Gemini AI Solutionsis in the Chatbots Industry

Gemini AI Solutions

The wait is over! - it’s time to celebrate the champion startups of the world. Shout out to all of the participants in our ! You did a wonderful job showcasing your incredible startups and powering through another year. 2023 Startups of the Year is a community-driven voting platform brought to you by HackerNoon that recognizes and celebrates tech startups changing technology and the world for the better. The award started on May 8th, 2023, where the internet nominated and voted for 30k startups around the world. The voting period remained open until December 31, 2023, and now we are here with the winner announcement after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 To see the top 3 startups in each respective city, visit and pick a city. hackernoon.com/startups You’ll get a little surprise 😉 Here are the Startups of the Year Regional Announcements: North America Europe Asia Africa South America Oceania Misc/Remote From all of us at HackerNoon, thank YOU for your excellent campaign perseverance 🥺 This year has been awesome! Startups of the Year 2023 is concluded with 623k+ total votes, up from 215k+ votes in the inaugural startup competition. We look forward to seeing you again in the next campaign (stay tuned 😉)! Without further ado, let us kick off the announcement by celebrating the cities with top votes per region for 2023 🎉 North America (11,697 votes): Winner: Bloomfilter Cleveland, Ohio (8,835 votes) - Winner: SerpApi Austin, Texas , California (5,564 votes) - Winner: Finch San Francisco (4,258 votes) - Winner: RELAYTO SoMa, California - (3339 votes) Winner: Windscribe Toronto, Canada, North America (3304 votes) - Winner: Vouched Seattle (2716 votes) - Winner: Seccuri Palo Alto, CA, North America (2671 votes) - Winner: Salsa Valley Miami, FL, North America (2,613 votes) - Winner: Majhi Group Manhattan, New York (2423 votes) - Winner: Flieber, Inc. New York City, NY, North America See the complete announcement for the . Startups of the Year, North America, here Europe (45,612 votes) - Winner: Algomo London, UK (2,344votes) - Winner: Data Lake Warsaw, Poland (1,955 votes) - Winner: Hoken Tech Bari, Italy (1716 votes) - Winner: Not8 Amsterdam, Netherlands (1657 votes) - Winner: KYVE Frankfurt Am Main, Germany (1566 votes) - Winner: BazaIT Kyiv, Ukraine (1496 votes) - Winner:  Unity Network Tallinn, Estonia (1,478 votes) - Winner: Volcaino Ghent, Belgium (1,288 votes) - Winner: Owl Me Dublin, Ireland (1198 votes) - Winner: Groover Paris, France See the complete announcement for the . Startups of the Year, Europe, here Oceania (3,350 votes) - Winner: Sharepass Melbourne (2,107 votes) - Winner: The Catfisher Project Perth, Australia (220 votes) - Winner: Gemini AI Solutions Auckland, New Zealand, Oceania (213 votes) - Winner: Nexustorage Wellington, New Zealand, Oceania (138 votes) - Winner: Coviu Sydney (124 votes) - Winner: Bopple Brisbane, Australia, Oceania (124 votes) - Winner: Regional CFO New South Wales, Australia, Oceania (106 votes) - Winner: Edit on the Spot Gold Coast, Australia, Oceania (93 votes) - Winner: Knowledge Satnav Canbera, Australia, Oceania , Australia, Oceania (48 votes) - Winner: Peptalk360 North Melbourne, Melbourne See the complete announcement for the . Startups of the Year, Oceania, here Asia (16,345 votes) - Winner: Serenity Shield Singapore (13,588 votes) - Winners: QUIXY Telangana, India (10,168 votes) - Winner: HealthySure Mumbai, India (3,865 votes) - Winner: InterviewBuddy Visakhapatnam, India (3,733 votes) - Winner: Omniflo Bengaluru, India (4589 votes) - Winner: MeNow Tel Aviv (3877 votes) - Winner: ForestVPN Dubai (2478 votes) - Winner: TechGraph Powai, Mumbai, India (1004 votes) - Winner: Reelo Ahmedabad, GJ, India (875 votes) - Winner: Debt Hunter Hong Kong, China See the complete announcement for the . Startups of the Year, Asia, here Africa (8,179 votes) - Winner: GO PLATFORM Algiers, Algeria (767 votes) - Winner: Tudu Accra, Ghana (415 votes) - Winner: Treford Lagos, Nigeria (265 votes) - Winner: Phalconwise Ogbomosho, Nigeria (157 votes) - Winner: AbuErdan Cairo (151 votes) - Winner: Eazipay Lekki (144 votes) - Winner: KaziConnect Dar es Salaam, Tanzania (101 votes) - Winner: faceATT Gauteng, South Africa (79 votes) - Winner: Dimagi Cape Town (71 votes) - Winner: Sabi Addis Ababa See the complete announcement for the . Startups of the Year, Africa, here South America (376 votes ) - Winner: UpGirl Santiago, Chile (217 votes) - Winner: Klever Sao Paulo, Brazil (191 votes) - Winner: Tributo Simple Buenos Aires, Argentina (127 votes) - Winner: Light-it Montevideo, Uruguay (87 votes) -Winner: Thousand Antioquia, Colombia (108 votes) - Winner: GetLavado Lima (101 votes) - Winner: Cogniflow Medellin (73 votes) - Winner: TPAGA Bogota (73 votes) - Winner: Reliv Quito (47 votes) - WInner: Quantex Cordoba See the complete announcement for the . Startups of the Year, South America, here Misc/Remote: Featured Startups (1500 votes) - Winner: CIC Chain Remote, Earth (1193 votes) - Winner: Reship Colony US Misc (146 Votes) - Winner: Partful UK, Misc (116 votes) - Winner: GoMining British Virgin Islands Misc (283 Votes) - Winner: tomorrowSpace Germany Misc (225 votes) - Winner: Dtravel Cayman Islands See the complete announcement for Misc/Remote startups . here Once again, HUGE CONGRATULATIONS and BIG PROPS to all of the top Startups of each region this year! The whole team at HackerNoon would like to thank you for your perseverance in the campaign, and we look forward to seeing you in the next campaign. About HackerNoon’s Startups Of The Year Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated this year to be crowned the best startup in their city. Visit our page to learn more. FAQ Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Stand Up for the Champion Startups of the Year! 

বছরের চ্যাম্পিয়ন স্টার্টআপের জন্য দাঁড়ান!

Setzen Sie sich für die Champion-Startups des Jahres ein!

¡Defiende a las startups campeonas del año!

Défendez les startups championnes de l’année !

वर्ष के चैंपियन स्टार्टअप के लिए खड़े रहें!

今年のチャンピオンスタートアップのために立ち上がろう!

올해의 챔피언 스타트업을 위해 일어서세요!

Defenda as startups campeãs do ano!

Встаньте на защиту стартапов-чемпионов года!

Yılın Şampiyon Startup'ları için Ayağa Kalkın!

Hãy ủng hộ các công ty khởi nghiệp vô địch của năm!

为年度冠军初创企业挺身而出！

Memoization is awesome. Let's abuse it. TL;DR: Don't apply premature optimization too early Problems Readability
Code Complexity
Premature Optimization
Obscured Logic Solutions Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. Context Memoization can help you improve the performance of recursive functions involving redundant computations but compromise code readability and maintainability. It would help if you only used it with strong factual evidence on real business case scenarios. Sample Code Wrong memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. Right def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) Detection [x]Semi-Automatic You can search for all places where you are using this technique and validate if they are worth it. Exceptions Real performance problems with strong factual evidence Tags Premature Optimization Level [x]Intermediate AI Generation Unless you explicitly ask the IAs to use this technique, they will suggest cleaner solutions. AI Detection ChatGPT, Gemini, and Claude.ai detect some problems with this technique but do not mention readability as a concern. Conclusion It would be best if you kept a balance between performance optimization and code clarity. You can consider alternatives such as iterative approaches or algorithmic optimizations since memoization significantly compromises code readability. Relations Code Smell 06 - Too Clever Programmer Code Smell 20 - Premature Optimization More Info Wikipedia Disclaimer Code Smells are my opinion. Credits Photo by Steffen Lemmerzahl on Unsplash A cache with a bad policy is another name for a memory leak. Rico Mariani Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code Memoization is awesome. Let's abuse it. Memoization is awesome. Let's abuse it. TL;DR: Don't apply premature optimization too early TL;DR: Don't apply premature optimization too early premature optimization Problems Readability Code Complexity Premature Optimization Obscured Logic Readability Code Complexity Premature Optimization Obscured Logic Solutions Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. memoization Context Memoization can help you improve the performance of recursive functions involving redundant computations but compromise code readability and maintainability. It would help if you only used it with strong factual evidence on real business case scenarios. strong factual evidence real Sample Code Wrong memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. Right def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) Detection [x]Semi-Automatic [x] Semi-Automatic [x] You can search for all places where you are using this technique and validate if they are worth it. Exceptions Real performance problems with strong factual evidence Real performance problems with strong factual evidence Tags Premature Optimization Premature Optimization Level [x]Intermediate [x] Intermediate [x] AI Generation Unless you explicitly ask the IAs to use this technique, they will suggest cleaner solutions. AI Detection ChatGPT, Gemini, and Claude.ai detect some problems with this technique but do not mention readability as a concern. Claude.ai Conclusion It would be best if you kept a balance between performance optimization and code clarity. You can consider alternatives such as iterative approaches or algorithmic optimizations since memoization significantly compromises code readability. Relations Code Smell 06 - Too Clever Programmer Code Smell 06 - Too Clever Programmer Code Smell 20 - Premature Optimization Code Smell 20 - Premature Optimization More Info Wikipedia Wikipedia Disclaimer Code Smells are my opinion . opinion Credits Photo by Steffen Lemmerzahl on Unsplash Steffen Lemmerzahl Unsplash A cache with a bad policy is another name for a memory leak. A cache with a bad policy is another name for a memory leak. Rico Mariani Rico Mariani Software Engineering Great Quotes Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code

Premature Memoization: How to Properly Apply It - Code Smell 250

Do you find yourself exhausted from wrestling with intricate data for hours on end? Are you yearning for AI that comprehends beyond mere words? Google's Gemini AI emerges as a transformative force, revolutionizing the landscape of AI model development and integration. Upon completion, in various sizes and functionalities, allowing you to select the ideal match for your requirements, whether tackling extensive projects or concentrated assignments. This guarantees that organizations can opt for the model that perfectly aligns with their objectives, be it for expansive applications or specific tasks. Google will present Gemini AI What exactly is Google Gemini AI? Google Gemini AI is an advanced platform harnessing deep learning algorithms to produce remarkably lifelike and inventive results. It propels AI models forward, enhancing their flexibility and efficiency through continuous learning from fresh data. Diverse iterations Offered in – Google Gemini AI accommodates the distinct requirements of individuals and businesses. Whether it's optimizing processes or conducting advanced data analysis, Gemini ensures there's a suitable version tailored to your needs. three variations – Ultra, Pro, and Nano The Gemini AI Model Central to Google's generative AI platform is the Gemini AI model. Utilizing cutting-edge deep learning algorithms, it assimilates extensive datasets to produce authentic outputs. With its adaptability, the model can excel across diverse domains such as natural language processing (NLP), image generation, text composition, music creation, and beyond. Key Features Simplified: Human-like Conversational Proficiency: Gemini demonstrates remarkable conversational abilities akin to humans, . ideal for chatbots and virtual assistants It provides an immersive, seamless, and organic conversational experience. Redefining benchmarks for human-like interactions within digital environments. Image understanding and interpretation: Gemini deciphers image content, responds to inquiries, and produces contextual text. It is exceptionally suited for image search and captioning, establishing pioneering benchmarks in AI. This amplifies user satisfaction and broadens the horizons of image-centric applications. Prolific code generation: Gemini excels in generating high-quality code across different programming languages. It is vital for optimizing coding workflows, guaranteeing both efficiency and precision. This innovation revolutionizes developers' approaches to software development. Data analytics expertise: Empowers users in the realms of data analytics and business intelligence. Critical for making data-driven decisions, unlocking the full potential of data. Serves as a catalyst for driving transformative advancements in analytics. Developer empowerment: Empowers developers to innovate by creating advanced AI applications and APIs. Nurtures a vibrant ecosystem for collaborative development of AI-driven solutions. Improves accessibility, fostering creativity and innovation. Real-time language translation: Gemini demonstrates excellence in , promoting global communication. real-time language translation It enriches user experiences by overcoming language barriers. A versatile tool catering to diverse communication requirements. Emotion recognition: Incorporates emotion recognition, elevating interaction sophistication. Applications span from enhancing user experience to sentiment analysis. Contributes to nuanced and responsive interactions between users and AI. Customizable AI applications: Provides developers with flexibility, enabling customization to address specific industry requirements. Adaptable across diverse sectors including healthcare, finance, and creative fields. Positions Gemini as a dynamic force across various professional domains. Continuous learning and adaptation: Gemini's continuous learning dynamically adapts based on user interactions. It learns from experience, ensuring relevance and ongoing advancement. Embodies a dynamic and adaptive nature, showcasing forefront AI capabilities. Multimodal focus: Gemini emphasizes , highlighting tools and API integrations. multimodal capabilities It aims to foster broader collaboration and drive future development in the AI landscape. Striving to enhance versatility through a multimodal approach. Tools and API integration: Gemini provides effortless integration of tools and APIs, ensuring a versatile AI experience. It prioritizes collaborative environments by facilitating seamless integration processes. Enhances the overall user experience through accessible and interconnected tools. Versatility for future developments: Gemini remains adaptable to evolving technologies, ensuring continuous relevance and effectiveness. It prioritizes versatility to accommodate forthcoming advancements in the AI field. Committed to staying at the forefront of technology for sustained innovation. Discover the practical applications of Gemini AI: Facilitates the generation of text and images directly within applications such as Google Docs and Sheets. Duet AI: Aids in crafting compelling and clear writing for various purposes including essays, proposals, and more. Help Me Write: Enhances AI-powered search capabilities for quicker and simpler information retrieval. Smarter Search: Google ensures responsible development by prioritizing safety and unbiased AI through rigorous testing and expert collaboration. Safety Measures: Advantages of AI models within Gemini: a. Improved Decision Making: Empowers businesses with rapid and precise data analysis, facilitating confident decision-making. b. Creative Content Generation: Enables the development of engaging and unique content across various industries. c. Personalization: Customizes responses according to user interactions, thereby enhancing the overall user experience. d. Automation: Streamlines tasks, enabling businesses to concentrate on high-value activities and innovation. Simplified Generative AI Integration: Google Gemini AI transforms AI models and through advanced machine learning algorithms. This allows for the creation of highly realistic and imaginative outputs, unlocking new potentials for businesses across diverse industries. Positioned at the forefront, Google Gemini AI is shaping the future of AI models and generative AI integration. generative AI integration Industry-wise Impact of Gemini: Banking and Finance: Google Gemini optimizes risk management, fraud detection, and customer service through predictive capabilities, enabling accurate financial forecasts. Manufacturing: Gemini enhances predictive maintenance, quality control, and supply chain optimization, leading to increased efficiency and productivity in the manufacturing sector. Retail: In the retail industry, Gemini transforms the shopping experience by offering personalized recommendations, efficient inventory management, and enhanced customer engagement strategies. Healthcare: Gemini plays a crucial role in healthcare by aiding diagnostics, drug discovery, and personalized medicine, accelerating research efforts and improving patient outcomes. Oil and Gas: In the oil and gas sector, Gemini optimizes operations by predicting equipment failures, improving safety protocols, and enhancing exploration strategies, resulting in cost savings and sustainability improvements. , Google Gemini AI represents a major advancement in artificial intelligence, providing a distinctive solution to intricate data dilemmas. It transcends mere word analysis, providing profound comprehension and valuable insights. With its unmatched generative AI capabilities, Gemini AI transforms AI model development and integration, heralding a future defined by innovation, effectiveness, and boundless opportunities. For customized insights tailored to your business needs, reach out to our team of AI experts. In conclusion Also seen here.

Gemini AI by Google: Characteristics, Applications, and Industrial Influence

has made a groundbreaking announcement with the launch of Gemma, a cutting-edge platform that provides open access to pre-trained AI models. Gemma is set to transform the landscape of machine learning by offering developers and researchers a powerful tool to expedite the development and deployment of AI applications. Google Empowering Innovation with Gemma Gemma, built on the foundation of Google's renowned , offers a diverse array of pre-trained models spanning various domains such as image recognition, natural language processing, and speech recognition. This innovative platform enables users to leverage Google's extensive computational resources without the need for laborious model training, significantly reducing the time and resources required for AI development. TensorFlow framework Enhancing Accessibility and Efficiency One of the key advantages of Gemma is its ability to streamline the machine-learning process, allowing developers to kickstart their projects with pre-trained models that can be easily fine-tuned for specific applications. By providing access to a wealth of tools, tutorials, and documentation, Gemma empowers users of all levels to delve into the realm of machine learning with confidence and ease. Transparency and Interpretability at the Core Gemma places a strong emphasis on transparency and interpretability, offering detailed explanations and documentation for each pre-trained model. This commitment ensures that developers have a clear understanding of how the models function, fostering trust and enabling informed decision-making in AI. Customization and Flexibility The flexibility of Gemma allows developers to tailor pre-trained models to suit their unique requirements or embark on creating entirely new models from scratch. This adaptability empowers users to craft machine learning solutions that are finely tuned to address specific use cases, enhancing the efficacy and relevance of AI applications. Applications Across Diverse Fields Gemma opens up a world of possibilities in various domains, including natural language processing (NLP) and computer vision. With access to pre-trained NLP models, developers can create sophisticated chatbots, virtual assistants, and language-understanding applications. Similarly, pre-trained image recognition models enable the development of cutting-edge solutions in computer vision applications such as object identification and visual analysis. Final Thoughts The introduction of Gemma marks a significant milestone in the evolution of machine learning technology. By democratizing access to pre-trained AI models and providing a comprehensive suite of resources, Google is catalyzing innovation and accelerating progress in the field of artificial intelligence. And, while Gemma offers immense potential for advancing AI development, developers need to remain vigilant about potential biases and ethical considerations associated with machine learning models. Careful evaluation and fine-tuning are crucial steps in ensuring that AI solutions are optimized for their intended purposes while upholding ethical standards. Stay ahead of the curve with the latest in AI trends, groundbreaking projects, and free mini-courses by subscribing to our weekly newsletter, . It's your go-to resource for staying informed in the fast-paced world of artificial intelligence, and the best part? It won't cost you a dime! 'AI Hunters' P.S. Check out some of my previous articles at HackerNoon: Sora's AI Innovation Set to Disrupt Video Content Creation Breaking Down the Next Big Thing in NFTs: ERC-404 Spotlight Gemini 1.5 Unleashes Unprecedented Context for AI Applications The AI Revolution in Journalism: A New Era of Enhanced Reporting DeFi Community Building: A Step-by-Step Guide for Crypto Startups

Google Introduces Gemma: Revolutionary Access to Pre-Trained AI Models


Exploring Shadow AI's impact on business: risks, strategies, and the quest for a secure, innovative future. How will companies navigate this new frontier? In December 2023, Amazon unveiled its latest venture, Q, promising a safer alternative to consumer-focused chatbots like ChatGPT. However, the excitement was short-lived. Just three days after the announcement, Amazon Q was embroiled in controversy. Employees were alarmed over its inadequate security and privacy measures, revealing that Q fell short of Amazon's stringent corporate standards. Critics its tendency for "hallucinations" and leaking sensitive information, including AWS data center locations, unreleased product features, and internal discount programs. Amazon's engineers were forced into damage control mode, addressing critical issues tagged as a "sev 2" emergency to prevent future fallout. AI highlighted Around the same time, Samsung Electronics Co. grappled with its own AI-induced headache. Sensitive internal source code found its way onto ChatGPT, spotlighting glaring security vulnerabilities. The response was swift: a company-wide ban on generative AI tools was communicated through an internal memo. Samsung's decision underscored the difficulties of managing data on external AI platforms, such as Google Gemini and Microsoft Copilot, where control over data retrieval and deletion is elusive. This move mirrored the concerns of , who viewed these AI services as a digital . Despite the ban's impact on productivity, Samsung remained firm, opting to develop in-house AI solutions for translation, document summarization, and software development until a secure AI-using environment could be established. 65% of Samsung employees Trojan horse Apple, too, joined the fray, prohibiting its employees from using ChatGPT and similar AI-powered tools. The ban was partly fueled by the tools' affiliations with Microsoft, a direct competitor, stoking fears about Apple's sensitive data security. This trend wasn't exclusive to tech giants; financial behemoths like , Deutsche Bank, Wells Fargo, and others also limited AI chatbots' use, aiming to shield sensitive financial information from third-party eyes. JPMorgan Chase Yet, these restrictions inadvertently birthed a culture of "Shadow AI," where employees use their personal devices at work in their quest for efficiency and time-saving, highlighting a significant policy-practice gap in AI usage. Shadow AI: Unseen Threat Although concrete data is scarce, numerous individuals at companies with AI restrictions have to employing such workarounds — those are only the ones open about it! This Shadow AI usage is prevalent in many organizations, encouraging the use of AI in ways that contradict or violate company policies, thus becoming an activity employees feel compelled to conceal. confessed As I dug into this issue deeper, I found some recent studies confirming that despite about in the workplace, . Recent research by Dell that 91% of respondents have dabbled with generative AI in their lives in some capacity, with another 71% reporting they've specifically used it at work. numerous stories companies restricting genAI use employees don't seem to be using it any less indicates The study conducted by highlights a significant gap between AI adoption in the workplace and the formal policies governing its use in Australia and New Zealand. While 63% of employees in these regions utilize AI for various tasks, only 36% of organizations officially allow it. The survey reveals that AI is being applied for creating written content (51%), enhancing productivity (37%), automating repetitive tasks (37%), improving decision-making (29%), and customer service (20%). However, only 11% of organizations have a comprehensive policy for AI usage, and 21% have no intention to establish any. ISACA Moreover, the study by ISACA indicates a lack of AI-related training within organizations, with only 4% offering it to all staff and 57% not providing any training, even to those directly affected by AI technologies. This situation raises concerns similar to those regarding Shadow IT, where employees use IT resources without formal approval, potentially risking organizational security and governance. Navigating the New Frontier of Risk and Responsibility Much like how Shadow IT snuck up on businesses, Shadow AI is already present, forcing organizations to confront their GenAI stance head-on while still figuring out how to use it. Experts guardrails will not stop employees from using AI tools as they significantly enhance productivity and save time. Therefore, company CIOs must confront this issue and explore mitigation strategies that align with their organization's tolerance for risk. Inevitably, employees with good intentions will utilize these tools to increase their efficiency, so corporate tech leaders can prevent any potential harm to the organization by proactively addressing this trend and managing it effectively. believe Every employee's interaction with AI tools can be a potential point of vulnerability. The history of Shadow IT is marked by significant data breaches, such as the infamous incidents involving , which led to the public exposure of the personal data of 30,000 individuals. These historical precedents serve as a cautionary tale, emphasizing the need for rigorous data governance in the age of AI. unsecured Amazon S3 buckets Shadow AI is a more formidable challenge than Shadow IT for several reasons. First, the decentralized nature of AI tool usage means that the potential for data misuse or leakage is not limited to a technical subset of employees (e.g., developers) but extends across the entire organization. Additionally, inherently learn from the data they process, creating a dual layer of risk: the possibility of accessing sensitive data by AI vendors and the enhanced capability of bad actors to discover and exploit exposed data. AIaaS (AI as a Service) models Strategies to Tackle Shadow AI According to , regional VP of EMEA and Asia and head of digital transformation at SAS, tech leaders with a data-first mindset will be able to drive enhanced efficiencies in 2024 and beyond. This is because maximizing the benefits of generative AI tools is contingent upon well-organized data, necessitating robust data management practices encompassing data access, hygiene, and governance. Amir Sohrabi In his for CIO.com, Nick Brackney, Gen AI & Cloud Evangelist Leader at Dell Technologies, points to "three prescriptive ways" businesses should use to combat Shadow AI successfully. article First, establish a centralized strategy for generative AI usage, involving executive leadership to define use cases, create secure access, and protect data. This approach simplifies enforcement and scaling across the organization while requiring effort to build and identify easy wins to ensure success. Second, keep your data organized and understand which types should not be placed in public or hosted private cloud AI offerings, such as trade secrets and sensitive information. Use AI solutions that allow for complete control or do not retain conversation logs for these types of data. Third, control the AI service by bringing it to your data, whether on-premises or through secure cloud solutions, to leverage advantages in governance, employee productivity, and secure data access. This approach enhances the end-user experience, ensuring compliance and reducing the risk of data exposure. Crafting a clear is crucial for delineating improper AI practices that could potentially harm your organization and for guiding the integration of AI applications in line with data security protocols and risk management strategies. This policy serves as a benchmark, allowing decision-makers to evaluate the usage of AI tools within the organization against established guidelines, swiftly pinpoint any risk exposures, and determine the necessary corrective actions. AI Acceptable Use Policy Ethan Mollick, professor at the Wharton School of the University of Pennsylvania, another thought-provoking approach. He believes that traditional methods for integrating new technologies are ineffective for AI due to their centralized nature and slow pace, making it difficult for IT departments to develop competitive in-house AI models or for consultants to provide specific guidance. The real potential for AI application lies with the employees who are experts in their own jobs, suggesting that for organizations to truly benefit from AI, they must engage their workforce (aka "Secret Cyborgs") in using AI technologies. offers First and foremost, brands should acknowledge that employees at any level could possess valuable AI skills, irrespective of their formal role or past performance. Having detected the among their AI-savvy employees, companies must foster a collective learning environment such as crowd-sourced prompt libraries and create a culture that diminishes the apprehension around AI by offering assurances against job loss due to AI, promoting the use of AI for eliminating mundane tasks and encouraging more engaging work. secret cyborgs Establishing psychological safety is crucial to encouraging open AI usage among employees. Employers should be able to offer substantial rewards for identifying significant opportunities where AI can aid the organization. This could include financial incentives, promotions, or flexible working conditions and be handled through gamification. Today's organizations should act swiftly to determine how productivity gains from AI will be utilized, how work processes should be reorganized in light of AI capabilities, and how to manage potential risks associated with AI use, such as data hallucinations and IP concerns. This calls for a proactive approach to crafting comprehensive AI policies, engaging employees across all levels to leverage their insights, and fostering a culture that rewards AI-driven innovation. As technophiles and businesses navigate the complexities of AI integration, what strategies will you deploy to responsibly and innovatively leverage this transformative technology within your organization or personal projects, ensuring a balanced approach to privacy, security, and efficiency? Don’t forget to check out my previous article to discover ! AI’s dirty secret

Shadow AI: Reshaping the Future, But at What Cost?

শ্যাডো এআই: ভবিষ্যতকে পুনর্নির্মাণ করা, কিন্তু কী মূল্যে?

Schatten-KI: Die Zukunft neu gestalten, aber zu welchem Preis?

IA en la sombra: remodelando el futuro, pero ¿a qué precio?

Shadow AI : remodeler l’avenir, mais à quel prix ?

शैडो एआई: भविष्य को नया आकार देना, लेकिन किस कीमत पर?

シャドウ AI: 未来を再構築するが、その代償は?

Shadow AI: 미래를 재편하려면 비용이 얼마나 듭니까?

Shadow AI: remodelando o futuro, mas a que custo?

Теневой ИИ: меняя будущее, но какой ценой?

Shadow AI: Geleceği Yeniden Şekillendirmek, Ama Maliyeti Ne Olacak?

Shadow AI: Định hình lại tương lai, nhưng với cái giá nào?

影子人工智能：重塑未来，但代价是什么？

The meteoric growth of is set to continue into 2024 as the transformative technology moves into its implementation phase. generative AI Whether you believe that generative AI is a fresh dotcom bubble or the biggest innovation of the 21st Century, it’s clear that the stock market rally driven by the technology isn’t ready to slow down just yet. According to a recent Bloomberg Intelligence has suggested that the emerging industry could grow at a CAGR of 42% to become a , a feat that would provide masses of prosperity to the generative AI stocks that sustain the boom period. $1.3 trillion market by 2032 This sentiment is echoed by Wedbush analyst Dan Ives, who suggested that the rise of generative AI is the “fourth industrial revolution playing out.” “I think this is really transformational changes to technology that I think would change the tech space for the next 20-30 years,” . “I think we are just starting what we believe is the start of a new tech bull market, despite many of the bears continuing to really being skeptical.” Ives added Generative AI Revolution Shifts into the Implementation Phase Crucially, the generative AI boom will shift its focus starting in 2024 as early adopters move beyond concepts and into implementing the technology for their operations. This is likely to be a difficult process for many enterprises. Much of the early hype surrounding GenAI stocks was focused on Nvidia as a leading chipmaker that could power much of this shift toward artificial intelligence, but will entry costs temper enthusiasm? 2024 will see more business leaders looking to and into piloting the technology to optimize operational efficiency, productivity, and creativity. move beyond the ideation process To supplement this, generative AI providers will spend the year seeking profitable business models that are ready to support premium quality systems. So, what will fully integrated generative AI models look like as businesses seek to implement the technology?  The MIT Technology Review suggests that early implementation will take the form of that will offer more efficient support for customers based on powerful large language models (LLMs). customizable chatbots Although the growth of GenAI chatbots for businesses will be dependent on eliminating existing biases and inaccuracies within models, it’s logical to expect that the success of ChatGPT manifests itself in the development of LLMs for business as the technology becomes more commonplace. Will Barriers Get The Better of GenAI in 2024? Despite the vast potential of generative AI, there will likely be many bumps in the road as the technology grows. 2024 is likely to uncover many flaws and weaknesses in generative AI as the technology remains in its infancy. The will be a major barrier to the widespread adoption of generative AI technology and could impact some of the stocks that have performed exceptionally well on Wall Street in recent months. threat of error and inefficiencies Patience is always a virtue when it comes to emerging tech, and any short-term volatility is set to give way to more widespread market optimism as more sophisticated solutions are developed. However, the inevitability of inefficiencies means that investors could be best placed to trust larger generative AI stocks for the first half of 2024 as reality begins to bite for firms with big ideas and few efficient solutions to show for them. Where Should Investors Look in H1 2024? As generative AI shifts into its implementation phase, we’re likely to see some fundamental changes to how investors view stocks in the first half of 2024. Market euphoria as innovations emerge can quickly give way to timely reality checks as investors begin to remember the value of fundamentals and sustainable business models. We can expect this to deliver more value to resource-rich firms that have the power to overcome the challenges thrown up by 2024 with greater efficiency. However, there will still be plenty of room for strong growth stocks with innovative plans for the industry. With this in mind, let’s explore three stocks that are set to show strong performance in H1 2024: 1. Alphabet (​​NASDAQ: GOOGL) Alphabet’s influence in the world of generative AI can’t be understated. Crucially, are Google Cloud customers, and the tech giant’s cloud services are growing at a healthy 22% pace in a market still blighted by economic headwinds. more than half of generative AI startups In addition to this, Alphabet’s strategic artificial intelligence investments are set to provide more industry growth throughout the coming months. Most notable is the firm’s Gemini generative AI model, which could help to bolster the evolution of the technology throughout its future. “In Q3 2023, Alphabet reported revenue of $76.7 billion, showcasing notable YoY growth of 22% and 11% in Google Cloud and Search revenues, respectively,” highlights Maxim Manturov, head of investment research at . “The integration of generative AI played a key role in boosting ad revenues on YouTube to an impressive $7.95 billion.” Freedom Finance Europe “Alphabet strategically plans to integrate AI broadly across its business segments, leveraging its substantial advantage in data,” Manturov added. Given that Alphabet is already solutions to make existing processes like advertising on YouTube more profitable, it provides a relatively safe foundation for investors to buy in the hopes of accelerating GenAI innovation in the future. utilizing generative AI 2. Amazon (NASDAQ: AMZN) Amazon represents another safe bet for investors to continue growing its generative AI competencies in early 2024. The eCommerce giant has already sought to integrate AI and recently announced its new generative AI chatbot, Q. across a vast array of services In addition to this, the launch of text-to-speech and speech-to-text services, , is another example of high-performance artificial intelligence solutions that are immediately ready for market. Amazon Polly Investors can expect Amazon to continue scouting out innovative AI solutions in the new year at a rapid pace. This is underlined by the waves that the tech leader has made in its in healthcare AI startup Anthropic. $4 billion investment 3. Palantir Technologies (NYSE: PLTR) Finally, Palantir is an example of a specialist artificial intelligence company that’s continually shown sustainable growth, paving the way for greater investor confidence in the firm’s sustainability as the generative AI boom grows in 2024. The financial performance of Palantir is a cause for optimism, reporting , representing 16.8% growth over the same period in 2022. Q3 2023 revenue of $558.16 million Palantir’s strong market position in the world of AI was underlined by a recent market study from Dresner Advisory Services, which highlighted the firm as a of analytics features in model operations. leading provider This indicates that Palantir could be a key beneficiary as generative AI ideation leads to implementation, with the firm likely to be at the forefront of the minds of many business leaders during the first half of the year. Market Growth to be Underlined by Efficiency The furor surrounding generative AI will transform into a widespread quest for efficiency in the first half of 2024, with business leaders seeking practical, reliable, and affordable solutions to incorporate into their operations. We can be sure that the draw of generative AI and its incredible pull over investors will ensure its widespread appeal among would-be adopters, but the successful implementation of such a transformative technology will be key over the coming months. There will still be room for innovative new ideas and fresh industry breakthroughs, but the quest for sustainability will likely provide a timely reality check. With this in mind, we’re likely to see investors place their trust in key industry players with a track record of innovation.

Why These 3 Stocks are a Safe Bet to Take The Reigns of the Generative AI Boom in H1 2024

Picture this: You copy a file and don't verify it TL;DR: Don't rely on external solutions without good handlers Problems Silent Modifications


Least Surprise Principle violation


Fail Fast Principle Violation Solutions Ensure you meet your function's postconditions


Use mature languages Context The copy() function is used to copy files from one location to another. However, when used on some systems, it can fail silently or make unexpected conversions. For example, Windows interprets paths ending with a backslash () as directories. If the intended destination file has the same name as a directory in the path, copy() will silently create an empty file with the intended filename within that directory. This can be confusing and lead to data loss. Sample Code Wrong <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination.txt';
  $copyWasSuccessful = copy($sourceFile, $destination); // true
  $destinationFileExists = file_exists($destination); // true
  
  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified 
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination); 
  // true - this is a mistake

  $destinationFileExists = file_exists($destination); 
  // false since it was not created

  $destinationChangedFileExists = file_exists('C:\temp\destination '); 
  // true but unexpected Right <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination);  
  if (!$copyWasSuccessful || !$file_exists($destination)) {
    // Don't trust the function result. Handle the postcondition error
  } Detection [x]Semi-Automatic You can check all copy() handlers and wrap them Tags Fail Fast Level [x]Beginner AI Generation Gemini is the only generator that avoided the problem dealing with ":" on file names AI Detection With this prompt: What happens with this code on windows and what is the value of copyWasSuccessful ChatGPT found the mistake and (wrongly) predicted the operation would fail. Gemini, on the other hand, found the typo but also couldn't accurately predict the behavior of the operation. Claude also noticed the mistake but refused to display the execution result Conclusion Always check important function's post-conditions even if you think you will have performance penalties. You can never be too safe. Relation Code Smells Code Smell 15 - Missed Preconditions Disclaimer: Code Smells are my opinion. Blaming programmers has been the prevailing approach for a half century of software development: It has not solved the problem yet, so it is time to look in different directions. - Boris Beizer from Software Engineering Great works. This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code Photo Credit: Luke Jernejcic on Unsplash Picture this: You copy a file and don't verify it Picture this: You copy a file and don't verify it TL;DR: Don't rely on external solutions without good handlers TL;DR: Don't rely on external solutions without good handlers Problems Silent Modifications Least Surprise Principle violation Fail Fast Principle Violation Silent Modifications Silent Modifications Least Surprise Principle violation Least Surprise Principle violation Fail Fast Principle Violation Fail Fast Principle Violation Solutions Ensure you meet your function's postconditions Use mature languages Ensure you meet your function's postconditions Ensure you meet your function's postconditions Use mature languages Use mature languages Context The copy() function is used to copy files from one location to another. copy() However, when used on some systems, it can fail silently or make unexpected conversions. For example, Windows interprets paths ending with a backslash () as directories. If the intended destination file has the same name as a directory in the path, copy() will silently create an empty file with the intended filename within that directory. This can be confusing and lead to data loss. Sample Code Wrong <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination.txt';
  $copyWasSuccessful = copy($sourceFile, $destination); // true
  $destinationFileExists = file_exists($destination); // true
  
  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified 
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination); 
  // true - this is a mistake

  $destinationFileExists = file_exists($destination); 
  // false since it was not created

  $destinationChangedFileExists = file_exists('C:\temp\destination '); 
  // true but unexpected <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination.txt';
  $copyWasSuccessful = copy($sourceFile, $destination); // true
  $destinationFileExists = file_exists($destination); // true
  
  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified 
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination); 
  // true - this is a mistake

  $destinationFileExists = file_exists($destination); 
  // false since it was not created

  $destinationChangedFileExists = file_exists('C:\temp\destination '); 
  // true but unexpected Right <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination);  
  if (!$copyWasSuccessful || !$file_exists($destination)) {
    // Don't trust the function result. Handle the postcondition error
  } <?

  $sourceFile = 'C:\temp\source.txt';
  $destination = 'C:\temp\destination :txt';
  // The filename is simplified
  // and might come from a programmatic construction

  $copyWasSuccessful = copy($sourceFile, $destination);  
  if (!$copyWasSuccessful || !$file_exists($destination)) {
    // Don't trust the function result. Handle the postcondition error
  } Detection [x]Semi-Automatic [x] Semi-Automatic [x] You can check all copy() handlers and wrap them Tags Fail Fast Fail Fast Level [x]Beginner [x] Beginner [x] AI Generation Gemini is the only generator that avoided the problem dealing with ":" on file names AI Detection With this prompt: With this prompt: What happens with this code on windows and what is the value of copyWasSuccessful What happens with this code on windows and what is the value of copyWasSuccessful ChatGPT found the mistake and (wrongly) predicted the operation would fail. Gemini, on the other hand, found the typo but also couldn't accurately predict the behavior of the operation. Claude also noticed the mistake but refused to display the execution result Conclusion Always check important function's post-conditions even if you think you will have performance penalties. You can never be too safe. you think Relation Code Smells Code Smell 15 - Missed Preconditions Code Smell 15 - Missed Preconditions Disclaimer: Code Smells are my opinion. Disclaimer: Code Smells are my opinion . opinion Blaming programmers has been the prevailing approach for a half century of software development: It has not solved the problem yet, so it is time to look in different directions. Blaming programmers has been the prevailing approach for a half century of software development: It has not solved the problem yet, so it is time to look in different directions. - Boris Beizer from Software Engineering Great works. - Boris Beizer from Software Engineering Great works. Boris Beizer This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code This article is part of the CodeSmell Series: How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code Photo Credit: Luke Jernejcic on Unsplash Photo Credit: Luke Jernejcic on Unsplash Luke Jernejcic Unsplash

How To Find the Stinky Parts of Your Code: Code Smell 248 – Unreliable Copy

You need to model an expiration date. Which object will you use? TL;DR: Model real word expiration dates with... expiration dates Problems Bijection Violation
Unexpected Behavior
Small Objects Missing
Primitive Obsession Solutions Honor the bijection and model correct behavior Context In many systems, the expiry date of a credit card is often represented by simply using a Date object. This can lead to potential issues and misunderstandings, especially when dealing with operations such as comparisons and calculations based on the expiry date. It's generally considered a better practice to represent the expiration date with an adequate object. Sample Code Wrong import java.util.Date;

public class CreditCard {
    private String cardNumber;
    private Date expiryDate;

    public CreditCard(String cardNumber, Date expiryDate) {
        // Not a complete date
        this.cardNumber = cardNumber;
        this.expiryDate = expiryDate;
    }

    public boolean isExpired() {
        Date currentDate = new Date();
        return expiryDate.before(currentDate);
        // How will it work? 
        // using the last day of the month?
    }
} public class CreditCard {
    private String cardNumber;
    private int expiryMonth;
    private int expiryYear;

    public CreditCard(String cardNumber, int expiryMonth, int expiryYear) {
        this.cardNumber = cardNumber;
        this.expiryMonth = expiryMonth;
        this.expiryYear = expiryYear;
        // No validations on number ranges?
    }

    public boolean isExpired(int currentMonth, int currentYear) {
        return (expiryYear < currentYear) ||
            (expiryYear == currentYear && expiryMonth < currentMonth);
    }
    // Inappropriate intimacy code smell
 
} Right class CreditCard {
  private String number;
  private MonthOfYear expiryDate;
  // expiryDate is the role
  // MonthOfYear is the type
}

class MonthOfYear {
  private Month month;  
  private Year year;
  // These are other small objects

  public MonthOfYear(Month month, Year year) {
    // You don't need to add validations since 
    // month is a valid month
    // year is a valid year
    this.month = month;
    this.year = year;
  } 
  
 public boolean isBeforeEndOfMonth(Date date) {
    Calendar calendar = Calendar.getInstance();
    calendar.setTime(date);
    return (calendar.get(Calendar.YEAR) < year.value()) ||
           (calendar.get(Calendar.YEAR) == year.value() &&
            calendar.get(Calendar.MONTH) < month.value())      
    // Notice there are no days involved   
  }
  
  // This protocol is just for MonthOfYears  
  public Day[] getDaysInMonth() { }
  
  public boolean isLeapYear() { } // ...
  
  public void iterateDays() { } // ...
  
} Detection [x]Manual This is a design smell Tags Primitive Obsession Level [x]Intermediate This is not an obvious design decision AI Generation Actual AI assistants are not very good at creating these kinds of small objects AI Detection Gemini detected this is a possible smell Conclusion ExpiryDate explicitly separates month and year, making the code more readable and making it easier to understand the specific information needed for expiry. It can also encapsulate logic specific to expiry dates, such as calculating days remaining, validating expiry, or iterating through days in the month. While Date objects offer date manipulation functionalities, they don't inherently represent the specific concept of a credit card expiry. Finding small objects with concrete behavior is always a difficult task. Relations Code Smell 122 - Primitive Obsession Code Smell 177 - Missing Small Objects More Info The One and Only Software Design Principle Disclaimer Code Smells are my opinion. Credits Photo by CardMapr.nl on Unsplash Thank you, Hernan Wilkinson, for this tip Standards are always out of date. That’s what makes them standards. Alan Bennett https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code Also published here. You need to model an expiration date. Which object will you use? You need to model an expiration date. Which object will you use? TL;DR: Model real word expiration dates with... expiration dates TL;DR: Model real word expiration dates with... expiration dates expiration dates Problems Bijection Violation Unexpected Behavior Small Objects Missing Primitive Obsession Bijection Violation Bijection Unexpected Behavior Small Objects Missing Small Objects Primitive Obsession Primitive Obsession Solutions Honor the bijection and model correct behavior Honor the bijection and model correct behavior Context In many systems, the expiry date of a credit card is often represented by simply using a Date object. This can lead to potential issues and misunderstandings, especially when dealing with operations such as comparisons and calculations based on the expiry date. It's generally considered a better practice to represent the expiration date with an adequate object. Sample Code Wrong import java.util.Date;

public class CreditCard {
    private String cardNumber;
    private Date expiryDate;

    public CreditCard(String cardNumber, Date expiryDate) {
        // Not a complete date
        this.cardNumber = cardNumber;
        this.expiryDate = expiryDate;
    }

    public boolean isExpired() {
        Date currentDate = new Date();
        return expiryDate.before(currentDate);
        // How will it work? 
        // using the last day of the month?
    }
} import java.util.Date;

public class CreditCard {
    private String cardNumber;
    private Date expiryDate;

    public CreditCard(String cardNumber, Date expiryDate) {
        // Not a complete date
        this.cardNumber = cardNumber;
        this.expiryDate = expiryDate;
    }

    public boolean isExpired() {
        Date currentDate = new Date();
        return expiryDate.before(currentDate);
        // How will it work? 
        // using the last day of the month?
    }
} public class CreditCard {
    private String cardNumber;
    private int expiryMonth;
    private int expiryYear;

    public CreditCard(String cardNumber, int expiryMonth, int expiryYear) {
        this.cardNumber = cardNumber;
        this.expiryMonth = expiryMonth;
        this.expiryYear = expiryYear;
        // No validations on number ranges?
    }

    public boolean isExpired(int currentMonth, int currentYear) {
        return (expiryYear < currentYear) ||
            (expiryYear == currentYear && expiryMonth < currentMonth);
    }
    // Inappropriate intimacy code smell
 
} public class CreditCard {
    private String cardNumber;
    private int expiryMonth;
    private int expiryYear;

    public CreditCard(String cardNumber, int expiryMonth, int expiryYear) {
        this.cardNumber = cardNumber;
        this.expiryMonth = expiryMonth;
        this.expiryYear = expiryYear;
        // No validations on number ranges?
    }

    public boolean isExpired(int currentMonth, int currentYear) {
        return (expiryYear < currentYear) ||
            (expiryYear == currentYear && expiryMonth < currentMonth);
    }
    // Inappropriate intimacy code smell
 
} Right class CreditCard {
  private String number;
  private MonthOfYear expiryDate;
  // expiryDate is the role
  // MonthOfYear is the type
}

class MonthOfYear {
  private Month month;  
  private Year year;
  // These are other small objects

  public MonthOfYear(Month month, Year year) {
    // You don't need to add validations since 
    // month is a valid month
    // year is a valid year
    this.month = month;
    this.year = year;
  } 
  
 public boolean isBeforeEndOfMonth(Date date) {
    Calendar calendar = Calendar.getInstance();
    calendar.setTime(date);
    return (calendar.get(Calendar.YEAR) < year.value()) ||
           (calendar.get(Calendar.YEAR) == year.value() &&
            calendar.get(Calendar.MONTH) < month.value())      
    // Notice there are no days involved   
  }
  
  // This protocol is just for MonthOfYears  
  public Day[] getDaysInMonth() { }
  
  public boolean isLeapYear() { } // ...
  
  public void iterateDays() { } // ...
  
} class CreditCard {
  private String number;
  private MonthOfYear expiryDate;
  // expiryDate is the role
  // MonthOfYear is the type
}

class MonthOfYear {
  private Month month;  
  private Year year;
  // These are other small objects

  public MonthOfYear(Month month, Year year) {
    // You don't need to add validations since 
    // month is a valid month
    // year is a valid year
    this.month = month;
    this.year = year;
  } 
  
 public boolean isBeforeEndOfMonth(Date date) {
    Calendar calendar = Calendar.getInstance();
    calendar.setTime(date);
    return (calendar.get(Calendar.YEAR) < year.value()) ||
           (calendar.get(Calendar.YEAR) == year.value() &&
            calendar.get(Calendar.MONTH) < month.value())      
    // Notice there are no days involved   
  }
  
  // This protocol is just for MonthOfYears  
  public Day[] getDaysInMonth() { }
  
  public boolean isLeapYear() { } // ...
  
  public void iterateDays() { } // ...
  
} Detection [x]Manual [x] Manual [x] This is a design smell Tags Primitive Obsession Primitive Obsession Level [x]Intermediate [x] Intermediate [x] This is not an obvious design decision AI Generation Actual AI assistants are not very good at creating these kinds of small objects AI Detection Gemini detected this is a possible smell Conclusion ExpiryDate explicitly separates month and year, making the code more readable and making it easier to understand the specific information needed for expiry. It can also encapsulate logic specific to expiry dates, such as calculating days remaining, validating expiry, or iterating through days in the month. While Date objects offer date manipulation functionalities, they don't inherently represent the specific concept of a credit card expiry. Finding small objects with concrete behavior is always a difficult task. Relations Code Smell 122 - Primitive Obsession Code Smell 122 - Primitive Obsession Code Smell 177 - Missing Small Objects Code Smell 177 - Missing Small Objects More Info The One and Only Software Design Principle The One and Only Software Design Principle Disclaimer Code Smells are my opinion . opinion Credits Photo by CardMapr.nl on Unsplash CardMapr.nl Unsplash Thank you, Hernan Wilkinson, for this tip Hernan Wilkinson, Standards are always out of date. That’s what makes them standards. Standards are always out of date. That’s what makes them standards. Alan Bennett Alan Bennett https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code Also published here. Also published here . here

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GEMINI AI SOLUTIONS

geminiaisolutions.com

-- employees

Since n.d.

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GEMINI AI SOLUTIONS

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