Monday, September 8, 2025

AI

AI can boost teamwork in engineering teams by providing context and suggesting next steps. The key to effective teamwork lies in trust, transparency, accountability, and autonomy, all delivered through a "shared brain" consisting of systems for context, record-keeping, and action. Humans are essential in unlocking collective intelligence with AI-powered tools, driving innovation and success.

A new MIT study reveals that most companies struggling with AI are failing to see a return on investment, with fewer than one in ten projects generating significant value. Instead, AI is being used to free up employees for higher-value tasks, highlighting the need for workers to develop practical AI skills beyond technology proficiency.

Small language models are being used to revolutionize cybersecurity by addressing psychological vulnerabilities that make employees susceptible to social engineering and phishing attacks. The Cybersecurity Psychology Framework categorizes human vulnerabilities into 10 distinct states, enabling organizations to detect mental conditions leading to security incidents and provide targeted intervention before breaches occur effectively.

Patterns, Predictions, and Actions", a machine learning textbook by Moritz Hardt and Benjamin Recht, covers fundamentals of prediction, supervised learning, deep learning, and more. The book also includes problem sets, a table of contents, references, citation information, licensing details, and typesetting guidance, providing a comprehensive resource for students and professionals in the field.

The Digital Differential Analyzer (DDA) algorithm is a method for casting rays in 2D space. Created by an author who initially struggled to grasp it, the algorithm iterates over grid squares intersected by a ray using angles and distances to determine the next step. It uses Pythagoras' theorem to calculate line segment lengths.

Focusing solely on strategy and execution can lead to costly mistakes if team readiness is ignored. A motivated and capable team is essential for project success, providing continuity and carrying learnings from past projects. Timing new projects with team state is crucial, as a balanced approach considers both vision and team readiness.

Developers often overlook the potential for accidental complexity in their systems, suggesting a simplistic approach like "just use SQL." However, even simple queries can become complicated when dealing with user input and filtering criteria. The author highlights the need to be aware of one's limitations to avoid unforeseen problems later on.

The WFGY project aims to develop an open-source, symbolic reasoning architecture for natural language processing with a comprehensive guide and repository. The guide offers quick access to key sections, including setup instructions, diagnostic frameworks, and community resources, making it a valuable resource for newcomers and developers alike.

Package managers are often criticized for exacerbating dependency hell rather than solving it. By automating tasks like managing dependencies, they contribute to a culture of high trust in unvetted code, increasing security risks and liability concerns. This is further compounded by expertise in one area leading to blind trust in open-source packages.

Some developers resist using Large Language Models (LLMs) due to limiting beliefs about their power and limitations, concerns over job identity, and worries about losing technical skills. The author shares their personal experience, transitioning from skepticism to acceptance, and challenges these concerns by highlighting LLMs' benefits, such as increased efficiency and productivity.

Generative AI's popularity has declined due to its limitations in replacing human intelligence, highlighting the power of human knowledge and skills. Initially used for solving specific problems, it gained traction after ChatGPT's rise in 2022, but an overreliance on low-quality content led to a decline, restoring confidence among programmers and professionals.

A new approach to learning category theory is presented through the creation of the programming language Я, simplifying complex concepts like natural transformations and functors. This unconventional method aims to apply theoretical concepts to everyday problems, such as user data mapping, while introducing key ideas like covariant and contravariant functors.

The author's childhood experiences exploring nature sparked an appreciation for the outdoors, which inspired them to create an interactive story where readers take on the role of a hiker at Mount Valor, making choices that progress through the narrative. This immersive experience brings a new level of interaction and agency to storytelling.