ChatGPT and AI for web developers - Maximiliano Firtman

Building a conversational AI experience that can respond to a wide variety of inputs and situations depends on gathering high-quality, relevant training data. Dialog with humans is an important part of this training process. In this session, learn how researchers at Facebook use Amazon Mechanical Turk within the ParlAI (pronounced “parlay”) framework for training and evaluating AI models to perform data collection, human training, and human evaluation. Learn how you can use this interface to gather high-quality training data to build next-generation chatbots and conversational agents.

Transform your marketing game with AI! View our presentation and explore the power of ChatGPT for creating personalized customer experiences.

This document provides an overview and roadmap for building a simple guessing game with JavaScript. It begins with introductions and background on programming concepts. It then outlines the steps to build the game, including generating a random number on page load, accepting user input, checking guesses, and allowing new games. Code examples are provided for functions to generate random numbers and display guesses. Homework extends the game with additional feedback and counting number of guesses. Information is also given on Thinkful's mentorship program for learning to code.

As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other? Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real. Keywords: AI, Containeres, Kubernetes, Cloud Native Event Link: https://meine.doag.org/events/cloudland/2024/agenda/#agendaId.4211

Microsoft Cognitive Services Language APIs - Bing Spell Check, Language Understanding, Linguistic Analysis, Text Analytics, Translator and Web LM - can enable your apps to understand language and communicate with people.

As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other? Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real. Keywords: AI, Containeres, Kubernetes, Cloud Native Event Link: https://mlconference.ai/tools-apis-frameworks/containers-ai-infrastructure/

APIs define contracts between a service and a client, and with the rise of representation languages like Swagger, Apiary, and RAML, these contracts can be consumed programmatically and adapted easily into our codebases. Other tools like JSON Schema also contribute to this idea of integration between service and client. But what about our documentation? If API contracts can be assimilated into software, surely it can drive our documentation too? In this talk, I want to introduce some of the techniques I've used on past projects that allow exactly that. By using remote schemas to generate software, it also allows us to generate working documentation that is always relevant and never out of date. Apart from accuracy, we also get the added benefits of reduced development time, reduced effort, and reduced duplication. We can all of this by documenting once, and re-using across multiple projects!

A comprehensive exploration of artificial intelligence, particularly focusing on its historical development, notable milestones, and various applications. It begins with a brief history of AI, tracing its ancient philosophical roots through to contemporary advancements like quantum computing and advanced robotics. Key historical highlights include the development of "Shakey," the first mobile robot capable of reasoning about its environment, and ELIZA, the first chatbot. The presentation also covers the evolution of self-driving technology, starting with Ernst Dickmanns' pioneering work in the 1980s. It delves into the profound impact of AI in games, exemplified by AlphaGo's victory over a human Go champion. Furthermore, it details the types of AI and machine learning, emphasizing the revolutionary role of ChatGPT. Introduced by OpenAI, ChatGPT quickly became the fastest app to reach 100 million users due to its versatile capabilities in language processing and interaction. Lastly, the slides provide practical insights on effectively utilizing ChatGPT, such as optimizing input to enhance outcomes and integrating ChatGPT's API into various applications. The presentation is aimed at both educating on AI's capabilities and demonstrating its practical applications in modern technology scenarios.

OpenAI GPT in depth – misconceptions and questions you would like answered Have you ever wondered why GPT models work? Do you ask questions like: How does GPT work? Why does the same problem receive different answers for different users? Is there a way to improve explainability? Can GPT model provide its sources? Why does Bing chat work differently? What are my ways to have better performance and improve completions? How can I work with data in my enterprise? What practical business cases could a generative AI model fit solving? If you are tired of sessions just scratching the surface of OpenAI GPT, this one will go deeper and answer questions like why, why not and how.

The document discusses various professional practices for web development including proper coding techniques, layout, use of images and other multimedia, adherence to web standards, avoiding plagiarism, and respecting copyright laws. Key practices include commenting code for clarity, using indentation and spacing for readability, choosing appropriate image formats and sizes, validating code, and continually learning new skills and technologies.

This report offers an in-depth exploration of the application and potential of ChatGPT, a sophisticated AI conversational model developed by OpenAI. With over 100 practical examples of prompts, we aim to demonstrate the breadth of the model's capacity and its utility across diverse fields and industries, such as education, customer service, research, entertainment, and more. Introduction: ChatGPT is a highly advanced machine learning model that utilizes a transformer architecture for generating human-like text based on given prompts. It's part of OpenAI's GPT (Generative Pretrained Transformer) series, and as of our knowledge cutoff in 2021, its latest version is GPT-4. It has proven to be a transformative tool for various applications, such as drafting emails, writing code, creating content, answering queries, tutoring in various subjects, translating languages, simulating characters for video games, and more. Chapter 1: Understanding ChatGPT In this chapter, we delve into the basics of ChatGPT, starting with its origins and development. We touch on the model's architecture, including its use of attention mechanisms and transformer models, its training process using reinforcement learning from human feedback, and how it generates responses. Here, we explore some of the myriad applications of ChatGPT across multiple sectors. We discuss how it's revolutionizing customer service by providing 24/7 support, aiding in education by personalizing learning, assisting researchers with literature reviews, and even creating dialogue for video games. Real-world examples and case studies are included to illustrate these applications. This chapter serves as a comprehensive guide for utilizing ChatGPT effectively. We provide over 100 prompt examples spanning various fields, like marketing, healthcare, entertainment, etc. These prompts range from simple inquiries to complex, layered questions, giving readers a thorough understanding of how to harness the full potential of ChatGPT. While the potential of ChatGPT is unquestionable, it's crucial to address the ethical implications of its use. This chapter delves into areas such as data privacy, the risk of misuse, and the importance of transparency. We also contemplate the future directions of AI conversation models like ChatGPT, discussing the potential for even more nuanced understanding and response generation. In our concluding remarks, we reflect on the transformative potential of ChatGPT and similar AI models. We emphasize the model's ability to democratize access to information, offer personalized learning and support, and the broader implications for society.

Dive deep into the world of ChatGPT-powered SEO and unlock its hidden potential. This comprehensive webinar will not only demonstrate the sheer power of integrating by Joseph S. Kahn

The document discusses the opportunities presented by bots, including high demand from companies, the ability to create more natural experiences for users on messaging apps, and simpler deployment and updating than traditional apps. It provides an overview of the typical architecture of a bot, including components like the Bot Builder SDK, LUIS, and the Developer Portal. Several use cases for bots are presented, such as managing cloud resources from Skype, handling customer service, and acting as knowledgeable assistants. Guidelines for creating effective bots focus on solving users' needs with minimal effort and guiding users to discover what the bot can do.

This document provides an agenda and summary for a meetup on Augmented Reality and ChatGPT hosted by MuleSoft. The meetup includes introductions to AR, its future applications, and types of AR. It also covers how MuleSoft can contribute to the future of AR and a demo of integrating ChatGPT with MuleSoft. The meetup organizers provide a safe harbor statement and housekeeping details like submitting questions and providing feedback. Speakers introduce themselves and their roles.

Keynote at 2nd International Workshop on Bots in Software Engineering on the lessons learned while building our chatbot platform Xatkit

How AI is going to change the world? "AI: The Future of Our World“ "AI and its Transformative Impact on the World: Understanding the Potential of Chatbots and Conversational AI" What is Artificial Intelligence and how it works? What are Chatbots? What Is ChatGPT? Difference between chatGPT 3 and chatGPT 4? Is Jasper artificial intelligence? What is Character AI and how it works? How chatGPT is going to change the world? Why we are calling ChatGPT the future?

Building automated conversational agents is a balancing act between fine-grained control of messaging and maintaining logic. In this chalk talk, CarLabs, a leader in developing digital assistants for automotive brands, describes how they create their platform using a combination of Amazon Neptune to encode business rules, Amazon SageMaker to create a RNN model, and Amazon Mechanical Turk to determine the highest levels of accuracy.

This document discusses WebAssembly (Wasm) runtimes and use cases. It provides an overview of Wasm, including how it is compiled from source code to binary format and imported into JavaScript. It describes how Wasm provides portability across execution contexts and systems through standards like WASI. Examples of using Wasm include a search component and demonstrating isomorphism. Potential tradeoffs discussed include additional debugging layers and unstable preview interfaces.

The document discusses auditing design systems for accessibility. It begins by explaining how design systems can proliferate both accessibility issues and fixes if accessibility is considered. It then covers conducting accessibility audits, which involve using the WCAG as criteria to manually and automatically test components for various issues. The audit process involves planning, reviewing designs, code and documentation, documenting any issues found, grouping by theme, prioritizing by impact, and sharing results. Accessibility auditing is presented as a way for teams to advocate for and improve accessibility in their design systems.

This document discusses designing interfaces that adapt to different user situations and contexts. It covers adapting designs for different content amounts, loading/error states, user preferences like dark mode, interactions using mouse/keyboard/touch. It also discusses designing for responsive layouts, conditional content, different stages of user journeys, and going beyond assumptions to consider edge cases and ensure designs are inclusive. The key message is that designers need to move beyond pixel perfection and consider how interfaces will really behave for diverse users in varied real-world contexts.

This document discusses considerations for building a research repository to share findings and learnings across teams. It recommends that the repository make information recoverable, accessible, actionable, traceable, and safe. Key points include having a good taxonomy to organize data, labeling insights clearly, allowing traceability to original observations and evidence while protecting personal data, and designing the experience to be self-explanatory so the repository can democratize research learnings.

This document presents a framework for effective collaboration between designers and developers. It discusses three levels needed for collaboration: tools and communication, aligning processes, and developing a collaborative mindset. At each level, it provides examples of practices that can bridge the gaps between disciplines like using common work spaces, design systems, and involving all parties early in the design process. The overall message is that to collaborate, teams need shared goals, processes, and a willingness from all members to understand each other's work and make compromises.

The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like anxiety and depression.

The document discusses declarative programming versus imperative programming and provides examples of declarative programming approaches including structured query language and CSS. It also discusses how declarative design can be applied to buttons, controls, and design systems. While declarative design has advantages, whether it is better than imperative depends on factors like the medium, platform, and how tightly one wants to control the design versus allowing flexibility. An overall philosophy of responsive and declarative design is suggested for the open Web.

This document provides an overview of design concepts and examples through history. It discusses how ideology, social values, and technology shape design outcomes. Examples shown include calculating machines from the 1940s, typewriters from the 1970s, and modern devices like the OP-1 music production tool. The document emphasizes that the most meaningful designs authentically express the values of their time and that the quality of a civilization's designs reflects the quality of the civilization itself.

This document provides guidance on how to successfully implement emerging technologies by bridging the gap between business and technology needs. It recommends: 1) Clearly defining the technology being discussed; 2) Laying out all potential options visually to facilitate collaboration between business and technical teams; and 3) Creating service blueprints to define how new technologies integrate into customer experiences. The goal is to move innovative ideas from hype to viable solutions that create real business value.

Laura Kalbag presented on building a white noise machine application using state machines. She began by modeling the application logic as a finite state machine with states like "power on" and "power off". She then enhanced it to a statechart by adding hierarchy with child states for different sounds, and parallel states for features like light and volume. By exporting the statechart to code, it became an executable specification that could be simulated and developed further. Statecharts provide benefits like managing complexity, clear documentation, and easier testing and debugging of application logic.

Session replay records a user's interactions on a website to help debug issues and improve the user experience. The presenter discussed lessons learned from building a session replay product at Sentry, including knowing your specific use case, expecting unexpected problems, optimizing bundle size through techniques like tree shaking, and compressing recorded data to reduce network traffic.

The document discusses taking screenshots and snapshots of elements in Cypress tests. It shows how to take snapshots of the entire page or individual elements using the .track() method. It also demonstrates how to freeze the system time, wait for elements to load, and create a custom command to change an element's styling for snapshots.

This document discusses solving common problems with web components using server side rendering. It begins by explaining what web components are - custom elements, shadow DOM, and HTML templates. It then discusses why web components are useful, such as component reuse and interoperability. Common problems with web components are described like flash of undefined custom elements (FOUCE) and shadow DOM not playing well with native forms. Solutions to these problems include declarative shadow DOM and the Enhance framework, which allows server side rendering of components to avoid FOUCE and uses the light DOM for styling instead of shadow DOM. Overall, the document presents server side rendering as an effective way to solve problems with web components.

This document discusses the concept of "malleable applications", which refers to software that can be incrementally and individually modified by end-users to better suit their needs and preferences. The current state of most applications is that they are "one-size-fits-all" and do not provide users with enough control and agency over their digital experiences. New technologies like AI, GraphQL, and substrate computing could help empower users to tailor applications and have more control over how their data is transformed and displayed. The goal is to move beyond a world where users just consume apps, and instead have the ability to author and customize their own computing experiences through more flexible, moldable software.

The document summarizes trends in UX tools and methodologies discussed by Josephine Scholtes. It covers four topics: 1) Humanity-centered design focuses on solving problems for societies rather than individuals. 2) Need-based personas categorize users based on shared needs rather than demographics. 3) Inclusive design aims to make designs usable for diverse groups through the design process. 4) Designing to avoid unintended consequences by exploring possible futures and scenarios. The document provides overviews and examples of applying each trend.

The document discusses web accessibility testing. It defines accessibility and why it is important for websites to be accessible to all users, including those with disabilities. It then describes how to test for accessibility using keyboards, screen readers, and browser tools. Specific things to test include page structure, alternative text for images, form labels, and dynamic changes. Testing tools mentioned include browser developer tools, Lighthouse, and the Axe accessibility inspector extension. The key takeaway is the importance of testing for accessibility from the start of a project from the perspective of different users.

This document discusses the CIA triad of security - confidentiality, integrity, and availability. It explains that the CIA triad can help evaluate the security of a project by asking how each element could be broken. Confidentiality involves who can access resources and sensitive data. Integrity considers who can modify resources and the risks of malicious actions. Availability examines rate limiting, outages, and maintenance windows. The document encourages shifting security left by injecting CIA triad questions into development processes to catch issues earlier.

Dynamic CSS Secrets - Lea Verou

The document discusses Douglas Crockford's work developing programming languages like Crocktran, Candy, Ply, Elemeno, Neo, and Misty. It argues that the actor model provides a better paradigm for distributed computing compared to past paradigms. Misty adds actors to Neo to demonstrate this paradigm, and a new programming language fully based on the actor model may be needed in the future. The document also outlines Crockford's vision for an actor protocol and format to replace HTTPS for actor systems.

The document discusses optimizing web performance for users in harsh conditions like rural Africa. It recommends letting users know what's happening, loading initial information quickly, progressively enhancing the website, avoiding unnecessary requests, lazy loading non-critical content, and leveraging features like preconnecting, prefetching, preloading, and the back/forward cache. Testing on low-powered devices and networks is also suggested to ensure usability in harsh conditions.

Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.

Six months into 2024, and it is clear the privacy ecosystem takes no days off!! Regulators continue to implement and enforce new regulations, businesses strive to meet requirements, and technology advances like AI have privacy professionals scratching their heads about managing risk. What can we learn about the first six months of data privacy trends and events in 2024? How should this inform your privacy program management for the rest of the year? Join TrustArc, Goodwin, and Snyk privacy experts as they discuss the changes we’ve seen in the first half of 2024 and gain insight into the concrete, actionable steps you can take to up-level your privacy program in the second half of the year. This webinar will review: - Key changes to privacy regulations in 2024 - Key themes in privacy and data governance in 2024 - How to maximize your privacy program in the second half of 2024