AI technology can be used to alleviate the cybersecurity workforce shortage by automating threat detection. It also has potential in training cybersecurity professionals and enhancing skill development in areas like code reverse-engineering. As the cybersecurity landscape evolves, organizations must adapt their strategies to combat emerging threats. Emphasizing employee training, robust technology defenses, and the innovative use of AI are crucial steps. Simultaneously, the industry must remain vigilant against the misuse of AI, ensuring that cybersecurity defenses stay ahead of ever-evolving
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Currently, the two most dominant technologies in the world are machine learning (ML) and artificial intelligence (AI), as these aid numerous industries in resolving their business decisions. Therefore, to accelerate business-related decisions, IT professionals work on various business situations and develop data for AI and ML platforms. The ML and AI platforms pick appropriate algorithms, provide answers based on predictions, and recommend solutions for your business; however, for the longest time, stakeholders have been worried about whether to trust AI and ML-based decisions, which has been
The business world is increasingly turning to artificial intelligence (AI) systems and machine learning (ML) algorithms to automate complex and simple decision-making processes. Thus, to break through the paradigm in the field of IT operations, IT professionals and top managers started opting for AIOps platforms, tools, and software, as they promised to streamline, optimize, and automate numerous tasks quickly and efficiently. However, there are a few shortcomings, like algorithmic bias, that have been a major concern for IT professionals and other employees in the company.
Quantum computing is currently an emerging field that requires the development of computers based on the principles of quantum mechanics. Recently, scientists, technologists, and software engineers have found advancements in QC, which include increasingly stable qubits, successful demonstrations of quantum supremacy, and efficient error correction techniques. By leveraging entangled qubits, quantum computing enables dramatic advances in ML models that are faster and more accurate than before. As cybersecurity is constantly evolving, companies are seeking ways to automate their security soluti
Alessio Alionço is the founder and chief executive officer of Pipefy, a global leader in no code workflow automation solutions. Brazilian-born Alionco is a high-impact global leader, and has grown Pipefy from its founding in 2015 to a company with more than 400 employees and customers in 70 countries around the world, including Visa, IBM, Volvo, Santander, and Kraft Heinz. A veteran business consultant and entrepreneur, Alionço has a Lean Six Sigma Black Belt along with a certificate from the Stanford LEAD: Personal Leadership program of the Stanford University Graduate School of Business.
AI and AIOps have been transforming the future of the workplace and IT operations, which accelerates digital transformations. The AIOps stands out as it uses machine learning (ML) and big data tracking, such as root cause analysis, event correlations, and outlier detection. According to the survey, large organizations have been solely relying on AIOps to track their performance. Thus, it is an exciting time for implementing AIOps that can help software engineers, DevOps teams, and other IT professionals to serve quality software and improve the effectiveness of IT operations for their compani
In the realm of technology, few terms evoke as much excitement and apprehension as Artificial Intelligence (AI). As the CEO of Neurons, a company at the forefront of predicting consumer behavior using neuroscience and AI, I’ve witnessed this dichotomy firsthand. A meeting with a leader of a large social media channel, a traditionalist in the world of research and insights. The skepticism in the room was palpable as we introduced our AI-driven solutions. The journey from apprehension to understanding to acceptance was not a sprint, but a marathon. But as they say, the longest journey begins wi
In the last few years, artificial intelligence for IT operations (AIOps) and observability have been hot topics in the IT operations sector. Organizations are looking for improvements in development and operation processes as these technologies have become more accessible, with various benefits and challenges. With the power of artificial intelligence (AI), machine learning (ML), and natural language processing, IT professionals such as engineers, DevOps, SRE (Site Reliability Engineering) teams, and CIOs can detect and resolve incidents, drive operations, and optimize system performance.
Embracing AI in data management provides a competitive advantage, driving sophisticated decision-making and valuable insights across industries. This article will highlight the transformative potential of AI in data management, informing data decision-makers why it is essential to seize this opportunity for growth and success. Artificial intelligence (AI) has revolutionized data management, empowering organizations to leverage data for informed decision-making. AIOps has a lot to offer, like improving key metrics and helping businesses survive and develop in an increasingly digitized environm
In the dynamic environment of IT operations, the emergence of AIOps (artificial intelligence for IT operations) has changed how IT professionals manage and optimize their systems. AIOps represent a radical shift in the integration of artificial intelligence (AI) and machine learning (ML) into conventional IT operations to enhance productivity, identify issues, and automate responses. AIOps has evolved analytics in IT operations and benefited numerous businesses by helping them make informed decisions.
Kenta Yasukawa is CTO and Co-Founder of Soracom, where he has led deployment of the industry’s most advanced cloud-native telecom platform, designed specifically for the needs of connected devices. Before co-founding Soracom, Kenta served as a Solutions Architect with AWS and conducted research for connected homes and cars at Ericsson Research in Tokyo and Stockholm. Kenta holds a PhD in Engineering from the Tokyo Institute of Technology, with additional studies in Computer Science at Columbia University’s Fu Foundation School of Engineering and Applied Science.
Hyper-automation is a new term for technology and other industries where automation is needed. According to Gartner, hyper-automation is one of the most trending technologies that will greatly impact the next few decades. The motive of hyper-automation is to cancel out the repetitive tasks and make the whole task automatic by creating bots to perform them. These tasks will be performed with the combination of robotic process automation (RPA) and other advanced technologies like artificial intelligence (AI).
In AI-Tech Park’s commitment to uncovering the path toward realizing enterprise AI, we recently sat down with Chris Lynch, an esteemed figure in the industry and accomplished Executive Chairman and CEO of AtScale. With a remarkable track record of raising over $150 million in capital and delivering more than $7 billion in returns to investors, Chris possesses invaluable knowledge about what it takes to achieve remarkable results in the fields of AI, data, and cybersecurity. During our interview, Chris shared his insights into the key leadership qualities that drive success when building a com
In today’s rapidly evolving business landscape, the Banking, Financial Services, and Insurance (BFSI) sector is at the forefront of digital transformation. To succeed in this dynamic environment, industry leaders, executives, and decision-makers must not only recognize the challenges but also harness the opportunities presented by technology. This article is a comprehensive exploration of how Robotic Process Automation (RPA) and Artificial Intelligence (AI) provide strategic solutions to address these challenges, foster innovation, and drive growth within the BFSI sector.
As Caregility’s Chief Strategy Officer, Pete provides leadership to our growing product and solution focus in the healthcare market. He is a pioneer, innovator and leader in the field of telehealth video and communications solutions with 20 years of experience in the healthcare industry.
The Artificial Intelligence (AI) industry has experienced tremendous growth and buzz, with Generative AI leading the charge. However, it’s crucial to acknowledge that these impressive technologies are only part of the larger puzzle. In many situations, businesses require different technologies to achieve their desired outcomes.
Manav Mital is the co-founder and CEO of Cyral, a leader in data security governance that stops data exfiltration by delivering enterprise security across all databases in every cloud. He was previously the founder and CEO of Instart, a startup in the CDN space focused on improving web and mobile application performance, consumer experience, and security before it was acquired by Akamai.
Artificial intelligence (AI) has improved the outcomes for hundreds of thousands of businesses by automating and speeding up their processes. Yet, it has also helped the criminals too, making it easier for them to commit fraud and steal money. Application fraud is fast becoming one of the most prevalent forms of deception.
Conrado Vina is a Founding Partner & Head of Partnerships at Qubika. He has 20 years of experience in the tech industry, he previously worked at Feng Office, Moove-it, Cuti – Cámara Uruguaya de Tecnologías de la Información, and CEPA International. At CEPA International, they were in charge of development and maintenance of CEPA’s software and infrastructure systems.
Artificial intelligence (AI) has long been positioned (by its creators) as a force for good. A labour-saving, cost-reducing tool that has the potential to improve accuracy and efficiency in all manner of fields. It’s already been used across sectors – from finance to healthcare – and it’s changing the way we work. But the time has come to ask, ‘at what cost?’ Because the more AI is developed and deployed, the more examples are being found of a darker side to the technology.