advancements in recent years, with the introduction of modern technology.

Chile's mining industry reported 58 accidents and 68 deaths in the last five years (2017-21), according to geology and mining bureau Sernageomin. Those grim figures could change with the internet of things and artificial intelligence through metrics and predictive models that manage human errors and save lives. That is the technological option of a local start-up, Gauss Control, which in 2020 received recognition from the MIT Technology Review as one of the main innovators in Latin America. Today it monitors more than 20,000 workers, many in the mining industry, where most accidents are caused by the operation of equipment such as trucks, buses, pick-ups, mechanical shovels, etc. To find out how new technological devices can help reduce accidents and fatalities in the mining sector, BNamericas spoke with José Rafael Campino, founder and CEO of Gauss Control.

Machine Learning and Artificial Intelligence, together with other advanced modelling techniques, are continuously evolving and you can find thousands of algorithms, tools, platforms, etc., making it challenging to identify and validate the correct approach, technologies and solutions to use in the Mining industry. Furthermore, the success of a data analytics solution can only be realized if it can be readily deployed, managed and operated. We look forward to seeing you there.

MineExcellence, which is a leading provider of digital technologies for mining, with a special focus on drill and blast operations, in the controlled use of explosives to break rock for excavation, has established a collaboration with A2I2 to enhance the efficiency and safety of drill and blast processes, using AI and machine learning (ML). The mining industry is increasingly using AI and ML as tools to optimise processes, enhance decision-making, derive value from data, and improve safety. A memorandum of understanding between the two organisations was recently signed by MineExcellence MD Amit Bhandari and Deakin Research Innovations senior manager of commercialisation Greg Pullen. A2I2 head of Translational Research Professor Rajesh Vasa highlighted the importance of this collaboration and the core aim of the research project. "The collaboration between Mine Excellence and A2I2 includes joint research, industry connections and PhD placements. "Our research in this area aims to pioneer new methods and approaches that deliver high impact results to drilling and blasting, making the process safer and more efficient." Initial work has already started through a co-funded PhD student based at A 2I2 and working in collaboration with the industry. MineExcellence will provide its drill and blast domain knowledge as well as its digital platform. AI models will be developed in collaboration with A2I2, with support from drill and blast expert Professor Sushil Bhandari as external supervisor. Vasa said A2I2 has a solid capacity to apply novel AI techniques to the mining sector. "A2I2 has a proven track record of positively impacting society, spanning health, education, and defence technologies.

The proportion of mining industry operations and technologies companies hiring for artificial intelligence related positions rose in March 2022 compared with the equivalent month last year, with 38.8% of the companies included in our analysis recruiting for at least one such position. This latest figure was higher than the 29.9% of companies who were hiring for artificial intelligence related jobs a year ago but a decrease compared to the figure of 41.4% in February 2022. When it came to the rate of all job openings that were linked to artificial intelligence, related job postings rose in March 2022, with 2% of newly posted job advertisements being linked to the topic. This latest figure was the highest monthly figure recorded in the past year and is an increase compared to the 1.9% of newly advertised jobs that were linked to artificial intelligence in the equivalent month a year ago. Artificial intelligence is one of the topics that GlobalData, from whom our data for this article is taken, have identified as being a key disruptive force facing companies in the coming years.

PLEASE NOTE: This is the first generated blog and each new run of the code will be different. This should not be taken as the ground truth. The mining industry has been globalised for many years, with companies operating in multiple countries to maximise production and profits. However, this has led to a number of challenges, including the need to operate in different regulatory environments, manage different labour forces, and navigate different tax systems. Additionally, the volatility of commodity prices has also led to challenges for the industry. Despite these challenges, the mining industry remains a key driver of globalisation, and offers a number of opportunities for companies looking to expand into new markets.

AI in the mining industry can help increase productivity, reduce industrial waste, and enhance machine reliability!

It was only a few years earlier that Artificial Intelligence (AI) was a brand-new concept that was much too technical for anyone to anticipate how it will affect the world. Things have surely altered by the year 2019. It has changed the game for a variety of sectors, including significant participants in the mining industry. Small increases in yields, pace, and efficiency may have a huge influence on the mining sector, therefore increasing efficiency and productivity is critical for profitability. Now, let's take a look at how the companies which are using AI in the mining sector.

Optimized performance, reliability, availability and safety can be achieved with the automated operation. Digitalization in the mining industry is allowing mines to expand the utilization of technologies being used successfully both at the mine and plant levels, one of the most significant of which is mine equipment autonomy. While an exciting prospect, the mining industry is still having challenges as it works to integrate new technologies onto its mining equipment, such as shovels, drills, and trucks for capabilities like communications and positioning. Consider, too, that just because a mine has become automated does not mean that maintenance programs should be eliminated. On the contrary, they are perhaps more important than ever to support the optimized factors like availability and utilization of mine equipment now-automated workings as customers demand more than ever from their technology.