# challenges Published articles for challenges. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Ten Ways Consumer and Prosumer NAS Products Are Changing DevFeed: [Ten Ways Consumer and Prosumer NAS Products Are Changing]() Original publisher: [Read original article]() Author: Rob Andrews Published: 2026-07-31T16:00:41Z Content type: article Language: en Sources: [NAS Compares]() Topics: [Network Attached Storage (NAS)](), [Hardware](), [Software]() Tags: [10gbe-paywall](), [1gbe-nas-bottleneck](), [anti-consumer-hardware](), [challenges](), [closed-storage-appliances](), [consumer](), [debian-nas-os](), [design](), [disguised-product-refreshes](), [diy-nas](), [dram-less-ssd-nas](), [dram-less-ssds](), [drive-locking](), [dsm-7-3](), [emmc-boot-drives](), [emmc-boot-storage](), [enterprise-hdd-squeeze](), [fixed-os-drives](), [hard-drive-market](), [hardware](), [hardware-enshittification](), [hdd-compatibility-lists](), [hyperscaler-hdd-allocation](), [legacy-socs](), [lpddr5-nas](), [m-2-bandwidth-throttling](), [minisforum-nas](), [multi-gigabit-networking](), [multi-gigabit-premium](), [nand-density-bottlenecks](), [nas](), [nas-boot-drive-failure](), [network-attached-storage-nas](), [software](), [uncategorised]() ### AI overview The article examines ten ways the consumer and prosumer Network Attached Storage (NAS) market has changed over the past 18 to 24 months, focusing on design priorities, hardware architecture, and software accessibility. It acknowledges component supply constraints and manufacturing priorities as contributing engineering pressures while presenting broader concerns about recent market changes. ### Source excerpt 10 WAYS that NAS is Getting Screwed Over the past 18 to 24 months, the consumer and prosumer Network Attached Storage (NAS) market has undergone a noticeable shift in design priorities, hardware architecture, and software accessibility. While broader industry pressures--ranging from component supply constraints to shifting manufacturing priorities--have introduced genuine engineering challenges, many recent market [...] ## The Strange Theatre of Technical Hiring DevFeed: [The Strange Theatre of Technical Hiring]() Original publisher: [Read original article]() Author: Daniel Glejzner Published: 2026-06-18T18:15:04Z Content type: opinion Language: en Sources: [Daniel Glejzner]() Topics: [engineering-leadership](), [Software Engineering](), [Code Challenge](), [Development]() Tags: [challenges](), [coding](), [developers](), [engineering](), [engineering-leadership](), [hiring](), [interview](), [software](), [software-engineering](), [technical](), [technical-interview]() ### AI overview The article argues that technical hiring often evaluates experienced engineers through narrow, timed coding exercises that may reward speed, recall, confidence under pressure, and familiarity with interview rituals more than the judgment and contextual skills required in software engineering work. ### Source excerpt A senior engineer joins a technical interview... Hi Angular Space community :) It's been a while since I pushed myself to write something. AI is changing the way we consume literally everything online, and I'm still trying to figure out what the best and most compelling way ## Keycloak Community Survey Finds Demand for Official Helm Charts and More Robust GitOps Flows DevFeed: [Keycloak Community Survey Finds Demand for Official Helm Charts and More Robust GitOps Flows]() Original publisher: [Read original article]() Author: Keycloak Cloud Native team Published: 2026-03-18T00:00:00Z Content type: article Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [Helm charts](), [argocd](), [GitOps](), [configuration]() Tags: [adoption](), [argocd](), [challenges](), [community](), [configuration](), [containerized](), [deployments](), [gitops](), [helm-charts](), [idm](), [kerberos](), [keycloak](), [ldap](), [openid-connect](), [results](), [saml](), [sso](), [survey]() ### AI overview Keycloak's survey of more than 360 respondents examined how the community deploys and manages Keycloak. Respondents expressed demand for official Helm Charts and more robust GitOps workflows, while adoption of the Keycloak Operator was reported as low because its setup is difficult to understand and its functionality is perceived as insufficient. ### Source excerpt Earlier this year, we conducted a survey to better understand how the community deploys and manages Keycloak in the real world. With over 360 respondents (!!), the results provide a better understanding of the community's needs and wishes. What we learned The survey results highlight a community that is deeply invested in the containerized ecosystem but is facing specific challenges in day-to-day operations. Key Findings: The Helm Charts: A significant portion of the community explicitly requested official Helm Charts, particularly for managing Keycloak installation and managing deployments via tools like ArgoCD. Operator: Adoption of the Keycloak Operator is not very high in the community, which is mainly caused by the fact that the Operator setup is hard to grasp, and do not provide the required functionality. GitOps & Configuration: There is a strong desire for more robust GitOps flows, especially when it comes to managing Keycloak resources like Realms and Clients. The whole Keycloak team is aware of these results and is discussing the next steps. Thank you to everyone who shared their feedback in this survey! More details: You can browse the detailed breakdown of the survey results in the slides below: ## Building AI agents that overcome the complexity cliff DevFeed: [Building AI agents that overcome the complexity cliff]() Original publisher: [Read original article]() Author: Ethan Ruhe Published: 2026-03-10T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [AI Agent](), [systems](), [Framework](), [Artificial Intelligence]() Tags: [agents](), [ai](), [building](), [challenges](), [complexity](), [infrastructure](), [system](), [system-design](), [temporal-voices]() ### AI overview This article presents a framework for understanding how AI agent capability grows with execution time and the number of tools and systems an agent can use. It argues that greater capability also increases the likelihood of failures and slows iteration, creating a "complexity cliff" where conventional frameworks may break down and Durable Execution becomes necessary. ### Source excerpt A principled framework for assessing agent capability -- why advanced agents need different infrastructure. ## Solving impossible problems DevFeed: [Solving impossible problems]() Original publisher: [Read original article]() Published: 2025-09-17T00:00:00Z Content type: tutorial Language: en Sources: [Aha! Engineering Blog]() Topics: [coding](), [Extension](), [API](), [Security](), [Back end]() Tags: [api](), [backend](), [build](), [challenges](), [extension](), [how-to](), [problems](), [security]() ### AI overview An engineering article describes how to approach software features that seem impossible to build. Using the Aha! Develop TestRail extension as an example, it explains how changing controllable constraints can make difficult problems manageable. ### Source excerpt If you've been working on software for any reasonable length of time, you might have had an experience like this: You're looking at a feature, and you have no idea how to build it. You have the context and understanding you need. But it's all pointi ## Practical Considerations for Advancing AI Collaboration in Software Development DevFeed: [Practical Considerations for Advancing AI Collaboration in Software Development]() Original publisher: [Read original article]() Author: Peter Lawrey (noreply@blogger.com) Published: 2025-05-15T19:35:00Z Content type: opinion Language: en Sources: [Vanilla Java]() Topics: [Artificial Intelligence](), [AI Development](), [Development](), [Prompt Engineering](), [Software Engineering]() Tags: [ai](), [challenges](), [collaboration](), [development](), [evaluation](), [info](), [maintainability](), [mentoring](), [opinion](), [practical]() ### AI overview This article examines practical considerations for collaborating with AI in software development. It argues for human oversight, stronger documentation and context, critical evaluation of probabilistic outputs, diverse model use, and awareness of deskilling, ethical, intellectual-property, and software-economics risks. ### Source excerpt TL;DR Human-in-the-loop is essential; AI offers probability, not certainty. AI excels at word-smithing, so spend more time on documentation and context. Leverage diverse AI models for varied research, improvements, and analysis. Be wary of deskilling: if AI makes a task trivial, agents may soon replace it. You should feel like you are testing the boundaries of what AI is capable of for at least some tasks. The Problem AI's proficiency in handling routine coding allows human engineers to dedicate more time to strategic activities such as system design, architectural planning, intricate requirement elicitation, and the rigorous evaluation of application performance across multifaceted metrics. Tools often amplify underlying behaviours and failures -- Rob Lambert Value is increasingly found not in rote knowledge, which AI can often provide, but in the capacity to frame complex problems effectively for AI, critically evaluate its probabilistic outputs, and innovatively integrate AI's capabilities into novel solutions. Developing with AI is not merely about adopting a new tool but about learning to collaborate with intelligence that operates on different principles, sometimes without profound contextual understanding, yet capable of processing and synthesising information at a scale and speed that surpasses human capability. However, this power comes with new challenges: ensuring the reliability of probabilistically generated outputs, managing the 'black box' nature of some AI reasoning, and navigating the ethical and IP landscapes of AI-generated content. Effective collaboration requires developers to master prompt engineering, the art of providing precise context, critically verifying outputs, and understanding the AI's inherent limitations to guide it effectively. This is akin to mentoring an exceptionally capable but occasionally erratic junior partner. Moreover, "disposable" or "ephemeral" AI-generated software carries profound and often unexamined implications for s ## Integrating Xandr's Real-Time Data Provider On-Premises: Infrastructure Requirements and Engineering Challenges DevFeed: [Integrating Xandr's Real-Time Data Provider On-Premises: Infrastructure Requirements and Engineering Challenges]() Original publisher: [Read original article]() Author: Guy Watson Published: 2025-04-22T22:57:37Z Content type: article Language: en Sources: [GumGum]() Topics: [real-time](), [Requirements](), [on-prem](), [Latency](), [Low Latency](), [Hardware](), [data](), [digital]() Tags: [ads](), [advertising](), [challenges](), [clients](), [data-processing](), [decision-making](), [hardware](), [infrastructure](), [latency](), [low-latency](), [metric](), [on-prem](), [performance](), [platform](), [real-time]() ### AI overview The article describes GumGum's experience integrating Xandr's Real-Time Data Provider on-premises, focusing on infrastructure requirements, scaling challenges, latency, traffic volume, and the decision to own hardware. ### Source excerpt How We Slashed Our Infrastructure Costs by 80% While Successfully Integrating Xandr's Real-Time Ad Platform!Introduction In the fast-paced world of digital advertising, maximizing return on investment (ROI) for ad spend is paramount. Buyers need to make data-driven decisions in real time to ensure their ads reach the right audience at the right moment. For us, integrating Xandr's Real-Time Data Provider (RTDP) was essential to providing the real-time optimization signals that would help our clients maximize their ROI by boosting Attention Time -- the key metric driving the effectiveness of programmatic ad campaigns. Our story is one of navigating through technical hurdles, experimenting with new infrastructure, and finding creative solutions to challenging engineering problems. As we embarked on integrating Xandr Real Time Data Provider, the path was far from straightforward. From vendor selection to scaling issues, and even the decision to own our hardware, every step had its complications. Yet, each obstacle presented an opportunity for innovation and refinement. In this article, we'll take you through the key challenges we faced, how we overcame them, and the lessons we learned from integrating Xandr on-prem. Whether you're considering a similar project or are simply curious about the behind-the-scenes of large-scale advertising tech deployments, our experience might just offer the insights you need. Xandr Integration and Its Requirements Xandr, a leading programmatic advertising platform, provides powerful tools to streamline and optimize ad delivery, targeting, and performance tracking. For us, integrating with Xandr RTDP meant integrating with the real time optimisation Xandr platform. Xandr's system, built to handle vast amounts of data in real time, comes with certain infrastructure demands. These include: Volume: The platform must be capable of handling massive amounts of traffic at any given time. For example, billions of ad impressions are processed daily, ## Choosing the Right Granularity for Microservices: Klarna's Payments Architecture Journey DevFeed: [Choosing the Right Granularity for Microservices: Klarna's Payments Architecture Journey]() Original publisher: [Read original article]() Author: Raya Rizk Published: 2025-03-24T07:22:27Z Content type: article Language: en Sources: [Klarna Engineering]() Topics: [Microservices](), [Architecture & Design](), [Development](), [Software Engineering](), [Scalability]() Tags: [architecture](), [challenges](), [distributed](), [klarna](), [led](), [microservices](), [modular-monolith](), [monolith](), [organizational-structure](), [scalability](), [software-architecture]() ### AI overview This article describes Klarna's transition from a monolithic architecture to payment-specific microservices and examines the trade-offs of service granularity. It reports that independently managed services improved team autonomy and development speed, while duplicated shared functionality created a complex distributed monolith. ### Source excerpt Our journey towards striking the right balance The debate between monolithic and microservices architectures is a hot topic in software development. While monolithic systems are known for their simplicity and tightly integrated structure, they face challenges with scaling and flexibility. In contrast, microservices offer greater scalability and autonomy in development, but carry complexity in inter-service interactions. In this article, I'll share our experience in navigating between these two paradigms while working on a recent project at Klarna, exploring different architectural decisions while addressing a fundamental question: what is the optimal granularity for a microservice? From monolith to microservices: the company is growing πŸš€ A monolithic architecture is often the natural starting point for businesses, serving well initially but revealing its limitations as organizations scale. Klarna was no exception. Like many in the IT industry, the company embraced the microservices paradigm alongside its rapid growth a few years ago. In the payments domain, we are focused on offering customers various payment options, allowing them to choose between paying directly, later, over time, or through other tailored methods. This demand for diverse options led each payment method to evolve into a distinct microservice, managed by dedicated teams. Each payment service acts as a key orchestrator in the purchase flow, coordinating with other services to guide customers through the required steps until order completion. This adoption of microservices naturally aligned with the company's organizational structure, offering team autonomy and the ability to scale services independently. Each service was self-contained, with its own database and code residing in a separate repository. By decoupling payment options into distinct services, we gained greater flexibility and enabled faster development cycles, as teams could focus on their respective components. Landing the distributed ## Reliable data processing: Queues and Workflows DevFeed: [Reliable data processing: Queues and Workflows]() Original publisher: [Read original article]() Author: Angela Zhou Published: 2025-01-22T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [data-processing](), [distributed-systems]() Tags: [challenges](), [data-processing](), [distributed-systems](), [queues](), [temporal-concepts](), [workflows]() ### AI overview This article explains how persistent queues store and forward messages reliably in distributed systems, including their benefits, limitations, and implementation patterns. It also describes how Temporal uses Durable Execution and Workflows to continue execution through outages, crashes, and hardware failures. ### Source excerpt Learn the ins and outs of persistent queues including what they are, how they work, the challenges, and the benefits. ## The problems of Kotlin/Wasm I had when making a game DevFeed: [The problems of Kotlin/Wasm I had when making a game]() Original publisher: [Read original article]() Published: 2025-01-20T00:00:00Z Content type: article Language: en Sources: [Kt. Academy]() Topics: [wasm](), [Kotlin](), [compose-multiplatform](), [multiplatform](), [CSV]() Tags: [challenges](), [compose](), [compose-multiplatform](), [csv](), [game](), [kotlin](), [kotlin-wasm](), [wasm](), [workshop-learning-programming]() ### AI overview An account of building a fruit-based collection-processing game with Compose Multiplatform and publishing it to Kotlin/Wasm. The author describes limitations in Kotlin reflection on common modules, an illegal cast exception occurring on Wasm, and an alternative approach involving generating challenges on the JVM and loading them from a CSV file. ### Source excerpt A short story of the problems I needed to face when publishing a simple game made with Kotlin/Wasm. ## Event-driven systems and the truth about "loosely coupled" architectures DevFeed: [Event-driven systems and the truth about "loosely coupled" architectures]() Original publisher: [Read original article]() Author: Erica Sadun Published: 2024-12-04T16:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [event driven](), [Resilience](), [systems](), [Developer experience]() Tags: [architectures](), [challenges](), [coupling](), [developer-experience](), [event-driven](), [resilience](), [scale](), [services](), [systems](), [temporal-concepts](), [troubleshooting]() ### AI overview This article explains how event-driven architectures use independently operating services and message-based communication to support scalability and resilience. It discusses tradeoffs including coupling, troubleshooting, and developer experience, and describes how Temporal abstracts failure and retry logic. ### Source excerpt Explore the challenges of event-driven systems and how loosely coupled architectures improve developer experience and troubleshooting. ## Going Global with Twig Globals in Craft CMS DevFeed: [Going Global with Twig Globals in Craft CMS]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2024-09-02T18:25:00Z Content type: tutorial Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [Content Management System](), [Web](), [coding]() Tags: [added](), [article](), [challenges](), [cms](), [collection](), [craft](), [global](), [globals](), [how-to](), [insights](), [learn](), [leveraging](), [simplify](), [templating](), [twig](), [variables]() ### AI overview This tutorial explains how variable scope works in Twig templates used by Craft CMS, including the challenges of making variables globally available. It discusses the trade-offs of global variables and how they can reduce component reusability and modularity, while noting that they can be appropriate in simpler websites. ### Source excerpt Learn how to simplify some Twig templating challenges by leveraging the global variables & the _globals Collection added in Craft CMS 4.5 ## Why Kotlin Multiplatform Teams Should Share Source, not Binaries - Kevin Galligan DevFeed: [Why Kotlin Multiplatform Teams Should Share Source, not Binaries - Kevin Galligan]() Original publisher: [Read original article]() Published: 2024-07-24T00:00:00Z Content type: opinion Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [Kotlin Multiplatform](), [multiplatform](), [Kotlin](), [Mobile](), [kotlin-multiplatform-libraries](), [Developer experience]() Tags: [adopting](), [challenges](), [debugging](), [ios](), [kmmbridge](), [kotlin](), [kotlin-multiplatform](), [libraries](), [mobile](), [mobile-apps](), [multiplatform](), [native](), [xcode]() ### AI overview The article explains why the authors changed their recommendation for native mobile teams evaluating Kotlin Multiplatform: share Kotlin source code instead of only publishing binary dependencies. Source lets iOS developers browse and debug the Kotlin code, while GitPortal supports versioned source publishing based on Git tags. ### Source excerpt Virtually all native mobile teams evaluating KMP start with a library publishing model. KMP module libraries are written, versioned, and "consumed" by the apps. The classic approach is to build and publish binary dependencies. In 2024, with KMP at stable and gaining significant traction, we no longer recommend this approach. It makes an inherently imbalanced iOS developer experience worse. Share Kotlin source instead. ## Summer of Spin 2024 DevFeed: [Summer of Spin 2024]() Original publisher: [Read original article]() Author: Jasmine Mae Alindayu Published: 2024-07-23T12:00:00Z Content type: article Language: en Sources: [Fermyon - Experience the next wave of cloud computing.]() Topics: [coding]() Tags: [challenges](), [coding](), [fun]() ### AI overview Fermyon's Summer of Spin 2024 is a Spin-off of Advent of Spin featuring fun coding challenges. ### Source excerpt Fermyon's Summer of Spin is a Spin-off on the Advent of Spin, consisting of fun coding challenges! ## 4 Essential Skills For Navigating Workplace Pressures DevFeed: [4 Essential Skills For Navigating Workplace Pressures]() Original publisher: [Read original article]() Author: jesalg Published: 2024-05-03T00:00:00Z Content type: opinion Language: en Sources: [Jesal Gadhia]() Topics: [integrity](), [communications](), [trust](), [reliability]() Tags: [career](), [challenges](), [coaching](), [collaboration](), [communications](), [emotional-intelligence](), [integrity](), [leadership](), [stress]() ### AI overview This article applies the four agreements from Don Miguel Ruiz's book to workplace pressures. It presents integrity, clear communication, emotional self-management, and avoiding assumptions as practical ways to handle difficult professional situations. ### Source excerpt Manage the stresses of complex problem-solving, tight deadlines, and high-pressure situations at work with integrity and emotional intelligence. ## Lessons from an Indian Software Engineer DevFeed: [Lessons from an Indian Software Engineer]() Original publisher: [Read original article]() Author: TheAnkurTyagi Published: 2023-11-30T14:00:28Z Content type: article Language: en Sources: [ByteSizedBets]() Topics: [Software Engineering](), [Development](), [Software](), [coding]() Tags: [career-growth](), [challenges](), [germany](), [india](), [journey](), [learning](), [software-developer](), [software-engineer](), [stories]() ### AI overview An interview-style profile of Santosh, an Indian software engineer living and working in Germany, covering his early education, entry into computing, and career journey in software engineering. ### Source excerpt From Mumbai to Hamburg- Unveiling the Success of a Software Engineer ## Building a ChatGPT Add-On for Google Workspace: Integration Challenges and Lessons Learned DevFeed: [Building a ChatGPT Add-On for Google Workspace: Integration Challenges and Lessons Learned]() Original publisher: [Read original article]() Author: Mikael Wulfcrona Published: 2023-10-16T09:50:38Z Content type: opinion Language: en Sources: [Klarna Engineering]() Topics: [ChatGPT](), [Google Apps Script](), [Google](), [API](), [JavaScript](), [Language models]() Tags: [add-ons](), [api](), [challenges](), [chatgpt](), [google-workspace](), [javascript](), [langchain](), [limit](), [productivity](), [work]() ### AI overview The author describes building a Google Workspace add-on that integrates ChatGPT for textual interactions with data in Google Sheets. The main challenges included extracting text across Google Workspace, ChatGPT's token limit, the 60-second execution limit for Google add-ons, and handling raw spreadsheet data. ### Source excerpt Overcoming the Hurdle of Unformatted Input: What I Learned From Building a ChatGPT Add-On for Google Workspace While ChatGPT is an incredibly powerful language model, it still struggles with unformatted input. As a tech nerd and passionate data scientist, I recently embarked on a journey to create an add-on for Google Workspace that could seamlessly interact with data stored in Sheets. Follow along as I share some of the main challenges, learnings, and solutions that eventually allowed me to integrate ChatGPT into Google's productivity tools for textual interactions. Unleashing the Potential of ChatGPT I was one of many people who was very impressed with the early versions of ChatGPT, released at the end of last year. Its capability to generate human-like responses fascinated me. However, I struggled to integrate it into my daily work. Having to switch tabs and copy-pasting text from different documents kept me away from really adopting this new tool. Determined to overcome this hurdle, I dove into the world of Google Workspace add-ons. You know where the work with text actually happens. Armed with enthusiasm and basic JavaScript knowledge, I got into building my first add-on. Having never built an add-on before, I forked Google's own example repo and started working. Working with the Google API As I delved into the project, I realized integrating ChatGPT via API calls was relatively straightforward. OpenAI provided excellent documentation, and Google Apps Script offered built-in features to make API calls. The main challenges, actually, laid on the Google side. Extracting text from different apps within the Google Workspace ecosystem initially baffled me. I spent hours unraveling the intricacies of the Google API, determined to find a way to seamlessly access and manipulate data. Overcoming GPT's Limitations with Raw Data in Google Sheets As I progressed, I encountered more roadblocks. Firstly, the infamous token limit. Some document were quite long and simply not ## Open challenges in LLM research DevFeed: [Open challenges in LLM research]() Original publisher: [Read original article]() Author: Chip Huyen Published: 2023-08-16T00:00:00Z Content type: opinion Language: en Sources: [Chip Huyen]() Topics: [Large Language Model](), [Hallucination detection](), [context](), [LLM evaluation / benchmarking](), [Chain-of-thought](), [multimodal]() Tags: [ai](), [chain-of-thought](), [challenges](), [context](), [evaluation](), [hallucination-detection](), [llm](), [multimodal](), [research]() ### AI overview This article surveys ten research directions aimed at improving large language models. The supplied excerpt focuses on reducing and measuring hallucinations, optimizing context length and construction, and briefly identifies multimodality, new architectures, and GPU alternatives as areas of interest. ### Source excerpt [LinkedIn discussion, Twitter thread] Never before in my life had I seen so many smart people working on the same goal: making LLMs better. After talking to many people working in both industry and academia, I noticed the 10 major research directions that emerged. The first two directions, hallucinations and context learning, are probably the most talked about today. I'm the most excited about numbers 3 (multimodality), 5 (new architecture), and 6 (GPU alternatives). 1. Reduce and measure hallucinations Hallucination is a heavily discussed topic already so I'll be quick. Hallucination happens when an AI model makes stuff up. For many creative use cases, hallucination is a feature. However, for most other use cases, hallucination is a bug. I was at a panel on LLM with Dropbox, Langchain, Elastics, and Anthropic recently, and the #1 roadblock they see for companies to adopt LLMs in production is hallucination. Mitigating hallucination and developing metrics to measure hallucination is a blossoming research topic, and I've seen many startups focus on this problem. There are also ad-hoc tips to reduce hallucination, such as adding more context to the prompt, chain-of-thought, self-consistency, or asking your model to be concise in its response. To learn more about hallucination: Survey of Hallucination in Natural Language Generation (Ji et al., 2022) How Language Model Hallucinations Can Snowball (Zhang et al., 2023) A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity (Bang et al., 2023) Contrastive Learning Reduces Hallucination in Conversations (Sun et al., 2022) Self-Consistency Improves Chain of Thought Reasoning in Language Models (Wang et al., 2022) SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models (Manakul et al., 2023) A simple example of fact-checking and hallucination by NVIDIA's NeMo-Guardrails 2. Optimize context length and context construction A vast ma ## Algorithm-focused technical interviews can overlook application development skills DevFeed: [Algorithm-focused technical interviews can overlook application development skills]() Original publisher: [Read original article]() Author: Mike Published: 2023-07-08T20:12:06Z Content type: opinion Language: en Sources: [Dev Details]() Topics: [Programming](), [Application Development](), [LeetCode](), [Algorithms, Complexity](), [Data structures](), [Development]() Tags: [algorithms](), [challenges](), [complexity](), [interview](), [interviews](), [order](), [technical-interview](), [time]() ### AI overview This opinion article argues that LeetCode-style algorithm interviews can produce false signals because they assess algorithm problem solving and Big-O analysis while overlooking the broader skills needed for application development. It suggests that developing applications is the way to build those skills. ### Source excerpt Interviews that focus on algorithms get false signals and overlook qualified candidates ## Overcoming KMM's Early Adopter Blues - Samuel Hill DevFeed: [Overcoming KMM's Early Adopter Blues - Samuel Hill]() Original publisher: [Read original article]() Published: 2022-10-04T20:12:22Z Content type: opinion Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [kotlin multiplatform mobile](), [Kotlin Multiplatform](), [Mobile](), [configuration](), [Development](), [jetbrains](), [legacy](), [migration]() Tags: [adoption](), [challenges](), [configuration](), [development](), [featured](), [jetbrains](), [kmm](), [kotlin](), [kotlin-multiplatform](), [legacy](), [memory-management](), [migration](), [production]() ### AI overview The article reviews challenges faced by early Kotlin Multiplatform Mobile adopters, including difficult project setup, library integration, and the legacy memory model. It describes Touchlab's KaMPKit and Stately efforts and notes JetBrains' subsequent project and memory-model improvements, before introducing challenges for larger production teams. ### Source excerpt As we approach a Kotlin Multiplatform Mobile Beta, we take a look back at some of the challenges and missteps early KMM adoption had to overcome. ## Tasteless 21: Godot Game Hacking in Tasteless Shores DevFeed: [Tasteless 21: Godot Game Hacking in Tasteless Shores]() Original publisher: [Read original article]() Published: 2021-10-03T00:00:00Z Content type: tutorial Language: en Sources: [mahaloz.re]() Topics: [Godot](), [Hacking](), [ctf](), [Script](), [client](), [servers](), [Linux]() Tags: [challenges](), [ctf](), [game](), [game-hacking](), [game-servers](), [github](), [hacking](), [hosting](), [ida](), [linux](), [multiplayer](), [reversing](), [scripts]() ### AI overview A writeup of Tasteless 21 multiplayer game-hacking challenges involving a Godot game. It describes analyzing resource packs and binaries, modifying and recompiling Godot scripts, and abusing client-side computations to create hacks such as flying, taking no damage, moving faster, and manipulating random-number behavior. ### Source excerpt A series of game hacking challenges hosted in Tasteless 21. Decompiling, modifying, and recompiling Godot scripts to abuse client-side computations for a multiplayer game. Fly hacks, no-damage, super speed, and rng abuse. ## The Business Executive's Guide to Kubernetes DevFeed: [The Business Executive's Guide to Kubernetes]() Original publisher: [Read original article]() Published: 2019-07-23T15:09:26Z Content type: opinion Language: en Sources: [Jessie Frazelle]() Topics: [Kubernetes](), [Databases](), [data](), [Replication](), [dashboards]() Tags: [challenges](), [control-plane](), [data](), [database](), [kubernetes]() ### AI overview This opinion article explains Kubernetes considerations for business leaders, focusing on challenges with stateful data and the need for separate data-replication mechanisms. It also warns that organizations may expose or fail to secure the Kubernetes control-plane dashboard. ### Source excerpt Hello! I thought it would be fun to write a post aimed towards business leaders making technology decisions for their organizations. There is a lot of hype in our field and little truth behind the hype. Like most things I write about, this started from an idea I had on Twitter: has anyone ever done technical breakdowns of these products in Gartner reports that are actually just trash, is this something you'd read..? -- jessie frazelle πŸ‘©πŸΌπŸš€ (@jessfraz) July 24, 2019 This post will cover some hard truths of Kubernetes and what it means for your organization and business. You might have heard the term "Kubernetes" and you might have been led to believe that this will solve all the infrastructure pain for your organization. There is some truth to that, which will not be the focus of this post. To get to the state of enlightenment with Kubernetes, you need to first go through some hard challenges. Let's dive in to some of these hard truths. Stateful Data is Hard Kubernetes is not to be used for stateful data. There has been a lot of work done in this area but it is still not sufficent. For the more technical members of our audience I direct you to exhibit A. The linked issue goes over problems when a "StatefulSet" gets into an error during deploying or upgrading. This can lead to data loss or corruption since Kubernetes will need manual intervention to fix the state of the deployment. This could even lead to the point where the only recommended fix is you delete the state. What does this mean for your business? Well, if you lose or corrupt your data it could mean a lot of different things depending on what the data was. If the data was your customer database of new account signups, well you might have just lost the data for your new customers. If you are an ecommerce site, it might have been your latest sale. If you are in banking or investments, it might have been data accounting for the movement of capital. Databases holding valuable information like the examples above ## Introducing Cyber Portfolio Management DevFeed: [Introducing Cyber Portfolio Management]() Original publisher: [Read original article]() Author: Adam Published: 2017-02-21T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [risk-management](), [Security](), [Business Security]() Tags: [challenges](), [communication](), [management](), [portfolio](), [risk-management](), [security](), [strategy](), [talk]() ### AI overview The article introduces Cyber Portfolio Management, a proposed approach to driving effective security programs by managing distributed security portfolios and improving communication between security and business teams. It also discusses a related RSA talk, audio and slides, and an upcoming ebook draft. ### Source excerpt [no description provided] ## Slicing SVG 9 Ways DevFeed: [Slicing SVG 9 Ways]() Original publisher: [Read original article]() Author: Paul Lewis Published: 2016-08-30T00:00:00Z Content type: tutorial Language: en Sources: [Paul Lewis]() Topics: [SVG](), [CSS](), [SVG animations in CSS](), [Web Development]() Tags: [3d](), [challenges](), [css](), [explain](), [gpu](), [performance](), [responsive](), [series](), [svg](), [video](), [youtube]() ### AI overview This tutorial explains how to approach dynamically sized shadows for a 3D card flip in responsive web design. It compares CSS box-shadow and blur filters, focusing on editability, animation performance, and rendering costs. ### Source excerpt I recently made a 3D Card Flip element as part of my Supercharged YouTube video series, and I ran into some challenges with the shadows. I decided I should explain how I approached the solution. [Next page]()