Sammy Selim strode through the dense, shiny green bushes on the slopes of his coffee farm in Sorwot village in Kericho, Kenya, accompanied by a younger farmer called Kennedy Kirui. They paused at each corner to input the farm's coordinates into a WhatsApp conversation. The conversation was with Virtual Agronomist, a tool that uses artificial intelligence to provide fertiliser application advice using chat prompts. The chatbot asked some further questions before producing a report saying that Selim should target a yield of 7.9 tonnes and use three types of fertiliser in specific quantities to achieve that goal. "My God!" Selim said upon receipt of the report.

The rapid advancement of large language models (LLMs) has led to the rise of LLM-based agents. Recent research shows that multi-agent systems (MAS), where each agent plays a specific role, can outperform individual LLMs. However, configuring an MAS for a task remains challenging, with performance only observable post-execution. Inspired by scaling laws in LLM development, we investigate whether MAS performance can be predicted beforehand. We introduce AgentMonitor, a framework that integrates at the agent level to capture inputs and outputs, transforming them into statistics for training a regression model to predict task performance. Additionally, it can further apply real-time corrections to address security risks posed by malicious agents, mitigating negative impacts and enhancing MAS security. Experiments demonstrate that an XGBoost model achieves a Spearman correlation of 0.89 in-domain and 0.58 in more challenging scenarios. Furthermore, using AgentMonitor reduces harmful content by 6.2% and increases helpful content by 1.8% on average, enhancing safety and reliability. Code is available at \url{https://github.com/chanchimin/AgentMonitor}.

According to Statista, a market research platform, the market value for artificial intelligence (AI) is expected to grow up to nearly $two trillion dollar by 2030. Chatbots, image-generating AI and mobile applications can be considered the future trends in AI. In a conversation with FE Blockchain's Poulami Saha, Abhijeet Satani, a researcher in the field of neuroscience, talks about how the development of AI can create an impact today and in future(Edited Excerpts). How much has the AI industry grown till now? The rising adoption of AI technology across a range of industries is one of the major reasons for the rise of the AI industry.

If you follow business technology trends, you've likely heard that in the future artificial intelligence will play a role in almost every aspect of business operations -- from sales and marketing to the customer experience. While AI is not yet mainstream, it is gaining traction among many businesses. People use it more than they realize, and there are possibilities across every industry. Once only available to the largest, most financially sound corporations, AI and machine learning are finding their way into the small businesses that make up the backbone of the United States economy. They are reshaping the way firms conduct business, allowing owners to do more with less.

In today’s fast-paced world, artificial intelligence (AI) has become a game-changer for businesses and individuals looking to increase productivity. The...

Artificial intelligence (AI) is a rapidly growing field that has captured the attention of scientists, engineers, business leaders, and policymakers worldwide. It refers to the development of computer systems that can perform tasks that typically require human intelligence, such as learning, problem-solving, perception, and decision-making. AI has the potential to transform various industries and sectors, including healthcare, transportation, education, manufacturing, and finance, among others. In this article, we will explore the importance of artificial intelligence in the future and its potential benefits and challenges. One of the most significant advantages of artificial intelligence is its ability to automate routine and repetitive tasks, allowing humans to focus on more complex and creative work.

The phrases artificial intelligence and digital transformation are interlinked in today's tech world. Even if businesses only mention one, they will almost certainly be talking about both simultaneously. In short, AI now powers the next stage of digital transformation activities and software and will continue to do so, opening up new opportunities and enabling advancements that were previously impractical. When discussing artificial intelligence (AI) in engineering and manufacturing, we frequently speak to Artificial Narrow Intelligence (ANI), created to carry out particular tasks using predetermined inputs. ANI aims to use sophisticated algorithms to carry out predefined tasks, such as CAD applications, rather than mimic human thought.

In the recent "Big Ideas 2023" report by Ark Invest, the investment management firm forecasted that AI could lead to a 10-fold increase in coding productivity. Based on a 70% annualized drop in trading costs and feedback loops, AI coding assistants like Copilot could increase the output for software engineers 10-fold by 2023. Generative AI has the potential to revolutionize the coding process and significantly increase productivity. By using deep learning algorithms, generative AI can learn from large datasets of code and generate new code that is syntactically and semantically correct. This can significantly reduce the time and effort required to write new code, especially for routine tasks that require repetitive coding patterns.

Intelligent automation is a game-changer for businesses. It allows them to automate complex tasks, reduce costs, and improve efficiency. By using advanced technologies like artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA), businesses can keep up with the fast-paced demands of the modern world. Intelligent automation unlocks new efficiencies and growth opportunities, making it a powerful tool for staying ahead of the competition. Let's discuss in detail, what is intelligent automation?

Ronan Burke is the co-founder and CEO of Inscribe, a leading fintech solution for fraud detection and automation. Companies in every industry are embracing the power of automation. From streamlining processes to simplifying operations, organizations are finding new ways to increase efficiency and improve experiences for both customers and employees. For companies in the financial services sector, however, reaching the full potential of their automation requires that they also manage and mitigate risk. Automated workflows do increase productivity--but they're not all built to support the varying levels and vectors of risk faced by financial institutions every day.