Thailand’s AI development is hindered by limited digital infrastructure, with disparities in internet access and computational resources between urban and rural areas, requiring expansion of 5G networks and af
AI,Machine Learning,Agile software developmentWhen developing software systems that contain Machine Learning (ML) based components, the development process become significantly more complex. The central part of the ML process is training iterations to find the best possible prediction model. Modern ...
There are several challenges in developing and deploying AI models, which can be broken into three main categories. 1. Misallocation Of Talent From Innovation Toward Support And Maintenance Of Deployment AI is expensive to deploy. For every dollar spent on algorithm development, companies might spend...
Accordingly, trust in AI functions as a driver in AI usage, and distrust is considered a barrier to the development and application of AI systems, and it would negatively affect the stakeholder’s perspective toward AI systems in different contexts. Different dimensions and impacts of trust/...
Enel is a global leader in the energy sector, covering everything from electricity generation to distribution and retail. The Enel Innothon 2025 is a contest for the remote development of AI-based applications, designed on specific challenges aimed at fostering innovative solutions that Enel’s busi...
What is AI-augmented software development? Will it ever replace software developers? Let's find out. What is AI-augmented software development? The game changer: how AI is redefining software development? AI for programmers: will AI replace software developers? AI in software development: o...
This shift necessitates adaptability and ongoing skill development to ensure professionals can effectively develop and implement AI solutions. Simon Parkinson: Whilst there is hesitation around AI impacting the job market, the reality is that there will be a shift in the job market that will result...
However, rapid advancement also presents complex challenges in regulating AI technologies effectively, raising concerns about the risks of uncontrolled AI development and deployment. To help you understand the complexities of AI and regulation, download our whitepaper, Navigating the Challenges of AI Regul...
what constitutes a high-quality evaluation and develop robust, replicable methodologies that enable comparative assessments of AI systems. We recommend that governments opt for quality over quantity (i.e., funding the development of one higher-quality evaluation rather than ten lower-quality evaluations...
AI is no longer confined to small circles of developers and enthusiasts. Data analysis and machine learning services, likeGoogle Colaband Microsoft's Azure OpenAI Service's various models, make it easier than ever to include a larger circle ofemployees in AI developmentby enabling anyone to ...