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The article outlines the Codex Ambassadors program, which aims to create a community of Codex experts who can help others learn and use the AI model effectively. It covers the program's objectives, requirements, and benefits for participants.

The article discusses the increasing popularity of virtual YouTubers (VTubers) in Japan, with companies and artists creating their own animated virtual personalities to engage with audiences. It highlights the growth of the VTuber industry and the creative ways in which these virtual performers are connecting with fans.

The article explores how small, everyday cultural activities can have a profound impact on the broader cultural landscape. It examines how individuals' participation in local arts, food, and community events can shape larger cultural trends and drive significant social change.

The article explores the history of typewriting, from its origins as a tool for the blind to its widespread adoption in the business world and its influence on popular culture. It examines how the act of typing became not only a practical skill but also a means of self-expression and a reflection of cultural values.

Apache JMeter is an open-source software application designed to load test and measure the performance of web applications, servers, and other resources. It provides a comprehensive set of features for creating, executing, and analyzing performance tests.

We're a YC W23 company building AI agents for engineering labs - our customers run similar analyses repeatedly, and the agent treated every session like a blank slate.

We looked at Mem0, Letta/MemGPT, and similar memory solutions. They all solve a different problem: storing facts from conversations — "user prefers Python," "user is vegetarian." That's key-value memory with semantic search. Useful, but not what we needed.

What we needed was something that learns user patterns implicitly from behavior over time. When a customer corrects a threshold from 85% to 80% three sessions in a row, the agent should just know that next time. When a team always re-runs with stricter filters, the system should pick up on that pattern. So we built an internal API around a simple idea: user corrections are the highest-signal data. Instead of ingesting chat messages and hoping an LLM extracts something, we capture structured events — what the agent produced, what the user changed, what they accepted. A background job periodically runs an LLM pass to extract patterns and builds a confidence-weighted preference profile per user/team/org.

Before each session, the agent fetches the profile and gets smarter over time. The gap as I see it:

Mem0 = memory storage + retrieval. Doesn't learn patterns.

Letta = self-editing agent memory. Closer, but no implicit learning from behavior.

Missing = a preference learning layer that watches how users interact with agents and builds an evolving model. Like a rec engine for agent personalization.

I built this for our domain but the approach is domain-agnostic. Curious if others are hitting the same wall with their agents. Happy to share the architecture, prompts, and confidence scoring approach in detail.

This study investigates the role of vitamin D in COVID-19 severity and mortality, finding that lower vitamin D levels are associated with increased COVID-19 risk and poorer outcomes, and suggesting that vitamin D supplementation may help mitigate the impact of the disease.

The article discusses the Claude composer, an AI language model developed by Anthropic that can assist with a variety of tasks such as writing, analysis, and problem-solving. It highlights the model's capabilities and potential applications in various fields.

The article discusses the pros and cons of building a custom authentication system versus using a pre-built solution like FusionAuth. It covers factors such as development time, security, scalability, and cost considerations to help businesses make an informed decision.

This article provides an overview of genetic algorithms, a type of optimization technique inspired by the process of natural selection. It explains how these algorithms work, their applications, and the advantages they offer for solving complex problems.

The article discusses research on the evolution of artificial hands (manus), exploring how machine learning and genetic algorithms can be used to develop more dexterous and capable robotic hands. The study aims to enhance understanding of the evolutionary processes that led to the development of human hands and apply these insights to improve the design and capabilities of artificial hands.

This article discusses the declining effectiveness of workflow management tools and the rise of aggregation platforms in the software development industry. It examines how the 'workflow moat' that once protected workflow tools is crumbling, leading to the increasing dominance of aggregation platforms that provide a more comprehensive suite of services.

The article discusses the involvement of a German researcher in receiving funding from the Jeffrey Epstein Charitable Trust, raising concerns about the ethics of accepting money from individuals with questionable reputations. It examines the researcher's response and the broader implications for academic institutions accepting such donations.

The article discusses Antide's Law, which suggests that the more complex a system, the more it is prone to failure. It explores how this principle applies to various domains, including technology, organizations, and society, highlighting the importance of simplicity and resilience in complex systems.

Disk Scout is a free, open-source disk usage analysis tool that helps users visualize and manage their file storage. The software provides detailed insights into disk space usage, allowing users to identify and delete large or unnecessary files to free up storage on their devices.

This article explores the common reasons why machine learning projects often fail to make it into production, including lack of a clear business case, data quality issues, and challenges with model deployment and monitoring.

Intel's Panther Lake Core Ultra is a powerful laptop CPU that offers significant performance improvements over previous generations, making it a standout choice for high-end laptops and workstations.

The article discusses the challenges of migrating from Kafka to newer data platforms, emphasizing the need to rethink data architecture in the context of data products. It highlights the importance of scalability, flexibility, and real-time data processing in modern data-driven organizations.

This article compares the writing abilities of various AI models, including ChatGPT and Anthropic's Bench AI, using the Hemingway test as a benchmark. It provides insights into the strengths and limitations of these AI systems in producing clear, concise, and readable text.

The article discusses Kilo Code, a startup that has developed a model-agnostic command-line interface (CLI) that spans over 500 AI models, allowing users to interact with various AI models through a single unified platform. The company's focus is on 'agentic engineering', which aims to create AI systems that can autonomously adapt and evolve to solve problems.

The article introduces the Agentic Trust Framework, a zero-trust governance model for AI agents that focuses on establishing trust, transparency, and accountability in AI systems. It outlines key principles and components of the framework to ensure responsible development and deployment of AI technologies.