Market Creation and Liquidity on Zeitgeist
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Slides used during the "Market Creation and Liquidity on Zeitgeist" workshop for the Encode x Polkadot Spring 2023 Hackathon!
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In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
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How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
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So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
In this talk, Lee will share his lessons learned from over 30 years of working with, and mentoring, hundreds of Test Automation Engineers. Whether you’re looking to get started in test automation or just want to improve your trade, this talk will give you a solid foundation and roadmap for ensuring your test automation efforts continuously add value. This talk is equally valuable for both aspiring Test Automation Engineers and those managing them! All attendees will take away a set of key foundational knowledge and a high-level learning path for leveling up test automation skills and ensuring they add value to their organizations.
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HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
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AppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
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Using MobSF for static analysis of mobile applications.
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Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
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Market Creation and Liquidity on Zeitgeist
- 1. Market Creation and Liquidity Using Zeitgeist Markets
- 2. Prediction Markets Overview • Two types of markets currently available on Zeitgeist: Categorical ("How will event X play out?") and scalar ("What will measurement A be in the future?"). • In the future: Combinatorial markets ("How will event X play out contingent on event Y?"). • Traders (informants) buy tokens according to which outcomes they think are likely to occur. They are rewarded if they get it right and punished if they get it wrong. • Liquidity providers make these markets to gather information.
- 3. Trading
- 4. Categorical Markets • Suppose we have a categorical market with outcomes • Suppose an informant believes has a probability of . When would we expect them to buy ? • A good way to f igure this out is to calculate the expected value. If the current price of is , then my expected pro f it of buying is... • . • This is positive if and only if . • Informants are expected to buy if and only if the current price (i.e. the current prediction) is lower than their prediction . A, B, … A p A A q A 𝔼 = p ⋅ $1 − q p > q q p
- 5. Scalar Markets • Scalar markets a range and two assets: LONG and SHORT. • They are used to predict the value of some future quantity or measurement in that range. • For example: "What will the USD Currency Index be at the end of Q2 2023 (UTC)?" • Let p be the price of SHORT and q the price of LONG. Then the prediction is . • Recall that . Thus, the higher the price of LONG (resp. SHORT), the closer the prediction is to (resp. ). [a, b] v = pa + qb p + q = 1 b a
- 6. Scalar Markets • Suppose is the current prediction and is the value that you predict. When do we expect an informant to buy LONG or SHORT? • A little bit of calculating gives... and . • An informant is expected to buy SHORT if and LONG if . v w 𝔼 long = (w − v)/(b − a) 𝔼 short = (v − w)/(b − a) w > v w < v
- 7. Summary • Users are incentivized to " f ix" the prediction of the market. • They are rewarded if they are correct and they go broke if they're wrong. • Where do the rewards come from...?
- 8. Liquidity
- 9. Liquidity Providers Who are the Traders Buying from? • Anyone can provide liquidity to a market on Zeitgeist... This means taking the opposite side of the bet (it's informants vs. LPs). • Why would you want to provide liquidity? • Liquidity providers "make the market". They pay traders to make predictions and receive information. • Liquidity providers can collect fees. Largest allowed fee is 10%. • "Everybody's wrong." If the LPs have inside information, they can pro f it off of everybody else's ignorance. • Nevertheless, LPing is inherently risky.
- 10. Risk Mitigation • Set good initial predictions. The better the initial prediction, the less the informants can pro f it off of making corrections. • Prepare for information shock by con f iguring your market with long grace periods. • Withdraw liquidity on information shock if necessary.