Zero Reinforcement Learning (Zero-RL) has proven to be an effective approach for enhancing the reasoning capabilities of large language models (LLMs) by directly applying reinforcement learning with verifiable rewards on pretrained models, without the need for a supervised fine-tuning phase. However, current research on zero-RL primarily focuses on domains with easily verifiable reward signals, such as mathematics, programming, and other reasoning tasks. The challenge of eliciting reasoning abilities in more diverse scenarios, where verification is not straightforward, remains underexplored. To address this gap, we propose a novel zero-RL paradigm designed to improve a model's reasoning ability across both verifiable and non-verifiable domains. By combining verifiable rewards with a generative reward model, we conduct multi-task zero-RL training across both domains, facilitating the transfer of reasoning capabilities between them. Furthermore, to mitigate reward hacking in the generative reward model, we design a smooth length penalty that encourages the generation of more comprehensive thinking tokens in general domains. Experimental results on Qwen3-8B-Base and Qwen3-14B-Base demonstrate that our approach achieves superior reasoning performance, not only on tasks requiring extensive reasoning but also on more general tasks.

There are many excellent books and articles describing those topics and how they can be implemented in various software frameworks, and those descriptions will not be repeated here. There also are many articles on Big Tech implementing AI at scale. But how do "regular" organizations implement AI projects successfully, especially within an existing portfolio of solutions? In the BLOG@CACM post "Anna Karenina on Development Methodologies," I described how the famous opening line "happy families are all alike, unhappy families are unhappy each in their own way" applies to software development. This post will describe in a similar vein the development behaviors with the highest chance of success for AI efforts.

The advancements in AI technology have left no field untouched. With Artificial Intelligence tools taking over mundane tasks, (in addition to seemingly creative tasks), it has become a question of when, not if, AI will replace human workers in various industries. While some may argue that AI will replace human workers in all industries, in this article, I'm about to give you the real tea on why managers are more likely to be replaced'first'. According to Gartner, by 2030, 80% of today's project management's work will be automated, eliminating the discipline and replacing PM traditional functions with AI. In a global survey by Pega, 78% of the executives surveyed believe that increasing the use of AI and robots will dramatically reduce the middle management ranks.

Gullview Technologies is an exciting and rapidly growing technology company focused on taking on the most vital and challenging business and technical challenges our clients face in our highly connected business world today. We have an exceptional focus at Gullview on developing deep and long-lasting relationships (several years and counting) with our clients. This focus enables us to deliver an ongoing continuum of projects and solutions to them with high value, meaningful impact, and predictable performance. We have a great opportunity to help refine a Snowflake Data Solution for a strategic client of ours as part of their Enterprise Data journey. This is a fantastic opportunity to join our firm, and work with our client in the foundational stages of a Data Practice for Gullview and the Enterprise Data Practice for the client with significant opportunities to influence Enterprise Data and Analytics capabilities.

There have been Kondratiev waves throughout history, commonly referred to as innovation waves, including the invention of electricity, the printing press, and the steam engine. All of these technologies spurred a paradigm shift which resulted in transforming the way the world operated. Today, many believe AI is the next Kondratiev wave and that it will be responsible for transforming how businesses create value, how people work, and ultimately how people live. For businesses to survive the era of AI, they must prepare to abandon legacy technology and invest in new ways of doing things, sometimes reasonably quickly in order to stay relevant. This phenomenon is called the "burning platform" effect, based on the idea that in order to stay competitive, businesses must adopt a radical change strategy as if their current way of doing things was on fire.

There have been Kondratiev waves throughout history, commonly referred to as innovation waves, including the invention of electricity, the printing press, and the steam engine. All of these technologies spurred a paradigm shift which resulted in transforming the way the world operated. Today, many believe AI is the next Kondratiev wave and that it will be responsible for transforming how businesses create value, how people work, and ultimately how people live. For businesses to survive the era of AI, they must prepare to abandon legacy technology and invest in new ways of doing things, sometimes reasonably quickly in order to stay relevant. This phenomenon is called the "burning platform" effect, based on the idea that in order to stay competitive, businesses must adopt a radical change strategy as if their current way of doing things was on fire.